| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
(Hypertension. 2007;49:1015.)
© 2007 American Heart Association, Inc.
Original Articles |
From the Departments of Medicine (F.R., G.W., L.Z., B.P.K., R.M.S., Y.C., S.K., B.A.H., M.G.Z., D.T.O.), Psychiatry (J.W., B.K.R., T.A.G., D.W.S., N.J.S.), Biology, and Pharmacology, Polymorphism Research Laboratory, and Center for Human Genetics and Genomics, University of California at San Diego; the VA San Diego Healthcare System, Calif; and the Department of Medical Physiology (N.-H.H.-R.), University of Copenhagen, Copenhagen, Denmark.
Correspondence to Daniel T. OConnor or Nicholas J. Schork, Department of Medicine (0838), University of California San Diego School of Medicine and VA San Diego Healthcare System, 9500 Gilman Dr, La Jolla, CA 92093-0838. E-mail doconnor{at}ucsd.edu or nschork@ucsd.edu
| Abstract |
|---|
|
|
|---|
Key Words: hypertension metabolic inflammation glomerulus catecholamine receptor adrenergic
| Introduction |
|---|
|
|
|---|
The sympathetic nervous system exerts minute-to-minute control over both blood pressure and renal function.4 An excess of sympathetic transmitters elevates urinary albumin excretion; indeed, a half-century ago, King and Baldwin5 showed that systemic infusion of catecholamines (norepinephrine or epinephrine) elevates albumin excretion in association with increased filtration fraction, suggesting efferent arteriolar vasoconstriction, increased glomerular capillary hydrostatic pressure, and perhaps altered glomerular permeability as potential culprits.
Because microalbuminuria is frequently associated with hypertension,1,6 and hypertension displays genetic association with allelic variants in the adrenergic pathway, including catecholamine biosynthetic enzymes 7,8 and adrenergic receptors,911 we wondered whether allelic variation in the adrenergic pathway also influenced albumin excretion. Here we hypothesized that albumin excretion is also subject to genetic determination and that common variations in albumin excretion might be adrenergically mediated. We tested this hypothesis using the classical twin method,12,13 by evaluating the heritability of the trait, where heritability is the fraction of trait variance accounted for by genetic variance (h2=VG/VP, where VG is genetic variance, and VP is total phenotypic variance). We also evaluated albumin and its associated renal and adrenergic traits for shared genetic determination using the genetic covariance14,15 in twin pairs. Because glomerular permeability is likely to be influenced by adrenergic mechanisms,5 we coupled estimates of twin heritability to allelic variation at genetic loci known to govern the activity of the sympathetic nervous system and its effects on target cells.
| Methods |
|---|
|
|
|---|
-adrenergic agonists (1), angiotensin receptor antagonists (4), or calcium channel antagonists (7); because of combination therapy, these numbers add up to >28. Subjects were studied in the late morning or early afternoon, after fasting for
3 hours. None of the subjects had a history of renal failure, and each had a plasma creatinine concentration
1.5 mg/dL. Subject characteristics are according to previous reports from our group.18,19 Subjects were volunteers from Southern California, and each gave informed, written consent; the protocol was approved by the University of California San Diego Human Research Protection Program. Our previous reports on this twin set include 2 genotype association studies: the effects of polymorphism at the tyrosine hydroxylase (TH) locus intronic microsatellite on adrenergic function7 and the effect of coding region polymorphism of rho kinase (ROCK2) on the cardiovascular response to environmental stress.20 The twins also gave rise to sibling pairs for genomewide linkage on sympathochromaffin peptide secretion.21
Physiological Phenotyping
Blood pressure, heart period, cardiac output, stroke volume, systemic vascular resistance, and systemic vascular compliance were obtained noninvasively in seated subjects with an oscillometric device (DynaPulse), as described previously.20,22 Triplicate values (within ±10%) were averaged.
Urine Albumin Determination
Information on urine albumin determination can be found in the expanded Methods section in an online supplement available at http://www.hypertensionaha.org.
Biochemical Phenotyping
Information on biochemical phenotyping can be found in the online data supplement.
SNPs
Information on SNPs can be found in the online data supplement.
Calculations
Information on calculations can be found in the online data supplement.
Statistical Analyses
Information on statistical analyses can be found in the online data supplement.
| Results |
|---|
|
|
|---|
|
Heritability was highly significant (P<0.001) for both albumin urinary excretion (milligrams per gram of creatinine; at 45.2±7.4%, P=2x107) and urine albumin concentration (milligrams per deciliter of urine; at 32.5±8.0%, P=1.26x104). Heritability of albumin excretion (milligrams per gram) did not significantly differ by sex (male h2=55.8±13.3%, P=0.00077; female h2=29.5±9.0%, P=0.0012; male versus female P=0.11) or by age (divided about the median age=41 years: older individuals h2=30.5±10.7%, P=0.0043; younger individuals: h2=45.8±10.2%, P=0.0001; older versus younger P=0.302). In preliminary heritability analyses including subjects in whom albumin excretion extended into the pathological range of microalbuminuria (>30 mg/gm; n=6, 1.7% of twins), heritability declined from 45.2±7.4% to 18.8±7.7%, which is still significant (P=0.0091), but suggesting increasing determination by nongenetic causes; thus, we confined further genetic analyses (eg, SNP marker-on-trait associations) to individuals in the more heritable, physiological range of albumin excretion (<30 mg/g).
Other renal traits also displayed significant heritability, including several estimators of glomerular filtration rate (GFR) by National Institute of Diabetes and Digestive and Kidney Diseases/Modification of Diet in Renal Disease Study algorithm at 77.6±3.4% (P=7.67x1026), as well as fractional Li+ excretion (59.2±7.2%, P=4.89x109), as an estimator of proximal tubular avidity for Na+. Other phenotypic variables tested, especially physical variables (eg, height, weight, and body mass index), confirmed that heritability results in this particular twin sample were in the same range as those typically found in the literature.23
Urine Albumin Excretion Quantiles: Associated Traits
Table 1
illustrates descriptive statistics for the entire subject group, as well as values for twins dichotomized around the median value (4.17 mg/g of creatinine) of urine albumin excretion: below the 50th percentile (<4.17 mg/g) versus above the 50th percentile (
4.17 mg/g). Age, family history, and blood pressure status did not differ between these 2 groups, although males were overrepresented in the lower albumin stratum.
|
|
Adrenergic Traits
In the upper albumin stratum, the renal excretions of both epinephrine and norepinephrine were increased (Figure 2), although urine dopamine did not differ, nor did plasma catecholamine (epinephrine, norepinephrine, and dopamine) concentrations.
|
Renal Traits
Individuals in the higher urine albumin excretion quantile displayed a number of significant (P<0.05) trait differences in renal function, both glomerular and tubular (Figure 3). Estimated GFR was substantially higher in the upper stratum; as expected from this GFR change, plasma creatinine was lower, whereas the inverse of plasma creatinine was elevated. Renal excretions of both Na+ and K+ were substantially elevated, suggesting increased dietary intake at steady state. Consistent with elevated steady-state Na+ intake, the renal fractional excretion of Na+ was also elevated, as was the fractional excretion of Li+, suggesting decreased renal proximal tubular avidity for Na+. As expected, urinary Na+ excretion (milliequivalent per gram of creatinine) and plasma renin correlated inversely (
=0.109; P=0.045).
|
Metabolic Traits
Individuals in the upper albumin quantile showed several signs of increased sensitivity to the actions of insulin: with unchanged plasma glucose, they had decreased plasma insulin, decreased insulin resistance (homeostasis model assessment) index, and increased insulin sensitivity (Quantitative Insulin Sensitivity Check Index) index. However, body mass index, leptin, lipids, free fatty acids, and apolipoproteins were not different.
Hemodynamic Traits
Blood pressure, heart rate, systemic resistance, and systemic compliance did not differ between the albumin quantiles. Cardiac output was lower (by
5%), although stroke volume was unchanged.
Albumin Trait Correlations
Table S2 presents interindividual correlations between variables: correlations above and to the right of the diagonal are nonparametric (Spearman), whereas those below and to the left of the diagonal are parametric (Pearson). In general, similar correlations were obtained with both methods. Because of the effects of age and sex on several of biochemical and physiological traits, further inferential statistics (Sequential Oligogenic Linkage Analysis Routines [SOLAR] and generalized estimating equations [GEEs]) were performed on age- and sex-adjusted data. A number of phenotypes correlated with urinary albumin excretion, both physical/physiological and biochemical. Significant correlations were found for body mass index, heart rate, cardiac output, cardiac index, stroke volume, systemic resistance, systemic compliance, glomerular filtration rate, plasma creatinine, potassium excretion, fractional excretion of Na+ and Li+, plasma insulin, insulin resistance index (homeostasis model assessment), insulin sensitivity index (Quantitative Insulin Sensitivity Check Index), leptin, high-density lipoprotein cholesterol, apolipoprotein A-1, free fatty acids, urinary dopamine excretion, urinary epinephrine excretion, and urinary norepinephrine excretion.
Especially prominent correlations with albumin excretion were found for adrenergic traits (urinary excretions of dopamine, epinephrine, and norepinephrine; Table S2 and Figure 2) and renal traits (GFR and fractional Li+ excretion; Figure 3 and Table S2).
Pleiotropy (Shared Heritability): Genetic Covariance of Albumin Excretion
Because several other heritable (Table S1) traits correlated with urine albumin excretion (Table S2), we tested such traits for shared genetic determination (ie, pleiotropy) with the albumin trait (Figure 4 and Table S3).
|
G: Genetic Covariance
The results indicate that urine albumin excretion shares significant (P<0.05) genetic determination with correlated physical, renal (plasma creatinine, fractional excretion of Na+), and adrenergic (urine epinephrine excretion) traits. Pleiotropy was especially apparent for urine albumin with epinephrine excretions (
G=0.391±0.113, P=0.0012). Among multiple traits displaying significant genetic covariance with albumin (Table S3), a multivariable analysis was undertaken in SOLAR (dependent variable, albumin excretion; independent variables, plasma creatinine, epinephrine excretion, and fractional Na+ excretion [%]); the results suggest that both epinephrine excretion (P=0.0034) and plasma creatinine (P=0.00041) independently share significant genetic determination with albumin excretion.
E: Environmental Covariance
The results also indicate that urine albumin excretion shares significant (P<0.05) environmental codetermination with correlated renal (GFR and electrolyte), adrenergic (norepinephrine excretion), and hemodynamic (cardiac output) traits, although not with metabolic phenotypes. Environmental covariance was especially prominent for urine albumin and fractional Na+ excretion (
E=0.446±0.078; P<0.001). Among multiple traits displaying significant environmental covariance with albumin (Table S3), a multivariable analysis was undertaken in SOLAR (dependent variable, albumin excretion; independent variables, cardiac output, GFR [by National Institute of Diabetes and Digestive and Kidney Diseases/Modification of Diet in Renal Disease Study algorithm], plasma creatinine, Na+ excretion [milliequivalents per gram], and K+ excretion [milliequivalents per gram]); the results suggest that cardiac output (P=0.0074), GFR (P=0.0066), and K+ excretion (P=0.0095) independently share significant environmental determination with albumin excretion.
Pleiotropy Illustration
Figure 4 illustrates 2 different patterns for the relative roles of shared hereditary (
G) versus environmental (
E) codetermination for pairs of traits involving albumin. Adrenergic traits (albumin with epinephrine and norepinephrine excretions) show predominant
G with relatively little
E, suggesting that the codetermination of such traits is largely genetic. The converse is found for albumin and renal traits: relatively high
E but only modest
G; this is perhaps not unexpected for measurements likely to be reflective of dietary electrolyte intake, a clearly environmental exposure. Of note, dietary and adrenergic influences on albumin excretion may not be entirely independent; for example, urine Na+ excretion correlates directly (Table S2) with the excretions of both epinephrine (r=0.269; P<0.001) and norepinephrine (r=0.195; P<0.001).
Catecholaminergic Genetic Polymorphisms: Associations With Urinary Albumin
We found a number of significant associations between urinary albumin excretion and polymorphisms in the catecholamine biosynthetic pathway, as well as catecholamine transport, vesicular storage, and catabolism pathways (Table 2 for significant effects; Table S4 for all genes).
|
Synthesis
In the catecholamine biosynthetic pathway (Table 2 and Table S4), significant urinary albumin excretion association was found for the rate-limiting enzyme tyrosine hydroxylase (TH) in the proximal promoter region, 824 bp upstream of the translational start site: C-824T (P=0.0286). The associations did not reach significance for 3 other SNPs in the TH proximal promoter. No associations were found at either dopamine ß-hydroxylase or the epinephrine biosynthetic enzyme phenylethanolamine N-methyltransferase (PNMT).
Storage and Exocytosis
In the vesicular storage complex, significant urinary albumin associations were found for chromogranin A (CHGA) variants (Table 2) spanning
19 kbp over the locus (13 of 19 variants polymorphic and in HardyWeinberg equilibrium; Table S4). In the CHGA coding region (Figure 5), SNPs in exon 5 at Glu246Asp (P=0.0388) and exon 7 at Gly364Ser (P=0.0412) were associated. In the CHGA promoter region, associated SNPs were at A-1018T (P=0.0225) and T-415C (P=0.0112). CHGA associations persisted whether albumin excretion was analyzed as a continuous trait or as a dichotomous trait (by forming quantiles about the median value). In a multivariable analysis within SOLAR, albumin excretion was best predicted by promoter variant CHGA A-1018T (P=0.034); the percentage of total trait variance (VP) predicted by the model was 3.7%. CHGA haplotype effects are presented below. Variants at chromogranin B (CHGB) did not associate with albumin.
|
Disposition
In the catecholamine catabolic and transport pathways (Table 2 and Table S4), monoamine oxidase A (MAOA) Arg297Arg was associated with albumin (P=0.0043). Variants at monoamine oxidase B, norepinephrine transporter (NET1), vesicular monoamine transporter 1 (VMAT1), and vesicular monoamine transporter 2 (VMAT2) did not associate.
Receptors
At adrenergic receptor loci (Table 2 and Table S4), the renal dopamine D1 receptor (DRD1) promoter polymorphism G-94A significantly predicted albumin excretion (
2=7.17; P=0.0278; Figure 6), accounting for 7.5% of total trait variance (VP). Because G-94A diploid genotype ratios deviated from HardyWeinberg equilibrium (
2=50.0; P<0.001; Table S4), we also scored this polymorphism by resequencing in genomic DNA from 47 of the twins: resequencing and matrix-assisted laser desorption ionization-time of flight results were concordant in 47 of 47 individuals (100%). DRD1 promoter polymorphism G-48A did not associate with albumin.
|
There were no albumin excretion associations at other adrenergic receptor loci (Table S4): ß-1 adrenergic receptor (ADRB1), ß-2 adrenergic receptor (ADRB2), ß-3 adrenergic receptor (ADRB3),
1-adrenergic receptors (ADRA1A, ADRA1B, and ADRA1C),
2-adrenergic receptors (ADRA2A, ADRA2B, and ADRA2C), or 2 other SNPs at the dopamine D1 receptor (DRD1).
Signal Transduction
Within adrenergic receptor signal transduction pathways (Table 2 and Table S4), a variant at
-kinase (ROCK2; C115634T) in intron 5 was associated with urinary albumin excretion (P=0.0412). There was also a significant association at a G protein chaperone (Sorting nexin 13 [SNX13] in intron 14, C105820T, rs4721661; P=0.0221). Other ROCK2 and SNX13 variants did not associate. There were no associations with polymorphisms at multiple other points of signaling: G (GTP binding) proteins (GNAS1, GNB3, and ARHA), ARRB, protein kinases (ADRBK1 and GPRK4), or phospholipases (PLCB1).
Permutation
To apply Fishers exact (permutation) test to the data, we dichotomized both the albumin trait and the diploid genotypes (see Methods). Despite the expected loss of statistical power inherent in conversion of a continuous trait to a categorical variable, significant marker-on-trait effects persisted for CHGA A-1018T (P=0.027) and DRD1 G-94A (P=0.038).
Haplotypes: CHGA
Extended haplotypes were reconstructed from diploid genotypic data across 12 SNP loci spanning the CHGA gene, wherein the contributing SNPs were polymorphic, in HardyWeinberg equilibrium, and had minor allele frequencies 5% (Table S4): promoter G-1106A, A-1018T, G-988T, A-462G, T-415C, A-89C, and C-57T; intron 4 A5088T; exon 5 Glu246Asp and exon 7 Arg399Trp; and 3' (downstream) C12602G and C17757T. The HAP algorithm24 detected evidence of 40 haplotypes spanning 4 blocks, with frequencies ranging from 24.6% down to 0.15%.
There was a significant association of haplotype GA TGTCC TC CGG with albumin excretion (P=0.0262; the sixth most common haplotype at 4.97% frequency; blocks indicated by " | "; Figure 5). Other CHGA haplotypes (eg, the 2 most common haplotypes, AATGTCCAGCGG and GAGATACTGCCA) did not associate.
We then created haplotypes encompassing 3 common CHGA SNPs (Table 2) that had significant individual associations with albumin excretion: promoter A-1018T and T-415C and exon 5 Glu246Asp. Here, haplotype ATC (P=0.0241; the fourth most common haplotype at 5.56% frequency; Figure 5) associated with albumin excretion, although 2 more common haplotypes (ATG or ACG) did not. Of note, the ATC motif is contained within the longer (12-SNP) associated CHGA haplotype (Figure 5).
Epistasis: Gene-by-Gene Interactions
We tested 36 [n(n1)/2] possible gene-by-gene interactions among polymorphisms that independently (Table 2) affected the albumin trait (using interaction terms in both SOLAR and GEE) and found 3 significant interactions (Table 3 and Figure 7); each of these interactions involved signaling molecule ROCK2 (
kinase) C115634T, a common variant in intron 5. There were interactions of this variant with TH T-824C (interaction SOLAR: P=0.019; GEE
2=15.45, P=0.051; 9.6% of trait variance [VP] explained; Figure 7a), with CHGA T-415C (interaction SOLAR: P=0.0057; GEE:
2=19.07, P=0.0145; 6.9% of VP explained; Figure 7b), and with SNX13 (RGSPX1) T105820C (interaction SOLAR: P=0.0016, GEE:
2=16.95, P=0.0306; 8.4% of VP explained; Figure 7c).
|
|
With increasing numbers of the TH T-824C minor (T) allele (from C/C, through C/T, to T/T) urine albumin declines monotonously if the ROCK2 C115634T genotype is C/C. However, on a background of ROCK2 C/T heterozygosity, there is no effect of increasing TH T-824C minor (C) allele copy number, and with ROCK2 T/T homozygosity, TH T/T homozygosity actually elevates albuminuria (Figure 7a).
On a background of CHGA T-415C T/T homozygosity, increasing numbers of the ROCK2 T allele decrease albumin; by contrast, in the setting of CHGA T/C heterozygosity or C/C homozygosity, increasing numbers of the ROCK2 T allele decrease albumin excretion (Figure 7b). The SNX13 T105820C C allele increases albumin excretion on a background of ROCK2 C/C homozygosity, yet the same SNX13 T allele seems to decrease albumin excretion in the setting of ROCK2 T/T homozygosity (Figure 7c).
| Discussion |
|---|
|
|
|---|
Moreover, individuals in the higher urine albumin excretion quantile exhibited elevated urinary catecholamine excretion (Table 1
and Figure 2, top). Common genetic variants in loci crucial to catecholamine biosynthesis (TH), storage and exocytosis (CHGA; 4 SNPs and haplotypes), catabolism (MAOA), target recognition (DRD1), and postreceptor signaling (SNX13 and ROCK2) were significantly associated with albumin excretion (Table 2). Results from this study, therefore, suggest novel functional links between the adrenergic pathway and renal albumin excretion (Figure 8a and 8b).
|
Heritability: Genes and Environment
Shared Genetic Determination: Pleiotropy (
G)
Albumin excretion displayed substantial heritability (h2) at h2=45.2±7.4% (P=2x107). What factors might underlie such genetic influences on the trait? Heritability itself does not reveal the culprit genes (or even the number of contributory genes), but an initial clue comes from the genetic covariance (
G) of albumin with its correlated traits (Figure 4 and Table S3). The genetic covariance, or shared heritability, allows us to probe the extent to which 2 traits share the shame genetic determination.14,15 Especially prominent
G for albumin was noted with such adrenergic traits as the renal excretion of norepinephrine and epinephrine (Figure 4 and Table S3). Indeed, on multivariate analysis of
G, a strong independent predictor of albumin was epinephrine excretion (P=0.0034). Thus, it was reasonable to suspect that genetic factors governing catecholamine release might also determine albumin excretion. Indeed, that proved to be the case (Table 2 and Figures 4 and 5
).
Shared Environmental Determination (
E)
Additional clues to the physiological determinants of albumin come from analysis of
E. Indeed, albumin displayed particularly striking
E values with such renal traits as electrolyte excretion and GFR (Figure 4 and Table S3). On a multivariate analysis, urinary K+ excretion was an independent environmental predictor of albumin (P=0.0095). Figure 4 illustrates the relatively prominent
E for shared determination of albumin with such renal traits as GFR, Na+ excretion, and fractional Li+ excretion.
Polygenic Determination of Albumin Excretion: Role of Adrenergic Pathway Polymorphism(s), Heterosis, and Epistasis
Adrenergic Pathway Genes
If albumin excretion is influenced by hereditary factors, which genes can we implicate? Because of the shared genetic determination of albumin and adrenergic function, it seemed reasonable to turn to genetic loci encoding components of the sympathetic neuroeffector junction. Indeed, we found evidence that multiple components of this pathway harbor common genetic variants that predict albumin excretion: the rate-limiting enzyme in catecholamine biosynthesis, TH; CHGA, which has a catalytic function in catecholamine storage vesicle formation25,26; the catecholamine catabolic enzyme MAOA; the DRD1; and 2 points of post-G protein coupled receptor signal transduction: the regulator of G protein signaling family member SNX13 (also known as RGS-PX127) and ROCK2. Adrenergic pathway polymorphisms seemed to exert a global effect on albumin: when 12 loci in the contributory pathway were considered as a group (biosynthesis TH, dopamine ß-hydroxylase, and PNMT; storage CHGA; uptake NET1, VMAT1, and VMAT2; catabolism MAOA and monoamine oxidase B; receptor DRD1; and signaling SNX13 and ROCK2), positive findings from polymorphisms at 6 associated loci (TH, CHGA, MAOA, DRD1, SNX13, and ROCK2) differed significantly from the null expectation (Fishers exact test P=0.0069).
Epistasis
The twin design28 also enabled us to explore whether epistasis was at work in the genetic determination of albumin, where epistasis is defined as nonadditive interaction between
2 genes in determining a trait.29 Four of these trait-associated genes seemed to cooperate in their effect on the albumin trait, suggesting epistasis (Figure 7a through 7c); in each case, ROCK2 alleles showed a permissive effect on the trait determination by alleles at 3 other loci in the adrenergic pathway: TH, CHGA, and SNX13. Because these variants occur in elements in series within a pathway (Figure 8a and 8b), such a deviation from simple additivity of effects is perhaps not unexpected.29 We tested 36 [n(n1)/2] potential gene-by-gene interactions (Table 3) and found 3 instances of epistasis (Figure 7) at nominal (uncorrected) significance levels of P=0.0016 to 0.019 (by SOLAR). Because these interaction tests were not entirely independent (eg, ROCK2 was involved in each of the positive results), a simple Bonferroni correction for multiple comparisons may be unnecessarily conservative. Nonetheless, the findings of epistasis should be considered exploratory, in part because of the loss of statistical power inherent in calculations dependent on those few individuals homozygous for both minor alleles (Figure 7).30
Heterosis
Several of the biallelic loci (TH, CHGA, SNX13, and ROCK2; Table 2) influencing the albumin trait displayed an effect for heterozygotes that was more extreme than that for either homozygote group, thus fulfilling the fundamental criterion for heterosis (or overdominance).31 Phenotypic heterosis is consistent with our previous suggestion of "balancing selection" evidenced by an excess of heterozygosity at the CHGA promoter.29 The phenomenon of heterosis may be far more common than generally realized in human genetics,31 and may reflect 1 of several underlying mechanisms, including a U-shaped dose/response relationship for gene-on-trait, greater "fitness" in heterozygotes, or hidden stratification in 1 homozygote class; indeed, epistasis represents 1 such stratification, now made explicit graphically (Figure 7) and by statistical test of interaction (Table 3). Regardless of mechanism, the phenomenon of heterosis points out the value of trait associations with diploid genotypes rather than simply with alleles, which might not readily capture such effects.31
Specificity
The specificity of our findings is reinforced by the lack of influence of polymorphisms at other genetic loci encoding components of the adrenergic system (Table S4): catecholamine biosynthesis (dopamine ß-hydroxylase and PNMT), catecholamine storage complex (CHGB), catecholamine disposition (monoamine oxidase B and NET1), adrenergic receptors (ADRA1A/B/C, ADRA2A/B/C, and ADRB1/2/3), or a number of signal transduction components.
Also of note are the negative findings for polymorphisms in the reninangiotensinaldosteronekallikrein pathway, including: angiotensinogen (AGT), renin (REN), angiotensin-converting enzyme (ACE), angiotensin II type 1 receptor (AGTR1), mineralocorticoid receptor (NR3C2), aldosterone synthase (CYP11B2), 11-hydroxy-ß-steroid dehydrogenase (HSD11B2), kallikrein 1 (KLK1) (Table S4). Although polymorphisms at such loci have been implicated in determining the magnitude of proteinuria in pathological states of overt glomerular disease,32 common genetic variation in this pathway does not seem to influence the modest interindividual variation of albumin excretion in the physiological range (<30 mg/g; current study).
Significance of CHGA for Albumin Excretion
Role of CHGA
CHGA is the major protein in the core of catecholamine storage vesicles33 and plays a necessary catalytic role in the formation of such vesicles25,26; indeed, it may represent a "master switch" for the sympathochromaffin system.34 Genetic ablation of CHGA in the mouse25 profoundly alters sympathochromaffin secretion and blood pressure.
Catestatin
CHGA is also the source of catestatin (human CHGA352 to 372), a sympatho-inhibitory peptide functioning as an endogenous nicotinic cholinergic antagonist.35 Indeed, 1 albumin-correlated or predictive variant (Gly364Ser; Table 2 and Figure 5) is within the catestatin domain and has already demonstrated an alteration of nicotinic inhibitory potency.36
Pancreastatin
The albumin quantiles differed in indices of insulin sensitivity (homeostasis model assessment and QUICKI), although body mass index was not altered (Table 1
); of note in this context, CHGA is also the source of the dysglycemic peptide pancreastatin (human CHGA250 to 301), which exerts potent inhibitory effects on insulin action in humans in vivo.37 We did not score any SNP variants within the pancreastatin/exon-5 region. However, because CHGA promoter variants are associated with albumin (Figure 5) and are functionally active,38 it is conceivable that CHGA promoter polymorphism leading to quantitative changes in pancreastatin expression could cause the differences in insulin sensitivity in the albumin quantiles (Table 1
).
Promoter
Of the many associated variants spanning
19 kbp across the CHGA locus, which is likely to be primary? We found significant effects on albumin for 2 gene regions (Table 2): the proximal promoter and the coding region (peaking in exon 6). We have already established that naturally occurring variation in each of these 2 regions of the gene, the promoter and catestatin/exon 7, is functionally significant.38 Here multivariable analysis implicated promoter variant A-1018T for a key role in albumin excretion (P=0.034).
Albumin Excretion and Pleiotropy: Role of DRD1 Polymorphism
Bivariate Genetic Analysis: Two Traits, Dopamine and Albumin
Not only did DRD1 promoter polymorphism G-94A predict albumin excretion (Figure 6a), but it also seemed to alter the coupling (or gain) between the endogenous DRD1 agonist dopamine and the albumin trait (Figure 6b). Albumin excretion paralleled dopamine excretion in the twins (Figure 6b). However, this is not a simple, homogeneous correlation; stratification by DRD1 G-94A diploid genotype (Figure 6b) reveals the segregation of the twins into relatively discrete subgroups of dopamine coupling to albumin; G/G homozygosity in particular seems to augment the effect of dopamine on albumin excretion (Figure 6b); of note, G is the major allele at this SNP locus (at 84% allele frequency; Figure 6a). Not only did DRD1 G-94A exert univariate effects on both dopamine (
2=7.0; P=0.0302) and albumin (
2=7.17; P= 0.0278) excretion, but a bivariate analysis indicated that G-94A diploid genotype altered the coupling of dopamine to albumin (
2=9.4; P=0.0022; Figure 6b). This constitutes genetic evidence for a pleiotropic effect of DRD1 G-94A.14,15
Site of Action of Dopamine and DRD1 Polymorphism
How might the DRD1 polymorphism influence the coupling of dopamine to albumin excretion? Dopamine may be synthesized locally within the kidney,39 and then act at multiple sites, including the glomerulus and the proximal tubule. In the kidney, the DRD1 receptor is a major functional target of dopamine, although other subtypes are also active.40 In the glomerulus, dopamine acts on podocytes in a receptor-mediated fashion to generate cAMP and rearrange the subplasmalemmal cytoskeleton,41 events that may alter podocyte slit/pore permeability to albumin. Dopamine also has postsynaptic actions in the proximal tubule to affect Na+ reabsorption,40 although it does not have a documented effect on proximal tubular peptide/protein reabsorption/endocytosis.42 In addition, renal dopamine has presynaptic actions to reduce catecholamine release from postganglionic axons in the kidney; however, the responsible receptor subtype seems to be DRD2.43 The effect of DRD1 G-94A polymorphism on excretion of the agonist itself (dopamine; Figure 6b;
2=7.00; P=0.0302) suggests that agonist signaling through DRD1 is coupled in "feedback" fashion to agonist synthesis/secretion; such feedback is likely in the proximal renal tubule.40
Advantages and Limitations of This Study
Twin Method: Heritability and Pleiotropy
The fundamental contribution here is the application of the classical twin method12,13 to renal function. First of all, twins allowed us to estimate heritability14,44 of the albumin phenotype, a fundamental test of the tractability of any trait to genetic analysis. Second, twins allowed quantitative estimation of the extent to which different renal traits shared genetic or environmental determination (Figure 4 and Table S3), in the form of the genetic covariance14,15 or the environmental covariance. Such covariance clusters (Figure 4) suggest discrete and novel genetic or environmental strategies for intervention into the albumin trait. A total of 28 (8.3%) of the 336 twin individuals were on antihypertensive medications, likely contributing to the environmental covariance.
Twin Method: Random Sample of the Population
Because the twinship was the ascertainment criterion for this study, this cohort may in some sense constitute a random (unbiased) sample of the population.13,12,45 Indeed, our cohort spans both sexes and a spectrum of ages (from the second to ninth decades of life). One advantage of this approach is that the results should be generalizable and applicable to the entire population, rather than to only 1 disease state.
We studied individuals with generally normal renal function (Table 1
and Figure 3) and albumin excretion of only <30 mg/g of creatinine (Table 1
and Figure 3), with mean values of 2.47±0.16 mg/g in the lower quantile and 10.3±0.65 mg/g in the upper quantile (Table 1
). Is this range of albumin excretion pertinent to cardiovascular risk? Recent studies13 indicate that albumin excretion levels as low as
5 to 7 mg/g may confer disease risk, values well within our twins range (Table 2 and Figure 3).
Another advantage of this population approach is that physiological relationships may be observed counter to those sometimes seen in disease samples; for example, in incipient type 2 diabetic nephropathy, albumin excretion is found in insulin-resistant individuals; by contrast, in this twin cohort, the upper albumin quantile identifies subjects with enhanced insulin sensitivity (Table 1
).
One caveat to the twin sample is that the 2 members of each twinship are genetically correlated and, hence, these are not independent observations; therefore, statistical methods have been developed to account for and even exploit this dependence, such as the heritability estimates of SOLAR44 and the clustered statistics of GEEs46; but even genetically identical individuals (monozygotic twins) contribute different phenotypic information and increase the power of the association analyses.47 Another caveat to the study of healthy individuals is that the sample does not readily capture a particular disease spectrum, such as glomerular disease; thus, whether our adrenergic pathway polymorphisms are pertinent to the progression of overt renal disease remains to be tested.
Phenotypes Coupled: Glomerular, Tubular, and Adrenergic
Our twin cohort is carefully phenotyped to probe the heritability of traits in several physiological systems: renal (both glomerular and tubular; Table S1 and Figure 1), adrenergic, endocrine, and hemodynamic. This strategy allowed us to uncover previously unsuspected etiologic relationships among traits, by resolving traits into groups of shared genetic and environmental determination (Figure 4 and Table S3).
Adrenergic Pathway Genotyping
We systematically probed polymorphism at a number of loci in series within the adrenergic pathway (Figure 8a and 8b and Table S4): catecholamine biosynthesis, metabolism, transport, storage, release, receptors, and signal transduction. Such a systematic approach allowed us to build a comprehensive picture of the role of adrenergic polymorphism in the albumin trait and to uncover gene-by-gene interactions (epistasis; Figure 7)29 in trait determination.
Ethnicity
We confined our allelic associations to a single ethnicity here (European ancestry), as is customary to prevent spurious marker-on-trait associations as a result of population stratification/admixture.48 Because this association study was confined to a single subset of the population, the results may not be generalizable to all population subsets. Thus, our results will require confirmation in other population subgroups.
Candidate Genetic Loci
Although we tested polymorphisms at a large number of candidate genetic loci in the adrenergic and renal pathways (Figure 8a and 8b and Table S4), our approach was clearly hypothesis driven and could well have missed contributing alleles at other loci. Hypothesis-free approaches, such as sibling pair linkage or genomewide allelic association, can be implemented in the future for more comprehensive discovery of the genetic determinants of albumin; indeed, such approaches have been undertaken for albumin in hypertension,6 detecting novel logarithm of odds peaks on chromosomes 12 and 19. However, neither of those 2 logarithm of odds peaks harbor our adrenergic candidate genes (Table 2, Figure 8a and 8b, and Table S4), reinforcing the relative power of association over linkage in at least some settings, especially locus heterogeneity.49
Study Design
Although some studies of albumin excretion use first-voided morning urines in fasting subjects, our subjects were typically studied later in the day after fasting periods of as little as 3 hours. Albumin in such urines is likely to be less concentrated than that obtained after more prolonged (overnight) fasting and perhaps more variable as a result of different fasting periods. Nonetheless, heritability in these subjects with physiological range albumin excretion was h2=45.2±7.4% (P=2x107; Figure 1 and Table S1), documenting a major effect of heredity on the trait.
Statistical Confidence
In a comprehensive study of a trait involving multiple genotypes, the possibility of false-positive (type 1) statistical conclusions must be considered. We approached this issue in 5 ways: haplotyping, multivariable tests, pathway (global) effects, exact (permutation) tests, and interaction (epistasis) effects. At CHGA, not only individual SNPs (Table 2 and Figure 5) but also extended haplotypes (Figure 5) associated with albumin excretion. In a multivariable analysis at CHGA, promoter variant A-1018T best predicted albumin (P=0.034). In a global test of the adrenergic pathway, albumin associations at 6 of 12 pathway loci (Figure 8) exceeded expectation under chance (P=0.0069). Permutation (exact) tests further established effects of CHGA A-1018T (P=0.027) and DRD1 G-94A (P=0.038) on albumin. Finally, epistasis tests documented gene-by-gene interactions of ROCK2 with TH, CHGA, and SNX13 (Figure 7) to predict albumin. Nonetheless, the polymorphisms explained but a small portion of albumin excretion trait variance (VP), for example, 3.7% by CHGA A-1018T and 7.5% by DRD1 G-94A; hence, the complex and multifactorial nature of this trait is apparent.
Perspectives and Conclusions. Pathways: Adrenergic Signaling and Mechanisms
We conclude that albumin excretion is a highly heritable trait, displaying joint genetic determination (pleiotropy) with adrenergic and renal functions, such as epinephrine and electrolyte transport. We further conclude that interindividual variability in albumin excretion is controlled in substantial part by genetic variation in the adrenergic pathway encoding catecholamine formation and actions. Thus, albumin excretion is a polygenic trait. Nonadditive effects of combinations of genotypes at multiple points in this pathway indicate epistasis, or gene-by-gene interactions. Our results document for the first time novel pathophysiological links between the adrenergic system and albumin excretion and suggest new strategies for probing the role and actions of the pathway within this setting.
Hypothesis Schematic
A hypothesis schematizing our results is presented in Figure 8a and 8b, outlining the role of candidate adrenergic polymorphisms in the determination of albumin excretion, at the level of both adrenergic synapses in the glomerulus (Figure 8a) and postreceptor signal transduction in glomerular cells (Figure 8b).
Implications for Pathophysiology, Mechanism, and Therapeutics
Our results suggest that the adrenergic pathway is crucially involved in determination of albumin excretion in healthy individuals, perhaps by altering vascular tone or permeability at the glomerulus. Adrenergic determination of this renal trait (Figures 5 and 7
) suggests that treatments targeting sympathetic outflow, adrenergic receptors, or catecholaminergic signaling might be especially beneficial in ameliorating the trait. Indeed, Amann et al50 have also noted the particular value of sympatholytic treatment in halting progressive renal injury in animal models. Our results raise that possibility that adrenergic genetic profiling of patients with glomerular injury might yield practical pharmacogenetic predictors of patients most likely to benefit from sympatholytic therapy.51
Implications for Prevention: Heredity and Environment
Our results raise the possibility that profiling subjects for particular adrenergic polymorphisms (Figure 8) would provide an index of risk for susceptibility to glomerular injury. In addition, shared environmental determination (
E; Figure 4 and Table S3) of the albumin trait with electrolyte intake/excretion, as well as GFR, suggests a strategy to reduce albumin excretion: reduction of excessive dietary electrolyte (especially Na+) intake.
| Acknowledgments |
|---|
Sources of Funding
This work was supported by the University of California San Diego General Clinical Research Center (National Institutes of Health RR00827), Department of Veterans Affairs, and National Institutes of Health.
Disclosures
None.
Received October 1, 2006; first decision October 25, 2006; accepted February 14, 2007.
| References |
|---|
|
|
|---|
2. Romundstad S, Holmen J, Kvenild K, Hallan H, Ellekjaer H. Microalbuminuria and all-cause mortality in 2,089 apparently healthy individuals: A 4.4-year follow-up study. The nord-trondelag health study (hunt), Norway. Am J Kidney Dis. 2003; 42: 466473.[CrossRef][Medline] [Order article via Infotrieve]
3. Klausen K, Borch-Johnsen K, Feldt-Rasmussen B, Jensen G, Clausen P, Scharling H, Appleyard M, Jensen JS. Very low levels of microalbuminuria are associated with increased risk of coronary heart disease and death independently of renal function, hypertension, and diabetes. Circulation. 2004; 110: 3235.
4. Guyton AC. Blood pressure controlspecial role of the kidneys and body fluids. Science. 1991; 252: 18131816.
5. King SE, Baldwin DS. Production of renal ischemia and proteinuria in man by the adrenal medullary hormones. Am J Med. 1956; 20: 217224.[CrossRef][Medline] [Order article via Infotrieve]
6. Freedman BI, Beck SR, Rich SS, Heiss G, Lewis CE, Turner S, Province MA, Schwander KL, Arnett DK, Mellen BG. A genome-wide scan for urinary albumin excretion in hypertensive families. Hypertension. 2003; 42: 291296.
7. Zhang L, Rao F, Wessel J, Kennedy BP, Rana BK, Taupenot L, Lillie EO, Cockburn M, Schork NJ, Ziegler MG, OConnor DT. Functional allelic heterogeneity and pleiotropy of a repeat polymorphism in tyrosine hydroxylase: prediction of catecholamines and response to stress in twins. Physiol Genomics. 2004; 19: 277291.
8. Sharma P, Hingorani A, Jia H, Ashby M, Hopper R, Clayton D, Brown MJ. Positive association of tyrosine hydroxylase microsatellite marker to essential hypertension. Hypertension. 1998; 32: 676682.
9. Lee YW, Oh VM, Garcia E, Taylor EA, Wu H, Yap EP, Kazeem GR, Caulfield MJ, Munroe PB. Haplotypes of the beta2-adrenergic receptor gene are associated with essential hypertension in a Singaporean Chinese population. J Hypertens. 2004; 22: 21112116.[CrossRef][Medline] [Order article via Infotrieve]
10. Ranade K, Shue WH, Hung YJ, Hsuing CA, Chiang FT, Pesich R, Hebert J, Olivier M, Chen YD, Pratt R, Olshen R, Curb D, Botstein D, Risch N, Cox DR. The glycine allele of a glycine/arginine polymorphism in the beta2-adrenergic receptor gene is associated with essential hypertension in a population of Chinese origin. Am J Hypertens. 2001; 14: 11961200.[CrossRef][Medline] [Order article via Infotrieve]
11. Bao X, Mills PJ, Rana BK, Dimsdale JE, Schork NJ, Smith DW, Rao F, Milic M, OConnor DT, Ziegler MG. Interactive effects of common beta2-adrenoceptor haplotypes and age on susceptibility to hypertension and receptor function. Hypertension. 2005; 46: 301307.
12. Boomsma D, Busjahn A, Peltonen L. Classical twin studies and beyond. Nat Rev Genet. 2002; 3: 872882.[CrossRef][Medline] [Order article via Infotrieve]
13. MacGregor AJ, Snieder H, Schork NJ, Spector TD. Twins. Novel uses to study complex traits and genetic diseases. Trends Genet. 2000; 16: 131134.[CrossRef][Medline] [Order article via Infotrieve]
14. Falconer DS, Mackay TFC. Introduction to Quantitative Genetics. Harlow, London, UK: Longman; 1996.
15. Almasy L, Dyer TD, Blangero J. Bivariate quantitative trait linkage analysis: pleiotropy versus co-incident linkages. Genet Epidemiol. 1997; 14: 953958.[CrossRef][Medline] [Order article via Infotrieve]
16. Cockburn M, Hamilton A, Zadnick J, Cozen W, Mack TM. The occurrence of chronic disease and other conditions in a large population-based cohort of native californian twins. Twin Res. 2002; 5: 460467.[CrossRef][Medline] [Order article via Infotrieve]
17. OConnor DT, Insel PA, Ziegler MG, Hook VY, Smith DW, Hamilton BA, Taylor PW, Parmer RJ. Heredity and the autonomic nervous system in human hypertension. Curr Hypertens Rep. 2000; 2: 1622.[Medline] [Order article via Infotrieve]
18. OConnor DT, Kailasam MT, Kennedy BP, Ziegler MG, Yanaihara N, Parmer RJ. Early decline in the catecholamine release-inhibitory peptide catestatin in humans at genetic risk of hypertension. J Hypertens. 2002; 20: 13351345.[CrossRef][Medline] [Order article via Infotrieve]
19. Herrmann V, Buscher R, Go MM, Ring KM, Hofer JK, Kailasam MT, OConnor DT, Parmer RJ, Insel PA. Beta2-adrenergic receptor polymorphisms at codon 16, cardiovascular phenotypes and essential hypertension in whites and African Americans. Am J Hypertens. 2000; 13: 10211026.[CrossRef][Medline] [Order article via Infotrieve]
20. Seasholtz TM, Wessel J, Rao F, Rana BK, Khandrika S, Kennedy BP, Lillie EO, Ziegler MG, Smith DW, Schork NJ, Brown JH, OConnor DT. Rho kinase polymorphism influences blood pressure and systemic vascular resistance in human twins: role of heredity. Hypertension. 2006; 47: 937947.
21. Greenwood TA, Rao F, Stridsberg M, Mahapatra NR, Mahata M, Lillie EO, Mahata SK, Taupenot L, Schork NJ, OConnor DT. Pleiotropic effects of novel trans-acting loci influencing human sympathochromaffin secretion. Physiol Genomics. 2006; 25: 470479.
22. Brinton TJ, Kailasam MT, Wu RA, Cervenka JH, Chio SS, Parmer RJ, DeMaria AN, OConnor DT. Arterial compliance by cuff sphygmomanometer. Application to hypertension and early changes in subjects at genetic risk. Hypertension. 1996; 28: 599603.
23. Rosenberg NA, Nordborg M. Genealogical trees, coalescent theory and the analysis of genetic polymorphisms. Nat Rev Genet. 2002; 3: 380390.[CrossRef][Medline] [Order article via Infotrieve]
24. Halperin E, Eskin E. Haplotype reconstruction from genotype data using imperfect phylogeny. Bioinformatics. 2004; 20: 18421849.
25. Mahapatra NR, OConnor DT, Vaingankar SM, Hikim AP, Mahata M, Ray S, Staite E, Wu H, Gu Y, Dalton N, Kennedy BP, Ziegler MG, Ross J, Mahata SK. Hypertension from targeted ablation of chromogranin a can be rescued by the human ortholog. J Clin Invest. 2005; 115: 19421952.[CrossRef][Medline] [Order article via Infotrieve]
26. Taupenot L, Harper KL, OConnor DT. Role of h+-atpase-mediated acidification in sorting and release of the regulated secretory protein chromogranin a: evidence for a vesiculogenic function. J Biol Chem. 2005; 280: 38853897.
27. Zheng B, Ma YC, Ostrom RS, Lavoie C, Gill GN, Insel PA, Huang XY, Farquhar MG. Rgs-px1, a gap for galphas and sorting nexin in vesicular trafficking. Science. 2001; 294: 19391942.
28. Blangero J, Williams JT, Almasy L. Variance component methods for detecting complex trait loci. Adv Genet. 2001; 42: 151181.[Medline] [Order article via Infotrieve]
29. Cordell HJ. Epistasis: what it means, what it doesnt mean, and statistical methods to detect it in humans. Hum Mol Genet. 2002; 11: 24632468.
30. Moore JH, Hahn LW. A cellular automata approach to detecting interactions among single-nucleotide polymorphisms in complex multifactorial diseases. Pac Symp Biocomput. 2002; 7: 5364.
31. Comings DE, MacMurray JP. Molecular heterosis: a review. Mol Genet Metab. 2000; 71: 1931.[CrossRef][Medline] [Order article via Infotrieve]
32. Boright AP, Paterson AD, Mirea L, Bull SB, Mowjoodi A, Scherer SW, Zinman B. Genetic variation at the ace gene is associated with persistent microalbuminuria and severe nephropathy in type 1 diabetes: the dcct/edic genetics study. Diabetes. 2005; 54: 12381244.
33. Taupenot L, Harper KL, OConnor DT. The chromogranin-secretogranin family. N Engl J Med. 2003; 348: 11341149.
34. Kim T, Loh YP. Chromogranin a: a surprising link between granule biogenesis and hypertension. J Clin Invest. 2005; 115: 17111713.[CrossRef][Medline] [Order article via Infotrieve]
35. Mahata SK, OConnor DT, Mahata M, Yoo SH, Taupenot L, Wu H, Gill BM, Parmer RJ. Novel autocrine feedback control of catecholamine release. A discrete chromogranin a fragment is a noncompetitive nicotinic cholinergic antagonist. J Clin Invest. 1997; 100: 16231633.[Medline] [Order article via Infotrieve]
36. Mahata SK, Mahata M, Wen G, Wong WB, Mahapatra NR, Hamilton BA, OConnor DT. The catecholamine release-inhibitory "catestatin" fragment of chromogranin a: naturally occurring human variants with different potencies for multiple chromaffin cell nicotinic cholinergic responses. Mol Pharmacol. 2004; 66: 11801191.
37. OConnor DT, Cadman PE, Smiley C, Salem RM, Rao F, Smith J, Funk SD, Mahata SK, Mahata M, Wen G, Taupenot L, Gonzalez-Yanes C, Harper KL, Henry RR, Sanchez-Margalet V. Pancreastatin: multiple actions on human intermediary metabolism in vivo, variation in disease, and naturally occurring functional genetic polymorphism. J Clin Endocrinol Metab. 2005; 90: 54145425.
38. Wen G, Mahata SK, Cadman P, Mahata M, Ghosh S, Mahapatra NR, Rao F, Stridsberg M, Smith DW, Mahboubi P, Schork NJ, OConnor DT, Hamilton BA. Both rare and common polymorphisms contribute functional variation at chga, a regulator of catecholamine physiology. Am J Hum Genet. 2004; 74: 197207.[CrossRef][Medline] [Order article via Infotrieve]
39. Quinones H, Collazo R, Moe OW. The dopamine precursor l-dihydroxyphenylalanine is transported by the amino acid transporters rbat and lat2 in renal cortex. Am J Physiol Renal Physiol. 2004; 287: F74F80.
40. Jose PA, Eisner GM, Felder RA. Dopamine and the kidney: a role in hypertension? Curr Opin Nephrol Hypertens. 2003; 12: 189194.[CrossRef][Medline] [Order article via Infotrieve]
41. Endlich N, Endlich K. Camp pathway in podocytes. Microsc Res Tech. 2002; 57: 228231.[CrossRef][Medline] [Order article via Infotrieve]
42. Orlando RA, Rader K, Authier F, Yamazaki H, Posner BI, Bergeron JJ, Farquhar MG. Megalin is an endocytic receptor for insulin. J Am Soc Nephrol. 1998; 9: 17591766.[Abstract]
43. Rump LC, Schwertfeger E, Schuster MJ, Schaible U, Frankenschmidt A, Schollmeyer PJ. Dopamine da2-receptor activation inhibits noradrenaline release in human kidney slices. Kidney Int. 1993; 43: 197204.[Medline] [Order article via Infotrieve]
44. Almasy L, Blangero J. Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet. 1998; 62: 11981211.[CrossRef][Medline] [Order article via Infotrieve]
45. Cockburn MG, Hamilton AS, Zadnick J, Cozen W, Mack TM. Development and representativeness of a large population-based cohort of native californian twins. Twin Res. 2001; 4: 242250.[CrossRef][Medline] [Order article via Infotrieve]
46. Do KA, Broom BM, Kuhnert P, Duffy DL, Todorov AA, Treloar SA, Martin NG. Genetic analysis of the age at menopause by using estimating equations and bayesian random effects models. Stat Med. 2000; 19: 12171235.[CrossRef][Medline] [Order article via Infotrieve]
47. Visscher PM, Duffy DL. The value of relatives with phenotypes but missing genotypes in association studies for quantitative traits. Genet Epidemiol. 2006; 30: 3036.[CrossRef][Medline] [Order article via Infotrieve]
48. Knowler WC, Williams RC, Pettitt DJ, Steinberg AG. Gm3;5, 13, 14 and type 2 diabetes mellitus: an association in american indians with genetic admixture. Am J Hum Genet. 1988; 43: 520526.[Medline] [Order article via Infotrieve]
49. Risch N, Merikangas K. The future of genetic studies of complex human diseases. Science. 1996; 273: 15161517.
50. Amann K, Rump LC, Simonaviciene A, Oberhauser V, Wessels S, Orth SR, Gross ML, Koch A, Bielenberg GW, Van Kats JP, Ehmke H, Mall G, Ritz E. Effects of low dose sympathetic inhibition on glomerulosclerosis and albuminuria in subtotally nephrectomized rats. J Am Soc Nephrol. 2000; 11: 14691478.
51. Cadman PE, OConnor DT. Pharmacogenomics of hypertension. Curr Opin Nephrol Hypertens. 2003; 12: 6170.[CrossRef][Medline] [Order article via Infotrieve]
This article has been cited by other articles:
![]() |
Y. Chen, M. Mahata, F. Rao, S. Khandrika, M. Courel, M. M. Fung, K. Zhang, M. Stridsberg, M. G. Ziegler, B. A. Hamilton, et al. Chromogranin A Regulates Renal Function by Triggering Weibel-Palade Body Exocytosis J. Am. Soc. Nephrol., July 1, 2009; 20(7): 1623 - 1632. [Abstract] [Full Text] [PDF] |
||||
![]() |
P.-a. B. Shih and D. T. O'Connor Hereditary Determinants of Human Hypertension: Strategies in the Setting of Genetic Complexity Hypertension, June 1, 2008; 51(6): 1456 - 1464. [Full Text] [PDF] |
||||
![]() |
C. Zeng, I. Armando, Y. Luo, G. M. Eisner, R. A. Felder, and P. A. Jose Dysregulation of dopamine-dependent mechanisms as a determinant of hypertension: studies in dopamine receptor knockout mice Am J Physiol Heart Circ Physiol, February 1, 2008; 294(2): H551 - H569. [Abstract] [Full Text] [PDF] |
||||
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Hypertension Home | Subscriptions | Archives | Feedback | Authors | Help | AHA Journals Home | Search Copyright © 2007 American Heart Association, Inc. All rights reserved. Unauthorized use prohibited. |