University of Groningen
Genome-Wide Association Meta-Analysis of Individuals of European Ancestry Identifies
Suggestive Loci for Sodium Intake, Potassium Intake, and Their Ratio Measured from
24-Hour or Half-Day Urine Samples
Kho, Minjung; Smith, Jennifer A; Verweij, Niek; Shang, Lulu; Ryan, Kathleen A; Zhao, Wei;
Ware, Erin B; Gansevoort, Ron T; Irvin, Marguerite R; Lee, Jung Eun
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The Journal of Nutrition
DOI:
10.1093/jn/nxaa241
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Kho, M., Smith, J. A., Verweij, N., Shang, L., Ryan, K. A., Zhao, W., Ware, E. B., Gansevoort, R. T., Irvin,
M. R., Lee, J. E., Turner, S. T., Sung, J., van der Harst, P., Arnett, D. K., Baylin, A., Park, S. K., Seo, Y. A.,
Kelly, K. M., Chang, Y. P. C., ... Kardia, S. L. R. (2020). Genome-Wide Association Meta-Analysis of
Individuals of European Ancestry Identifies Suggestive Loci for Sodium Intake, Potassium Intake, and Their
Ratio Measured from 24-Hour or Half-Day Urine Samples. The Journal of Nutrition, 150(10), 2635-2645.
https://doi.org/10.1093/jn/nxaa241
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The Journal of Nutrition
Biochemical, Molecular, and Genetic Mechanisms
Genome-Wide Association Meta-Analysis of
Individuals of European Ancestry Identifies
Suggestive Loci for Sodium Intake, Potassium
Intake, and Their Ratio Measured from
24-Hour or Half-Day Urine Samples
Minjung Kho,
1Jennifer A Smith,
1,2Niek Verweij,
3Lulu Shang,
4Kathleen A Ryan,
5Wei Zhao,
1Erin
B Ware,
2Ron T Gansevoort,
6Marguerite R Irvin,
7Jung Eun Lee,
8Stephen T Turner,
9Joohon Sung,
10,11Pim van der Harst,
3Donna K Arnett,
12Ana Baylin,
1,13Sung Kyun Park,
1,14Young Ah Seo,
13Kristen M Kelly,
1Yen Pei C Chang,
5Xiang Zhou,
4John C Lieske,
9,15and Sharon LR Kardia
11Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA;2Survey Research Center, Institute
for Social Research, University of Michigan, Ann Arbor, MI, USA;3Department of Cardiology, Medical Center Groningen, University of
Groningen, Groningen, Netherlands;4Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA; 5Department of Medicine, School of Medicine, University of Maryland Baltimore, Baltimore, MD, USA;6Department of Nephrology,
Medical Center Groningen, University of Groningen, Groningen, Netherlands;7Department of Epidemiology, School of Public Health,
University of Alabama at Birmingham, Birmingham, AL, USA;8Department of Food and Nutrition, Seoul National University, Seoul,
Republic of Korea;9Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA;10Department of Epidemiology, School
of Public Health, Seoul National University, Seoul, Republic of Korea;11Institute of Environment and Health, Seoul National University,
Seoul, Republic of Korea;12College of Public Health, University of Kentucky, Lexington, KY, USA;13Department of Nutritional Sciences,
School of Public Health, University of Michigan, Ann Arbor, MI, USA;14Department of Environmental Health Sciences, School of Public
Health, University of Michigan, Ann Arbor, MI, USA; and15Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester,
MN, USA
ABSTRACT
Background: Excess sodium intake and insufficient potassium intake are risk factors for hypertension, but there is
limited knowledge regarding genetic factors that influence intake. Twenty-hour or half-day urine samples provide robust estimates of sodium and potassium intake, outperforming other measures such as spot urine samples and dietary self-reporting.
Objective: The aim of this study was to investigate genomic regions associated with sodium intake, potassium intake,
and sodium-to-potassium ratio measured from 24-h or half-day urine samples.
Methods: Using samples of European ancestry (mean age: 54.2 y; 52.3% women), we conducted a meta-analysis of
genome-wide association studies in 4 cohorts with 24-h or half-day urine samples (n= 6,519), followed by gene-based analysis. Suggestive loci (P< 10−6) were examined in additional European (n= 844), African (n = 1,246), and Asian (n= 2,475) ancestry samples.
Results: We found suggestive loci (P < 10−6) for all 3 traits, including 7 for 24-h sodium excretion, 4 for 24-h potassium excretion, and 4 for sodium-to-potassium ratio. The most significant locus was rs77958157 near cocaine- and amphetamine-regulated transcript prepropeptide (CARTPT) , a gene involved in eating behavior and appetite regulation (P= 2.3 × 10−8with sodium-to-potassium ratio). Two suggestive loci were replicated in additional samples: for sodium excretion, rs12094702 near zinc finger SWIM-type containing 5 (ZSWIM5) was replicated in the Asian ancestry sample reaching Bonferroni-corrected significance (P = 0.007), and for potassium excretion rs34473523 near sodium leak channel (NALCN) was associated at a nominal P value with potassium excretion both in European (P= 0.043) and African (P = 0.043) ancestry cohorts. Gene-based tests identified 1 significant gene for sodium excretion, CDC42 small effector 1 (CDC42SE1), which is associated with blood pressure regulation.
Conclusions: We identified multiple suggestive loci for sodium and potassium intake near genes associated with
eating behavior, nervous system development and function, and blood pressure regulation in individuals of European ancestry. Further research is needed to replicate these findings and to provide insight into the underlying genetic mechanisms by which these genomic regions influence sodium and potassium intake. J Nutr 2020;150:2635–2645.
Keywords:
genome-wide association study, meta-analysis, sodium intake, potassium intake, sodium-to-potassiumratio
CopyrightC The Author(s) on behalf of the American Society for Nutrition 2020.
Manuscript received April 18, 2020. Initial review completed May 19, 2020. Revision accepted July 17, 2020.
Introduction
Sodium and potassium are essential dietary components, but
excess sodium intake (
1
) and low potassium intake (
2
) are
established risk factors for hypertension and cardiovascular
disease (CVD). More than 630,000 people die of heart disease
in the United States every year, accounting for 1 in every
4 deaths (
3
). In 2010,
∼1.7 million (9.5%) of all worldwide
deaths from cardiovascular causes were attributed to high
sodium intake (
4
). The average American’s daily consumption
of sodium is 2.2 times the recommended maximum 1,500 mg/d,
while daily consumption of potassium is 2000 mg/d below the
recommended minimum of 4700 mg/d (
5
).
Sodium-to-potassium ratio has been shown to be a stronger
predictive risk factor for hypertension than sodium and
potassium amounts alone (
6
). Identifying the factors associated
with maintaining an optimal sodium-to-potassium ratio is
important because it can provide a basis for interventions to
reduce the burden of hypertension and CVD (
7
). Sodium and
potassium intakes are related to eating behavior, and many
factors influence the level of consumption including sex, age,
socioeconomic status, dietary habits, area of residence, and
cultural factors (
4
). A previous study of 2209 Koreans in
a twin-family study showed that genetic factors contribute
to variability in sodium intake (heritability
= 30–35%) (
8
).
The intraclass correlation coefficients for 24-h urinary sodium
excretion were the highest among monozygotic twin pairs
(0.47) and the lowest among first-degree relative pairs (siblings
combined with dizygotic twins: 0.09).
Recent behavioral genomics investigations have started to
identify loci associated with a range of eating behavior
pheno-types including dietary patterns (
9
), macronutrient composition
(
10
), intake of sweets (
11
), alcohol consumption (
12
), and coffee
intake (
13
). Although the effect of the genetic components on
these food consumption characteristics is modest, identifying
associated genetic variants assessing potential causal links to
chronic diseases might help identify new drug targets or to
improve personalized nutritional recommendations.
However, there has been limited investigation into the
specific genetic variants that influence sodium and
potas-sium intake or excretion. Yang et al. (
14
) recently found
significant associations of single nucleotide polymorphisms
(SNPs) in the epithelial sodium channel gene, sodium channel
epithelial 1 subunit gamma (SCNN1G), with 24-h urinary
Funding for the meta-analysis was provided by R01 HL119443 from the National Heart, Lung, and Blood Institute. Cohort-specific funding sources are provided in Supplemental Table 1.Author disclosures: NV is an employee of Genomics plc. The other authors report no conflicts of interest.
Supplemental Tables 1–8, and Supplemental Figures 1–7 are available from the “Supplementary data” link in the online posting of the article and from the same link in the online table of contents athttps://academic.oup.com/jn/.
Address correspondence to MK (e-mail:mjkho@umich.edu).
Abbreviations used: BMI, body mass index; CARTPT, cocaine- and amphetamine-regulated transcript prepropeptide; CDC42SE1, CDC42 small effector 1; CVD, cardiovascular disease; DEG, differentially expressed gene; eQTL, expression quantitative trait loci; FHS, Framingham Heart Study; FUMA, Functional Mapping and Annotation of Genome-Wide Association Studies; GENOA, Genetic Epidemiology Network of Arteriopathy; GWAS, genome-wide association study; GWGAS, Genome-Wide Gene Association Analysis; HAPI Heart, Heredity and Phenotype Intervention Heart; HTS, Healthy Twin Study, Korea; HyperGEN, Hypertension Genetic Epidemiology Network; LD, linkage disequilibrium; LVM, left ventricular mass; MAF, minor allele frequency; MAGMA, Multi-marker Analysis of GenoMic Annotation; PREVEND, Prevention of REnal and Vascular ENd-stage Disease; SCNN1G, sodium channel epithelial 1 subunit gamma; SNP, single nucleotide polymorphism; ZSWIM5, zinc finger SWIM-type containing 5.
sodium excretion estimated from spot urine samples in a
Korean population. Pazoki et al. (
15
) identified 50 loci
for the concentrations of sodium excretion and 13 for
the concentrations of potassium excretion using spot urine
samples in European ancestry UK Biobank data. Another
study using European ancestry UK Biobank data found
6 loci each for sodium-to-creatinine and
potassium-to-creatinine concentration ratios, and 4 loci for
sodium-to-potassium concentration ratio measured in spot urine samples
(
16
). One Japanese genome-wide association study (GWAS)
was unable to identify loci for urinary sodium and potassium
concentrations, probably due to limited sample size (
17
). Other
studies have identified genes related to sodium sensitivity of
blood pressure (
18
) and the ability to detect salty taste (
19
).
In the current study, we conducted a meta-analysis of GWASs
for 24-h sodium and potassium excretion measured from 24-h
or half-day urine samples. Sodium and potassium excretion in
a 24-h urine sample well represents all sources of sodium and
potassium intake and has been shown to have higher validity
compared with methods based on spot urine samples or
self-reported dietary data (
20
). Our objective was to use high-quality
measurements of sodium and potassium intake and genotype
data from 4 cohorts of European ancestry as well as 3 cohorts
for replication analysis (European, African, and Asian ancestry)
to better understand the genetic architecture of sodium and
potassium intake and their ratio.
Methods
Participants
The European ancestry discovery sample (n = 6,519) included the Genetic Epidemiology Network of Arteriopathy (GENOA) (21), Prevention of REnal and Vascular ENd-stage Disease (PREVEND) (22), Hypertension Genetic Epidemiology Network European ancestry (HyperGEN EA) (21), and the Framingham Heart Study (FHS) (23). We maximized the sample size of the discovery set by including all European ancestry cohorts with high-quality sodium and potassium intake measurements, estimated with sodium and potassium excretion measured from 24-h (gold-standard measurement) or half-day urine samples. The replication sample included a European ancestry cohort with a different measurement method [Heredity and Phenotype Intervention Heart (HAPI Heart) Study (n= 844), spot urine samples] (24), and 2 cohorts from other ethnicities, one with African ancestry (HyperGEN AA; n = 1,246, half-day urine samples) (21) and one with Asian ancestry [Healthy Twin Study, Korea (HTS); n= 2,475, half-day and spot urine samples] (25). The replication sample allowed us to examine whether loci identified in the main analysis would replicate across measurement methods and across ethnicities (trans-ethnic loci). The descriptions and acknowledgments for participating cohorts are described in Supplemental Table 1. Institutional review boards at participating institutions approved all cohort-specific study protocols.
Measurements of sodium and potassium intake
Urinary sodium and potassium excretions were quantified as continuous variables (millimoles/day) from urine collections in each cohort. Sodium and potassium excretion in a 24-h urine sample is the gold standard for the assessment of sodium and potassium intake among individuals whose intake is in a steady state. Twenty-four-hour urine measurements have been shown to have higher validity for measuring sodium and potassium intake than methods based on self-report such as 24-h recalls, dietary records, or food-frequency questionnaires (20). For cohorts with half-day urine samples (HyperGEN and HTS), volume-time linear extrapolation was used to estimate 24-h urinary sodium and potassium excretions, and the Kawasaki formula was used for
TABLE 1 Characteristics of participating cohorts1 Replication Discovery GENOA (n= 811) PREVEND (n= 3649) FHS (n= 801) HyperGEN EA (n= 1258) HAPI Heart (n= 844) HyperGEN AA (n= 1246) HTS (n= 2475) Race/ethnicity EA EA EA EA EA AA Asian
Cohort Family Population Family Family Family Family Family
Country USA Netherlands USA USA USA USA South Korea
Female, % 57.6 51.5 53.2 50.4 46.6 67.0 64.0 Age, y 65.7± 9.1 49.6± 12.5 70.2± 7.62 50± 14 43.8± 14.0 45± 13 44.1± 13.3 SBP, mmHg 146± 22.8 129± 19.9 125± 16.2 123± 19.1 121± 14.6 129± 22.2 116± 17.0 DBP, mmHg 84.1± 10.8 74.1± 9.9 71.3± 9.6 70.7± 10.0 76.8± 8.7 74.0± 11.6 73.7± 10.9 Hypertension, % 88.2 34.4 52.6 52.2 13.6 63 10.7 BMI, kg/m2 30.9± 5.9 26.1± 4.3 28.1± 5.13 29.5± 6.13 26.6± 4.5 32.6± 8.04 23.7± 3.3 Urine measure 24-h urine 24-h urine 24-h urine Half-day urine Spot urine Half-day urine Half-day and spot
urine Sodium excretion, mmol/d 139± 58.3 144± 50.3 136± 57.0 203± 107.3 216± 50.8 237± 121.9 212± 77.8 Potassium excretion, mmol/d 58.5± 22.9 73.6± 21 67.9± 23.2 65.1± 36.3 47.9± 13.4 65.7± 41.4 84.0± 32.2 Sodium-to-potassium excretion ratio 2.5± 1.0 2.0± 0.7 2.1± 0.9 3.7± 1.9 4.7± 1.2 3.7± 2.3 2.7± 1.0 1For continuous variables, values are mean± SD, For binary variables, values are percentages. AA, African ancestry; BMI, body mass index; BP, blood pressure; DBP, diastolic blood pressure; EA, European ancestry; FHS, Framingham Heart Study; GENOA, Genetic Epidemiology of Arteriopathy; HAPI Heart, Heredity and Phenotype Intervention Heart Study; HTS, Healthy Twin Study, Korea; HyperGEN, Hypertension Genetic Epidemiology Network; PREVEND, Prevention of REnal and Vascular ENd-stage Disease; SBP, systolic blood pressure.
spot urine samples (HAPI Heart and HTS) (8, 26). Estimated 24-h sodium and potassium excretion measurements from half-day samples have relatively high correlation with measures from 24-h urine samples (Pearson correlation coefficient r= 0.84) (8), allowing us to use the sodium and potassium excretions measured and estimated from half-day urine samples in the discovery sample in order to increase power. The European ancestry cohort with spot urine samples, the HAPI Heart study, was used in a replication analysis because the correlation between 24-h urine measures and estimates from spot urine samples is lower (Pearson correlation coefficient r= 0.36–0.71) (27). The method of urinary sodium and potassium excretion measurement in each cohort is described inTable 1and Supplemental Table 2. In each study, 24-h urinary sodium and potassium excretion measures were c24-hecked for normality, and outliers> or <4 SDs from the mean were removed.
Genotyping
Genotypes for each cohort were obtained using either Affymetrix (Thermo Fisher Scientific, Inc.) or Illumina (Illumina, Inc.) genotyping arrays (Supplemental Table 3). Each cohort performed internal quality-control assessments of initial genotype data including omitting individuals with poor genotype call rate (i.e.,<95%) and checking for relatedness between participants. Quality checks for SNPs included checks for call rate, Hardy-Weinberg equilibrium, duplicate discordance rates, and monomorphic SNPs. Imputation was performed using the 1000 Genomes Project Phase I Integrated Release Version 3 (March 2012) cosmopolitan reference panel in each cohort with IMPUTE (28) or MACH (29).
Statistical analysis
GWASs.
To identify the genetic loci associated with sodium and potassium intake and the sodium-to-potassium intake ratio, GWAS analyses were conducted separately using the imputed genetic data from each cohort assuming an additive model. In HyperGEN, analysis was stratified by ethnicity. Age and sex were included as covariates in all GWAS analyses. Principal components were used to adjust for any potential population genetic stratification within each cohort (Supplemental Table 3). For family-based cohorts (GENOA, FHS, HyperGEN, HTS, and HAPI Heart), linear mixed-effects modeling with “family” as a random intercept was used to account for familial correlation. The statistical packages used for these analyses are described in detail in Supplemental Table 3. Each cohort applied a preliminary filter on their imputed data excluding variants with minor allele frequency (MAF) <1% or imputation quality measure (Rsq or INFO score) <0.1.
Although sodium and potassium intake may be correlated with total energy intake, we could not directly adjust for total energy intake because not all of our cohorts had this measurement. Instead, to partially account for energy intake, we repeated the analysis with added adjustment for body mass index (BMI). We also adjusted for height, because among individuals with the same BMI, taller individuals are likely to require a higher energy intake to maintain the same BMI. We confirmed the appropriateness of this approach using data from GENOA. Multivariate regression models showed that both BMI and height were significantly associated with 24-h urinary sodium and potassium excretion and there was no statistically significant correlation between BMI and height.
Meta-analysis and replication.
Cohort-specific GWAS results were first cleaned using EasyQC software 15.6 (30) to check the allele frequencies against those in the ancestry-specific 1000 Genomes Reference panel, and to harmonize genetic marker names across cohorts. We conducted a fixed-effects meta-analysis using the inverse-variance weightings across the discovery samples (GENOA, PREVEND, FHS, and HyperGEN EA) using the METAL package (31). GWAS results were corrected for study-specific genomic control λ values when λ was >1, and genomic control correction was again applied after meta-analysis. In order to be included in the final results, SNPs had to be present in≥2 of the discovery cohorts. Variants were further excluded if imputation quality measured <0.3. To account for multiple testing, we used ɑ levels of 5 × 10−8to define significant associations and 1× 10−6for suggestive associations. To assess heterogeneity of results across cohorts, we calculated the Cochran’s Q statistic, and we estimated the percentage of total variation across studies that was due to heterogeneity rather than chance for each SNP (I2statistic) (32). A cutoff of 25% of I2statistics was used to define low heterogeneity, 50% for moderate, and 75% for high heterogeneity (32). For the lead SNPs of each genomic region with at least a suggestive association in the meta-analysis of GWASs (P< 1 × 10−6), we examined the SNPs in the HAPI Heart study and in trans-ethnic follow-up cohorts (HyperGEN AA and HTS, Korea). A Bonferroni-corrected significance threshold was set accounting for the number of SNPs tested for each trait in the replication analysis (e.g., P< 0.007 for sodium excretion, P < 0.013 for potassium excretion, and P < 0.013 for sodium-to-potassium ratio).
Genomic risk loci and functional annotation.
We used Functional Mapping and Annotation of Genome-Wide Association Studies (FUMA) (33) to define the genomic risk loci, obtain functional annotations for the loci, and to annotate results
from our meta-analysis. Following the protocol presented in Savage et al. (34), “independent suggestive or significant SNPs” were identified using association P< 1.0 × 10−6 and linkage disequilibrium (LD) r2 < 0.6. We then selected the “lead SNPs,” which are a subset of the “independent suggestive or significant SNPs” that are independent at r2< 0.1. Finally, “genomic loci” were defined by combining any physically overlapping lead SNPs (LD blocks<250 kb apart). SNPs within these genomic loci that were in LD (r2≥ 0.6) with one of the “independent significant or suggestive SNPs” that had P< 1.0 × 10−4 were then functionally annotated using ANNOVAR (35) and mapped to genes.
Gene-based analysis.
Since our sample size for the meta-analysis is limited due to the difficult nature of collecting urine measures over a defined span of time, we conducted genome-wide gene-based analysis to identify genes that may go unnoticed in SNP-based analysis, using the Genome-Wide Gene Association Analysis (GWGAS) method in Multi-marker Analysis of GenoMic Annotation (MAGMA) (36) based on the results of the meta-analysis. GWGAS used the SNP-based P values from the meta-analysis as input and annotated the SNPs to the genes if they were located within the gene body using the NCBI 37.3 gene definition, and the resulting SNP P values were combined into a gene-based test statistic using the SNP-wise mean model. To correct for multiple testing, a stringent Bonferroni correction was applied to the results (0.05/18,805 genes tested, P< 2.7 × 10−6).
Pathway analysis and tissue expression analysis.
MAGMA gene-set analysis was conducted using FUMA to explore the involvement of specific biological pathways in the genetic etiology of our 3 phenotypes (33,36,37). The gene-set analysis uses the full distribution of SNP P values and is performed for curated gene sets and GO (Gene Ontology) terms derived from Msigdb version 6.2 (total of 10,678 gene sets). A significance threshold was set for all gene sets using Bonferroni-correction accounting (P< 0.05/10,678 = 4.7 × 10−6). We performed expression quantitative trait loci (eQTL) mapping in FUMA, which mapped the SNPs from the meta-analysis in the European discovery set to genes whose expression is likely to have been influenced by those SNPs, up to 1 Mb away (cis-eQTL, false discovery rate of the association<0.05). Since eQTLs are highly tissue specific, all tissue types were selected for the analysis. We then tested whether the mapped genes (defined as genes in which≥1 SNP was identified to be a cis-eQTL) were enriched for expression in a specific tissue type, using the Genotype Tissue Expression project (GTEx v7), by using the GENE2FUNC option in FUMA to identify differentially expressed gene (DEG) sets (genes which are significantly more or less expressed in a given tissue compared with others) (33,37). Tissue expression analysis using 53 specific tissue types were performed using a 2-sided Student’s t test, and the significance threshold was set following Bonferroni-correction accounting for all tested tissues (P< 0.05/53 = 0.0009).
Association with similar traits.
We examined whether SNPs previously reported by studies of the same or similar traits were replicated in our European ancestry meta-analysis results. We found 2 studies using spot urine samples from the UK Biobank (European ancestry) to examine the concentration (millimoles/liter) of sodium and potassium excretion (15), and sodium-to-creatinine, potassium-sodium-to-creatinine, and sodium-to-potassium ratios (16). We also found 2 studies using Asian ancestry samples, one examining 24-h urinary sodium and potassium excretion (mmol/d) estimated from spot urine (14) and the other examining salt sensitivity of blood pressure (18). For the SNPs reported by studies with samples of Asian ancestry, we tested for replication in both our European ancestry samples and our Asian ancestry samples (HTS, Korea). SNPs were defined as replicated for association with the same or similar traits if they reached a Bonferroni-corrected significance threshold in our results and had a concordant direction of the effect. We also considered a nominal significance threshold of P< 0.05. Finally, we examined whether our suggestive loci were replicated in the publicly available
GWAS summary statistics released by the 2 UK Biobank studies (15,16).
Results
Figure 1
shows an overview of the study design. The study
included 4 cohorts restricted to participants of European
ancestry with measures from 24-h or half-day urine samples in
the discovery set, and the replication set comprised 1 European
ancestry, 1 African ancestry, and 1 Asian ancestry cohorts with
measures from half-day or spot urine samples. The descriptive
characteristics of the 7 cohorts are presented in
Table 1
.
All cohorts were family-based except for PREVEND. Subjects
from 2 cohorts, GENOA and FHS, were 11.3 y older (mean
age
= 65.7 and 70.2 y, respectively; t test P < 0.0001) than
subjects from the other cohorts (range: 43.8–50 y). Average
24-h urinary sodium excretion was lower in cohorts with
24-h measures (GENOA, PREVEND, and FHS; range: 136.6–
144.9 mmol/d) and higher in those with half-day or spot urine
measures (HyperGEN, HTS, and HAPI Heart; range: 203.3–
237.8 mmol/d; t test P
< 0.0001). Average sodium-to-potassium
ratio was highest in HyperGEN and HAPI Heart (3.7–4.7) and
lowest in PREVEND and FHS (2.0–2.1). The prevalence of
hypertension was
>50% in GENOA and HyperGEN because
the participants of these 2 cohorts were recruited based on
their hypertensive status, while it was lower (10–30%) in other
cohorts except for FHS (52.6%).
We performed a meta-analysis of the 4 independent cohorts
restricted to participants of European ancestry (n
= 6519)
and identified 6, 3, and 4 genomic loci with at least
suggestive associations (P
< 1.0 × 10
−6) for 24-h sodium
excretion, 24-h potassium excretion, and their ratio, respectively
(
Table 2
). Additional adjustment for BMI and height produced
1 additional suggestive locus for sodium excretion and
1 for potassium excretion. Supplemental Figures 1 and 2
show the QQ plots and the Miami plots of the GWAS
meta-analysis results. The regional plots of each genomic locus are
presented in Supplemental Figure 3. The 2 variants that reached
genome-wide significance were for sodium-to-potassium ratio
after further adjustment for BMI and height: rs77958157 on
chromosome 5 near the cocaine- and amphetamine-regulated
transcript prepropeptide (CARTPT) gene (P
= 2.33 × 10
−8) and
rs72860355 on chromosome 6 near the proteasome 20S subunit
beta 9 (PSMB9) gene (P
= 3.77 × 10
−8). The associations
between SNPs and urinary measures had low heterogeneity
(I
2< 25%), except for a few genomic loci from the 24-h
potassium-excretion GWAS, based on I
2values (mean value
of I
2: 0, 28.1, and 11.5 for 24-h sodium excretion, 24-h
potassium excretion, and their ratio, respectively;
Table 2
). The
histogram of the I
2statistic for each meta-analysis is shown in
Supplemental Figure 4. More than 70% of SNP associations
had low heterogeneity (I
2< 25%) and only 1.2–1.3% had
considerable heterogeneity (I
2> 75%).
For each genomic locus from the meta-analysis of GWASs,
Supplemental Figure 5 shows the summary information
in-cluding size (kilobase) of the locus and the number of SNPs
(P
< 1.0 × 10
−4) in LD (r
2≥ 0.6) with one of the independent
significant or suggestive SNPs. Of all the top SNPs of each
genomic locus (n
= 15), 6 were in intronic regions and the
remainder were in intergenic regions (
Table 2
). The distributions
of functional annotations of SNPs (P
< 1.0 × 10
−4) in LD
(r
2≥ 0.6) with one of the independent significant or suggestive
FIGURE 1 Overview of study design and study participants. AA, African ancestry; EA, European ancestry; FHS, Framingham Heart Study;
FUMA, Functional Mapping and Annotation of Genome-Wide Association Studies; GENOA, Genetic Epidemiology of Arteriopathy; GWGAS, Genome-Wide Gene Association Analysis; HAPI Heart, Heredity and Phenotype Intervention Heart Study; HTS, Healthy Twin Study, Korea; HyperGEN, Hypertension Genetic Epidemiology Network; MAGMA, Multi-marker Analysis of GenoMic Annotation; PREVEND, Prevention of REnal and Vascular ENd-stage Disease.
SNPs for each meta-analysis are shown in Supplemental
Figure 6.
Out
of
15
significant
or
suggestive
genomic
loci
(P
< 1.0 × 10
−6) from the meta-analysis in the discovery
set, 2 loci (rs34473523 and rs12094702) had a P value
<0.05
either in the independent European ancestry (HAPI Heart
with n
= 844), African ancestry (HyperGEN with n = 1,246),
and/or Asian ancestry cohorts (HTS with n
= 2,448), and
the direction of the effect of each SNP was consistent with
the discovery set (
Table 3
). To inspect the regions of these
2 loci, regional plots (
Figure 2
) were created to visualize the
LD patterns within these 2 loci for 24-h urinary potassium
excretion and 24-h urinary sodium excretion, respectively, in
the European ancestry meta-analysis. One SNP (rs12094702,
associated with 24-h sodium excretion) near gene zinc finger
SWIM-type containing 5 (ZSWIM5) was replicated in the
Asian population (P
= 0.007) and remained significant even
after Bonferroni multiple testing correction. rs34473523 on
chromosome 13 near sodium leak channel (NALCN) was
nominally associated with 24-h potassium excretion both in
the European and African ancestry populations (P
< 0.05), but
the P values did not reach Bonferroni-corrected significance
levels. The effect size of rs34473523 in the discovery set
(B
= 2.06) was comparable to the effect size of the SNP in
the European ancestry replication cohort (β = 1.3), but much
smaller than that from the African ancestry replication cohort
(B
= 7.6). Gene-based tests identified 1 genome-wide significant
gene, CDC42 small effector 1 (CDC42SE1), from the 24-h
sodium excretion meta-analysis (P
= 1.4 × 10
−6; Supplemental
Figure 7). Pathway analysis of genes near suggestive loci
using MAGMA (
36
) did not identify significant enrichment of
specific biological pathways after Bonferroni multiple testing
correction (Supplemental Table 4). Tissue enrichment analysis
of gene expression using DEG sets across 53 specific tissue types
with sodium-to-potassium ratio identified significantly higher
expression of the mapped genes in tissues including bladder
(P
= 5.8 × 10
−6), cervix (P
= 0.0004), vagina (P = 0.0002),
and coronary artery tissues (P
= 0.0007) (
Figure 3
).
In association analyses of previously identified loci for the
same or similar traits, none of the findings from previous studies
were replicated in our European ancestry meta-analyses when
using a Bonferroni-corrected significance threshold. However,
6 out of 50 loci for the spot urine sodium excretion measure
from Pazoki et al. (
15
) had P
< 0.05 in our European
ancestry meta-analysis of 24-h urinary sodium excretion and
the direction of effects was consistent for all loci except for
one (Supplemental Table 5). One locus for sodium-to-creatinine
ratio and 1 locus for potassium-to-creatinine ratio identified by
the Zanetti et al. (
16
) GWAS had P
< 0.05 with 24-h sodium
excretion and 24-h potassium excretion, respectively, in our
European ancestry meta-analyses, and the direction of effects
was consistent (Supplemental Table 6). Seven out of 9 SNPs
in the SCNN1G gene region previously identified by the Yang
et al. (
14
) sodium excretion association study (24-h estimated
from spot urine samples) or the Zhao et al. (
18
) salt sensitivity
of blood pressure in Asian samples association study had
TA B L E 2 Disco v e ry met a -analy sis results fo r 24-h s odium e x cretion, 24-h pot assium e x cretion, and s odium-to-pot assium ratio genomic loci in European a nce str y cohorts (P < 1 × 10 − 6) 1 Meta-analysis o f G W A S from G ENOA, PREVEND, H yperGEN E A, and FHS BMI and height unadjusted 2 BMI and height adjusted 3 Outcome-SNP N earest gene(s) 4 Chr:position 5 Alleles E AF n β 6 SE 6 P Dir . 7 I 2 QP β 6 SE 6 P Dir . 7 I 2 QP 24-h sodium excretion, mmol/d rs12094702 ZSWIM5 1:45714817 A/G 0.98 5243 17.8 3.92 5.80 × 10 − 6 ++ ?+ 0 0.76 19.1 3.73 3.31 × 10 − 7 ++ ?+ 00 .7 0 rs16852403 RASAL2-AS1 1:178039226 T/C 0.80 6500 5.86 1.18 6.84 × 10 − 7 ++++ 0 0.40 5.42 1.12 1.39 × 10 − 6 ++++ 00 .4 9 rs847573 RN7SL13P 7:97681761 T/C 0.28 6500 –5.23 1.06 7.47 × 10 − 7 —-0 0.40 – 5.04 1.01 5.38 × 10 − 7 — + 10.4 0.34 rs139574219 IMMP2L 7:110287083 T/C 0.99 1608 –47.4 9.27 3.21 × 10 − 7 -??-0 0.51 – 43.5 8.81 7.88 × 10 − 7 -??-6.5 0.30 rs188869607 CTD-2377D24.8 8 17:46764522 A/T 0.48 6500 5.26 1.05 5.63 × 10 − 7 ++ -+ 0 0.44 5.09 1.00 3.70 × 10 − 7 ++ -+ 0.8 0.39 rs11880134 NUCB1: N UCB1-AS1 8 19:49417246 A/G 0.45 4442 7.91 1.60 7.69 × 10 − 7 ++ ?? 0 0.98 6.90 1.52 5.94 × 10 − 6 ++ ?? 0 0.77 rs7291524 GTPBP1 22:39100545 T/C 0.04 6500 12.8 2.52 3.40 × 10 − 7 ++++ 0 0.85 9.60 2.40 6.43 × 10 − 5 ++++ 00 .7 1 24-h potassium excretion, mmol/d rs78881198 CUL3 8 2:225434223 T/C 0.01 2056 19.1 4.04 2.32 × 10 − 6 ?? ++ 0 0.42 19.6 4.00 9.77 × 10 − 7 ?? ++ 00 .3 3 rs34473523 NALCN 8 13:101717401 A/C 0.33 6502 2.06 0.42 9.60 × 10 − 7 ++++ 29.2 0.24 1.87 0.41 6.09 × 10 − 6 ++++ 32.2 0.22 rs858673 CDC27 17:45268929 A/G 0.41 6502 –2.03 0.40 5.21 × 10 − 7 –+ -39.3 0.18 – 1.91 0.40 1.62 × 10 − 6 –+ -3 9. 9 0. 17 rs111345501 RP3-400N23.6 8 22:31719404 T/G 0.01 4890 12.7 2.58 9.04 × 10 − 7 ?++ ? 44.1 0.18 13.6 2.53 8.34 × 10 − 8 ?++ ?5 1. 1 0. 15 Sodium-to-potassium ratio rs4845198 RP11-398M15.1 1:189786356 A/G 0.18 6495 –0.10 0.02 5.02 × 10 − 7 —-0 0.91 – 0.10 0.02 1.11 × 10 − 7 —-0 0.89 rs72824746 SH3RF3 8 2:110034953 T/C 0.08 6495 0.17 0.03 8.78 × 10 − 7 ++++ 0 0.63 0.15 0.03 7.61 × 10 − 6 ++++ 00 .7 5 rs77958157 CARTPT 5:71166807 A/C 0.01 4413 0.51 0.09 5.46 × 10 − 8 ++ ?? 45.9 0.17 0.52 0.09 2.33 × 10 − 8 ++ ?? 41.2 0.19 rs72860355 PSMB9 6:32836582 T/G 0.01 4407 0.41 0.08 1.54 × 10 − 7 ?+ ?+ 0 0.88 0.42 0.08 3.77 × 10 − 8 ?+ ?+ 00 .7 2 1T h e S NPs w ith s trongest P v a lue from e ac h o f the genomic risk loci are p resented (LD r 2< 0.1 a nd LD bloc ks < 250 kb apart). A lleles, ef fe ct allele (coded allele)/non–ef fe ct allele (noncoded allele); Chr , ch romosome; D ir ., direction o f e ff ect in GENO A, PREVEND , HyperGEN E A, and F HS in European a ncestr y, respectiv e ly; E A, European a ncestr y; EAF , ef fe ct allele frequency; FHS , F ramingham H ear t S tudy; G ENO A , G enetic Epidemiology Net w ork o f A rteriopath y; HyperGEN, Hypertension G enetic Epidemiology Net w ork; LD , linkage d isequilibrium; P REVEND , P re v ention o f R Enal and V ascular E Nd-st a ge Disease; QP , C oc hran ’s Q test P v a lue; SNP , single nucleotide polymorphism. 2A g e a nd se x w ere a djusted in a model. 3A ge, se x, BMI, and height w e re adjusted in a m odel. 4Gene names w ere obt ained using A NNO V A R build v e rsion 1 9. 5P o sitions are b ased o n build 37 . 6Units for β and S E a re mmol/d. 7Th e “+ ” symbol indicates a positiv e d irection of ef fe ct, the “-” symbol indicates a negativ e direction o f e ff ect, and “ ?” indicates that the c ohort w as not in cluded in the m et a-analy s is. 8Indicates the S NP is within the gene boundaries.
TABLE 3 Replication analysis results of SNPs from the meta-analysis of 24-h sodium excretion, 24-h potassium excretion, and
sodium-to-potassium ratio in European, African, and Asian ancestry cohorts1
BMI and height unadjusted2
BMI and height adjusted3
Ancestry (cohort)—outcome SNP Nearest gene4 Chr:position5 n Alleles EAF β6 SE6 P β6 SE6 P
European ancestry (HAPI Heart Study)
24-h potassium excretion, mmol/d rs34473523 NALCN7 13:101717401 844 A/C 0.59 1.30 0.64 0.043 1.33 0.64 0.037
African ancestry (HyperGEN)
24-h potassium excretion, mmol/d rs34473523 NALCN7 13:101717401 1246 A/C 0.95 7.60 3.76 0.043 7.42 3.76 0.048
Asian ancestry (HTS, Korea)
24-h sodium excretion, mmol/d rs12094702 ZSWIM5 1:45714817 2448 A/G 0.82 5.49 2.17 0.007∗ 4.90 2.14 0.014
1Results displayed are for SNPs with P< 1 × 10−6in European discovery meta-analysis and P< 0.05 in ≥1 independent replication set.∗Reaching Bonferroni-corrected
significance. Alleles, effect allele (coded allele)/non–effect allele (noncoded allele); Chr, chromosome; EAF, effect allele frequency; HAPI Heart, Heredity and Phenotype Intervention Heart; HTS, Healthy Twin Study, Korea; HyperGEN, Hypertension Genetic Epidemiology Network; SNP, single nucleotide polymorphism.
2Age and sex were adjusted in a model.
3Age, sex, BMI, and height were adjusted in a model. 4Gene names were obtained using ANNOVAR build version 19. 5Positions are based on build 37.
6Units forβ and SE are mmol/d.
7Indicates the SNP is within the gene boundaries
P
< 0.05 in our European ancestry meta-analyses of
sodium-to-potassium ratio (Supplemental Table 7), but none remained
significant after adjusting for multiple testing. Additionally,
none of these SNPs had P
< 0.05 in our Asian ancestry GWAS
results (HTS, Korea).
When we attempted to replicate our findings using publicly
available summary statistics for spot urine sodium and
potas-sium excretion traits (the concentration of sodium/potaspotas-sium
excretion, sodium/potassium-creatinine ratio, and
sodium-to-potassium ratio), none of the findings were replicated in our
FIGURE 2 Regional association plots of discovery GWAS meta-analysis loci with P< 10−6in European ancestry and replication P< 0.05 in≥1 independent replication set. Two loci had a P value <0.05 either in the independent European ancestry (HAPI Heart with n = 844), African ancestry (HyperGEN with n= 1246), and/or Asian ancestry cohorts (HTS with n = 2448). (A) rs34473523 with 24-h potassium excretion, unadjusted for BMI and height. (B) rs12094702 with 24-h sodium excretion adjusted for BMI and height. The y-axis indicates the - log10 P value of the SNP association with the urine measure from the discovery GWAS meta-analysis, and the x-axis represents the genomic position. The Hg19/1000 Genomes (Mar 2012 EUR) reference panel was used to make the plots. The level of LD between a SNP and the lead SNP (purple) is indicated by color. AKR1A1, aldo-keto reductase family 1 member A1; CCDC163P, coiled-coil domain containing 163; CCDC17, coiled-coil domain containing 17; EIF2B3, eukaryotic translation initiation factor 2B subunit gamma; GWAS, genome-wide association study; HAPI Heart, Heredity and Phenotype Intervention Heart; HECTD3, HECT domain E3 ubiquitin protein ligase 3; HPDL, 4-hydroxyphenylpyruvate dioxygenase like; HTS, Healthy Twin Study, Korea; HyperGEN, Hypertension Genetic Epidemiology Network; ITGBL1, integrin subunit beta like 1; LD, linkage disequilibrium; LINC00411, Long Intergenic Non-Protein Coding RNA 411; LINC01144, Long Intergenic Non-Protein Coding RNA 1144; MMACHC, metabolism of cobalamin associated C; MUTYH, mutY DNA glycosylase; NALCN, sodium leak channel, non-selective; NALCN-AS1, NALCN antisense RNA 1; NASP, nuclear autoantigenic sperm protein; PRDX1, peroxiredoxin 1; SNP, single nucleotide polymorphism; TESK2, testis associated actin remodelling kinase 2; TMTC4, transmembrane O-mannosyltransferase targeting cadherins 4; TOE1, target of EGR1, exonuclease; UROD, uroporphyrinogen decarboxylase; ZSWIM5, zinc finger SWIM-type containing 5.
FIGURE 3 DEG sets across 53 specific tissue types using GTEx v7 with sodium-to-potassium ratio in European discovery meta-analysis
results. Analysis includes genes selected from eQTL mapping, which mapped the SNPs from the meta-analysis in the European discovery set to genes whose expression is likely to have been influenced by those SNPs, up to 1 Mb away (cis-eQTL, false discovery rate of the association <0.05). Tissues showing significant enrichment after Bonferroni correction accounting for all tested tissues (P < 0.05/53 = 0.0009) are colored in red. DEG, differentially expressed gene (genes that are significantly more or less expressed in a given tissue compared to others); EBV, Epstein-Barr virus; eQTL, expression quantitative trait loci; SNP, single nucleotide polymorphism.
results at a Bonferroni-corrected significance threshold. When
using a nominal P-value cutoff of 0.05, 2 loci for sodium
ex-cretion (rs12094702 and rs7291524) were replicated in Pazoki
et al. (
15
) and 1 locus for sodium-to-potassium excretion ratio
(rs4845198) was replicated in Zanetti et al. (
16
) (Supplemental
Table 8).
Discussion
Using 4 European ancestry discovery cohorts with measures
from 24-h or half-day urine samples, we identified a total of
7, 4, and 4 significant or suggestive loci (P
< 1.0 × 10
−6)
associated with 24-h sodium excretion, 24-h potassium
excre-tion, and sodium-to-potassium ratio, respectively, followed by
1 additional gene in the gene-based analysis. In a replication
analysis, 1 locus for 24-h sodium excretion was significantly
replicated in an Asian ancestry cohort reaching
Bonferroni-corrected significance, and 1 locus for 24-h potassium excretion
was associated at a nominal P value (P
< 0.05) with 24-h
potassium excretion both in European and African ancestry
cohorts.
The most significant SNP in the meta-analysis was
rs77958157 near CARTPT for sodium-to-potassium ratio
(associated with an increase of 0.51 mmol/d). However,
the association was not significant in the replication analyses,
possibly due to the relatively low MAF of this variant (1% in
Eu-ropean ancestry). CARTPT encodes the cocaine-amphetamine–
regulated transcript (CART) prepropeptide neurotransmitters,
which are associated with eating behavior, appetite, energy
expenditure, and obesity in humans (
38
) and with blood
pressure in rabbits (
39
). Since dietary sodium-to-potassium
ratio has also been considered an independent risk factor for
obesity and hypertension (
6
,
40
), this finding may be utilized
in future studies to better understand the genetic architecture
of sodium-to-potassium ratio and related outcomes. The gene
CDC42SE1 was significant in the gene-based analysis of sodium
excretion, which may be attributable to its GTPase inhibitor
activity, which is associated with blood pressure regulation,
kidney function, and other cardiovascular traits (
41
).
The SNP that had a replicated association with sodium
excretion in the Asian ancestry cohort after Bonferroni
correction, rs12094702, is near ZSWIM5, a gene that plays a
role in neural development and physiology (
42
,
43
). This is a
particularly interesting finding in light of animal studies that
have also suggested that salt appetite is regulated by neural
controls (
44
). The suggestive genetic locus for 24-h potassium
excretion with the lead SNP rs34473523 (P
= 9.6 × 10
−7)
is located in the intronic region of NALCN (sodium leak
channel) on chromosome 13. Although the multiple SNPs in
LD with rs34473523 also had suggestive associations (
Figure 2
)
and the lead SNP was nominally associated both in European
and African ancestry replication sets (P
< 0.05), the P values
did not reach the Bonferroni-corrected significance threshold.
NALCN encodes a voltage-gated sodium and calcium channel
and is involved in neuronal excitability. Its biological function
includes calcium ion transmembrane transport and potassium
ion transmembrane transport. Further studies are needed to
examine the mechanisms through which this gene may be
related to potassium intake.
The evidence from our tissue expression analysis indicates
that bladder, cervix, vagina, and coronary artery function might
relate to the genetics of the dietary sodium-to-potassium ratio.
Research has shown that high blood pressure is associated
with bladder dysfunction (
45
), but the association between
sodium/potassium intake and human bladder function has
received little attention. Researchers reported a causative
association between a high-salt diet and bladder dysfunction in
Dahl salt-sensitive rats, and they suggested that upregulation
of epithelial sodium channel
ɑ in the bladder epithelium
might be responsible (
46
). Rodriguez et al. (
47
) found an
association between sodium-to-potassium excretion ratio and
left ventricular mass (LVM), which is closely related to coronary
artery risk development and is an independent predictor of
morbidity and mortality from CVDs. They also found that
the LVM was more robustly associated with the
sodium-to-potassium ratio than either sodium or sodium-to-potassium excretion
alone. Our study suggests that the association of dietary
sodium-to-potassium ratio with bladder and coronary artery
function may involve underlying genetic variants that influence
both dietary intake and distal organ function (bladder and/or
coronary arteries).
To our knowledge, there have been a limited number of other
genome-wide investigations of daily sodium and potassium
intake. Recently, Yang et al. (
14
) conducted a candidate
gene association study with 24-h urinary sodium excretion
estimated from spot urine in an Asian ancestry sample and
found 6 significant SNPs in the epithelial sodium channel
gene (SCNN1G) region. We examined the association of these
SNPs with 24-h urinary sodium excretion and
sodium-to-potassium ratio in our European ancestry meta-analysis results,
and found that almost all of these SNPs replicated with a
sodium-to-potassium ratio at P
< 0.05. Two recent UK Biobank
papers identified multiple loci for sodium/potassium excretion
(mmol/d), sodium/potassium-to-creatinine ratio, and
sodium-to-potassium ratio measure from spot urine samples, but their
traits were based on the concentration in spot urine samples, not
representing daily sodium excretion amount as in the current
study, which might explain the lower levels of replication
between these papers and our results.
There has been increasing evidence that common SNPs
associated with complex human phenotypes are often shared
across ethnicities (
48
) and alleles at GWAS signals often have
concordant directions of effect across ethnicities (
49
). In our
trans-ethnic follow-up study, all loci with a replication P
value
<0.05 had concordant directions of effect with those in
European ancestry discovery meta-analysis. However, this result
should be interpreted with caution because each ancestry might
have a different LD structure (
48
).
Our results should be interpreted with caution because,
although excretion is highly correlated with intake, there are
other contributing factors, such as excretion efficiency, that
may also be under genetic influence. In addition, some of
the participants in this study (i.e., GENOA and HyperGEN)
were selected based on a family history of hypertension, which
may have led some participants to alter their dietary patterns
in order to manage their blood pressure levels. However,
we examined mean sodium intake across these 2 groups of
participants, and sodium intake was higher for those with
hypertension than those without hypertension in both cohorts,
suggesting that there was not notable dietary modification in
individuals with hypertension. Last, although we added BMI
and height as a proxy for energy intake in the second model,
we were not able to fully adjust for the influence of
food-intake quantities on sodium and potassium food-intake, or for other
potential confounding variables including individual dietary
pattern, geographic location, and cultural differences. One
possible reason for the low rate of significant association in
the replication analysis is the different method of measuring
sodium/potassium intake in the meta-analysis (using 24-h or
half-day urine samples) and the replication (half-day urine
samples or spot urine samples). Thus, the results should be
interpreted with caution because sodium/potassium excretion
measured from spot urine samples varies by timing of spot
urine collection and metabolic excretion rates (
50
). Another
reason for relative lack of replication may be related to differing
characteristics of participants in multiethnic populations, which
may include different amounts of sodium/potassium intake. It
is possible that genetic effects may only be present at certain
amounts of sodium or potassium intake, and thus may only be
contributing in cohorts with higher or lower amounts of intake.
A notable strength of our research includes having cohorts in
the discovery stage with high-quality measurements of sodium
and potassium intake using 24-h or half-day urine samples,
and low heterogeneity in the European ancestry meta-analysis
of GWAS results across cohorts. Only a few epidemiologic
cohorts have data for these important phenotypes, because
collecting 24-h urine samples in large epidemiologic studies is
both challenging and expensive. To our knowledge, this is the
first study to conduct a GWAS sodium and potassium intake
analysis as well as their ratio in cohorts of multiple ancestries
with measures from 24-h or half-day urine samples.
In the current study, we identified suggestive genetic loci
associated with 24-h urinary sodium and potassium excretion,
but these loci require further replication in independent cohorts
with larger sample sizes. Further work is also required to
identify functional variants in these genomic regions and to
investigate their link to CVD outcomes and other chronic
diseases. An improved understanding of genetic influences
on sodium and potassium intake may eventually lead to an
improved ability to assist individuals in managing their risk.
Acknowledgments
The authors’ responsibilities were as follows—MK, SLRK, JAS,
STT, JCL, MRI, DKA, PvdH, and RTG: designed the research;
MK, JAS, JEL, JS, AB, and SKP: wrote the manuscript; MK, JAS,
WZ, EBW, LS, NV, and KAR: analyzed the data; JCL, JEL, XZ,
YPCC, WZ, YAS, and KMK: assisted with data interpretation
and manuscript revisions; MK: had primary responsibility for
final content; and all authors: read and approved the final
manuscript.
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