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Genetically Determined Hypoalbuminemia As a Risk Factor for Hypertension: Instrumental Variable Analysis Jong Wook Choi1, Joon‑Sung Park2* & Chang Hwa Lee2*

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Genetically Determined Hypoalbuminemia As a Risk Factor for Hypertension: Instrumental Variable Analysis Jong Wook Choi1, Joon‑Sung Park2* & Chang Hwa Lee2* www.nature.com/scientificreports OPEN Genetically determined hypoalbuminemia as a risk factor for hypertension: instrumental variable analysis Jong Wook Choi1, Joon‑Sung Park2* & Chang Hwa Lee2* Hypoalbuminemia is associated with vascular endothelial dysfunction and the development of chronic cardiovascular diseases. However, the relationship between serum albumin concentration and blood pressure changes remains controversial. Community‑based longitudinal cohort data collected from Korean Genome and Epidemiology Study were used in this study. Hypoalbuminemia was defned as a serum albumin concentration of ≤ 4.0 g/dL. A total of 4325 participants were categorized into control (n = 3157) and hypoalbuminemia (n = 1168) groups. Serum albumin had a non‑linear relationship with the risk of hypertension development. A genome‑wide association study revealed 71 susceptibility loci associated with hypoalbuminemia. Among susceptibility loci, genetic variations at rs2894536 in LOC107986598 and rs10972486 in ATP8B5P were related to elevated blood pressure. Serum albumin (HR = 0.654, 95% CI 0.521–0.820) and polymorphisms of rs2894536 (HR = 1.176, 95% CI 1.015–1.361) and rs10972486 (HR = 1.152, 95% CI 1.009–1.316) were signifcant predictors of hypertension development. Increased albumin concentration instrumented by 2 hypoalbuminemia‑associated SNPs (rs2894536 and rs10972486) was associated with decreased HRs for hypertension development (HR = 0.762, 95% CI 0.659–0.882 and HR = 0.759, 95% CI 0.656–0.878). Our study demonstrated that genetically determined hypoalbuminemia is a signifcant predictor of incipient hypertension. Albumin, one of the major serum proteins, has multiple important physiological functions involving stabilization of plasma colloid osmotic pressure, transportation of diverse substances, and signifcant antioxidant activity, and its concentration is fnely regulated by various systems in the physiologic state 1. Hypoalbuminemia is strongly related to unfavorable health outcomes in various pathologic conditions, including hospitalized patients, surgical patients, and those with heart failure, chronic liver disease, chronic kidney disease, or end-stage renal disease 2–4. Furthermore, recent epidemiologic studies have shown that low serum albumin concentration is a reliable clinical biomarker of vascular endothelial dysfunction and is an important predictor of future cardiovascular diseases (CVDs) and all-cause mortality in the general population5–8. Hypertension is a well-known modifable risk factor in the development and progression of chronic CVDs 9. Te vascular endothelium is the primary site of systemic hemodynamic dysfunction in various metabolic and vascular diseases10. Vascular endothelial dysfunction is mainly characterized by the induction of a pro-infamma- tory or pro-thrombotic state and impairment in endothelium-dependent relaxation of blood vessels 10,11, which may play critical roles in the pathogenesis of hypertension. However, the pathophysiologic connection between hypoalbuminemia and hypertension has not yet been clarifed. Tere has been inconsistent evidence on the relationship between serum albumin concentration and the risk of hypertension. Previously, Hu et al. and Høstmark et al. showed that a rise in serum albumin levels was associated with elevated systolic blood pressure (SBP) and diastolic blood pressure (DBP) in a Caucasian population12,13. Recently, Oda et al. demonstrated that a decreased serum albumin level was also a signifcant predictor of hypertension in a Japanese health population 14. Such fndings may indicate that possible confound- ers, such as diferences across racial groups and selection bias, could alter the impact of serum albumin levels on the development of hypertension. Instrumental variables can be used to help address the efect of unobserved confounders by operating as a randomization process when evaluating the association between environmental exposures and outcomes of interest. Tus, we performed a genome-wide association study (GWAS) to identify 1Research Institute of Medical Science, Konkuk University School of Medicine, Chungju, South Korea. 2Department of Internal Medicine, Hanyang University College of Medicine, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, South Korea. *email: [email protected]; [email protected] Scientifc Reports | (2021) 11:11290 | https://doi.org/10.1038/s41598-021-89775-3 1 Vol.:(0123456789) www.nature.com/scientificreports/ Albumin (g/dL) > 4 ≤ 4 Variable (n = 3157) (n = 1168) P Age (year) 48.9 ± 7.9 51.1 ± 8.7 < 0.0001 Sex (male, %) 1625 (51.5) 334 (28.6) < 0.0001 Smoker (n, %) 889 (28.2) 226 (19.3) < 0.0001 Body mass index (kg/m2) 24.0 ± 3.1 23.9 ± 2.9 0.6863 Waist circumference (cm) 80.5 ± 8.6 79.9 ± 8.2 0.1709 Systolic BP (mmHg) 113.4 ± 10.8 113.2 ± 11.1 0.4836 Diastolic BP (mmHg) 76.0 ± 7.3 74.7 ± 7.5 < 0.0001 White blood cell (109/L) 6.4 ± 1.7 6.3 ± 1.9 0.0113 Hemoglobin (g/dL) 13.6 ± 1.5 12.8 ± 1.5 < 0.0001 Platelet (103/μL) 263.1 ± 61.5 259.9 ± 61.7 0.5100 Total protein (g/dL) 7.4 ± 0.4 6.9 ± 0.3 < 0.0001 Albumin (g/dL) 4.4 ± 0.3 3.9 ± 0.1 < 0.0001 Calcium (mg/dL) 9.3 ± 0.6 9.5 ± 0.4 < 0.0001 Fasting glucose (mg/dL) 82.9 ± 8.4 79.5 ± 6.9 < 0.0001 Post-prandial glucose (mg/dL) 113.8 ± 29.9 109.3 ± 27.9 0.0001 Hemoglobin A1c (%) 5.50 ± 0.34 5.51 ± 0.34 0.3316 eGFRa (mL/min/1.73 m2) 93.2 ± 13.7 97.7 ± 11.3 < 0.0001 Total bilirubin (mg/dL) 0.7 ± 0.3 0.5 ± 0.2 < 0.0001 Aspartate aminotransferase (IU/L) 28.2 ± 13.5 28.5 ± 19.4 < 0.0001 Alanine aminotransferase (IU/L) 26.2 ± 20.6 24.3 ± 22.8 < 0.0001 γ-Glutamyl transferase (IU/L) 28.3 ± 34.4 26.1 ± 71.9 < 0.0001 Triglyceride (mg/dL) 135.9 ± 86.0 146.0 ± 90.1 < 0.0001 HDL-cholesterol (mg/dL) 45.7 ± 10.1 44.0 ± 9.7 < 0.0001 LDL-cholesterol (mg/dL) 101.5 ± 27.8 118.0 ± 31.2 < 0.0001 C-reactive protein (mg/dL) 0.19 ± 0.39 0.23 ± 0.55 0.2859 UACR (mg/g Cr) 10.1 ± 6.2 9.7 ± 6.7 0.3833 Table 1. Baseline characteristics grouped by serum albumin concentration. Results are expressed as the mean ± standard deviation or as frequencies (and proportions). BP, blood pressure; eGFR, estimated glomerular fltration rate; HDL, high-density lipoprotein; LDL, low-density lipoprotein; UACR, urine albumin/ creatinine ratio; Cr, creatinine. a Estimated using the Chronic Kidney Disease Epidemiology Collaboration equation. genetic variants associated with hypoalbuminemia and instrumental variable analysis to establish robust causal relationships between genetically determined hypoalbuminemia and the development of hypertension in a community-based cohort population. Results Baseline characteristics. Te participants (n = 4325) comprised 1959 men and 2366 women, with a mean age of 49.5 ± 8.2 years. Tey were categorized into two groups according to their serum albumin levels. Partici- pants with hypoalbuminemia were older and more likely to have elevated DBP, decreased hemoglobin, increased eGFR, and poor lipid profles; there were more female subjects than male subjects with hypoalbuminemia. Par- ticipants with normal serum albumin levels had increased white blood counts, fasting glucose, and postprandial glucose. Other demographic data and clinical characteristics are presented in Table 1. Relationship between hypoalbuminemia and blood pressure. We performed linear regression analysis using age, sex, and smoking history as covariates and found that serum albumin levels were closely related with DBP, hemoglobin, platelet, total protein, calcium, fasting glucose, postprandial glucose, eGFR, total bilirubin, γ-glutamyl transferase, HDL-cholesterol, LDL-cholesterol, and C-reactive protein levels (Table 2). However, our restricted cubic spline regression analysis showed that there may be a non-linear relationship between serum albumin concentration and changes in blood pressure (Fig. 1). De novo GWAS for hypoalbuminemia. We examined genetic data from 1168 participants with hypoal- buminemia (case) and 3157 participants with non-hypoalbuminemia (control) from the Ansan-Anseong cohort of the Korean Genome and Epidemiology Study (KoGES). Afer a standard quality control procedure, we obtained genotyping results for 519,364 SNPs and generated a quantile–quantile plot (Supplementary Fig. S1). Te genomic infation factor λ was 1.0206 in the quantile-quantile plot and the observed p-values show an early Scientifc Reports | (2021) 11:11290 | https://doi.org/10.1038/s41598-021-89775-3 2 Vol:.(1234567890) www.nature.com/scientificreports/ Crude Model I Parameter β P β P Age (year) − 0.0070 < 0.0001 Sex (vs male) 0.2021 < 0.0001 Smoking history (vs never smoker) − 0.0707 < 0.0001 Systolic BP (mmHg) − 0.0001 0.9211 Diastolic BP (mmHg) − 0.0047 < 0.0001 − 0.0005 < 0.0001 Body mass index (kg/m2) − 0.0031 0.4377 Waist circumference (cm) − 0.0005 0.4193 White blood cell (109/L) 0.0104 0.0002 0.0029 0.2720 Hemoglobin (g/dL) 0.0647 < 0.0001 0.0391 < 0.0001 Platelet (103/μL) 0.0006 0.0006 0.0004 < 0.0001 Total protein (g/dL) 0.5119 < 0.0001 0.4824 < 0.0001 Calcium (mg/dL) − 0.2856 < 0.0001 − 0.2686 < 0.0001 Fasting glucose (mg/dL) 0.0141 < 0.0001 0.0117 < 0.0001 Post-prandial glucose (mg/dL) 0.0011 < 0.0001 0.0016 < 0.0001 Hemoglobin A1c (%) − 0.0284 0.0517 eGFR (mL/min/1.73 m2) − 0.0093 < 0.0001 − 0.0077 < 0.0001 Total bilirubin (mg/dL) 0.3306 < 0.0001 0.2403 < 0.0001 Aspartate aminotransferase (IU/L) − 0.0001 0.8388 Alanine aminotransferase (IU/L) 0.0008 0.0006 0.0003 0.1320 γ-Glutamyl transferase (IU/L) 0.0003 0.0001 0.0002 0.0219 Triglyceride (mg/dL) − 0.0002 0.0001 − 0.0001 0.5488 HDL-cholesterol (mg/dL) 0.0051 < 0.0001 0.0037 < 0.0001 LDL-cholesterol (mg/dL) − 0.0037 < 0.0001 − 0.0037 < 0.0001 C-reactive protein (mg/dL) − 0.0385 0.0002 − 0.0300 0.0075 UACR (mg/g Cr) 0.0008 0.2875 Table 2.
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