Prevalence of Homocysteine‐Related Hypertension in Patients With Chronic Kidney Disease

Abstract

Patients with both hypertension and hyperhomocysteinemia, termed H‐type hypertension, have a high risk for cardiocerebrovascular diseases. However, little is known about the prevalence of H‐type hypertension or its role in target organ damage in patients with chronic kidney disease (CKD). The authors recruited 1042 patients with CKD who were admitted to their hospital division. Multiple linear regression analyses were used to evaluate the association between H‐type hypertension and renal/cardiovascular parameters. A total of 460 (44.14%) CKD patients had H‐type hypertension. Multivariate logistic regression analysis showed that H‐type hypertension is associated with serum albumin, uric acid, estimated glomerular filtration rate (eGFR), and 24‐hour systolic blood pressure. Patients with H‐type hypertension had the worst renal function and left ventricular hypertrophy among all patients, while the levels of carotid intima‐media thickness (cIMT) in patients with H‐type hypertension were only slightly higher than in patients with normotension and normohomocysteinemia (P<.05). H‐type hypertension was associated with eGFR, left ventricular mass index, and cIMT according to multiple linear regression analyses. The prevalence of H‐type hypertension was high and H‐type hypertension was associated with target organ damage in patients with CKD.

Chronic kidney disease (CKD) has become a serious clinical and public health challenge globally.1, 2 In China, 147 million people are affected by CKD, which contributes to multiple adverse clinical consequences, especially end‐stage renal disease (ESRD) and cardiovascular events such as heart attack, stroke, and peripheral arterial disease. Hypertension, traditionally considered a marker of CKD, is additionally a significant and independent risk factor for progression. Cardiovascular diseases are the leading cause of premature death in patients with CKD, even before their progression to ESRD.3 Therefore, early intervention in high blood pressure (BP) to prevent renal and cardiovascular injury in CKD populations is of immense significance to prevent progression.

Elevated plasma homocysteine (Hcy) levels, termed hyperhomocysteinemia (HHcy), are a pathological condition characterized by elevated Hcy concentrations (usually defined as Hcy concentrations >15 μmol/L) in blood. HHcy is a risk factor for neural tube defects and has been associated with many noncommunicable diseases, including cardiovascular and cerebrovascular diseases, type 2 diabetes, and cancer.4, 5, 6

HHcy is a major independent biomarker for endothelial dysfunction, which leads to an imbalance between blood endothelin and nitric oxide levels, affects the proliferation of smooth muscle cells, and induces subclinical inflammation, contributing to increased vascular endothelial damage and atherosclerosis in patients.7 Previous studies have shown that HHcy is a significant risk factor for the development of cardiovascular disease in the general and diabetic populations.8 Studies have also shown that HHcy may predict the progression of renal function decline and incident CKD in hypertensive adults.9 A large randomized trial among hypertensive Chinese adults without a history of stroke or myocardial infarction showed that enalapril and folic acid therapy compared with enalapril alone significantly reduced the relative risk of first stroke by 21%.10 This study suggested that reductions in blood Hcy levels with folic acid supplementation might be beneficial for stroke prevention in hypertensive populations. However, many other investigations have not shown a benefit from Hcy‐lowering therapy.

H‐type hypertension (HH), defined as both elevated Hcy and hypertension, is associated with a significantly higher risk of stroke compared with either condition alone.11 China is a country without folic acid fortification or the widespread use of folic acid supplementation as well as a country with a high prevalence of stroke. According to one national survey, approximately 75% of hypertensive adults were found to have elevated Hcy levels (Hcy concentrations >10 μmol/L).12 This necessitates further investigation into HH and target organ damage in China. However, data on the prevalence of HH in Chinese patients with CKD are lacking. Recent evidence suggests that ambulatory BP monitoring (ABPM) might be the best tool to classify hypertensive status and the risk of adverse events.13, 14 In this study, we performed 24‐hour BP monitoring in CKD patients and measured the levels of plasma Hcy, and then examined the prevalence of HH in these patients. We also explored the clinical parameters that were associated with HH.

Materials and Methods

Study Population

Inclusion criteria for participation in the study included age 14 to 75 years and presence of CKD.

Exclusion criteria included treatment with corticosteroids or hormones, acute changes in estimated glomerular filtration rate (eGFR) >30% in the previous 3 months, pregnancy, history of abuse of drugs or alcohol, night work or shift‐work employment, acquired immunodeficiency syndrome, cardiovascular disorders (unstable angina pectoris, heart failure, life‐threatening arrhythmia, atrial fibrillation, and grade III or IV retinopathy), intolerance to ABPM, inability to communicate and comply with all of the study requirements, maintenance dialysis, and being in receipt of any antihypertensive drug in the previous month.

The study protocol was approved by the ethics committee of the Third Hospital of Sun Yat‐Sen University (Guangdong, China). All study participants provided written informed consent to be included in the study.

A total of 1042 patients with CKD were enrolled in this cross‐sectional study. Causes of renal diseases included 610 patients with chronic glomerulonephritis; 136 with diabetic nephropathy; 296 with other causes of renal disease, in which 60 had hypertensive nephrology; 55 with lupus nephritis; 43 with HBV hepatitis–related nephrology; 35 with obstructive nephrology; 28 with gouty nephrology; 26 with nephrology related to tumors; and 49 with unknown causes.

BP Measurements

BP was measured at the physician's office with a calibrated mercury sphygmomanometer after a 5‐minute rest in the sitting position. BP values were estimated as the minimum of three BP measurements at intervals of ≥1 minutes. Reported values of clinic BP were the mean of values. These patients then underwent 24‐hour ABPM using a TM‐2430 Monitor (A&D, Tokyo, Japan). Cuff size was chosen based on arm circumference and fixed to the nondominant arm. BP readings were obtained in the morning at three points from 7 am to 10 am using a mercury sphygmomanometer by a physician who did not have access to ABPM values. BP was then recorded every 15 minutes from 7 am to 10 pm and every 30 minutes from 10 pm to 7 am. Monitoring was performed on a working day. Patients were asked to attend to their usual activities but to keep motionless at the time of measurement. Patients had no access to ABPM values. Strenuous physical activity was discouraged in all patients during the monitoring period, and their daily activities were comparable. BP series were eliminated from the analyses if: >30% of the measurements were lacking; they had missing data for >3‐hour spans; they were collected from patients who were experiencing an irregular rest–activity schedule or a nighttime sleep span <6 hours or >12 hours during monitoring.

The patient cohort was divided into four groups according to levels of ambulatory BP and levels of plasma Hcy: (1) normotension and normohomocysteinemia (NN): patients with normal ambulatory tension and normal plasma Hcy; (2) normotension and HHcy (NH): patients with normal ambulatory tension and elevated plasma homocysteine; (3) hypertension and normohomocysteinemia (HN): patients with ambulatory hypertension and normal plasma Hcy; and (4) HH: patients with ambulatory hypertension and elevated plasma Hcy.

Assessment of Target Organ Damage

Renal Assessment

Serum concentrations of creatinine (Scr) were measured by an enzymatic method traceable to isotope dilution mass spectrometry. The eGFR was calculated using a modified version of the Modification of Diet in Renal Disease (MDRD) equation based on data from Chinese patients with CKD15:

$$\text{eGFR}=175\times \text{standardized}{\text{Scr}}^{-1.234}\times {\text{age}}^{-0.179}\times 0.79\text{(if female)}$$

with Scr indicating serum creatinine concentration (in mg/dL) and age measured in years.

Cardiac Assessment

Cardiac structure was assessed by two investigators trained for this purpose before starting the study. Left ventricular mass (LVM), systolic function, and diastolic function were assessed using two‐dimensional echocardiography. Linear measurements of end‐diastolic interventricular septal wall thickness (IVSd), end‐diastolic left ventricular internal dimension (LVIDd), and end‐diastolic posterior wall thickness (PWTd) were obtained from M‐mode tracings. LVM was calculated using the following formula16:

$$\text{LVM}=\left\{\right.1.04\times {\left(\text{IVSd}+\text{LVIDd}+\text{PWTd}\right)}^3-{\text{LVIDd}}^3\left.\right\}\times 0.8+0.6$$

LVM index (LVMI) was obtained by calculating the ratio of LVM to body surface area.17

Carotid Ultrasonography

Carotid intima‐media thickness (cIMT) was assessed by two trained investigators before study commencement. A MicroMaxx Ultrasound system paired with a 5‐to 10‐MHz multifrequency high‐resolution linear transducer (SonoSite, Bothell, WA) with Sono‐Calc IMT software was used for taking automatic measurements of cIMT. This was achieved by averaging three measurements taken on each carotid artery (anterior, lateral, and posterior directions) and measuring the distance between the leading edge of the lumen‐intima interface and the leading edge of the collagenous upper layer of the adventitia using high‐resolution B‐mode ultrasonography.

Collection of Other Data

We collected urine samples from 7 am to 7 am the next day to detect the extent of proteinuria and sodium levels over 24 hours. These patients were asked to void their bladders at 7 am. Proteinuria was measured by immunoturbidimetry. Plasma Hcy was measured by an Hcy measurement kit (direct chemiluminescence method) using the ADVIA Centaur systems (Siemens Healthcare Diagnostics Inc, Norwood, MA). In addition, medical history, including demographic and laboratory data (hemoglobin, albumin, globulin, calcium, phosphate, intact parathyroid hormone [iPTH], serum fasting glucose, total cholesterol, triglycerides [TGs], high‐density lipoprotein cholesterol [HDL‐C], low‐density lipoprotein‐cholesterol [LDL‐C], Hcy, uric acid, serum cystatin C, and serum urea nitrogen [BUN]) were obtained at the initial study visit. These experimental data were measured using a 7180 Biochemistry Autoanalyzer (Hitachi, Tokyo, Japan).

Definitions

Ambulatory normotension was defined as 24‐hour BP <130/80 mm Hg, daytime BP <135/85 mm Hg, and nighttime BP <120/70 mm Hg. Ambulatory hypertension was defined as 24‐hour BP ≥130/80 mm Hg, daytime BP ≥135/85 mm Hg, and nighttime BP ≥120/70 mm Hg. Nocturnal hypertension was defined as nighttime BP ≥120/70 mm Hg.18 ABPM daytime and ABPM nighttime were defined as time intervals from 7 am to 10 pm and from 10 pm to 7 am based on patients’ schedules, respectively.

HHcy was defined as plasma Hcy >15 μmol/L.19

CKD was defined as kidney damage or decreased renal function eGFR <60 mL/min per 1.73 m² for ≥3 months according to guidelines set by the Kidney Disease Outcomes Quality Initiative, and we divided the CKD patients into five stages (1–5) according to this guideline.20

Diabetes mellitus (DM) was defined as the need for anti‐DM drugs or meeting the diagnostic criteria for DM specified by the Chinese Guidelines for Diabetes Prevention and Treatment: (1) symptoms of DM and casual blood glucose >11.1 mmol/L, and (2) fasting blood glucose >7.0 mmol/L.21, 22

Target organ damage (TOD) was defined as having any of the following three conditions. Firstly, in terms of kidney disease, an eGFR <60 mL/min per 1.73 m² was regarded as “impaired renal function.”20 Secondly, in terms of heart disease, patients with LVMI >115 g/m² (in men) and >95 g/m² (in women) were diagnosed as having left ventricular hypertrophy (LVH).23 Thirdly, with respect to large‐vessel disease, cIMT >1 mm was regarded as an abnormal value.24

Statistical Analyses

Descriptive statistics are presented as the mean±standard deviation (SD) for continuous variables and median and interquartile range for nonparametric variables. Frequency and percentage were used for categorical variables. Log transformation for proteinuria in regression analyses was performed because of the skewed distribution of these data.

Comparisons of continuous variables between groups were evaluated by analysis of variance (ANOVA) or nonparametric tests. Differences among categorical variables were analyzed using chi‐square test or two‐tailed Fisher exact test, as appropriate. P value for multiple comparisons was corrected according to the Bonferroni method (six comparisons). Differences of target organ damage (eGFR, LVMI, and cIMT) were analyzed by two‐way, factorial designed ANOVA to assess the effects of HHcy vs hypertension.

Predictors associated with HH were explored by multivariable logistic regression analysis. The variables for this analysis were age, sex, course, DM, current smoker, alcohol intake, BMI, hemoglobin, albumin, calcium×phosphate, iPTH, uric acid, cholesterol, triglyceride, HDL‐C, LDL‐C, urinary sodium excretion, proteinuria, eGFR, clinic SBP, 24‐hour SBP, and nighttime SBP

Multivariable logistic regression models were employed to study the association of indices of renal function (impaired renal function) and cardiovascular damage (LVH and abnormal cIMT) with age, sex, different BP status, and other variables with P<.05 explored in univariate regression analysis.

All values were two‐tailed and P<.05 was considered significant. Data were analyzed using SPSS version 20.0 (IBM, Armonk, NY).

Results

Demographic and Clinical Characteristics of the Study Population

The mean age of the cohort was 44.34 years, and 61.52% of the cohort was male. A total of 192 patients had DM (18.43%), 20.92% were current smokers, and 9.98% consumed alcohol.

Patients with HH were older, had a longer course, had a higher prevalence of DM, and were current smokers. They also had lower hemoglobin, cholesterol, LDL‐C, and HDL‐C levels, as well as higher proteinuria, serum albumin, cholesterol, intact parathyroid hormone (iPTH), calcium×phosphate, uric acid, Hcy, serum cystatin C, BUN, and serum creatinine levels compared with patients in the NN group (P<.05). Compared with patients in the NH group, patients with HH were older and had lower hemoglobin and higher proteinuria, serum cystatin C, BUN, and serum creatinine levels (P<.05). The patients with HH were older, had a longer course, and lower hemoglobin, cholesterol, LDL‐C and HDL‐C levels, and higher proteinuria, serum albumin, iPTH, calcium×phosphate, uric acid, Hcy, serum cystatin C, BUN, and serum creatinine levels compared with patients in the HN group (P<.05). Patients in the NH group were older, had a higher prevalence of DM, lower hemoglobin, cholesterol, HDL‐C, and LDL‐C levels, and higher serum albumin, calcium×phosphate, iPTH, uric acid, Hcy, serum cystatin C, BUN, and serum creatinine levels compared with patients in the NN group (P<.05) (Table 1).

Table 1.

Differences of Demographic and Clinical Characteristics in Chinese CKD Patients With Different Blood Pressure Status and Plasma Homocysteine Level

	Total (N=1042)	Normotension and Normohomocysteinemia (n=199)	Normotension and Hyperhomocysteinemia (n=90)	Hypertension and Normohomocysteinemia (n=293)	H‐type Hypertension (n=460)
Age, y	44.34±16.53	33.43±14.45	41.63±14.58a	44.36±16.19a	49.56±15.54a,b,c
Male: female ratio	641:401	100:99	71:19a	166:127b	304:156a
Course, mo	6 (1–24)	2 (1–12)	10 (1–24)	6 (1–24)	12 (1–36)a , c
Diabetes mellitus, No (%)	192 (18.4)	8 (4.0)	14 (15.6)a	61 (20.8)a	109 (23.7)a
Current smoker, No. (%)	218 (20.9)	28 (14.1)	24 (26.7)	59 (20.1)	107 (23.3)a
Alcohol intake, No. (%)	104 (10.0)	11 (5.5)	11 (12.2)	32 (10.9)	50 (10.9)
BMI, kg/m2	23.24±4.02	22.39±4.48	23.33±4.09	23.78±3.81a	23.24±4.02
Hemoglobin, g/L	112.77±29.70	131.54±20.95	115.12±28.71a	117.75±29.20a	101.01±28.29a,b,c
Albumin, g/L	33.94±8.26	31.16±9.96	37.91±7.65a	31.43±8.73b	35.94±6.14a,c
Calcium×phosphate, mg2/dL2	37.87±11.44	31.77±6.02	38.76±11.20a	34.70±10.08	41.72±12.20a,c
iPTH, pg/mL	72.32 (37.70–230.80)	35.80 (23.58–51.87)	71.90 (36.04–289.97)a	49.39 (31.12–110.33)a	150.88 (62.62–332.88)a,c
Serum fasting glucose, mmol/L	5.24±1.93	4.81±1.16	5.33±1.97	5.39±1.97a	5.31±2.14
Total cholesterol, mmol/L	5.75±2.79	6.85±3.29	5.06±2.10a	6.51±3.27b	4.92±1.92a,c
Triglyceride, mmol/L	2.00±1.68	1.83±1.35	1.85±1.64	2.29±2.16	1.92±1.42
HDL‐C, mmol/L	1.19±0.44	1.45±0.48	1.12±0.38a	1.20±0.43a	1.08±0.39a,c
LDL‐C, mmol/L	3.70±2.13	4.66±2.56	3.23±1.61a	4.25±2.46b	3.04±1.42a,c
Homocysteine, μmol/L	18.14±10.44	9.47±2.96	22.81±7.86a	11.31±2.58b	25.35±10.42a, c
Uric acid, mmol/L	477.96±152.54	385.96±110.94	516.88±176.27a	441.41±128.79a,b	532.92±151.73a,c
Proteinuria, g/24 h	1.58 (0.52–4.03)	1.10 (0.31–4.48)	0.82 (0.16–1.78)	2.63 (0.80–5.6)a,b	1.44 (0.66–3.00)b,c
Urinary sodium excretion, mmol/24 h	123.83±78.29	135.11±103.51	118.64±71.22	130.16±73.19	114.68±66.57
Serum cystatin C, mg/L	2.69±2.03	1.00±0.49	2.67±1.96a	1.98±1.65a,b	3.87±1.94a,b,c
Blood urea nitrogen, mmol/L	9.87 (5.57 –20.38)	4.78 (3.79–5.90)	10.49 (6.60–20.55)a	7.29 (5.12–13.06)a,b	18.00 (11.03–27.02)a,b,c
Serum creatinine, μmol/L	158.70 (84.70–538.00)	71.75 (58.92–92.02)	162.65 (109.65–479.92)a	103.00 (75.15–210.47)a,b	481.40 (195.70–834.00)a,b,c
Clinic SBP, mm Hg	125.66±17.20	131.57±17.78	146.70±23.09a	155.43±24.09a,b	155.46±22.52a,b,c
Clinic DBP, mm Hg	78.47±10.72	79.35±10.97	89.21±12.96a	90.67±15.33a , b	90.89±14.25a,c
24‐h SBP, mm Hg	113.62±8.18	116.12±6.85	138.82±14.77a	143.89±15.51a,b	148.25±12.69a,b,c
24‐h DBP, mm Hg	68.96±4.92	70.22±5.00	82.99±8.72a	84.59±9.12a,b	86.97±8.49a,b,c
Daytime SBP, mm Hg	115.75±8.73	118.27±7.46	139.88±14.93a	144.98±15.42a,b	149.78±12.36a,b,c
Daytime DBP, mm Hg	70.51±5.33	71.77±5.54	83.75±8.92a	85.30±9.17a,b	88.06±8.60a,b,c
Nighttime SBP, mm Hg	102.84±7.93	105.22±7.14	133.71±17.53a	138.95±18.61a,b	143.59±16.76a,b,c
Nighttime DBP, mm Hg	60.80±5.11	62.53±5.15	79.06±10.42a	81.19±10.90a,b	83.64±10.10a,b,c
SBP nocturnal decline, %	10.93±5.77	10.84±5.82	4.34±8.13a	4.14±7.53a,b	4.19±7.52a,b,c
DBP nocturnal decline, %	13.61±6.54	12.68±6.85	5.48±9.09a	4.74±8.37a,b	4.94±8.05a,b,c

Abbreviations: BMI, body mass index; CKD, chronic kidney disease; DBP, diastolic blood pressure; HDL‐C, high‐density lipoprotein cholesterol; iPTH, intact parathyroid hormone; LDL‐C, low‐density lipoprotein cholesterol; SBP, systolic blood pressure. ^aComparison with the normotension and normohomocysteinemia group, P<.05. ^bComparison with the normotension and hyperhomocysteinemia group, P<.05. ^cComparison with the H‐type hypertension group, P<.05.

Prevalence of HH at Different Renal Stages

Of the 1042 patients in the cohort, 199 (19.10%) were in the NN group, 90 (8.64%) were in the NH group, 293 (28.12%) were in the HN group, and 460 (44.14%) were in the HH group.

The levels of plasma Hcy in CKD patients were increased with the decline in renal function, and patients with stage 5 CKD had the highest levels of plasma Hcy (P<.05). The prevalence of HH in patients with stages 1, 2, 3, 4, and 5 CKD was 5.75%, 20.13%, 42.76%, 63.06%, and 76.65%, respectively. With advancing CKD stage, the prevalence of HH was higher than in patients with early stage renal disease (P<.05) (Figure 1 and Figure 2).

Figure 1.

Comparison of plasma homocysteine level in different chronic kidney disease (CKD) stages (P value for multiple comparisons was corrected according to the Bonferroni method). *Comparison with CKD stage 1, P<.001. ^#Comparison with CKD stage 2, P<.001. ^$Comparison with CKD stage 3, P<.001. ^@Comparison with CKD stage 4, P<.001.

Figure 2.

Prevalence of normotension and normohomocysteinemia (NN), normotension and hyperhomocysteinemia (NH), hypertension and normohomocysteinemia (HN), and H‐type hypertension (HH) in different chronic kidney disease (CKD) stages (P value for multiple comparisons was corrected according to the Bonferroni method). *Comparison with CKD stage 1, P<.001. ^#Comparison with CKD stage 2. ^$Comparison with CKD stage 3. ^@Comparison with CKD stage 4.

Characteristics of ABPM in Chinese CKD Patients With Different BP Status and Plasma Hcy Levels

Patients with HH had higher clinic BP, 24‐hour BP, daytime BP, and nighttime BP, and a lower nocturnal BP decline rate compared with patients with normohomocysteinemia (P<.05). The HH patients also had higher clinic systolic BP (SBP), 24‐hour BP, daytime BP, nighttime SBP/diastolic BP (DBP), and a lower nocturnal SBP/DBP decline rate compared with patients in the NH group (P<.05). While patients in the NH group had higher clinic BP, 24‐hour BP, daytime BP, nighttime SBP/DBP, and a lower nocturnal SBP/DBP decline rate compared with patients in the NN group (P<.05) (Table 1).

Factors Associated With HH

Age, sex, course length, DM, current smoker, hemoglobin, serum albumin, calcium×phosphate, total cholesterol, HDL‐C, LDL‐C, uric acid, urinary sodium excretion, eGFR, clinic SBP, 24‐hour SBP, and SBP nighttime were associated with HH according to univariate logistic regression analysis. Multivariate logistic regression analysis showed that HH associated with serum albumin, uric acid, eGFR‐MDRD, and 24‐hour SBP (Table 2).

Table 2.

Univariate and Multivariate Logistic Regression Analysis for H‐Type Hypertension in Chinese CKD Patients

	Univariate Regression Analysis		Multivariate Regression Analysis
	OR (95% CI)	P Value	OR (95% CI)	P Value
Age, per 1 y	1.427 (1.107–1.839)	.006
Sex (female=0; male=1)	1.037 (1.029–1.045)	<.001
Course, per 1 month	1.005 (1.002–1.008)	<.001
Diabetes mellitus (no=0, yes=1)	1.867 (1.360–2.562)	<.001
Hemoglobin, per 1 g/L	0.974 (0.969–0.979)	<.001
Albumin, g/L	1.057 (1.040–1.075)	<.001	1.048 (1.020–1.078)	.001
Calcium×phosphate, per 1 mg2/dL2	1.069 (1.055–1.084)	<.001
Cholesterol, mmol/L	0.784 (0.737–0.834)	<.001
HDL‐C, per 1 mmol/L	0.326 (0.235–0.452)	<.001
LDL‐C, per 1 mmol/L	0.711 (0.654–0.772)	<.001
Uric acid, per 1 mmol/L	1.005 (1.004–1.006)	<.001	1.002 (1.000–1.004)	.015
Urinary sodium excretion, per 1 mmol/24 h	0.997 (0.995–0.999)	.011
eGFR‐MDRD, per 1 mL/min/1.73 m2	0.979 (0.976–0.983)	<.001	0.974 (0.968–0.981)	<.001
Clinic SBP	1.034 (1.028–1.040)	<.001
24‐h SBP	1.064 (1.054–1.074)	<.001	1.051 (1.036–1.066)	<.001
Nighttime SBP	1.052 (1.044–1.060)	<.001

Abbreviations: CI, confidence interval; OR, odds ratio; MDRD, Modification of Diet in Renal Disease. Variables of univariate regression analysis include age, sex (female = 0, male = 1), course, diabetes mellitus (no = 0, yes = 1), current smoker (no = 0, yes = 1), alcohol intake (no = 0, yes = 1), body mass index (BMI), hemoglobin, albumin, calcium×phosphate, intact parathyroid hormone (iPTH), uric acid, cholesterol, triglyceride, high‐density lipoprotein cholesterol (HDL‐C), low‐density lipoprotein cholesterol (LDL‐C), urinary sodium excretion, proteinuria, estimated glomerular filtration rate (eGFR), clinic systolic blood pressure (SBP), 24‐hour SBP, and nighttime SBP. All variables with significant associations were included in multivariate regression analysis.

Target Organ Damage According to BP Status and Plasma Hcy Levels

Patients with HH had a lower eGFR and a higher LVMI and cIMT compared with patients in the NN group (P<.05). They also had a lower eGFR and a higher LVMI compared with patients in the NH or HN groups (P<.05). Patients in the NH group had a lower eGFR and a higher LVMI compared with patients in the NN group (P<.05). ANOVA showed that for eGFR‐MDRD, LVMI, and cIMT, the main effects of hypertension and HHcy were statistically significant, but no statistically significant interactions between the two factors were found. The same results were found for the prevalence of impaired renal function, LVH, and abnormal cIMT in these patients (P<.05) (Table 3 and Figure 3).

Table 3.

Target Organ Damage in Chinese CKD Patients With Different Blood Pressure Status and Plasma Homocysteine Level and Analysis of Variance

	Normotension		Hypertension		P Value
	Normohomocysteinemia (n=199)	Hyperhomocysteinemia (n=90)	Normohomocysteinemia (n=293)	Hyperhomocysteinemia (n=460)	Hypertension	Hyperhomocysteinemia	Interaction
eGFR‐MDRD, mL/min/1.73 m2	109.77 (82.64–141.17)	39.11 (10.04–70.12)a	68.09 (26.02–103.17)a,b	10.49 (5.00–29.12)a,b,c	<.001	<.001	.869
LVMI, g/m2	84.44±17.67	107.77±26.79a	116.19±39.92a	132.67±35.45a,b,c	<.001	<.001	.291
cIMT, mm	0.58±0.17	0.68±0.20	0.77±0.29a	0.78±0.26a	<.001	.035	.078

Abbreviations: cIMT, carotid intima‐media thickness; eGFR‐MDRD, estimated glomerular filtration rate Modification of Diet in Renal Disease; LVMI, left ventricular mass index. ^aComparison with the normotension and normohomocysteinemia group, P<.05. ^bComparison with the normotension and hyperhomocysteinemia group, P<.05. ^cComparison with the hypertension and normohomocysteinemia group, P<.05.

Figure 3.

Comparison of target organ damage in Chinese patients with chronic kidney disease (CKD) with different blood pressure status and plasma homocysteine level (P value for multiple comparisons was corrected according to the Bonferroni method). *Comparison with the normotension and normohomocysteinemia group, P<.001. ^#Comparison with the normotension and hyperhomocysteinemia group, P<.001. ^$Comparison with the hypertension and normohomocysteinemia group, P<.001. cIMT indicates carotid intima‐media thickness; HH, H‐type hypertension; HN, hypertension and normohomocysteinemia; LVH, left ventricular hypertrophy; NH, normotension and hyperhomocysteinemia; NN, normotension and normohomocysteinemia.

Factors Associated With Target Organ Damage

Multiple linear regression analyses were performed to define factors associated with target organ damage. Age, hemoglobin, albumin, calcium×phosphate, uric acid, NH (vs NN), HN (vs NN), and HH (vs NN) were associated with eGFR. Age, sex, hemoglobin, iPTH, HN (vs NN) and HH (vs NN) were associated with LVMI. Age, DM, current smoker (no=0, yes=1), and HH (vs NN) were independently associated with cIMT (Table 4).

Table 4.

Multiple Linear Regression Analysis: Relationship Between Lg (eGFR), LVMI, and cIMT With Different Blood Pressure Status and Plasma Homocysteine Level in Chinese CKD Patients

Variables	Unstandardized Coefficients B (95% CI)	Standardized Coefficients Beta	P Value
Dependent variable: Lg (eGFR by MDRD formula) (adjusted R 2=0.745)
Age, per 1 y	−0.003 (−0.005 to −0.001)	−0.088	.001
Hemoglobin, per 1 g/L	0.007 (0.006 to 0.008)	0.397	<.001
Albumin, per 1 g/L	−0.005 (−0.008 to −0.001)	−0.069	.005
Calcium×phosphate, per 1 mg2/dL2	−0.013 (−0.016 to −0.011)	−0.262	<.001
Uric acid, per 1 mmol/L	−0.001 (−0.001 to 0.000)	−0.180	<.001
NH (vs NN)	−0.163 (−0.277 to 0.049)	−0.076	.005
HN (vs NN)	−0.093 (−0.170 to −0.016)	−0.074	.018
HH (vs NN)	−0.367 (−0.448 to −0.286)	−0.330	<.001
Dependent variable: LVMI, kg/m2 (adjusted R 2=0.373)
Age, per 1 y	0.274 (0.080 to 0.468)	0.113	.006
Sex (female=0; male=1)	13.021 (7.044 to 18.98)	0.163	<.001
Hemoglobin, per 1 g/L	−0.320 (−0.436 to −0.205)	−0.247	<.001
iPTH, per 1 pg/mL	0.042 (0.022 to 0.062)	0.241	<.001
NH (vs NN)	9.605 (−2.349 to 21.558)	0.071	.115
HN (vs NN)	26.116 (16.798 to 35.435)	0.290	<.001
HH (vs NN)	23.019 (13.767 to 32.270)	0.299	<.001
Dependent variable: cIMT, mm (adjusted R 2=0.401)
Age, per 1 y	0.009 (0.007 to 0.010)	0.511	<.001
Diabetes mellitus (no=0, yes=1)	0.106 (0.056 to 0.155)	0.166	<.001
Current smoker (no=0, yes=1)	0.057 (0.009 to 0.105)	0.087	.021
NH (vs NN)	0.012 (−0.008 to 0.031)	0.050	.234
HN (vs NN)	−0.007 (−0.077 to 0.064)	−0.008	.848
HH (vs NN)	0.049 (0.005 to 0.092)	0.083	.029

Abbreviations: adjusted variable, age; CI, confidence interval; CKD, chronic kidney disease; MDRD, Modification of Diet in Renal Disease. Variables of simple regression analysis for Lg (estimated glomerular filtration rate [eGFR]) include sex (female=0, male=1), course, diabetes mellitus (no = 0, yes = 1), current smoker (no = 0, yes = 1), alcohol intake (no = 0, yes = 1), body mass index (BMI), hemoglobin, albumin, calcium×phosphate, intact parathyroid hormone (iPTH), uric acid, cholesterol, triglyceride, high‐density lipoprotein cholesterol (HDL‐C), low‐density lipoprotein cholesterol (LDL‐C), urinary sodium excretion, proteinuria and normotension and hyperhomocysteinemia (NH), hypertension and normohomocysteinemia (HN), and H‐type hypertension (HH) (no = 0, yes = 1) (vs normotension and normohomocysteinemia [NN]). Variables of simple regression analysis for left ventricular mass index (LVMI) and carotid intima‐media thickness (cIMT) include sex (female=0, male=1), course, diabetes mellitus (no = 0, yes = 1), current smoker (no=0, yes=1), alcohol intake (no = 0, yes = 1), BMI, hemoglobin, albumin, calcium×phosphate, iPTH, uric acid, cholesterol, triglyceride, HDL‐C, LDL‐C, urinary sodium excretion, proteinuria, eGFR, NH, HN, and HH (no = 0, yes = 1) (vs NN). Significant variables of simple regression analysis for Lg (eGFR) include course, diabetes mellitus (no = 0, yes = 1), hemoglobin, albumin, calcium×phosphate, iPTH, uric acid, cholesterol, triglyceride, HDL‐C, LDL‐C, urinary sodium excretion, NH, HN, and HH (no = 0, yes = 1) (vs NN). Significant variables of simple regression analysis for LVMI include sex (male = 1, female = 2), course, diabetes mellitus (no = 0, yes = 1), current smoker (no = 0, yes = 1), hemoglobin, calcium×phosphate, iPTH, uric acid, HDL‐C, LDL‐C, eGFR, NH, HN, and HH (no = 0, yes = 1) (vs NN). Significant variables of simple regression analysis for cIMT include course, diabetes mellitus (no = 0, yes = 1), current smoker (male = 1, female = 2), BMI, albumin, HDL‐C, eGFR, NH, HN, and HH (no=0, yes=1) (vs NN). All variables with significant associations were included in multiple regression analysis.

Discussion

In this cross‐sectional study, we report that the prevalence of HH in Chinese CKD patients was 44.14%, and patients with poorer kidney function had a higher prevalence of HH. HH was associated with serum albumin, uric acid, eGFR‐MDRD, and 24‐hour SBP. Patients with HH had the worst target organ damages, poorest renal function, and most severe cardiovascular injuries in this cohort. HH was also associated with eGFR, LVMI, and cIMT according to multiple linear regression analyses. Taken together, these data above suggest that HH in Chinese CKD patients has a high prevalence and plays a role in target organ damage, highlighting the need to identify CKD patients with HH.

Hcy is a sulfur‐containing, nonprotein‐forming amino acid synthesized from the normal biosynthesis of methionine and cysteine, and is an important intermediate in the one‐carbon pathway.25 We classified patients as having HHcy when Hcy levels exceeded the normal limit. The damaging effects of HHcy on endothelial function are, at least in part, through the inhibition of endothelial nitric oxide synthase, which produces endoplasmic reticulum stress. This stress subsequently drives the development of inflammation, oxidative stress, and apoptosis of endothelial cells, eventually leading to atherosclerosis, plaque progression, and occurrence of atherosclerotic complications.26 HHcy occurrence involves a variety of factors, including genetics, nutrition, and lifestyle behaviors. Of these factors, genetic factors such as methylenetetrahydrofolate reductase (MTHFR), a key enzyme in folic acid metabolism, and vitamin B and folic acid deficiency are the most important.27, 28 Low dietary folate intake and a higher prevalence of MTHFR 677TT mutations contribute to the increased frequency of HHcy in Chinese compared with Western populations.29 It is important to investigate the role of HHcy in Chinese patients, but there are no data on the prevalence of HHcy in Chinese CKD patients. Our studies indicated that 52.88% of CKD patients had HHcy, which was associated with decreased renal function. Patients with poorer renal function had a higher incidence of HHcy than patients with better renal function. A previous study reported that annual eGFR decline was 25% higher in patients with elevated vs normal mean Hcy levels in the general population.8 HHcy may be a modifiable risk factor, and preventive interventions should be considered for adults with increased plasma Hcy levels. A number of strategies, including dietary modification and supplementation with folic acid and vitamins B6 and B12, have been reported to be effective at lowering Hcy levels and reducing cardiovascular risk.30 Folic acid supplementation is a cheap way to treat HHcy, but we first need to focus on identifying individuals with HHcy among CKD patients.

Furthermore, endothelial dysfunction induced by HHcy may exacerbate vascular inflammation and impaired nitric oxide release. Together, these contribute to increased systemic vascular resistance, thus leading to the development of hypertension.31, 32 Hypertension can further trigger and potentiate endothelial dysfunction, which can lead to irreversible damage to the heart and blood vessels, causing major cardiovascular events.33 Patients with HHcy and hypertension have more severe target organ damage. Patients with HH have a more than 12‐fold greater risk of having a stroke than hypertensive patients.34 However, the effects of the synergistic combination of these two factors on kidney and cardiovascular diseases in CKD patients remain unknown. The kidney plays a key role in the regulation of BP, this it is not surprising to find a higher prevalence of hypertension in CKD patients with decreased kidney function.21 We also found that eGFR was associated with HHcy and that patients with poorer renal function had higher levels of plasma Hcy. Previous studies have demonstrated that elevation in plasma Hcy concentration can occur as a result of the decreasing renal metabolic extraction of Hcy, to diminished extrarenal Hcy remethylation, which is one of the mainly metabolized pathways in Hcy, in CKD patients. In addition, other factors including smoking and some chronic medical condition may also elevate plasma Hcy level.35 These all contribute to a higher prevalence of HH in Chinese CKD patients and higher prevalence of HH in patients with poorer kidney function. We should pay special attention to individuals with HH in CKD patient populations because it is common, causes greater damage, and is associated with renal/cardiovascular parameters. We can identify these HH individuals as having poor renal function and elevated ambulatory SBP. In future studies, we aim to investigate whether patients with HH benefit from Hcy‐lowering therapy in addition to antihypertensive therapy.

Study Strengths and Limitations

The present study has strengths and limitations. Firstly, we monitored BP by ABPM, and assessed any associations between HH and 24‐hour SBP rather than clinic SBP so the diagnosis of hypertension would be more precise. Secondly, patients with CKD who had received antihypertensive drugs in the previous month were excluded, so drug use did not affect the analyses. Thirdly, all of our patients had comprehensive assessments, and the cohort size was large. Limitations of this study include patient selection. All patients were admitted to our hospital division with severe proteinuria or severe renal damage, and most patients were from southern China; therefore, our cohort may not reflect the general Chinese CKD patient population. We arranged the same schedule for all patients to expedite BP monitoring, but this arrangement might have led to different results from monitoring in an outpatient setting. In addition, the underlying etiology of CKD is highly variable across the world. In China, the most common cause is primary glomerulonephritides, followed by DM and hypertension. This is different from that reported from Western countries, thus there may be differences in the prevalence of HH in different regions. Finally, we cannot infer a cause–effect relationship based on our cross‐sectional data.

Conclusions

We have provided the first evidence of the prevalence of HH and its close association with target organ damage in CKD patients. Further studies are needed to determine whether combined treatment consisting of antihypertensive drugs and folic acid have a greater beneficial effect when compared with that of antihypertensive drugs alone in reducing cardiovascular disease and improve kidney function in CKD patients.

J Clin Hypertens (Greenwich). 2017;19:151–160. DOI: 10.1111/jch.12881. © 2016 Wiley Periodicals, Inc.