Association Study of Mitochondrial DNA Haplogroup D and C5178A Polymorphisms with Chronic Kidney Disease

Abstract

Objective:

To explore the associations of common mitochondrial DNA polymorphisms with chronic kidney disease (CKD).

Methods:

Data from 286 longevous individuals aged 95 years or older from the longevity arm from the Rugao Longevity and Ageing Study (RuLAS) were used. Twenty-eight common haplogroups defined by 33 single nucleotide polymorphisms were genotyped using SNaPshot minisequencing reaction assays. The creatinine-based estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation.

Results:

The prevalence of CKD was 23.6% among the longevous participants aged 95 years and older. The D haplogroup (67.37 ± 14.72 vs. 70.65 ± 11.07, p = 0.045), the D5 haplogroup (60.86 ± 18.36 vs. 70.34 ± 11.53, p = 0.002), and the 5178A allele (67.23 ± 14.48 vs. 70.75 ± 11.10, p = 0.029) were associated with lower eGFR levels compared with noncarriers. The D5 haplogroup (13.8% vs. 3.6%, p = 0.005) was significantly higher, while D haplogroup (35.4% vs. 24%, p = 0.067) and the 5178A allele (36.9% vs. 24.9%, p = 0.056) were borderline significantly higher in CKD individuals than those without CKD. Further, after adjusting for multiple covariates, the D haplogroup, the D5 haplogroup, and the 5178A allele were associated with increased odds of CKD with odds ratios of 1.93 (95% confidence interval [CI]: 1.00-3.72, p = 0.050), 4.76 (95% CI: 1.49-15.22, p = 0.009) and 2.04 (95% CI: 1.05-3.96, p = 0.035), respectively.

Conclusions:

The D and D5 haplogroups, as well as the 5178A allele are associated with decreased eGFR levels and an increased risk of CKD in a longevous population.

Introduction

Chronic kidney disease (CKD) is a serious clinical and public health challenge with a global prevalence of 11-13% in the general population (Hill et al., 2016; Coresh, 2017), and a prevalence of 23.4% for persons aged 65 years or older (Zhang and Rthenbacher, 2008). CKD is associated with an elevated risk of end-stage renal disease (ESRD), cardiovascular disease mortality, fractures, hospitalization, disability-adjusted life-years, and loss of quality of life (Go et al., 2004; Couser et al., 2011; Jha et al., 2013).

Multiple genetic, environmental, and behavioral risk factors contribute to the initiation and progression of CKD (Taal and Brenner, 2006; Kazancioglu, 2013). The heritability of CKD ranges from 30% to 70% (O'Seaghdha and Fox, 2012; Regele et al., 2015). However, there are a very limited number of studies that have reported associations between mitochondrial DNA (mtDNA) haplogroups and CKD. In the present study, we explored the influences of the mtDNA haplogroups on the estimated glomerular filtration rate (eGFR) levels and the risk of CKD in a longevous population aged 95 years or older.

Methods

Study population

We used data from the baseline survey of the longevity arm of the Rugao Longevity and Ageing Study (RuLAS), a population-based two-arm prospective cohort study. As previously described (Liu et al., 2015, 2016), the baseline survey of the Rugao longevity cohort was conducted between December 24, 2007 and February 29, 2008 in Rugao. After a strict four-step age verification, 705 persons aged 95+ years were identified in Rugao city. Four hundred sixty-three of the 705 persons were recruited with a response rate of 71.6%. Among them, 286 longevous participants with data of eGFR and mtDNA haplogroup were included in this study. The Human Ethics Committee of the School of Life Sciences, Fudan University, Shanghai, People's Republic of China, approved the present study. Written informed consent was obtained from all participants before the study.

mtDNA genotyping

Genomic DNA was extracted using standard method. Thirty-three mitochondrial single nucleotide polymorphisms defining 28 major mitochondrial haplogroups (D*, D4, D4a, D4b, D4b2, D4b2b, D5, M12, G*, G2, M7*, M7b, M8*, M8a, C, M9, M10, N9, N9a, A, F*, F1, B*, B5, B5a, B5b, B4a, and B4b) found in the Chinese population (Kim et al., 2008; Cai et al., 2009) were genotyped. A SNaPshot (Applied Biosystems, Foster City, CA) minisequencing reaction assay was used to genotype mitochondrial deoxyribonucleic acid single nucleotide polymorphisms (Salas et al., 2005) with minor modifications (Cai et al., 2009).

Outcome definitions

Plasma creatinine-based GFR was estimated using the following equations: eGFR_EPI = 144 × (serum creatinine [mg/dL]/0.7)^−0.329 × (0.993)^Age if female and serum creatinine ≤0.7 or eGFR_EPI = 44 × (serum creatinine [mg/dL]/0.7)^−1.209 × (0.993)^Age if female and serum creatinine >0.7 or eGFR_EPI = 141 × (serum creatinine [mg/dL]/0.9)^−0.411 × (0.993)^Age if male and serum creatinine ≤0.9 or eGFR_EPI = 141 × (serum creatinine [mg/dL]/0.9)^−1.209 × (0.993)^Age if male and serum creatinine >0.9 (Levey et al., 2009). CKD was defined as an eGFR of <60 mL/min/1.73 m² (Stevens et al., 2013).

Covariates

Covariates included in this study are gender, age, occupation (farmers, others, education (literate, illiterate), body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), plasma albumin, glucose, triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels. BMI was calculated by dividing weight (kg) by height squared (m²).

Statistical analysis

Characteristics are presented as the mean ± standard deviation or the percentage. Student's t-test and the χ² test were used to compare differences of continuous and categorical variables between CKD individuals and individuals without CKD, respectively. The effects of haplogroups on GFR levels were examined using ACNOVA adjusting for multiple covariates. Logistic regression models were used to estimate odds ratios (ORs) and 95% confidence interval (95% CI) for CKD. Covariates adjusted in this study include gender, age, occupation, education, smoking, drinking, BMI, SBP, DBP, albumin, glucose, TG, HDL-C, and LDL-C levels. A p-value of <0.05 (two-tailed) was considered statistically significant. All analyses were done with SPSS 19.0 software (SPSS, Inc., Chicago, IL).

Results

The prevalence of CKD was 23.6% among the longevous participants aged 95 years and older. There were significantly higher percentages of males, farmers, and literature individuals with CKD than those without CKD (Table 1).

Table 1.

Demographic Characteristics of the Participants

	All (n = 286)	CKD (n = 65, 23.6%)	Without CKD (n = 221, 76.4%)	p
Age (years)		97.45 ± 2.10	97.42 ± 2.12	0.932
Female (%)	220 (76.9)	43 (66.2)	177 (80.1)	0.019
Literate	54 (18.9)	21 (32.8)	33 (14.9)	0.001
Farmers	267 (94.7)	56 (88.9)	211 (96.3)	0.020
BMI (kg/m²)	22.42 ± 10.55	24.40 ± 15.32	21.83 ± 8.58	0.085
SBP (mmHg)	137.53 ± 23.52	139.55 ± 22.49	136.94 ± 23.83	0.432
DBP (mmHg)	79.60 ± 10.62	79.82 ± 10.77	79.54 ± 10.60	0.849
TG (mg/dL)	1.07 ± 0.44	1.15 ± 0.42	1.04 ± 0.44	0.081
Tc (mg/dL)	4.77 ± 0.89	4.95 ± 0.95	4.72 ± 0.86	0.064
HDL-C (mg/dL)	1.37 ± 0.34	1.36 ± 0.38	1.37 ± 0.33	0.702
LDL-C (mg/dL)	2.58 ± 0.68	2.72 ± 0.72	2.54 ± 0.67	0.063
Glucose (mM)	4.95 ± 1.33	4.78 ± 1.14	5.00 ± 1.38	0.250
Albumin (g/L)	69.53 ± 6.30	69.98 ± 6.54	69.40 ± 6.2	0.519
eGFR (mL/min/1.73 m²)	69.78 ± 12.20	50.59 ± 7.41	75.42 ± 6.02	0.000

BMI, body mass index; CKD, chronic kidney disease; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure; Tc, total cholesterol; TG, triglyceride.

Table 2 shows the results of the associations between the mtDNA haplogroups and eGFR levels. The D haplogroup (67.37 ± 14.72 vs. 70.65 ± 11.07, p = 0.045), the D5 haplogroup (60.86 ± 18.36 vs. 70.34 ± 11.53, p = 0.002), and the 5178A allele (67.23 ± 14.48 vs. 70.75 ± 11.10, p = 0.029) were associated with lower levels of eGFR compared with noncarriers. The associations remained significant after adjusting for multiple covariates, including gender, age, occupation, education, smoking, drinking, BMI, SBP, DBP, plasma albumin, glucose, TG, HDL-C, and LDL-C levels (Table 2). Other haplogroups were not associated with eGFR levels.

Table 2.

Estimated Glomerular Filtration Rate Levels Among Studied Haplogroups

Haplogroup	N (Carry/absent)	GFR in haplogroup carriers	GFR in haplogroup noncarriers	p	Model 1 p	Model 2 p	Model 3 p
D	76/210	67.37 ± 14.72	70.65 ± 11.07	0.045	0.021	0.021	0.013
D4	57/229	69.52 ± 12.99	69.84 ± 12.03	0.860	0.454	0.425	0.429
D4a	5/281	61.51 ± 14.28	69.92 ± 12.14	0.127	0.068	0.058	0.055
D4b	18/268	70.17 ± 13.23	69.75 ± 12.16	0.889	0.969	0.905	0.610
D4b2	18/268	70.17 ± 13.23	69.75 ± 12.16	0.889	0.969	0.905	0.610
D4b2b	13/273	69.39 ± 14.07	69.79 ± 12.14	0.908	0.747	0.874	0.857
D5	17/269	60.86 ± 18.36	70.34 ± 11.53	0.002	0.004	0.006	0.002
M12	16/270	72.17 ± 10.10	69.63 ± 12.32	0.421	0.459	0.548	0.278
G	16/270	72.17 ± 10.10	69.63 ± 12.32	0.421	0.459	0.548	0.278
G2	9/277	70.89 ± 10.03	69.74 ± 12.28	0.781	0.817	0.925	0.605
M7	21/265	69.10 ± 10.25	69.83 ± 12.36	0.791	0.771	0.729	0.587
M7b	10/276	68.95 ± 10.91	69.81 ± 12.26	0.828	0.888	0.880	0.901
M8	27/259	71.55 ± 13.78	69.59 ± 12.04	0.427	0.396	0.324	0.377
M8a	5/281	75.43 ± 5.82	69.68 ± 12.27	0.296	0.246	0.269	0.388
C	16/270	71.73 ± 15.43	69.66 ± 12.01	0.512	0.528	0.439	0.387
M9	0/286	/	69.78 ± 12.20	/	/	/	/
M10	6/280	73.42 ± 13.33	69.70 ± 12.19	0.461	0.553	0.602	0.522
N9	15/271	70.35 ± 7.04	69.74 ± 12.43	0.852	0.854	0.951	0.926
N9a	12/274	71.18 ± 5.95	69.71 ± 12.41	0.684	0.619	0.698	0.811
A	20/266	66.87 ± 13.49	69.99 ± 12.10	0.270	0.285	0.380	0.515
F	52/234	70.39 ± 11.15	69.64 ± 12.44	0.689	0.681	0.477	0.648
F1	30/256	69.66 ± 12.15	69.79 ± 12.23	0.958	0.943	0.540	0.763
B	44/239	71.13 ± 10.18	69.52 ± 12.59	0.423	0.297	0.414	0.382
B5	17/269	72.29 ± 12.21	69.62 ± 12.21	0.382	0.306	0.356	0.308
B5a	12/274	71.04 ± 11.85	69.72 ± 12.24	0.714	0.676	0.748	0.704
B5b	5/281	75.28 ± 13.94	69.68 ± 12.18	0.310	0.228	0.245	0.212
B4a	6/280	69.75 ± 12.07	69.78 ± 12.23	0.995	0.761	0.834	0.697
B4b	4/282	72.18 ± 9.17	69.74 ± 12.25	0.692	0.629	0.677	0.622
C5178A	79/207	67.23 ± 14.48	70.75 ± 11.10	0.029	0.014	0.014	0.006

The bold values indicates the statistical significance p < 0.05.

Model 1: adjusted for gender and age.

Model 2: adjusted for gender, age, occupation, and education.

Model 3: adjusted for gender, age, occupation, education, BMI, SBP, DBP, albumin, glucose, TG, HDL-C, and LDL-C.

Table 3 shows the frequencies of the haplogroups among subjects with CKD and without CKD. The percentage of the D5 haplogroup (13.8% vs. 3.6%, p = 0.005), a subhaplogroup of D, was significantly higher in the CKD group than in persons without CKD. Haplogroup D (35.4% vs. 24%, p = 0.067) and the 5178A allele (36.9% vs. 24.9%, p = 0.056) were borderline significantly higher in the CKD group than in subjects without CKD (Table 3).

Table 3.

Distributions of Mitochondrial DNA Haplogroups in Chronic Kidney Disease and Nonchronic Kidney Disease Groups

Haplogroup	Without CKD (n = 221, 76.4%)	CKD (n = 65, 23.6%)	p
D	53 (24%)	23 (35.4%)	0.067
D4	44 (19.9%)	13 (20.0%)	0.987
D4a	2 (0.9%)	3 (4.6%)	0.079^a
D4b	13 (5.9%)	5 (7.7%)	0.569^a
D4b2	13 (5.9%)	5 (7.7%)	0.569^a
D4b2b	9 (4.1%)	4 (6.2%)	0.501^a
D5	8 (3.6%)	9 (13.8%)	0.005^a
M12	14 (6.3%)	2 (3.1%)	0.538^a
G	14 (6.3%)	2 (3.1%)	0.538^a
G2	8 (3.6%)	1 (1.5%)	0.689^a
M7	16 (7.2%)	5 (7.7%)	1.000^a
M7b	8 (3.6%)	2 (3.1%)	1.000^a
M8	22 (10.0%)	5 (7.7%)	0.583
M8a	5 (2.3%)	0 (0.0%)	0.592^a
C	13 (5.9%)	3 (4.6%)	1.000^a
M9	0 (0.0%)	0 (0.0%)	—
M10	5 (2.3%)	1 (1.5%)	1.000^a
N9	13 (5.9%)	2 (3.1%)	0.533^a
N9a	11 (5.0%)	1 (1.5%)	0.309^a
A	13 (5.9%)	7 (10.8%)	0.175^a
F	42 (19.0%)	10 (15.4%)	0.506
F1	23 (10.4%)	7 (10.8%)	0.933
B	34 (15.6%)	10 (15.4%)	0.967
B5	13 (5.9%)	4 (6.2%)	1.000^a
B5a	9 (4.1%)	3 (4.6%)	0.783^a
B5b	4 (1.8%)	1 (1.5%)	1.000^a
B4a	4 (1.8%)	2 (3.1%)	0.622^a
B4b	3 (1.4%)	1 (1.5%)	1.000^a
C5178A	55 (24.9%)	24 (36.9)	0.056

The bold values indicates the statistical significance p < 0.05.

Fisher's exact test was used.

The D haplogroup, the D5 haplogroup, and the C5178A allele were associated with increased odds of CKD prevalence. After adjusting for multiple covariates, including gender, age, occupation, education, smoking, drinking, BMI, SBP, DBP, albumin, glucose, TG, HDL-C, and LDL-C levels, the D haplogroup, the D5 haplogroup, and the 5178A allele were associated with increased odds of CKD with ORs of 1.93 (95% CI: 1.00-3.72, p = 0.050), 4.76 (95% CI: 1.49-15.22, p = 0.009), and 2.04 (95% CI: 1.05-3.96, p = 0.035), respectively (Table 4). Other haplogroups did not show different frequencies between groups.

Table 4.

Odds of Chronic Kidney Disease According to D, D5 Haplogroups, and C5178 Polymorphism

CKD	D haplogroup	D5 haplogroup	D5178A
Crude OR (95% CI), p	1.74 (0.96-3.15), 0.069	4.23 (1.58-11.59), 0.004	1.77 (0.98-3.18), 0.058
Model 1 OR (95% CI), p	1.87 (1.02-3.43), 0.043	3.87 (1.41-10.65), 0.009	1.92 (1.05-3.50), 0.034
Model 2 OR (95% CI), p	1.85 (0.99-3.46), 0.054	3.48 (1.21-10.00), 0.021	1.90 (1.02-3.52), 0.043
Model 3 OR (95% CI), p	1.93 (1.00-3.72), 0.050	4.76 (1.49-15.22), 0.009	2.04 (1.05-3.96), 0.035

The bold values indicates the statistical significance p < 0.05.

Model 1: adjusted for gender and age.

Model 2: adjusted for gender, age, occupation, and education.

Model 3: adjusted for gender, age, occupation, education, BMI, SBP, DBP, albumin, glucose, TG, HDL-C, and LDL-C.

CI, confidence interval; OR, odds ratio.

Discussion

In this study, we conducted an association analysis between common mtDNA haplogroups with eGFR and CKD in a longevous cohort. To our knowledge, for the first time, we report the associations of the D haplogroup, the D5 haplogroup, and the 5178A allele with decreased eGFR levels and increased risk of CKD in the general longevous population.

mtDNA C5178A, the characteristic polymorphism that defines haplogroup D, causes a Leu→Met substitution at residue 237 of the NADH dehydrogenase subunit 2 (ND2), a mitochondrial subunit of complex I. The NADH dehydrogenase is the major site of reactive oxygen species (ROS) generation and a target of assault by ROS (Madamanchi and Runge, 2007). Two hospital-based studies explored the associations of C5178A/haplogroup D with phenotypes of kidney impairment. In 45 Chinese patients aged younger than 30 years with ESRD and 169 healthy controls, haplogroup D was associated with a 2.27-fold (95% CI: 1.11-4.67) increased risk of ESRD (Zhang et al., 2017). In 394 Japanese males (aged 29-76) who visited a hospital for medical check-ups, habitual drinking increased eGFR (p for trend = 0.003) or reduced the risk of mildly decreased eGFR (p for trend = 0.003) for Mt5178A carriers (Kokaze et al., 2013). In the present study, in line with the observations of Zhang et al. (2017), which was conducted in hospital patients, we found that the D haplogroup, the D5 haplogroup, and the 5178A allele were associated with decreased eGFR levels and an increased risk of CKD (eGFR <60 vs. >60 mL/min/1.73 m²) in a general Chinese longevous population.

The A genotype of the mtDNA polymorphism 5178A and the haplogroup D were not only associated with an increased risk of CKD in Chinese individuals, as observed by both Zhang et al. (2017) and our group, but have also been associated with an increased risk of esophageal cancer in Chinese individuals (Li et al., 2011) and presented in a significantly lower frequency among Japanese elite endurance runners than in control subjects (Tamura et al., 2010). Interestingly, the 5178A allele has been found to be associated with a decreased risk of myocardial infarction among the Japanese (Takagi et al., 2004) and a decreased risk of Parkinson's disease and diabetes among the Chinese (Liou et al., 2012; Gusdon et al., 2015), but is found at a significantly lower frequency among Japanese centenarians than controls (Tanaka et al., 1998). The reasons underlying the different observations among the aforementioned studies are unclear. The differences in environment and disease status among studies may partly explain the different findings.

Data concerning the linkage between the mtDNA haplogroups and pharmacogenetic effects on the kidney phenotype are also limited. In 303 Spanish diabetes patients and 153 healthy controls, kidney function was worse in JT haplogroup and other haplogroups (Diaz-Morales et al., 2018). In 466 Italian diabetes patients, haplogroup U3 was associated with increased risk of complication of nephropathy, and V with renal failure (Achilli et al., 2011). In 261 Spanish patients who received kidney transplant, haplogroup V and J had decreased risks of chronic renal allograft dysfunction than H haplogroup (Jiménez-Sousa et al., 2014). In 881 British patients receiving cardiac bypass surgery, the haplogroup profile comprised H, J, T, U, and K was significantly different between those who had postsurgery acute kidney injury and who did not have (Kanagasundaram et al., 2019). In 312 Spanish patients who received a cadaveric kidney and were treated with a standard immunosuppressive therapy, mitochondrial haplogroup H was associated with the risk for new-onset diabetes after transplantation (Tavira et al., 2014). However, since these European haplogroups such as JT, U, V, U3, and H were not the major mitochondrial haplogroups found in the Chinese population, we could not evaluate their effects on kidney phenotypes in Chinese populations.

The limitations of this study need to be mentioned. First, similar to most haplogroup-CKD association studies, the sample size of this study is relatively small. Second, given the advanced age of this patient population, and the sensitivity of the kidney to mitochondrial dysfunction, somatic mutations in the mtDNA are likely to play a decisive role in the eGFR. However, we did not determine if the somatic mutation rate is higher in the kidney or blood cells of haplotype D patients. Finally, we did not examine the functional significance of the alleles of the C5178A locus, which needs further exploration.

In conclusion, a cohort study was conducted among a population of longevous individuals, wherein we screened the common mtDNA haplogroups presented in the Chinese populations and found that the D haplogroup, D5 haplogroup, and 5178A allele were associated with decreased eGFR levels and increased risk of CKD. The associations need to be validated in future studies with larger cohorts.

Ethical Standard

The Human Ethics Committee of the School of Life Sciences, Fudan University, Shanghai, People's Republic of China, approved the present study. Written informed consent was obtained from all participants before the study.

Footnotes

Acknowledgments

We acknowledge all participants involved in the present study.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This work was financially supported by grants from the National Key R&D Program of China (2018YFC2000400, 2018YFC2002000), the National Natural Science Foundation of China (81670465, 81600577).

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