Skip to main content
PLOS One logoLink to PLOS One
. 2019 Dec 18;14(12):e0224923. doi: 10.1371/journal.pone.0224923

Early changes in pulmonary function and intrarenal haemodynamics and the correlation between these sets of parameters in patients with T2DM

He Tai 1,2,#, Xiao-lin Jiang 3,#, Jin-song Kuang 4, JJ JiaJia Yu 1, Ye-tao Ju 1, Wen-cong Cao 1, Wei Chen 1, Xin-yue Cui 1, Li-de Zhang 3, Xin Fu 1, Lian-qun Jia 1,*, Yi Zhang 5,*
Editor: Alon Harris6
PMCID: PMC6919602  PMID: 31851677

Abstract

Purpose

The main objectives of this study were to assess the early changes in pulmonary function and intrarenal haemodynamics and to determine the correlation between pulmonary function and intrarenal haemodynamics in patients with type 2 diabetes mellitus (T2DM).

Methods

96 patients with T2DM (diabetes group) without diabetes kidney disease (DKD) and 33 healthy subjects (control group) were enrolled in studies intended to assess the early changes in pulmonary function and intrarenal haemodynamics associated with diabetes, as well as to determine the correlation between pulmonary function and intrarenal haemodynamics.

Results

Pulmonary functional parameters were negatively correlated with HbA1c levels and diabetes duration (P< 0.05). Moreover, renal functional parameters were positively correlated with HbA1c levels and diabetes duration (P<0.05). Additionally, pulmonary functional parameters were negatively correlated with renal functional parameters (P<0.05). Multiple linear regression analysis of the relationship between pulmonary functional parameters and the bilateral kidney arterial resistivity index (RI) showed that all the pulmonary functional parameters were significantly correlated with the arterial RI (P< 0.05).

Conclusions

Patients displayed changes in pulmonary function and intrarenal haemodynamics during the preclinical stages of DKD. Regulating glycaemia may improve intrarenal haemodynamics in the bilateral interlobular renal arteries. Moreover, during the preclinical stages of DKD, the right kidney RI is a effective predictor of early changes in pulmonary function in adult T2DM patients.

Trial registration

ClinicalTrials.gov (NCT02798198); registered 8 June 2016.

Introduction

The prevalence of type 2 diabetes mellitus (T2DM) is increasing worldwide, particularly in Asian countries [1]. T2DM has been identified as an independent risk factor for cardiovascular disease, as affected patients have a two-fold higher risk of developing cardiovascular disease than unaffected patients [2], and leads to the development of vascular diseases such as diabetes nephropathy (DN) and diabetes retinopathy (DR) [3], which are the leading causes of end-stage renal disease (ESRD) and acquired blindness, respectively [4]. New terminology describing kidney disease attributable to diabetes has been introduced in recent guidelines (National Kidney Foundation, 2007), which stipulate that the term ‘DN’ should be replaced by ‘diabetes kidney disease (DKD)’.

More than 3 decades ago, researchers established that patients with T2DM had less alveolar gas exchange capacity than healthy subjects [5]. However, hyperglycaemia-induced pulmonary vascular injury is a complication of T2DM that has been overlooked by researchers attempting to devise treatments for the numerous complications associated with the disease [6].

Colour doppler ultrasound (CDU), a modality that is widely used in a variety of medical fields, evaluates blood flow velocity based on shifts in Doppler signals [7]. Patients with hyperglycaemia and uncontrolled blood pressure have significantly increased blood flow compared to patients with systemic hypertension without diabetes [8]. The Doppler resistivity index (RI) [peak systolic velocity (PSV) − end-diastolic velocity (PED)/PSV] that reflects intrarenal vascular resistance has been widely used to quantify the alterations in renal blood flow that may develop in renal disease [9].

To the best of our knowledge, no studies have investigated the correlation between pulmonary function and intrarenal haemodynamics in patients with T2DM with normal renal function. We believe that it is important to investigate the correlation between pulmonary functional parameters and intrarenal haemodynamics, as understanding this relationship may enable us to predict and prevent complications of diabetes and predict changes in pulmonary function and intrarenal haemodynamics in adults.

Materials and methods

Subjects

We selected 115 patients (60 males and 55 females) with T2DM without DKD, who were enrolled in a diabetes group, and 38 healthy subjects (21 males and 17 females), who were enrolled in a control group, from the diabetes outpatient clinic of the Fourth People’s Hospital in Shenyang (From August 2016 to October 2016). All the participants were Han Chinese. All the patients with T2DM were instructed to participate in a diet and exercise program developed by professional nutritionists.

Study design

A total of 115 patients with TD2M and 38 healthy subjects, all of whom provided urine samples for analysis (AER and UACR) to exclude DKD, were recruited for the single time-point measurement phase of the study. After the above analysis, 12 patients with T2DM who were found to have DKD were excluded from the study. Additionally, 3 healthy subjects suffering from colds were also excluded from the study. Thus, 103 patients with T2DM and 35 healthy subjects were eligible to participate in subsequent tests. The subjects fasted for at least 8 hours, after which 5 ml of venous blood was collected from each participant. The subjects also underwent pulmonary function tests, intraocular pressure measurements, and retrobulbar haemodynamics (RI) assessments, the latter of which were performed by CDU. We could not locate the interlobular renal arteries in 7 patients with T2DM and 2 healthy subjects (5.71%) with urolithiasis, who were subsequently excluded from the study. Thus, 96 patients with T2DM (52 males, 44 females) and 33 healthy subjects (18 males, 15 females) ultimately completed this phase of the study.

The two groups did not differ significantly (P>0.05) with respect to the sex ratio or age (range, 35 to 66 years). Data pertaining to diabetes durations (range, 4 to 12 years) and HbA1c values (range, 7.0% (53 mmol/mol) to 10% (86 mmol/mol)), FBG (range, 6.8 to 9.2 mg/dl), 2 hPBG (range, 9.2 to 13.6 mg/dl), the indicated pulmonary functional parameters (VC% (range, 73 to 90%), FVC% (range, 70 to 84%), FEV1% (range, 70 to 85%), PEF% (range, 47 to 73%), MVV% (range, 75 to 91%), TLC% (range, 81 to 99%), the FEV1/FVC% ratio (range, 70 to 82%), DLCO% (range, 74 to 90%), and the DLCO/VA% ratio (range, 74 to 92%)), the indicated intrarenal haemodynamics parameter (bilateral kidney resistivity index (RI)) (range, 0.6 to 0.7), and the indicated blood lipid (TC (range, 178 to 236 mg/dl), HDL-C (range, 31 to 48 mg/dl), LDL-C (range, 102 to 142 mg/dl), and TG(range, 138 to 173 mg/dl)) and renal functional parameters (BUN (range, 3.6 to 7.0 mmol/L), Cr (range, 31 to 62 μmol/L), and GFR (range, 110 to 150 ml/minute)), as well as data pertaining to the AER (range, 12 to 18 μg/min), the UACR (range, 13 to 18 mg/g) and BP (SBP (range, 112 to 138 mmHg), DBP (range, 75 to 100 mmHg), were recorded (Table 1). T2DM and DKD was diagnosed in accordance with the guidelines of the American Diabetes Association [10].

Table 1. Baseline demographic and clinical characteristics.

Characteristics Control group Diabetes group t2 value P value*
NO. (n) 33 96 - -
Sex, n (%) Male 18 (54.5) 52 (54.2) 0.001 0.970
Female 15 (45.5) 44 (45.8)
Age (years) 51.73±7.99 52.59±9.06 0.423 0.674
Diabetes duration (years) - 7.92±2.17 - -
FBG (mmol/l) 4.97±0.55 7.88±0.63 20.334 < 0.0001*
2 hPBG (mmol/l) 7.20±0.31 11.53±0.93 25.499 < 0.0001*
HbA1c % 5.19±0.57 8.04±0.85 16.303 < 0.0001*
mmol/mol 46.91±16.69 65.77±8.52 6.049 < 0.0001*
Baseline HbA1c,
n (%)
≤ 7%/ (53 mmol/mol) 33 (100.0) 6 (16.2) 49.63 < 0.0001*
> 7%/ (53 mmol/mol) 0 (0.0) 31 (83.8)
TC (mg/dl) 188.22±14.85 202.97±14.70 4.113 < 0.0001*
HDL-C (mg/dl) 45.64±4.68 37.89±4.34 -7.187 < 0.0001*
LDL-C (mg/dl) 112.06±9.22 122.19±9.87 4.422 < 0.0001*
TG (mg/dl) 142.21±8.85 153.03±8.37 5.251 < 0.0001*
Cholesterol-lowering drugs
n (%)
use 6 (18.2) 15 (40.5) 4.152 0.042
no use 27 (81.8) 22 (59.5)
SBP (mmHg) 124.70±6.72 127.54±5.96 1.876 0.065
DBP (mmHg) 88.97±5.07 89.97±5.71 0.774 0.442
Cr (μmol/L) 64.64±7.67 77.97±8.14 7.032 < 0.0001*
BUN (mmol/L) 4.79±0.61 6.13±0.72 8.361 < 0.0001*
GFR (ml/minute) 119.70±6.96 134.19±5.46 9.746 < 0.0001*
AER (μg/min) 7.97±1.69 16.22±1.27 23.25 < 0.0001*
UACR (mg/g) 7.82±1.33 15.68±1.18 26.16 < 0.0001*
Mean right kidney RI 0.61±0.02 0.65±0.02 8.089 < 0.0001*
Mean left kidney RI 0.61±0.02 0.65±0.02 7.765 < 0.0001*
Mean Doppler RI 0.61±0.02 0.65±0.02 11.240 < 0.0001*
VC Litre (% of predicted) 87.30±4.28 81.81±4.20 -5.414 < 0.0001*
FVC Litre (% of predicted) 79.12±3.80 76.08±3.14 -3.665 < 0.0001*
FEV1 Litre (% of predicted) 77.88±2.42 75.35±2.90 -3.932 < 0.0001*
PEF L/S (% of predicted) 58.21±2.88 51.62±2.63 -10.009 < 0.0001*
MVV Litre (% of predicted) 89.21±2.13 85.73±2.28 -6.574 < 0.0001*
TLC Litre (% of predicted) 95.39±2.78 91.35±3.75 -5.069 < 0.0001*
FEV1/FVC (% of predicted) 77.85±2.95 74.19±3.03 -5.111 < 0.0001*
DLCO (mL/min/mmHg) (% of predicted) 87.15±2.73 84.86±2.94 -3.362 0.001*
DLCO/VA(mL/min/mmHg) (% of predicted) 87.89±2.83 90.76±2.45 -4.506 < 0.0001*

Note: FBG, fasting plasma glucose; 2hPBG, 2-hour postprandial blood glucose; HbA1c, glycosylated hemoglobinA1c; TC, Total cholesterol; HDL-C, High-density lipoprotein cholesterol; LDL-C, Low-density lipoprotein cholesterol; TG, Triglycerides; SBP, systolic blood pressure; DBP, diastolic blood pressure; BUN, blood urea nitrogen; Cr, creatinine; UACR, urinary albumin/creatinine ratio; AER, albumin excrete rate; GFR, glomerular filtration rate; VC, vital capacity; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 second; PEF, peak expiratory force; MVV, maximal voluntary ventilation; TLC, total lung capacity; FEV1/FVC, forced expiratory volume in 1 second/ forced vital capacity; DLCO, diffusing capacity for carbon monoxide of lung; DLCO/VA, diffusing capacity for carbon monoxide of lung/unit volume

*P< 0.05, Statistically significant

Study assessments and endpoints

Blood specimen collection and laboratory testing: Venous blood samples were collected between 6 and 8 AM following a fasting period of at least 8 hours and used for measurements of FPG levels, HbA1c levels, blood lipid levels, and renal functional parameters. Plasma glucose levels were determined by the glucose oxidase method. Venous blood samples were collected to measure 2-hPG levels. They were measured according to the instructions of the corresponding research kits.

Urine sample collection and laboratory tests: Urine output was quantified via a single 24-h urine collection. Urinary albumin concentrations were measured using a double-antibody radio immunoassay with a sensitivity of 0.5 mg/l, an intra-assay coefficient of variation of 4.5%, and an interassay coefficient of variation of 5.3% within the range of 10–50 mg/l [11].

Blood pressure (BP) measurements: systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured using an electronic sphygmomanometer.

Pulmonary function measurements: The indicated pulmonary functional parameters (VC%, FVC%, FEV1%, PEF%, MVV%, TLC%, the FEV1/FVC% ratio, DLCO%, and the DLCO/VA% ratio) were measured using a spirometer. We used the measured-to-expected value ratios and the percentages of the predicted value to eliminate the influence of age, height, and weight on the results.

Intrarenal haemodynamic parameter measurements: We measured the indicated intrarenal haemodynamics parameters (PSV, EDV, and RI) in the bilateral interlobular renal arteries of subjects. The pulsed Doppler sampling gate was located in the interlobar arteries, and the angle of insonation. The PSV and EDV were documented in centimetres per second, and the RI was calculated [12].

Statistical analysis

Measurement data were expressed as the mean ±standard deviation (SD), and numerical data were expressed as percentages. Statistical analysis was conducted using the SPSS statistical package (Version 17.0, SPSS Inc. Chicago, IL, USA). The linear correlations between pulmonary function and HbA1c levels and diabetes duration, the linear correlations between intrarenal haemodynamics and HbA1c and diabetes duration and the linear correlations between pulmonary function and intrarenal haemodynamics were evaluated using Pearson’s correlation coefficient. For multiple linear regression analysis, the pulmonary functional parameters were the dependent variables, and the bilateral kidney RIs were the independent variables. P< 0.05 was considered statistically significant.

Results

Participant baseline characteristics

At last, 96 subjects (52 males and 44 females) were enrolled in the diabetes group, and 33 healthy people (18 males, 15 females) were enrolled in the control group.

Pulmonary functional parameters, FPG, 2 hPG, HbA1c, TC, LDL-C, TG, Cr, and BUN levels; the GFR, AER, and UACR; and the bilateral RIs were significantly greater in the diabetes group than in the control group (P< 0.05). HDL-C levels were lower in the diabetes group than in the control group (P< 0.05); however, SDP and DBP were not significantly different between the two groups (P> 0.05) (Table 1).

Correlation between pulmonary functional parameters and HbA1c and diabetes duration

Pulmonary functional parameters were significantly negatively correlated with HbA1c and diabetes duration (P< 0.05) (Table 2); however, in the control group, the correlation between pulmonary functional parameters and HbA1c was not statistically significant (P> 0.05).

Table 2. Correlation of pulmonary function parameters to HbA1c and diabetes duration in diabetes group.

Pulmonary function parameters HbA1c Diabetes duration
VC r = -0.161 r = -0.690*
P value 0.342 < 0.0001
FVC r = 0.250 r = -0.213
P value 0.135 0.205
FEV1 r = -0.017 r = -0.024
P value 0.918 0.886
PEF r = -0.132 r = -0.177
P value 0.435 0.294
MVV r = -0.168 r = -0.511*
P value 0.321 0.001
TLC r = -0.212 r = -0.373*
P value 0.208 0.023
FEV1/FVC r = -0.129 r = -0.394*
P value 0.447 0.016
DLCO r = -0.185 r = -0.303
P value 0.272 0.068
DLCO/VA r = -0.306 r = -0.329*
P value 0.066 0.047

Note:

*P< 0.05, Statistically significant

HbA1c, glycosylated hemoglobinA1c; VC, vital capacity; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 second; PEF, peak expiratory force; MVV, maximal voluntary ventilation; TLC, total lung capacity; FEV1/FVC, forced expiratory volume in 1 second/ forced vital capacity; DLCO, diffusing capacity for carbon monoxide of lung; DLCO/VA, diffusing capacity for carbon monoxide of lung/unit volume

Correlation between renal functional parameters and HbA1c and diabetes duration

Renal functional parameters were significantly positively correlated with HbA1c and diabetes duration (P< 0.05) (Table 3); however, in the control group, the correlation between renal functional parameters and HbA1c was not statistically significant (P> 0.05).

Table 3. Correlation of the renal parameters to HbA1c and diabetes duration in diabetes group.

Renal parameters HbA1c Diabetes duration
Cr r = 0.727* r = 0.046
P value < 0.0001 0.789
BUN r = 0.050 r = 0.151
P value 0.769 0.373
GFR r = 0.635* r = 0.291
P value 0.000 0.081
AER r = 0.017 r = 0.354*
P value 0.922 0.032
UACR r = 0.272 r = 0.348*
P value 0.103 0.035
Right kidney RI r = 0.411* r = 0.847*
P value 0.012 0.000
Left kidney RI r = 0.565* r = 0.738*
P value 0.000 0.000

Note:

*P< 0.05, Statistically significant

BUN, blood urea nitrogen; Cr, creatinine; UACR, urinary albumin/creatinine ratio; AER, albumin excrete rate; GFR, glomerular filtration rate; HbA1c, glycosylated hemoglobinA1c; RI, resistivity index

Correlation between pulmonary functional parameters and renal functional parameters

Pulmonary functional parameters were significantly negatively correlated with renal functional parameters (P< 0.05) (Table 4); however, in the control group, the correlation between pulmonary functional parameters and renal functional parameters was not statistically significant (P> 0.05). Multiple linear regression analysis showed that all nine pulmonary functional parameters assessed herein were significantly correlated with the bilateral kidney RI (P< 0.05). (Table 5).

Table 4. Correlation between pulmonary function parameters and renal parameters in diabetes group.

Pulmonary function Renal parameters
Cr BUN GFR AER UACR Right RI Left RI
VC r = 0.125 r = 0.090 r = -0.336* r = - .497* r = - 0.372* r = - 0.718* r = - 0.535*
P value 0.462 0.597 0.042 0.002 0.023 0.000 0.001
FVC r = 0.013 r = - 0.116 r = - 0.037 r = - 0.046 r = 0.105 r = - 0.328* r = - 0.194
P value 0.938 0.494 0.830 0.786 0.537 0.048 0.250
FEV1 r = 0.180 r = - 0.071 r = - 0.061 r = - 0.021 r = 0.010 r = - 0.174 r = - 0.114
P value 0.286 0.676 0.722 0.901 0.954 0.302 0.500
PEF r = - 0.172 r = - 0.155 r = - 0.142 r = 0.058 r = - 0.094 r = - 0.050 r = - 0.036
P value 0.308 0.358 0.402 0.731 0.578 0.769 0.831
MVV r = .100 r = - .005 r = - .447* r = - .037 r = - .240 r = - .446* r = - 0.343*
P value 0.556 0.978 0.006 0.829 0.153 0.006 0.038
TLC r = 0.026 r = 0.079 r = - 0.567* r = - 0.063 r = - 0.124 r = - 0.390* r = - 0.263
P value 0.881 0.641 0.000 0.711 0.464 0.017 0.115
FEV1/FVC r = - 0.244 r = - 0.043 r = - 0.255 r = - 0.047 r = 0.049 r = - 0.453* r = - 0.322
P value 0.146 0.802 0.128 0.782 0.774 0.005 0.052
DLCO r = 0.020 r = - 0.103 r = - 0.217 r = - 0.022 r = - 0.053 r = 0.327* r = - 0.267
P value 0.908 0.543 0.197 0.899 0.755 0.048 0.111
DLCO/VA r = 0.098 r = - 0.131 r = - 0.009 r = - 0.179 r = - 0.027 r = - 0.417* r = - 0.368*
P value 0.565 0.439 0.956 0.290 0.872 0.010 0.025

Note

*P< 0.05, Statistically significant

BUN, blood urea nitrogen; Cr, creatinine; UACR, urinary albumin/creatinine ratio; AER, albumin excrete rate; GFR, glomerular filtration rate; VC, vital capacity; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 second; PEF, peak expiratory force; MVV, maximal voluntary ventilation; TLC, total lung capacity; FEV1/FVC, forced expiratory volume in 1 second/ forced vital capacity; DLCO, diffusing capacity for carbon monoxide of lung; DLCO/VA, diffusing capacity for carbon monoxide of lung/unit volume; RI, resistivity index

Table 5. Multiple regression analysis between pulmonary function and bilateral kidney RI in diabetes group.

Dependent variable Coefficient P value*
R R2 F Right RI Left RI
VC 0.728 0.530 19.197 - 0.898 0.218 0.000*
FVC 0.355 0.126 2.451 - 0.529 0.244 0.101
FEV1 0.182 0.033 0.583 - 0.252 0.094 0.563
PEF 0.051 0.003 0.044 -0.063 0.016 0.957
MVV 0.448 0.201 4.270 - 0.513 0.081 0.022*
TLC 0.404 0.164 3.325 - 0.546 0.188 0.048*
FEV1/FVC 0.463 0.214 4.636 - 0.591 0.167 0.017*
DLCO 0.327 0.107 2.036 - 0.337 0.012 0.146
DLCO/VA 0.419 0.175 3.618 - 0.356 0.074 0.038*

Note:

*P< 0.05, Statistically significant

RI, resistivity index; BUN, blood urea nitrogen; Cr, creatinine; UACR, urinary albumin/creatinine ratio; AER, albumin excrete rate; GFR, glomerular filtration rate; VC, vital capacity; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 second; PEF, peak expiratory force; MVV, maximal voluntary ventilation; TLC, total lung capacity; FEV1/FVC, forced expiratory volume in 1 second/ forced vital capacity; DLCO, diffusing capacity for carbon monoxide of lung; DLCO/VA, diffusing capacity for carbon monoxide of lung/unit volume

Discussion

Renal Doppler RIs are widely used to evaluate blood flow in renal parenchymal diseases. RIs, which reflect intrarenal vascular resistance, a measure of vascular compliance [9], are also widely used to quantify changes in renal blood flow that may be attributable to renal diseases. Interestingly, previous studies have shown that renal Doppler sonography is an effective noninvasive and inexpensive means of screening for renovascular hypertension correctable via treatment with captopril [13]; therefore, we evaluated intrarenal haemodynamics by examining the RI using Doppler sonography.

HbA1c is an indicator of diabetes control; thus, the higher the HbA1c level, the poorer the diabetes control and the higher the circulating glucose concentration. Persistent elevations in circulating glucose levels (as measured by HbA1c) lasting 3 months or longer can lead to increases in nonenzymatic tissue protein glycosylation [14]. The findings of this study regarding HbA1c levels were consistent with those of other studies despite the fact that the current study enrolled patients with HbA1c levels as low as 7.0% (53 mmol/mol) [14]. Prabhu M et al [15] showed that only 23 (11.5%) patients enrolled in their study were aware of the importance of HbA1c levels. Moreover, the authors of that study noted that the proportion of patients who achieved the target HbA1c level of <7% (53 mmol/mol) was low in patients with DR. In our study, the proportion of patients (12/96; 12.50%) who reached this HbA1c standard [<7.0% (53 mmol/mol)] was also low, as most of the patients enrolled herein could not control their glycaemia adequately; thus, the mean FPG (7.88 mmol/l) and 2-hPG (11.53 mmol/l) levels in the diabetes group were higher than the corresponding target levels (7 mmol/l and 10 mmol/l respectively).

The mechanisms underlying the occurrence of lung damage in diabetes are not fully understood; however, glycaemic control appears to play a key role in the association between reductions in lung function and diabetes. In addition, nonenzymatic glycosylation of proteins in the lungs decreases lung compliance [16] and thus diminishes the large microvascular reserve of the alveolar-capillary system and increases its susceptibility oxidative damage. Thus, hyperglycaemia damages the lung [17]. Clinically, loss of microvascular reserve in the lung may be associated with an increased risk of hypoxia in acute or chronic pathological lung conditions [17].

Lung CO transfer capacity is significantly affected by the integrity of the lung capillary endothelium, a finding that supports that idea that clinicians should devote more attention to pulmonary vascular changes. The reports on lung function testing in patients with diabetes that have been published during the last 15 years have focused predominantly on pulmonary microangiopathy; however, relatively few studies have focused on pulmonary mechanical function. The lung functional parameters that are related specifically to pulmonary microangiopathy include pulmonary capillary blood volume and CO transfer capacity [18]. Niranjan V found that TLC, FVC, FEV1, and VC values were significantly lower in patients with type 1 diabetes than in healthy subjects [19]. However, we selected patients with T2DM whose diabetes durations ranged from 4 to 12 years (<15 years) and assessed a smaller population than Niranjan V [20]. The results pertaining to the correlations between HbA1c and pulmonary function that were noted in previous studies were inconsistent. Study noted weak associations between HbA1c and spirometric parameters and strong correlations between diabetes duration and pulmonary function [21]. Another cross-sectional population study noted that plasma glucose levels were negatively correlated with FVC and/or FEV [22]. HbA1c is an indicator of diabetes control, and our results revealed that pulmonary functional parameters were negatively correlated with HbA1c levels (P< 0.05); however, in healthy people, the correlations between the above parameters were not statistically significant (P> 0.05). The correlations between pulmonary functional parameters and diabetes duration were statistically significant (P< 0.05) (Table 2), results similar to those of previous studies [6, 2122]. Notably, good glycaemic control and regular diabetes treatment have positive effects on lung function in patients with T2DM.

The precise mechanisms underlying DKD development are unknown; however, several theories exist regarding the specific processes that affect haemodynamics in DKD. Renin-angiotensin system (RAS) activation reportedly induces intrarenal haemodynamic abnormalities in diabetes, the intrarenal RAS may be activated in diabetes and subsequently facilitate increases in the RI, and blocking RAS activation with captopril may reduce intrarenal vascular resistance in diabetes [23, 24].

Elevated RIs have been reported to be associated with vascular-interstitial diseases, including DKD (but not glomerulopathies). Increased RIs may be reflective of decreased tissue and vascular compliance, as well as increased vascular resistance [9]. However, the early stages of DN are associated with an increased GFR and variable increases in renal plasma flow and the filtration fraction in both clinical and experimental settings. These changes may also be reflected by increased RIs. Our results showed that the mean GFR in the diabetes group (134.19±5.46 ml/min) was significantly greater than that in the control group (119.70±6.96 ml/min) (P< 0.05), results similar to those of the study by Pelliccia P and Matsumoto N [24, 25]. RIs are measured by duplex Doppler sonography, a noninvasive and inexpensive tool that is useful for demonstrating the haemodynamic abnormalities present in patients with DKD [26]. Biopsy studies involving children have shown that basement membrane thickening and mesangial expansion in the kidney develop prior to the onset of microalbuminuria [27]. To our knowledge, our study is the first to assess the early changes in intrarenal haemodynamics associated with diabetes in adults with T2DM without any evidence of renal dysfunction, and our data indicate that the RI can be used to predict changes in renal function in the preclinical stage of DKD, results similar to those of the study by Pelliccia P, which involved children [24].

However, there is no general agreement with respect to the significance and predictive value of the renal RI in patients with DKD. Researchers have performed several studies regarding the application of Doppler sonography for the evaluation of intrarenal haemodynamic abnormalities in adults with DKD [9]; however, studies regarding the preclinical stage of DKD (in which renal function is normal) in adults are still lacking. In our study, we aimed to explore whether Doppler sonography could be used to detect alterations in the renal RI in adults with diabetes who had normal renal function, according to their laboratory test results.

We observed that adults with T2DM had significantly higher RI values than healthy controls (P< 0.05) (Table 1); however, all the patients (in both the diabetes and control groups) had at least one RI value less than or equal to 0.70, the generally accepted cut-off value separating healthy adults and children older than 6 years (rather than younger children) from unhealthy adults and children [28]. The RI is positively correlated with HbA1c and diabetes duration (both P< 0.05) (Table 3); however, in the control group, the correlation between renal functional parameters and HbA1c was not statistically significant (P> 0.05). In the present study, all the RI values were >0.5. Additionally, we observed that BUN and Cr and the GFR, AER, and UACR were positively correlated with HbA1c and diabetes duration; however, not all of these correlations were statistically significant. Thus, we concluded that the predictive value of the RI was greater than that of the other parameters listed above. As the sample size of the study was not large enough for the results pertaining to the other parameters to achieve sufficient statistical power, we able to analyse only the predictive value of the RI and GFR.

In our study, not all the correlations between pulmonary functional parameters and renal functional parameters were statistically significant. All the pulmonary functional parameters were significantly negatively correlated with the bilateral kidney RI (P< 0.05) (Table 4); however, in the control group, the correlations between pulmonary functional parameters and the RI were not statistically significant (P> 0.05). According to our results, the bilateral kidney RI may be used to evaluate the interactions between renal and pulmonary function during the preclinical stage of DKD. Moreover, multiple linear regression analysis showed that all the correlations between the pulmonary functional indices assessed herein and the bilateral kidney RI were statistically significant (P< 0.05). (Table 5). Therefore, the results of our multiple linear regression analysis indicated that the right RI could be used as a strong predictor of pulmonary function in adults with T2DM with normal renal function. Why the right RI is a more powerful predictor of pulmonary function than the left RI. We surmised that the right RI was more accurate than in the left in our study because our Doppler sonographer was standing on the right side of each patient.

Conclusions

The results of this study indicate that in addition to renal functional parameters, the combination of the right kidney RI, GFR, and HbA1c may also be good predictors of changes in pulmonary function in patients with diabetes, as well as a more sensitive indicator of changes in pulmonary function in such patients during the pre-clinical stages of DKD than the UACR or AER. The predictive value of the combination is higher than that of either parameter alone.

However, our study had several limitations that should be addressed in future studies. First, we failed to observe the changes in alveolar tissue morphology associated with diabetes and did not identify the specific protein responsible for inducing the changes. Because not all the patients underwent a lung biopsy, we had to adopt an animal model to study alveolar tissue samples. Second, we did not assess the long-term changes in pulmonary function associated with diabetes, and we studied the correlations between pulmonary and renal functional parameters only during the preclinical stage of DKD. It is worth evaluating whether they can be used to predict pulmonary function and renal function during the preclinical stage of DKD. Moreover, we studied T2DM without DKD but did not determine the correlations between the above parameters in different phases of DKD. Additionally, arterial elasticity (which influences haemodynamic parameters) decreases with increasing age; however, we did not consider age as a variable in our study. Therefore, we recommend that clinicians monitor patients with T2DM for signs of lung damage in addition to monitoring them for signs of DKD and DR.

Supporting information

S1 File. All data underlying the findings are described in this file.

(XLS)

Acknowledgments

The authors would like to thank all of the patients and their families, the team of investigators, research nurses, and operations staff involved in this study. Editorial support (in the form of writing assistance, including development of the initial draft based on author input, assembling tables and figures, collating authors comments, grammatical editing and referencing) was provided by He Tai.

Abbreviations

2hPBG

2-hour postprandial blood glucose

AER

albumin excrete rate

AGEs

advanced glycated end-products

BP

blood pressure

BUN

blood urea nitrogen

CDU

color doppler ultrasound

CMECs

cardiac microvascular endothelial cells

Cr

creatinine

DBP

diastolic blood pressure

DKD

diabetes kidney disease

DLCO

diffusing capacity for carbon monoxide of lung

DLCO/VA

diffusing capacity for carbon monoxide of lung/unit volume

DN

diabetes nephropathy

DR

diabetes retinopathy

EDV

end-diastolic velocity

ESRD

end-stage renal disease

FBG

fasting plasma glucose

FEV1

forced expiratory volume in 1 second

FEV1/FVC

forced expiratory volume in 1 second/ forced vital capacity

FVC

forced vital capacity

GFR

glomerular filtration rate

HbA1c

glycosylated hemoglobinA1c

HDL-C

High-density lipoprotein cholesterol

K/DOQI

kidney Disease Outcome Quality Initiatives

LDL-C

Low-density lipoprotein cholesterol

LS

least squares

MVV

maximal voluntary ventilation

OAPP

advanced oxidation protein products

OGTT

oral glucose tolerance test

PEF

peak expiratory force

PSV

peak systolic velocity

RAS

renin-angiotensin system

RBS

random blood sugar

RI

resistivity index

SBP

systolic blood pressure

SD

standard deviation

T2DM

type 2 diabetes mellitus

TC

Total cholesterol

TG

Triglycerides

TLC

total lung capacity

UACR

urinary albumin/creatinine ratio

VC

vital capacity

Data Availability

All relevant data are within the Supporting Information files.

Funding Statement

The study was supported by the Natural Science Foundation of China 81774022.

References

  • 1.Ma Ronald CW, Chan Juliana CN. Type 2 diabetes in East Asians: similarities and differences with populations in Europe and the United States. Ann N Y Acad Sci 2013. April; 1281: 64–91. 10.1111/nyas.12098 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Lin CH, Chang DM, Wu DJ, Peng HY, Chuang LM. Assessment of Blood Glucose Regulation and Safety of Resistant Starch Formula-Based Diet in Healthy Normal and Subjects With Type 2 Diabetes. Medicine 2015, 94 (33): e1332 10.1097/MD.0000000000001332 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Murea M, Ma L, Freedman BI. Genetic and environmental factors associated with type 2 diabetes and diabetes vascular complications. Rev Diabet Stud 2012; 9 (1): 6–22. 10.1900/RDS.2012.9.6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Yamagishi S, Fukami K, Matsui T. Crosstalk between advanced glycation end products (AGEs)-receptor RAGE axis and dipeptidyl peptidase-4-incretin system in diabetes vascular complications. Cardiovascular Diabetology 2015; 13;14: 2 10.1186/s12933-015-0176-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Kodolova IM, Lysenko IV, Saltykov BB. Change in the lung in diabetes mellitus. Arkh Pathol 1982, 44(7): 35–40. [PubMed] [Google Scholar]
  • 6.Kwon CH, Rhee EJ, Song JU, Kim JT, Kwag HJ, Sung KC. Reduced lung function is independently associated with increased risk of type 2 diabetes in Korean men. Cardiovasc Diabetol 2012. April 24;11:38 10.1186/1475-2840-11-38 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Goebel W, Lieb WE, Ho A, Sergott RC, Farhoumand R, Grehn F. Color Doppler imaging: a new technique to assess orbital blood flow in patients with diabetes retinopathy. Invest Ophthalmol Vis Sci 1995; 36 (5): 864–870. [PubMed] [Google Scholar]
  • 8.Dimitrova G, Kato S, Fukushima H, Yamashita H. Circulatory parameters in the retrobulbar central retinal artery and vein of patients with diabetesand medically treated systemic hypertension. Graefes Arch Clin Exp Ophthalmol 2009; 247 (1): 53–58. 10.1007/s00417-008-0925-1 [DOI] [PubMed] [Google Scholar]
  • 9.Tublin ME, Bude RO, Platt JF. The resistive index in renal Doppler sonography: where do we stand? AJR Am J Roentgenol 2003;180 (4): 885–887. 10.2214/ajr.180.4.1800885 [DOI] [PubMed] [Google Scholar]
  • 10.American Diabetes Association. Standards of medical care in diabetes 2007. Diabetes Care 2011; 34 (Suppl. 1): S11–S61. 10.2337/dc07-S004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Stevens LA, Coresh J, Schmid CH, Feldman HI, Froissart M, Kusek J, et al. Estimating GFR using serum cystatin C alone and in combination with serum creatinine: a pooled analysis of 3,418 individuals with CKD. Am J Kidney Dis 2008; 51 (5): 395–406. 10.1053/j.ajkd.2007.11.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Frauchiger B, Nussbaumer P, Hugentobler M, Staub D. Duplex sonographic registration of age and diabetes-related loss of renal vasodilatatory response to nitroglycerine. Nephrol Dial Transplant 2000;15 (6): 827–832. 10.1093/ndt/15.6.827 [DOI] [PubMed] [Google Scholar]
  • 13.Veglio F, Frascisco M, Melchio R, Provera E, Rabbia F, Oliva S, et al. Assessment of renal resistance index after captopril test by Doppler in essential and renovascular hypertension. Kidney Int 1995; 48 (5): 1611–1616. 10.1038/ki.1995.455 [DOI] [PubMed] [Google Scholar]
  • 14.Lukashevich V, Del Prato S, Araga M, Kothny W. Efficacy and safety of vildagliptin in patients with type 2 diabetes mellitus inadequately controlled with dual combination of metformin and sulphonylurea. Diabetes Obes Metab 2014; 16 (5): 403–409. 10.1111/dom.12229 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Prabhu M, Kakhandaki A, Chandra KR, Dinesh MB. A Hospital Based Study Regarding Awareness of Association Between Glycosylated Haemoglobin and Severity of Diabetes Retinopathy in Type 2 Diabetes Individuals. J Clin Diagn Res 2016; 10(1): NC01–4. 10.7860/JCDR/2016/15834.7014 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Cavan DA, Parkes A, O’Donnell MJ, Freeman W, Cayton RM. Lung function and diabetes. Respir Med 1991; 85 (3): 257–258 [DOI] [PubMed] [Google Scholar]
  • 17.Hsia CC, Raskin P. Lung function changes related to diabetes mellitus. Diabetes Technol Ther. 2007; 9 (Suppl 1): S73–S82. 10.1089/dia.2007.0227 [DOI] [PubMed] [Google Scholar]
  • 18.Barnes PJ. The role of inflammation and anti-inflammatory medication in asthma. Respir Med 2002; 96 (Suppl. A): S9 –S15. [PubMed] [Google Scholar]
  • 19.Niranjan V, McBrayer DG, Ramirez LC, Raskin P, Hsia CC. Glycemic control and cardiopulmonary function in patients with insulin-dependent diabetes mellitus. Am J Med 1997; 103 (6): 504–513. 10.1016/s0002-9343(97)00251-9 [DOI] [PubMed] [Google Scholar]
  • 20.Davis TM, Knuiman M, Kendall P, Vu H, Davis WA. Reduced pulmonary function and its associations in type 2 diabetes: the Fremantle Diabetes Study. Diabetes Res Clin Pract 2000; 50 (2): 153–159. 10.1016/s0168-8227(00)00166-2 [DOI] [PubMed] [Google Scholar]
  • 21.Lange P, Groth S, Kastrup J, Mortensen J, Appleyard M, Nyboe J, et al. Diabetes mellitus, plasma glucose and lung function in a cross-sectional population study. Eur Respir J 1989; 2 (1): 14–19. [PubMed] [Google Scholar]
  • 22.Miller JA. Impact of hyperglycemia on the renin angiotensin system in early human type 1 diabetes mellitus. J Am Soc Nephrol 1999; 10 (8): 1778–1785. [DOI] [PubMed] [Google Scholar]
  • 23.Taniwaki H, Ishimura E, Kawagishi T, Matsumoto N, Hosoi M, Emoto M, et al. Intrarenal hemodynamic changes after captopril test in patients with type 2 diabetes: a duplex Doppler sonography study. Diabetes Care 2003; 26 (1): 132–137. 10.2337/diacare.26.1.132 [DOI] [PubMed] [Google Scholar]
  • 24.Pelliccia P, Savino A, Cecamore C, Primavera A, Schiavone C, Chiarelli F. Early Changes in Renal Hemodynamics in Children with Diabetes: Doppler Sonographic Findings. J Clin Ultrasound 2008; 36 (6): 335–340. 10.1002/jcu.20457 [DOI] [PubMed] [Google Scholar]
  • 25.Matsumoto N, Ishimura E, Taniwaki H, Emoto M, Shoji T, Kawagishi T, et al. Diabetes mellitus worsens intrarenal hemodynamic abnormalities in non-dialyzed patients with chronic renal failure. Nephron 2000; 86 (1): 44–51. 10.1159/000045711 [DOI] [PubMed] [Google Scholar]
  • 26.Ellis EN, Warady BA, Wood EG, Hassanein R, Richardson WP, Lane PH, et al. Renal structural-functional relationships in early diabetes mellitus. Pediatr Nephrol 1997; 11 (5): 584–587. 10.1007/s004670050342 [DOI] [PubMed] [Google Scholar]
  • 27.Ohta Y, Fujii K, Arima H, Matsumura K, Tsuchihashi T, Tokumoto M, et al. Increased renal resistive index in atherosclerosis and diabetes nephropathy assessed by Doppler sonography. J Hypertens 2005;23 (10):1905–1910. 10.1097/01.hjh.0000181323.44162.01 [DOI] [PubMed] [Google Scholar]
  • 28.Kuzmić AC, Brkljacić B, Ivanković D, Galesić K. Doppler sonographic renal resistive index in healthy children. Eur Radiol 2000;10 (10): 1644–1648. 10.1007/s003300000466 [DOI] [PubMed] [Google Scholar]

Decision Letter 0

Alon Harris

23 Sep 2019

PONE-D-19-16612

Early Changes in Pulmonary Function and Intrarenal Haemodynamics and the Correlation between These Sets of Parameters in Patients with T2DM

PLOS ONE

Dear Dr jia,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We would appreciate receiving your revised manuscript by Nov 07 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Alon Harris

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2.  We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.  

Whilst you may use any professional scientific editing service of your choice, PLOS has partnered with both American Journal Experts (AJE) and Editage to provide discounted services to PLOS authors. Both organizations have experience helping authors meet PLOS guidelines and can provide language editing, translation, manuscript formatting, and figure formatting to ensure your manuscript meets our submission guidelines. To take advantage of our partnership with AJE, visit the AJE website (http://learn.aje.com/plos/) for a 15% discount off AJE services. To take advantage of our partnership with Editage, visit the Editage website (www.editage.com) and enter referral code PLOSEDIT for a 15% discount off Editage services.  If the PLOS editorial team finds any language issues in text that either AJE or Editage has edited, the service provider will re-edit the text for free.

Upon resubmission, please provide the following:

  • The name of the colleague or the details of the professional service that edited your manuscript

  • A copy of your manuscript showing your changes by either highlighting them or using track changes (uploaded as a *supporting information* file)

  • A clean copy of the edited manuscript (uploaded as the new *manuscript* file)

3. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.

We will update your Data Availability statement on your behalf to reflect the information you provide.

4. We note that you have reported significance probabilities of 0 in places. Since p=0 is not strictly possible, please correct this to a more appropriate limit, eg 'p<0.0001

5. Please include your tables as part of your main manuscript and remove the individual files. Please note that supplementary tables (should remain/ be uploaded) as separate "supporting information" files

6. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

Additional Editor Comments (if provided):

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This is very well written article on a subject which of great importance. Diabetes and its associated complications can affect the quality of life of patients affected by this disease. Evaluating the pulmonary functions and the RI of the blood vessels is a novel way to assess the prognosis of Diabetes.

Few grammatical errors need to be corrected.

Reviewer #2: Early Changes in Pulmonary Function and Intrarenal Haemodynamics and the Correlation between These Sets of Parameters in Patients with T2DM

This manuscript describes pulmonary function testing and renal function testing including the kidney resistivity index in patients with type 2 diabetes and controls. The study also compares the relationship between pulmonary and renal function in diabetic patients. The grammar, introduction, and methods are clear. The results and discussion may need more clarification.

Grammar:

There were few grammatical errors requiring revision. Examples include:

Author’s page: “Corresponding autuo” should read Corresponding author

Discussion, 4th paragraph: “that idea” should read the idea

Discussion, 4th paragraph: “Study noted weak associations…” should read One study

Discussion, 8th paragraph: “sufficient statistical power, we able…” should read we were able

Introduction:

The introduction explains the topic well, provides justification for the study, and cites existing literature. One point of clarification would be helpful:

Introduction, paragraph 4: “no studies have investigated the correlation between pulmonary function and intrarenal haemodynamics in patients with T2DM with normal renal function.” Are you stating that in your study, the diabetics had normal renal function? The discussion section references table 3 showing that the diabetics had increased GFR relative to controls.

Methods:

The methods section is very good. It includes sufficient information on the IRB/consent, protocol, inclusion/exclusion of patients, instruments used, and calculations. However, further clarification would be helpful in the following areas:

Study design, paragraph 1: “retrobulbar haemodynamics” I believe this is in error and should read intrarenal hemodynamics.

Results:

The results section is well organized and easy to read. However, further clarification would be helpful in the following areas:

Abstract and Results section: The results for renal function parameters are confusing and may be worded better:

Upon initial reads, stating that the renal function parameters are positively correlated with HbA1c and diabetes duration sounds like renal function gets better with diabetes, which is not the case, nor the point of your manuscript. You very nicely show that RI increases with both increased HbA1c and diabetes duration, which I believe is more clear.

In addition, when stating that pulmonary function and renal function are negatively correlated, it once again falsely sounds like the lungs do worse in diabetes while the kidneys get better. It would be clearer to state that the pulmonary function is negatively correlated with kidney RI, GFR, and HbA1C. I believe you state elsewhere in the paper that many of the other renal parameters were not statistically significant anyhow.

Discussion:

The discussion section reviews and analyzes the current study. It cites relevant literature. Limitations of the study are discussed as well as areas for future research. It explains findings well regarding pulmonary function. However, there are areas where further clarification of the renal findings would be helpful:

Discussion, paragraph 6: “our study is the first to assess the early changes in intrarenal haemodynamics associated with diabetes in adults with T2DM without any evidence of renal dysfunction…” You stated in the same paragraph that the GFR was higher in the diabetics. So, there is evidence of renal dysfunction? Could the increased GFR in early diabetes be a predictor of renal function change? There should be more clarification on why the RI is more predictive than GFR. Or, if it is a combination that is best, as stated in paragraph 8, that should be in the abstract conclusion.

Discussion, paragraph 11: “we had to adopt an animal model to study alveolar tissue samples.” Did you actually study an animal model? I did not see anything in the methods or results.

Reviewer #3: The authors described early changes in pulmonary function and intrarenal haemodynamics with patients with T2DM less than 12 years duration. Their findings are interesting and the study is well designed. Few things needed to be addressed:

- EDV abbreviation is not included in text of manuscript.

- PED and EDV had been used for same concept and need to be changed.

- Renal index defined as retobulbar hemodynamic which is confusing and not accurate; Also intraocular pressure measurement had been mentioned to be evaluated. This do not sound right in the context of the manuscript with no data provided to support.

-Table 1 indicate 33 healthy subjects and 37 patients in diabetic group. However, the text indicate 96 patients enrolled in the study. Authors should address the discrepancy and repeat the statistics on whole panel of patients group in table 1.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2019 Dec 18;14(12):e0224923. doi: 10.1371/journal.pone.0224923.r002

Author response to Decision Letter 0


30 Sep 2019

Reviewer 1

We spell-checked the manuscript, took out the redundancy, and also replaced few terminologies per Review #1’s comments. By doing so, we invited our colleague Ms. JJ JIAJIA Yu a more experienced in English language to help us with the correction.

Reviewer 2

Reviewer 2’s comments were taken seriously and we will try to put through a thorough revision. Meanwhile, we’d like to clarify Reviewer 2’s comments as following.

1. Grammar

① Author’s page: “Corresponding autuo” should read Corresponding author

②Discussion, 4th paragraph: “that idea” should read the idea

③Discussion, 4th paragraph: “Study noted weak associations…” should read One study

④Discussion, 8th paragraph: “sufficient statistical power, we able…” should read we were able

2. Introduction

① During the early period, the renal function is normal, the GFR had increaded relative to healthy people, but the GFR is in the normal range.

3. Methods

① We had researched the retrobulbar haemodynamics 2 years, so we make a mistake.

4. Results

① The renal function parameters are positively correlated with HbA1c and diabetes duration. the renal function will get worse and worse as the time (diabetes duration) went on, The worse renal function is accompanied by increased renal function parameters. The renal function is different from renal function parameters, two different concepts.

② Pulmonary functional parameters are different from Pulmonary function, the worse Pulmonary function is accompanied by depressed pulmonary functional parameters. So the pulmonary function parameters and renal function parameters are negatively correlated rather than the pulmonary function and renal function are negatively correlated.

5. Discussion

① Our study recruited the T2DM patients with normal renal function, so we choosed the T2DM patients during the early period, because during the early period, very few patients would appeared the abnormal renal function, although, the renal function parameters were increased.

② During the early period, the renal function parameters was higher than healthy people, but the renal function was normal. GFR as a important renal function parameters will be increased, so we can choose it as an predictor of renal function change. But we can not state the value of combination of GFR and RI, because in our study we do not research the combination, they will be studied in future.

③ Our group found the value of RI, and choosed the patients to study, discover the phenomenon and study the mechanism in animals and cells, we have build the rat model to study, in dddition, more and more studies had found the lung will get abnormal as following.

Heyuan Wang, Wei Wu, Guixia Wang, et al. Protective effect of ginsenoside Rg3 on lung injury in diabetic rats. J Cell Biochem. 2018;1-8. DOI: 10.1002/jcb.27601

Fang Zhang1, Fei Yang, Hongmei Zhao, et al. Curcumin alleviates lung injury in diabetic rats by inhibiting NF-κB pathway. doi: 10.1111/1440-1681.12438

Reviewer 3

Reviewer 3’s comments were taken seriously and we will try to put through a thorough revision. Meanwhile, we’d like to clarify Reviewer 3’s comments as following.

① We have corrected the PED, we mistaked the EDV.

② Renal index included renal function parameters and intrarenal RI

③ We had researched the retrobulbar haemodynamics 2 years, so we make a mistake.

④ We have corrected the table1, 96 patients.

Decision Letter 1

Alon Harris

25 Oct 2019

Early Changes in Pulmonary Function and Intrarenal Haemodynamics and the Correlation between These Sets of Parameters in Patients with T2DM

PONE-D-19-16612R1

Dear Dr. jia,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

With kind regards,

Alon Harris

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Alon Harris

4 Dec 2019

PONE-D-19-16612R1

Early Changes in Pulmonary Function and Intrarenal Haemodynamics and the Correlation between These Sets of Parameters in Patients with T2DM

Dear Dr. Jia:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Alon Harris

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 File. All data underlying the findings are described in this file.

    (XLS)

    Data Availability Statement

    All relevant data are within the Supporting Information files.


    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES