Article

Association between Monocyte Count and Risk ofIncident CKD and Progression to ESRD

Benjamin Bowe,* Yan Xie,* Hong Xian,*† Tingting Li,*‡ and Ziyad Al-Aly*‡§|

AbstractBackground and objectives Experimental evidence suggests a role for monocytes in the biology of kidney diseaseprogression; however, whether monocyte count is associated with risk of incident CKD, CKD progression, andESRD has not been examined in large epidemiologic studies.

Design, settings, participants, & measurementsWe built a longitudinal observational cohort of 1,594,700 UnitedStates veteranswith at least one eGFRduringfiscal year 2004 (date of last eGFRduring this perioddesignated timezero) and no prior history of ESRD, dialysis, or kidney transplant. Cohort participants were followed untilSeptember 30, 2013 or death.Monocyte count closest to and before time zerowas categorized in quartiles: quartile1,.0.00 to#0.40 thousand cells per cubicmillimeter (k/cmm); quartile 2,.0.40 to#0.55 k/cmm;quartile 3,.0.55to #0.70 k/cmm; and quartile 4, .0.70 k/cmm. Survival models were built to examine the association betweenmonocyte count and risk of incident eGFR,60 ml/min per 1.73 m2, risk of incident CKD, and risk of CKDprogression defined as doubling of serum creatinine, eGFR decline $30%, or the composite outcome of ESRD,dialysis, or renal transplantation.

Results Over a median follow-up of 9.2 years (interquartile range, 8.3–9.4); in adjusted survival models, therewas agradedassociationbetweenmonocyte counts and riskof renal outcomes.Comparedwithquartile 1, quartile4 was associated with higher risk of incident eGFR,60 ml/min per 1.73 m2 (hazard ratio, 1.13; 95% confidenceinterval, 1.12 to 1.14) and risk of incident CKD (hazard ratio, 1.15; 95% confidence interval, 1.13 to 1.16). Quartile4 was associated with higher risk of doubling of serum creatinine (hazard ratio, 1.22; 95% confidence interval,1.20 to 1.24),$30%eGFRdecline (hazard ratio, 1.18; 95%confidence interval, 1.17 to 1.19), and the composite renalend point (hazard ratio, 1.19; 95% confidence interval, 1.16 to 1.22). Cubic spline analyses of the relationshipbetween monocyte count levels and renal outcomes showed a linear relationship, in which risk was higher withhigher monocyte count. Results were robust to changes in sensitivity analyses.

ConclusionsOur results show a significant association between highermonocyte count and risks of incident CKDand CKD progression to ESRD.

Clin J Am Soc Nephrol 12: 603–613, 2017. doi: https://doi.org/10.2215/CJN.09710916

IntroductionEmerging evidence suggests that monocyte count maybe an important predictor of atherosclerotic vasculardisease (1,2), in which it is thought that increasednumber of circulating monocytes—in the presence of arepertoire of cues—may increase the probability oftheir differentiation into lipid-laden macrophages,thus contributing to progression of atheroscleroticlesions (3,4). Monocytes were the only white blood celltype to associate with peripheral artery disease andsmall cerebral vessel disease (5,6).

The observations establishing an association be-tween monocyte count and vascular disease led tofurther research. In a cross-sectional analysis of 4581cohort participants free of cardiovascular disease atbaseline, Ganda et al. (7) reported that, compared withquintile 1 of renal function, in which average eGFRwas 80.54 ml/min per 1.73 m2, quintile 5, in whichaverage eGFR was 68.84 ml/min per 1.73 m2, had

significantly increased odds of having higher mono-cyte count, therefore establishing—for the first time—arelationship between number of monocytes and ameasure of renal function. The investigators concludedthat mild decrease in renal function was associatedwith higher monocyte counts. Others have reportedsimilar associations between measures of renal func-tion and monocyte counts (8). The epidemiologicobservations are complemented by experimentalevidence suggesting a significant role of monocyte-derived macrophages, chemokines, and chemokinereceptors that entrain monocytes in renal injury andrepair (9–12). Studies from nonrenal literature, forexample, suggest that circulating monocytes areelevated in patients with chronic liver disease andalso suggest their functional contribution to theperpetuation of intrahepatic inflammation and pro-fibrogenic hepatic stellate cells in activation in livercirrhosis (13,14).

*ClinicalEpidemiology Center,Research andEducation Service and§Division ofNephrology,Department ofMedicine, USDepartment ofVeterans Affairs St.Louis Health CareSystem, St. Louis,Missouri; †Departmentof Biostatistics,College for PublicHealth and SocialJustice, St. LouisUniversity, St. Louis,Missouri; and‡Department ofMedicine and|Institute for PublicHealth, WashingtonUniversity School ofMedicine, St. Louis,Missouri

Correspondence: Dr.Ziyad Al-Aly, ClinicalEpidemiology Center,US Department ofVeterans Affairs St.Louis Health CareSystem, 915 NorthGrand Boulevard,151-JC, St. Louis, MO63106. Email: zalaly@gmail.com

www.cjasn.org Vol 12 April, 2017 Copyright © 2017 by the American Society of Nephrology 603

However, whether higher monocyte count is associatedwith risk of development of CKD and progression to ESRDis not known. An enhanced understanding of the relation-ship of monocyte count and renal outcomes may illuminatethe clinical relevance of experimental and epidemiologicfindings and further inform prediction models of CKDprogression. We hypothesized that higher monocyte countsare associated with higher risk of developing incident CKD,CKD progression, and ESRD. We, therefore, built a cohort of1,594,700 United States veterans to examine the association ofmonocyte countwith risk of incident CKD, CKD progression,and ESRD.

Materials and MethodsCohort ParticipantsUsing administrative data from the US Department of

Veterans Affairs (VA), we identified users of the VA Health-care System who had at least one eGFR value betweenOctober 1, 2003 and September 30, 2004, in which the date oflast eGFR during this period was designated as time zero(T0), with no prior history of ESRD, dialysis, or kidneytransplant (n=2,751,717). Additionally, cohort participantswere selected on having at least one monocyte count valuebetween October 1, 1999 and T0 (n=1,706,589) and at least oneeGFR subsequent to T0 (n=1,594,700). Serum creatinine (andeGFR), monocyte levels, and other laboratory parameterswere acquired during routine outpatient care. A flowchartand timeline for cohort selection are presented in Figure 1.The studywas approved by the Institutional Review Board ofthe VA St. Louis Health Care System.

Data SourcesVA datasets were used to obtain patient’s demographics,

inpatient and outpatient data, laboratory information

(including serum creatinine), vital signs, and medications.Data from the US Renal Data System were used to supple-ment ESRD status information (15). Details on data sourcesare provided in Supplemental Material.

Primary Predictor VariableThe primary predictor variable for analyses was mono-

cyte count. Monocyte count (1000 cells per cubic millimeter)closest to and before T0 was categorized into quartiles asquartile 1, from.0.00 to#0.40 (n=415,862 [26.1%]); quartile2, from .0.40 to #0.55 (n=382,263 [24.0%]), quartile 3, from.0.55 to #0.70 (n=498,843 [31.3%]); and quartile 4, .0.70(297,732 [18.7%]).

OutcomesWe evaluated the risk of incident eGFR,60 ml/min per

1.73 m2 in those with no prior history of eGFR,60 ml/minper 1.73 m2 at the time of cohort entry and additionally,risk of CKD among those with at least two eGFR values no,90 days apart. CKD was defined as two eGFR values,60 ml/min per 1.73 m2 at least 90 days apart (16,17). Weadditionally evaluated time until doubling of serum cre-atinine, time until $30% decline in eGFR, and time untilESRD, dialysis, or kidney transplant from creatinine at T0

(18,19). eGFR values were censored after onset of ESRD orat first record of dialysis or kidney transplant. All cohortparticipants were followed until September 30, 2013.

CovariatesBaseline covariates were ascertained from October 1,

1999 until cohort entry (T0). Covariates included age, race,sex, T0 eGFR, diabetes mellitus, hypertension, cardiovasculardisease, chronic lung disease, peripheral artery disease,cerebrovascular accident, hepatitis C, HIV, dementia,

Figure 1. | Cohort assembly. (A) Diagram of participant flow. (B) Timeline for cohort selection. T0, time zero.

604 Clinical Journal of the American Society of Nephrology

hyperlipidemia, cancer, white blood cell count, microalbumin-to-creatinine ratio, angiotensin-converting enzyme inhibitors /angiotensin receptor blockers use, proton pump inhibitor use,and nonsteroidal anti-inflammatory drug use (17,20,21).eGFR was calculated using the abbreviated Chronic

Kidney Disease Epidemiology Collaboration equation (22).Covariate definitions are provided in Supplemental Material.

Statistical AnalysesKaplan–Meier curves were generated to show the sur-

vival of each outcome by monocyte count quartile. In-cidence rates were calculated as number of events per100,000 person-years, and 95% confidence intervals (95%CIs) were built on the basis of the normal distribution.Because of the censoring of eGFR values by occurrence ofESRD, dialysis, transplant, and death, competing risk Coxproportional hazard regression models were used in theassessment of survival outcomes. Specifically, ESRD, di-alysis, transplant, and death were treated as competingrisks in doubling of serum creatinine, .30% decline,incident eGFR,60 ml/min per 1.73 m2, and incidentCKD models, whereas death was treated as a competingrisk in the ESRD, dialysis, or transplant model. Suchcensoring was considered noninformative (23,24). Multiplemodels were built to assess the relation between monocytecount and outcomes, while sequentially controlling fordemographics, comorbidities, and eGFR at T0. The pro-portional hazard assumption was assessed through use oflog-negative log plots and deemed to have been met in allmodels. P values for trends were obtained by addingquartiles as a continuous variable to models. We repeatedall analyses in a subcohort of participants with white bloodcell counts between 4 and 10 thousand cells per cubicmillimeter (counts considered in the normal range). Anal-yses were repeated with monocyte deciles, where decile 2was the referent category. Cubic spline analyses—thatallows for assessment of nonlinear relationships of contin-uous monocyte count with outcomes—of the associationbetween monocytes and renal outcomes were performed(23). Details of the spline analyses may be found inSupplemental Material. Attributable fraction (AF) andpopulation attributable fraction (PAF) were calculatedusing piecewise constant hazard models for disease in-cidence (25). Details of AF and PAF analyses are includedin Supplemental Material.In survival analyses, a 95% CI of a hazard ratio (HR) that

does not include unity was considered statistically sig-nificant. In all analyses, a P value of#0.05 was consideredstatistically significant. Missing data were not imputed.All analyses were performed and graphs were madeusing SAS Enterprise Guide, version 7.1 and SAS 9.4 (SASInstitute, Cary, NC).

Sensitivity AnalysesWe evaluated the consistency and robustness of study

findings by performing a number of sensitivity analyses asdescribed in Supplemental Material.

ResultsThe demographic and health characteristics of the overall

cohort and according to monocyte count quartile are

presented in Table 1. Cohort participants in the highestmonocyte quartile were more likely to be of white race andmen; they also had a higher burden of comorbid illnesses,including diabetes mellitus, hypertension, cardiovasculardisease, chronic lung disease, peripheral vascular disease,and lower eGFR (Table 1). Cohort participants werefollowed for a median of 9.2 years (interquartile range,8.3–9.4).

Monocyte Count and Risk of Incident eGFR<60 ml/min per1.73 m2 and Incident CKDWe evaluated the risk of incident eGFR,60 ml/min per

1.73 m2 among those who had no history of eGFR,60 ml/minper 1.73 m2 before the time of cohort entry (n=1,074,166).Among those, 366,191 (34.1%) experienced eGFR,60 ml/minper 1.73 m2 during the time in the cohort, and 95,830 (32.5%),88,643 (34.0%), 114,906 (35.0%), and 66,812 (35.2%) experiencedeGFR,60 ml/min per 1.73 m2 in monocyte quartiles 1–4,respectively (Figure 2A, Table 2). In adjusted survival modelsfor demographics, comorbid conditions, and eGFR, there was agraded and significant association between quartiles of mono-cyte count and risk of incident eGFR,60 ml/min per 1.73 m2;compared with participants with a monocyte count in thelowest quartile (quartile 1), those with a monocyte count inquartiles 2–4 had HRs and 95% CIs of HR, 1.02 and 95% CI,1.01 to 1.03; HR, 1.04 and 95%CI, 1.04 to 1.05; andHR, 1.13 and95% CI, 1.12 to 1.14, respectively (Table 2). Cubic splineanalyses of the relationship between monocyte count and theoutcome of incident eGFR,60 ml/min per 1.73 m2

suggested a near-linear relationship, in which riskwas higheramong patients with higher monocyte count (Figure 3A).We evaluated the risk of incident CKD (defined as two

eGFR values ,60 ml/min per 1.73 m2 at least 90 daysapart) in a subcohort of people with at least two eGFRmeasurements separated by at least 90 days who had nohistory of eGFR,60 ml/min per 1.73 m2 (n=1,024,422)before the time of cohort entry. Among those, 218,839(21.4%) developed incident CKD, and 56,419 (20.1%),53,370 (21.4%), 69,306 (22.1%), and 39,744 (22.1%) devel-oped incident CKD in monocyte quartiles 1–4, respectively(Figure 2B, Table 2). Compared with participants with amonocyte count in the lowest quartile (quartile 1), thosewith a monocyte count in quartiles 2–4 had higher risk ofCKD, with HR, 1.03 and 95% CI, 1.02 to 1.05; HR, 1.06 and95% CI, 1.05 to 1.07; and HR, 1.15 and 95% CI, 1.13 to 1.16,respectively (Table 2). Cubic spline analyses suggested alinear relationship between monocyte count and the out-come of incident CKD (Figure 3B).

Monocyte Count and Risk of CKD Progression to ESRDIn the overall cohort of 1,594,700 participants, 124,212

(7.8%) experienced a doubling of serum creatinine, and30,463 (7.3%), 28,415 (7.4%), 38,885 (7.8%), and 26,449(8.9%) experienced a doubling of serum creatinine inmonocyte quartiles 1–4, respectively (Figure 2C, Table 2).There were 500,402 (31.4%) who experienced$30% declinein eGFR in the overall cohort; 123,897 (29.8%), 116,637(30.5%), 157,895 (31.7%), and 101,973 (34.3%) experienced$30% decline in eGFR in monocyte quartiles 1–4, respec-tively (Figure 2D, Table 2). In the overall cohort, 61,019(3.8%) developed ESRD, required dialysis, or requiredkidney transplant; 14,875 (3.6%), 13,576 (3.6%), 19,141 (3.8%),

Clin J Am Soc Nephrol 12: 603–613, April, 2017 Monocytes and CKD Progression, Bowe et al. 605

Tab

le1.

Dem

ograp

hic

andclinical

charac

teristicsofove

rallstudyco

hort

andac

cordingto

quartilesofmonocyte

count

Cha

racteristic

Ove

rallCoh

ort

Mon

ocyteQua

rtile

1.0.00

to#0.40

k/cm

mMon

ocyteQua

rtile

2.0.40

to#0.55

k/cm

mMon

ocyteQua

rtile

3.0.55

to#0.70

k/cm

mMon

ocyteQua

rtile

4.0.70

k/cm

m

No.

(%)

1,59

4,70

041

5,86

2(26.1)

382,26

3(24.0)

498,84

3(31.3)

297,73

2(18.7)

Med

ianmon

ocytecoun

t(IQR),

k/cm

m0.55

(0.40–

0.70

)0.40

(0.30–

0.40

)0.50

(0.50–

0.50

)0.60

(0.60–

0.70

)0.90

(0.80–

1.00

)

Med

iantimefrom

mon

ocyte

count

toT0(IQR),yr

2.1(0.6–3.6)

2.1(0.6–3.6)

2.0(0.6–3.6)

2.2(0.7–3.7)

2.1(0.6–3.7)

Race(%

)W

hite

1,30

8,28

9(82.0)

312,04

5(75.0)

313,50

7(82.0)

425,01

0(85.2)

257,72

7(86.6)

Black

245,59

9(15.4)

90,462

(21.8)

58,770

(15.4)

62,491

(12.5)

33,876

(11.4)

Other

40,812

(2.6)

13,355

(3.2)

9986

(2.6)

11,342

(2.3)

6129

(2.1)

Men

(%)

1,51

2,68

0(94.9)

380,75

9(91.6)

361,81

8(94.7)

479,95

4(96.2)

290,14

9(97.5)

Med

ianag

e(IQR),yr

62.0

(54.6–

71.8)

60.5

(53.2–

70.9)

62.1

(54.7–

71.8)

63.0

(55.2–

72.2)

62.6

(55.1–

72.1)

Diabe

tesmellitus(%

)45

6,59

1(28.6)

114,61

3(27.6)

108,23

7(28.3)

145,25

2(29.1)

88,489

(29.7)

Hyp

ertens

ion(%

)1,08

7,78

8(68.2)

265,73

9(63.9)

257,15

5(67.3)

349,49

7(70.1)

215,39

7(72.4)

Cardiova

scular

disease

(%)

502,25

0(31.5)

109,05

1(26.2)

115,02

6(30.1)

167,03

2(33.5)

111,14

1(37.3)

Chron

iclung

disease

(%)

336,52

0(21.1)

70,301

(16.9)

72,146

(18.9)

110,46

6(22.1)

83,607

(28.1)

Periphe

rala

rterydisease

(%)

48,455

(3.0)

9483

(2.3)

10,350

(2.7)

16,225

(3.3)

12,397

(4.2)

Dem

entia(%

)51

,000

(3.2)

13,141

(3.2)

11,869

(3.1)

15,756

(3.2)

10,234

(3.4)

HIV

(%)

109,41

7(6.9)

28,482

(6.9)

24,534

(6.4)

33,164

(6.7)

23,237

(7.8)

Hep

atitisC(%

)78

,339

(4.9)

20,929

(5.0)

17,156

(4.5)

22,899

(4.6)

17,355

(5.8)

Cereb

rova

scular

acciden

t(%)

8169

(0.5)

1620

(0.4)

1773

(0.5)

2784

(0.6)

1992

(0.7)

Hyp

erlip

idem

ia(%

)94

6,65

7(59.4)

233,22

1(56.1)

228,45

5(59.8)

306,46

1(61.4)

178,52

0(60.0)

Can

cer(%

)20

2,95

7(12.7)

53,424

(12.9)

47,192

(12.4)

62,623

(12.6)

39,718

(13.3)

Ave

rage

eGFR

atT0(SD),

ml/min

per1.73

m2

76.39(18.7)

77.68(18.4)

76.46(18.5)

75.59(18.7)

75.87(19.5)

Med

iannu

mbe

rof

eGFR

measu

resafterT0(IQR)

12(7–20

)12

(7–19

)12

(7–19

)12

(7–20

)13

(7–20

)

Microalbumin-to-crea

tinine

ratio(%

),amg/g

0–,30

88,187

(77.6)

23,276

(79.3)

20,513

(78.2)

28,546

(77.4)

15,852

(75.0)

30–,30

021

,792

(19.2)

5297

(18.0)

4899

(18.7)

7087

(19.2)

4509

(21.3)

$30

036

17(3.2)

785(2.7)

819(3.1)

1229

(3.3)

784(3.7)

Med

ianfollo

w-uptim

e(IQR),yr

9.2(8.3–9.4)

9.2(9.0–9.4)

9.2(9.0–9.4)

9.2(8.0–9.4)

9.1(6.5–9.4)

Death

duringfollo

w-up(%

)43

2,55

8(27.1)

94,039

(22.6)

93,775

(24.5)

140,67

6(28.2)

104,06

8(35.0)

k/cm

m,1

000cells

percu

bicmillim

eter;IQR,interqu

artile

rang

e;T0,timezero.

a Num

bers

areforasu

bset

ofthecoho

rtforwhich

thecorrespo

ndingdatawereav

ailable(n=11

3,59

6).

606 Clinical Journal of the American Society of Nephrology

and 13,427 (4.5%) developedESRD, requireddialysis, or requiredkidney transplant in monocyte quartiles 1–4, respectively(Figure 2E, Table 2).In models adjusted for demographic variables, comorbid

conditions, and baseline eGFR (eGFR at the time of cohortentry), there was a graded and significant association betweenmonocyte count and risk of doubling of serum creatinine, riskof eGFR decline $30%, and risk of the composite outcome ofESRD, dialysis, or kidney transplant (Table 2). Cubic spline

analyses of the relationship between monocyte count andthe outcomes of doubling of serum creatinine, $30% declinein eGFR, and the composite outcome of ESRD, dialysis, andtransplantation showed a linear relationship (Figure 3, C–E).

Monocyte Count and Risk of Chronic Renal Outcomes inParticipants with Normal White Blood Cell CountWe repeated all analyses in participants with normal

white blood cell counts, and results remained consistent

Figure 2. | Kaplan–Meier curves representing the survival probability of renal outcomes by monocyte quartiles. (A) eGFR,60 ml/min per1.73 m2. (B) Chronic Kidney Disease. (C) Doubling of serum creatinine. (D) .530% decline in eGFR. (E) ESRD, dialysis, or transplant. Insetrepresents the same Kaplan-Meier curves on a narrower y-axis scale.

Clin J Am Soc Nephrol 12: 603–613, April, 2017 Monocytes and CKD Progression, Bowe et al. 607

Tab

le2.

Riskofinciden

teG

FR<6

0ml/min

per

1.73m

2,inciden

tCKD,doublingofserum

crea

tinine,

‡30%

dec

linein

eGFR

,an

dES

RD,dialysis,ortran

splantationbymonocy

teco

untquartile

Outcomean

dMeasu

reMon

ocyteQuartile

1.0.00

to#0.40

k/cm

mMon

ocyteQuartile

2.0.40

to#0.55

k/cm

mMon

ocyteQuartile

3.0.55

to#0.70

k/cm

mMon

ocyteQuartile

4.0.70

k/cm

m

eGFR

<60ml/min

per

1.73

m2a

No.

ofev

ents

(%)

95,830

(32.5)

88,643

(34.0)

114,90

6(35.0)

66,812

(35.2)

Inciden

cerate

per10

0,00

0pe

rson

-yr(95%

CI)

4560

.4(453

1.5to

4589

.2)

4854

.1(482

2.1to

4886

.0)

5105

.7(507

6.2to

5135

.3)

5327

.8(528

7.4to

5368

.2)

HR(95%

CI)

1.00

1.02

(1.01to

1.03

)1.04

(1.04to

1.05

)1.13

b(1.12to

1.14

)Inciden

tCKD

c

No.

ofev

ents

(%)

56,419

(20.1)

53,370

(21.4)

69,306

(22.1)

39,744

(22.1)

Inciden

cerate

per10

0,00

0pe

rson

-yr(95%

CI)

2522

.3(250

1.5to

2543

.1)

2728

.7(270

5.5to

2751

.8)

2865

.6(284

4.3to

5887

.0)

2949

.2(292

0.2to

2978

.2)

HR(95%

CI)

1.00

1.03

(1.02to

1.05

)1.06

(1.05to

1.07

)1.15

b(1.13to

1.16

)Dou

blingof

seru

mcrea

tinine

No.

ofev

ents

(%)

30,463

(7.3)

28,415

(7.4)

38,885

(7.8)

26,449

(8.9)

Inciden

cerate

per10

0,00

0pe

rson

-yr(95%

CI)

900.4(890

.2to

910.5)

922.1(911

.4to

932.8)

988.2(978

.4to

998.0)

1184

.1(116

9.9to

1198

.4)

HR(95%

CI)

1.00

1.02

(1.00to

1.04

)1.07

(1.05to

1.08

)1.22

b(1.20to

1.24

)‡3

0%Declinein

eGFR

No.

ofev

ents

(%)

123,89

7(29.8)

116,63

7(30.5)

157,89

5(31.7)

101,97

3(34.3)

Inciden

cerate

per10

0,00

0pe

rson

-yr(95%

CI)

4170

.7(414

7.5to

4193

.9)

4325

.7(430

0.9to

4350

.5)

4614

.5(459

1.8to

4637

.3)

5324

.1(529

1.4to

5356

.7)

HR(95%

CI)

1.00

1.02

(1.01to

1.03

)1.06

(1.05to

1.07

)1.18

b(1.17to

1.19

)ESRD,d

ialysis,or

tran

splant

No.

ofev

ents

(%)

14,875

(3.6)

13,576

(3.6)

19,141

(3.8)

13,427

(4.5)

Inciden

cerate

per10

0,00

0pe

rson

-yr(95%

CI)

430.2(423

.3to

437.1)

430.7(423

.4to

437.9)

475.1(468

.3to

481.8)

584.7(574

.8to

594.6)

HR(95%

CI)

1.00

0.98

(0.96to

1.00

)1.04

(1.02to

1.06

)1.19

b(1.16to

1.22

)

Mod

elsweread

justed

forag

e,race,sex,cardiova

scular

disease,cereb

rova

scular

acciden

t,ch

roniclung

disease,d

emen

tia,

diabe

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#60

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timeof

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bPva

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tCKDwas

evalua

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per1

.73m

2at

thetimeof

coho

rten

try

(n=1,02

4,42

2).

608 Clinical Journal of the American Society of Nephrology

(Supplemental Table 1). There was a graded associationbetween monocyte count and risk of chronic renal outcomes.

AF and PAFAFs for incident eGFR,60 ml/min per 1.73 m2 and

incident CKD were 2.45% (95% CI, 1.95 to 2.94) and 3.63%(95% CI, 2.91 to 4.34), respectively (Table 3). AFs fordoubling of serum creatinine, eGFR decline $30%, andESRD, dialysis, or kidney transplant were 5.4% (95% CI,

4.2 to 6.6), 3.6 (95% CI, 3.2 to 4.1), and 2.2 (95% CI, 0.5 to3.8), respectively (Table 3).PAFs for incident eGFR,60 ml/min per 1.73 m2 and

incident CKD were 1.8% (95% CI, 1.4 to 2.2) and 2.7% (95%CI, 2.2 to 3.2), respectively (Table 3). PAFs for doubling ofserum creatinine, eGFR decline $30%, and ESRD, dialysis,or kidney transplant were 4.1% (95% CI, 3.2 to 4.5), 2.7 (95%CI, 2.4 to 3.1), and 1.7 (95% CI, 0.4 to 2.9), respectively(Table 3).

Figure 3. | Cubic spline analyses of risk of renal outcomes by monocyte count (median monocyte count as reference) in red, with monocyte countprobabilitydistribution ingray;blue lines represent95%confidence intervalsof thespline. (A)RiskofeGFR,60ml/minper1.73m2. (B)RiskofChronicKidney Disease. (C) Risk of doubling of serum creatinine. (D) Risk of$30% decline in eGFR. (E) Risk of ESRD, dialysis, or transplant.

Clin J Am Soc Nephrol 12: 603–613, April, 2017 Monocytes and CKD Progression, Bowe et al. 609

Sensitivity AnalysesWe evaluated the robustness and consistency of study

findings in a number of sensitivity analyses. High mono-cyte count was associated with higher risk of the alternativeoutcomes of severe CKD progression defined as eGFRloss .25 ml/min per 1.73 m2 per year (HR, 1.32; 95% CI,1.30 to 1.65) and ESRD, kidney transplant, or $50% declinein eGFR (HR, 1.23; 95% CI, 1.21 to 1.24) (SupplementalTables 2 and 3) (15,17,21,26–29). When average monocytecount during the period at or before T0 was used as theprimary predictor variable, the results were consistent withthose in the primary analyses (Supplemental Table 4). Thepotential effect of censoring at ESRD, dialysis, or kidneytransplant—in models in which it was not the outcome ofinterest—was found at both extremes of informative cen-soring to have results consistent with the primary analyses(Supplemental Table 5) (17,21). In bias analyses thatassessed potential changes in associations using MonteCarlo sensitivity analysis to simulate accounting for themicroalbumin-to-creatinine ratio as a potential confounder,results were consistent with those shown in primary analyses(Supplemental Table 6) (17). The results were consistentwhere monocyte count was categorized into deciles (Sup-plemental Table 7) and where monocyte count was groupedinto 0.1 (1000 cells per cubic millimeter) increasing ordinalcategories (Supplemental Table 8). After additionally con-trolling for angiotensin-converting enzyme inhibitor / angio-tensin receptor blocker, proton pump inhibitor, andnonsteroidal anti-inflammatory drug use, results were foundto be congruent with those in the primary analysis (Supple-mental Table 9).

DiscussionIn a large observational cohort study of 1,594,700 United

States veterans followed for a median of 9.16 years, weshow a graded association between monocyte count andrisk of development of CKD (incident eGFR,60 ml/minper 1.73 m2 and incident CKD), risk of CKD progression(doubling of serum creatinine and.30% reduction in eGFR),and risk of ESRD. The results were consistent in analysesconsidering only participants with normal white blood cellcount and robust to challenges in multiple sensitivityanalyses. Spline analyses showed a linear relationship be-tween monocyte count and risk of adverse renal outcomes.This work sought to specifically examine the relationship

between monocyte count and risk of incident CKD and itsprogression. However, elevated monocyte count may alsobe present in the context of elevated overall white blood cellcount. Prior evidence suggested that total white blood cellcount predicts mortality in patients with kidney disease(30,31). Higher total white blood cell count is generallypresent in the context of infection or inflammation andassociated with higher risk of hospitalization, cardiovas-cular events, and a host of untoward outcomes (31). Thereare no data, however, specifically linking elevated totalwhite blood cell count with risk of development of kidneydisease and its progression. Our finding that, in partici-pants with normal white blood cell count, there was asignificant association between monocyte count and riskof chronic renal outcomes suggests that, in the absence ofleukocytosis, monocyte count remains a significant pre-dictor of kidney disease outcomes.

Tab

le3.

Attributable

frac

tionan

dpopulationattributable

frac

tion

Measu

reeG

FR,60

ml/min

per1.73

m2a

Inciden

tCKD

bDou

blingof

Serum

Creatinine

$30

%Declin

ein

eGFR

ESR

D,D

ialysis,

orTrans

plan

t

Attribu

tablefraction

(95%

CI),%

2.45

(1.95to

2.94

)3.63

(2.91to

4.34

)5.41

(4.24to

6.57

)3.64

(3.16to

4.14

)2.19

(0.53to

3.82

)Po

pulationattributab

lefraction

(95%

CI),%

1.80

(1.43to

2.17

)2.69

(2.15to

3.22

)4.08

(3.18to

4.50

)2.74

(2.37to

3.11

)1.65

(0.39to

2.90

)

Mod

elsweread

justed

forag

e,race,sex,cereb

rova

scular

acciden

t,ch

roniclung

disease,d

iabe

tes,dem

entia,

hepatitisC,H

IV,h

ypertension,

timezero

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,cardiova

scular

disease,h

yper-

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eral

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l.95

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withno

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#60

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per1.73

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thetimeof

coho

rten

try(n=1,07

4,16

6).

bInciden

tCKDwas

evalua

tedin

asu

bcoh

orto

fpeo

plewithat

leasttwoeG

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ratedby

atleast9

0day

swho

hadno

priorh

istory

ofeG

FR#60

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per1

.73m

2at

thetimeof

coho

rten

try

(n=1,02

4,42

2).

610 Clinical Journal of the American Society of Nephrology

The mechanism underlying the association of monocytesand kidney outcomes is not clear. One simple explanationof the observed associations is that monocyte count maybe a mere surrogate marker—a clinical predictor—of in-flammation, poorer overall health, and thus, higher risk ofadverse long-term renal outcomes. Epidemiologic findingssuggest that higher monocyte count is associated withatherosclerotic vascular disease, small vessel disease, andcross-sectional measures of renal function; a plausibleworking hypothesis is that the renal manifestations asso-ciated with higher monocyte counts are likely related toprogression of vascular disease and subsequently, reducedkidney function (1,3–6). Monocytes, chemokines, andchemokine receptors have also been implicated in thebiology of renal disease progression, where it is plausiblethat higher monocyte counts may facilitate progression ofrenal injury (11,12,32,33).Lee et al. (34) reported that, as CKD advances, the

proportion of proinflammatory CD14+CD16+ monocytesexpands, and notably, the expansion of CD14+CD16+

subtypes correlated with measures of impaired vascularhealth, including brachial-ankle pulse wave velocity. It isunclear whether the expansion of proinflammatory sub-types is the result of impaired kidney function or alterna-tively, in the pathway leading to deterioration in kidneyfunction (34). In our studies, we noted an associationbetween baseline monocyte counts and risk of incidentCKD and progression to ESRD, and although we did nothave data on the subtypes of monocytes, the epidemiologicfindings that higher monocyte count predicts future risk ofdevelopment of CKD and its progression lend furtherplausibility to the hypothesis that higher monocyte countmay be a marker that precedes or is in the pathwaymediating the development of CKD and its progression.Further studies are needed to determine which monocytesubtype exhibits the strongest association with or bestpredicts renal outcomes.Experimental evidence suggests that inflammatory cell

infiltrates play a role in the development and progressionof kidney disease (11,12). Blockade of chemokine receptor1 (CCR1)—which plays an important role in monocyte/macrophage adhesion to activated vascular endothelium,transendothelial migration, and activation—can effectivelyprevent recruitment of monocytes into the renal interstitialcompartment. CCR1 blockade abrogates the developmentof kidney disease in various types of experimental kidneydisease, including unilateral ureteral obstruction, lupus-like GN, adriamycin-induced nephrotic syndrome, Alportsyndrome, diabetic renal disease, and kidney allograftmurine models (11,33,35–38). In experimental models,CCR1 blockade also seems to be effective, even whentreatment is initiated after the disease process is estab-lished (39). The biology of monocytes, chemokines, andchemokine receptor in renal disease is highly complex,because these moieties are highly promiscuous in that theydrive both injury and repair processes, which makesidentifying translational therapeutic opportunities chal-lenging (12). Further studies are needed to develop a morecomprehensive understanding of the role of chemokines,chemokine receptors, and their genetic variants that pro-mulgate or—conversely—abrogate chronic renal injury.Our findings add to the existing body of knowledge—

largely derived from murine experimental models—andprovide that, in a large national cohort, monocyte count—awidely available marker—is a significant predictor ofkidney disease development and progression. The epide-miologic observations establish a clinical epidemiologicrelevance of monocyte in kidney disease, further illumi-nate our understanding of this important field, and informthe discussion on filling the translational gap betweenexperimental biology and clinical epidemiology—where abidirectional flow of information from clinical epidemio-logic observations informs biologic research (17,21,40).More experimental and clinical investigation is needed tobetter understand the biology of monocyte in kidneydisease and translate the understanding into opportunitiesand therapeutic avenues to halt kidney disease progression(17,29).The study has several limitations. There were signifi-

cant baseline differences in demographic and healthcharacteristics according to monocyte quartiles, in whichthose in the highest quartile were generally less healthy.Although we included these covariates in the models, theresults seen may still represent residual confounding, inthat there may be confounders either unmeasured orunknown that may explain the higher risk of renaloutcomes seen in those with higher monocyte counts. Amore cautious interpretation of the study results is thatmonocyte count may be a heavily confounded measurethat undermines the validity of making causal inferenceswith renal outcomes and as such, that monocyte countmay just be a—valuable clinical—predictor (or surrogatemarker) of kidney disease progression. Higher monocytecounts could be present in the context of inflammation orinfection, which may confound the described association.To minimize this possibility, we included measures re-lated to burden of illness and cancer as covariates in themodels. We used a single value of monocyte as a predictorin the primary analyses, and to account to intraindividualvariation, we conducted sensitivity analyses using aver-age monocyte count in participants with more than onemonocyte count before cohort entry; these sensitivityanalyses are necessarily limited by the selection bias ofrequiring more than one value. Monocytes are not ahomogenous group of cells, because there are functionallyand phenotypically distinct subtypes on the basis of CD14and CD16 positivity; our datasets did not include in-formation on these subtypes of monocytes. In this obser-vational study, cohort participants were mostly olderwhite men; additionally, potential participants had tomeet criteria for cohort inclusion, and as such, the resultsmay not be generalizable to a less defined population. Theimperfect nature of administrative data and the retro-spective design of the study may also lead to samplingbias and inaccurate measurements of the predictor var-iables. To minimize such measurement bias, we useddefinitions of comorbid illnesses that are validated for usein the VA administrative data (16,17,41,42). Although AFand PAF are statistically significant, these estimates aresmall and must be interpreted with caution. Strengths ofthe described results include the fact that this is a verylarge cohort of veterans followed for nearly a decade toascertain renal outcomes, the consistency of the magni-tude and direction of the association across multiple renal

Clin J Am Soc Nephrol 12: 603–613, April, 2017 Monocytes and CKD Progression, Bowe et al. 611

outcomes tested, and the robustness of study findings tochanges in epidemiologic design and specification ofstatistical models. In sum, our results show a significantassociation between higher monocyte count and risks ofincident CKD and CKD progression to ESRD; the findingsprovide epidemiologic context to enhance our understandingof the experimental observations of a role for monocyte in thebiology of kidney disease and its progression.

AcknowledgmentsThe data reported here have been supplied by the US Renal Data

System (USRDS).This work was funded by a grant from the US Department of

Veterans Affairs (VA; to Z.A.-A.). Support for the VA/Centers forUSRDS Data is provided by VA, Veterans Health Administration,Office of Research and Development, Health Services Research andDevelopment, VA Information Resource Center Project/Data UseAgreement Al-Aly-01.

The contents do not represent the views of the VA or the USGovernment. The interpretation and reporting of these data are theresponsibility of the authors and in no way should be seen as anofficial policy or interpretation of the US Government.

DisclosuresNone.

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Received: September 12, 2016 Accepted: January 18, 2017

Published online ahead of print. Publication date available at www.cjasn.org.

This article contains supplemental material online at http://cjasn.asnjournals.org/lookup/suppl/doi:10.2215/CJN.09710916/-/DCSupplemental.

Clin J Am Soc Nephrol 12: 603–613, April, 2017 Monocytes and CKD Progression, Bowe et al. 613