ResearchArticle Metabolic Differences between Dogs of ...downloads.hindawi.com/journals/jnme/2017/4535710.pdf · N-Formylmethionine 0.89 Aminoacid 0.029 1541 176.1 Bilirubin(E,E)

Research ArticleMetabolic Differences between Dogs of Different Body Sizes

Rondo P Middleton1 Sebastien Lacroix2 Marie-Pier Scott-Boyer2

Nikola Dordevic2 AdamD Kennedy3 Amanda R Slusky4 Jerome Carayol5

Christina Petzinger-Germain1 Alison Beloshapka1 and Jim Kaput5

1Nestle Purina Research St Louis MO USA2The Microsoft Research University of Trento Centre for Computational and Systems Biology (COSBI) Rovereto Italy3Metabolon Inc Morrisville NC USA4North Carolina State University College of Veterinary Medicine Raleigh NC USA5Nestle Institute of Health Sciences Lausanne Switzerland

Correspondence should be addressed to Rondo P Middleton rondomiddletonrdnestlecom

Received 13 July 2017 Accepted 25 September 2017 Published 26 October 2017

Academic Editor Phillip B Hylemon

Copyright copy 2017 Rondo P Middleton et al This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

IntroductionThedomesticated dogCanis lupus familiaris has been selectively bred to produce extreme diversity in phenotype andgenotype Dogs have an immense diversity in weight and height Specific differences in metabolism have not been characterized insmall dogs as compared to larger dogsObjectivesThis study aims to identifymetabolic clinical andmicrobiota differences betweensmall and larger dogs Methods Gas chromatographymass spectrometry liquid chromatographytandem mass spectrometryclinical chemistry analysis dual-energy X-ray absorptiometry and 16S pyrosequencing were used to characterize blood metabolicclinical and fecal microbiome systems respectively Eighty-three canines from seven different breeds fed the same kibble diet for 5weeks were used in the study Results 449 metabolites 16 clinical parameters and 6 bacteria (at the genus level) were significantlydifferent between small and larger dogs Hierarchical clustering of themetabolites yielded 8modules associated with small dog sizeConclusion Small dogs had a lower antioxidant status and differences in circulating amino acids Some of the amino acid differencescould be attributed to differences in microflora Additionally analysis of small dog metabolites and clinical parameters reflected anetwork which strongly associates with kidney function

1 Introduction

Significant genetic and metabolic variation occurs withinthe Canis lupus species that spans from the wolf throughall domesticated canines Artificial selection for phenotypictraits generated profound genetic differences within Canislupus familiaris the domesticated dog that is widespread inall human cultures Dogs can vary in size between roughly2 and 90Kg Segmenting dogs by size reveals some inherentcharacteristics Small dogs are more likely to suffer fromintegumentary cardiovascular and dental diseases and havea higher incidence of endocrine-related deaths compared tolarger dogs [1 2] Small dogs have a lower basal metabolicrate and a higher mass-specific metabolic rate than largerdogs [3] Interestingly small dogs have a longer lifespan than

larger dogs [4] which differs from what is observed in othermammalian species

We conducted a diet- and environment-controlled studyin canines to understand metabolic clinical and microbiotadifferences between small and larger dogsMultiple differenceswere found specifically in blood concentrations of antioxi-dants and amino acids as well as in microbiota compositionTo better understand these differences we identifiedmodulesof highly cooccurring metabolites and further analyzedcorrelations between metabolic and clinical data

2 Materials and Methods

21 Cohort Study Design Eighty-three (83) canines fromseven different breeds were all fed the same dry extruded

HindawiJournal of Nutrition and MetabolismVolume 2017 Article ID 4535710 11 pageshttpsdoiorg10115520174535710

2 Journal of Nutrition and Metabolism

kibble diet for 5 weeks Small dogs (34 individuals BeagleSmall Fox Terrier and Miniature Schnauzer) had a meanweight of 93 kg (range of 61ndash156 kg) Larger dogs (49 indi-viduals Labrador Retriever English Setter Siberian Huskyand Rottweiler) had a mean weight of 315 kg (range of184ndash544 kg) Small dogs had a mean age of 68 years (rangeof 24ndash133 years) while larger dogs had a mean age of 62years (range of 22ndash98 years) All dogs except Rottweilerswere housed in the same location Samples were handled andprocessed in the same manner to avoid technical variabilityor bias Plasma-EDTA and serum samples were taken afterovernight fasting during the fifth week of feeding Fecalsamples were collected during the fifth week of feedingPlasma serum and fecal samples not immediately analyzedwere frozen at minus80∘C

22 Canine Plasma Metabolites Metabolite profiling wasperformed as described previously [5] In summary metabo-lites from each blood sample were extracted and analyzedby GCMS (Thermo Fischer DSQ mass spectrometer) andLCMS (Thermo Fischer LTQ mass spectrometers) Wecarried out chromatographic separation followed by full-scanMS to record and quantify all detectable ions in the samples[6] All metabolites with known chemical structure wereidentified by matching the ionsrsquo chromatographic retentionindex andMS fragmentation signatureswith reference libraryentries created from authentic standard metabolites [7] Thereported masses within the supplemental table represent therespective masses of the ion features utilized to identifyeach molecule These ion features could be the mass ofthe parent molecule the mass of an ion featurefragmentof the molecule or an adduct (eg sodium adduct) ofthe parental molecule or an adduct of an ion fragmentAdditional library entries were added for ions that were notcovered by the standards based on their unique ion signatures(chromatographic and mass spectral) so these ions couldthen be routinely detected and quantified For quality controland run-day performance analysis labeled internal standardswere spiked into all samples at different stages of the dataacquisition process The median relative standard deviationswere 7 and 12 for the internal standards and endogenousbiochemicals 589 detected in total respectively

We identified 589 metabolites in plasma prior to removalof some for low percentage presence across all breeds Ofthese 401 biochemicals matched a named structure in thereference library (named) The remaining 188 biochemicalsrepresented distinct chemical entities that represent a singlemolecule of discretemolecular formula and structure but thatdo not currently match a named chemical in the referencelibrary (unnamed)

23 Canine Clinical Parameters Most clinical parameterswere analyzed in all dogs Some anthropometric analysesusing dual-energy X-ray absorptiometry (DEXA) and thy-roid hormones triiodothyronine (T3) and thyroxine (T4)were evaluated only in 34 small dogs and 35 larger dogs (notassessed in Rottweilers) Serum creatinine creatine kinasepotassium total bilirubin total antioxidant status (TAS)

aspartate transaminase (AST) gamma-glutamyltransferase(GGT) T3 and T4 were measured using the Cobas c311 ore411 clinical chemistry analyzer according to manufacturerrsquosdirections Protein digestibility was determined based onamount of protein in food consumed amount in feces andcorrected for microbial nitrogen [8] DEXA was performedaccording to manufacturerrsquos directions

24 Gut Microbiota Composition The sequences for 16Samplicon PCR forward and reverse primers for the variableregions V4 to V6 (V456) were 51015840AGGCCAGCAGCCGCG-GTAA and 51015840GCCRRCACGAGCTGACGAC respectivelyThe pyrosequencing was performed using Roche 454 GS-FLX Pyrosequencer 489290 sequences were generated for98 samples (83 samples were used in this analysis) Dataquality control and sequence trimming were performedusing QIIMErsquos python script ldquosplit librariesrdquo [9] with defaultsettings except the following parameters (i) no barcodemismatcheswere allowed (ii)maximum sequence lengthwasset to 520 bp and (iii) a sliding window of 50 nucleotideswas used with average quality score ge 25 Pyrosequencingerror was removed using flowgram clustering The chimericsequences were detected and removed using UCHIME [10]A total of 265401 high quality sequences were obtainedwith the average of 3198 sequences per sample for the83 samples used in this analysis The cleaned sequenceswere then clustered into operational taxonomic units (OTU)using a closed reference-based OTU picking method withsimilarity threshold of 97 [10 11] where the refer-ence data file was obtained from the greengenes website(httpgreengeneslblgov August 2013 release) [11] A con-sensus taxonomic assignment for each OTU was performedusing the ribosomal database project naıve Bayesian classifier[12] at a minimum confidence interval of 80 Welchrsquos 119905-testwas used to calculate 119875 values

25 Imputation of Missing Value and Outlier DetectionParameters (metabolites or clinical) missing more than 20values across all breeds were discarded while missing valueswere imputed in cases where less than 20 values wereabsent Imputed metabolites were randomly determinedfrom a uniform distribution between 0 and the lowestmeasured value Imputed clinical parameters were replacedby the breed-specific median value of corresponding clinicalparameter

Outlier detection was performed using robust principalcomponent analysis (PCA) as described previously [13] andimplemented in the rrcov package for R [14] PCA wasperformed separately for metabolites and clinical variablesOne small dog (Small Fox Terrier) was identified as an outlierand removed from subsequent metabolomics analyses Afterpreprocessing 449 metabolites (of which 131 were unnamedchemicals) were included in the final metabolomics datasetNo clinical outliers were detected

26 Evaluation ofVariable Importance Theability ofmetabo-lomics and clinical variables to distinguish between bodysizes was evaluated using random forest (RF) with the

Journal of Nutrition and Metabolism 3

rfPermute package for R [15] This method not only is anappropriate approach for variable selection [16] but alsoprovides a measure of variable importance RF model isinitially created to calculate variable importance and theresponse variable is then permuted 1000 times to estimate 119875values for RF importance

MannndashWhitney 119880 tests were also used to compare dif-ferences in distribution of measured variables between bodysize groups in addition to RF Biomarker studies show thattwo types of methods may provide complementary results[17] Metabolite ratio between small and larger dogs wasdetermined by dividing the metabolite value by its medianvalue across all samples then dividing the small dog mean bythe larger dog mean

27 Detection of Metabolite Modules and Correlation withClinical Parameters Weighted gene coexpression networkanalysis (WGCNA) implemented in the WGCNA R package[18] was used for determining coexpression patterns betweengenes We applied such methodology to metabolomics datato identify groups or modules of highly cooccurring metabo-lites Modules were identified using unsupervised clusteringDynamic Branch Cut method with an optimal value of 4for soft threshold and a minimal number of 10 metabolitesper module Note that modules were randomly assignedcolors while unassigned metabolites were grouped in thegrey module A variable representative of all metaboliteswithin a modulemdashequivalent to the first eigenvalue of thePCAmdashwas obtained (eigengene) and Spearman rank pairwisecorrelations between each eigengene and clinical parameterswere calculated with unadjusted and Bonferroni Hochberg[19] adjusted 119875 value significance thresholds of 005 and 01respectively

To assess the ability of themodules to distinguish betweenbody sizes a hierarchical tree was constructed with themetabolites from larger dogs and metabolites were coloredaccording to the small dogrsquos module memberships 119885-scoreswere then calculated to evaluate howwell a module identifiedwith one population of reference (in this case small dogs) waspreserved when the reference was modified (ie larger dogs)[20] Greater 119885-scores show higher preservation and thuslower ability to distinguish between body sizes All analyseswere conducted with R software version 301 [21]

Associations with kidney function were performed usingPathway Studio Mammalian ChemEffect and DiseaseFXdatabases (Elsevier) Kidney function was represented by thefollowing cell process and clinical parameter terms kidneyfunction kidney elimination kidney excretion renal reab-sorption kidney tubule function kidney filtration kidneyblood flow kidney vascularization renal vasodilation renalacidification renin-angiotensin system kidney developmentrenal water reabsorption renal tubular secretion renal clear-ance and glomerular filtration rate

3 Results

31 Plasma Circulating Metabolites and Clinical Measures AreDifferent between Dogs of Different Body Size 449 metabo-lites were used for statistical and computational analysis

(see Supplementary Table 1 in the Supplementary Materialavailable online at httpsdoiorg10115520174535710) Ofthese 131 represent unnamed metabolites Levels of 66metabolites of which 14 were unnamed were significantlydifferent between small and larger dogs (adjusted 119875 value lt005 Table 1) 69 clinical parameters were measured in thisstudy (Supplementary Table 2) with 16 being significantlydifferent between small and larger dogs (adjusted 119875 valuelt 005 Table 2) Many of these parameters were based onweight (overall weight DEXA parameters etc) which wereexpected to be different since this study compared two groupsof dogs based on weight

32 Antioxidant Status Is Lower in Small Dogs Total antiox-idant status bilirubin glutathione metabolites and urate(measures of overall antioxidant status) were lower in smalldogs compared to larger dogs (Tables 1 and 2) Totalantioxidant status is representative of antioxidants presentin the blood that inhibit the oxidation reaction assay Inhi-bition can be caused by many types of antioxidants andis thus not specific for an individual antioxidant Bilirubinis associated with heme breakdown but is also a powerfulantioxidant [22] Glutathionemetabolites includingmultiplegamma-glutamyl amino acids cysteine-glutathione and 5-oxoproline were lower in small dogs Glutathione (GSH)is a powerful antioxidant present at high concentrations incells Urate another powerful antioxidant was also lowerin small dogs Urate initially produced from xanthine byxanthine oxidase in the metabolism of purines is convertedto allantoin by the uricase enzyme inmost species In humansand great apes however the uricase enzyme activity is absentand urate concentrations in these species are elevated [23]

33 Circulating Levels of Amino Acids Are Different betweenDogs of Different Body Size Several amino acids and theirmetabolites differed between small and larger dogs (Table 1)Circulating levels of the essential amino acids phenylalaninetyrosine lysine and the nonessential amino acids glutaminehydroxyproline and prolylhydroxyproline were lower insmall dogs compared with larger dogs Circulating levels ofthe essential amino acid arginine were higher in small dogsProtein digestibility (Table 2) was unexpectedly higher insmall dogs even though levels of many circulating aminoacids were lower The amino acid metabolites phenol sulfateand p-cresol-sulfate levels were higher in small dogs Thesemetabolites are formed in the liver by sulfation of bacterial-derived tyrosine metabolites [24]

34 Other Plasma Metabolites and Clinical Measures AreDifferent between Dogs of Different Body Size Othermetabo-lites and clinical measures involved in biological processesdiffered between small dogs and larger dogs (Tables 1 and2) While most of these processes were represented by onlyone metabolite or clinical measure they have physiologicalsignificance since they function across processes Creatinelevels were higher in small dogs as were two of its buildingblocks citrulline and arginine (Table 1) Creatine can beendogenously synthesized by the kidneys pancreas and liver


Table 1 Plasma metabolites with adjusted 119875 value lt 005 between small dogs and dogs of larger body size

Metabolite name Ratio (smalllarger) Class Adj P RI MassCreatine 281 Amino acid 735119864 minus 08 758 1321Creatinine 078 Amino acid 247119864 minus 07 730 11415-Oxoproline 078 Amino acid 328119864 minus 07 744 1282gamma-Glutamylphenylalanine 071 Peptide 366119864 minus 06 2846 2951X-18487 048 Unnamed 541119864 minus 06 12696 2731Hydroxyproline 072 Amino acid 797119864 minus 05 705 1321Phenylalanine 084 Amino acid 797119864 minus 05 2056 1661X-14625 082 Unnamed 797119864 minus 05 742 3081X-17381 294 Unnamed 797119864 minus 05 41598 2931p-Cresol sulfate 148 Amino acid 105119864 minus 04 2896 1871X-11334 047 Unnamed 119119864 minus 04 982 2591Urate 072 Nucleotide 158119864 minus 04 1928 4412X-13731 192 Unnamed 357119864 minus 04 1902 235gamma-Glutamylisoleucine 078 Peptide 415119864 minus 04 2644 2612gamma-Glutamylleucine 076 Peptide 415119864 minus 04 2744 2612gamma-Glutamylvaline 077 Peptide 464119864 minus 04 2040 2472Pseudouridine 089 Nucleotide 496119864 minus 04 1104 2431Phenol sulfate 174 Amino acid 612119864 minus 04 2150 1731X-12668 172 Unnamed 676119864 minus 04 2318 2461C-Glycosyltryptophan 079 Amino acid 931119864 minus 04 1912 3671myo-Inositol 079 Lipid 0001 19249 21717-Methylstearate 142 Lipid 0001 5987 2974X-14314 079 Unnamed 0001 2302 2411Glutamine 089 Amino acid 0002 684 1472X-12010 072 Unnamed 0002 1707 2031Glycolate (hydroxyacetate) 087 Xenobiotics 0002 1119 177gamma-Glutamyltyrosine 075 Peptide 0002 2073 3112X-12822 062 Unnamed 0004 2786 3891Xylonate 058 Carbohydrate 0004 1722 292Prolylhydroxyproline 019 Peptide 0005 960 2292Mannitol 033 Carbohydrate 0005 1839 3191Hydroquinone sulfate 157 Xenobiotics 0005 1383 189Ethanolamine 061 Lipid 0005 1304 17414-Ethylphenyl sulfate 150 Xenobiotics 0006 3570 2011Arabonate 069 Cofactors and vitamins 0006 1736 2921N6-Carbamoylthreonyladenosine 087 Nucleotide 0006 2656 413Pantothenate (Vitamin B5) 132 Cofactors and vitamins 0006 2218 2201Pyroglutamine 074 Amino acid 0006 764 1292gamma-Glutamylmethionine 077 Peptide 0008 1993 2792X-16940 345 Unnamed 0010 16941 2049Citrulline 121 Amino acid 0010 715 1761Tyrosine 086 Amino acid 0010 1516 1821Gulono-14-lactone 068 Cofactors and vitamins 0011 1862 3331Methylpalmitate (15 or 2) 123 Lipid 0011 5698 2694X-16394 079 Unnamed 0011 1719 2292Xylitol 075 Carbohydrate 0014 16776 217Arginine 115 Amino acid 0015 728 173221015840-Deoxycytidine 084 Nucleotide 0021 1256 22821015840-O-Methylguanosine 059 Nucleotide 0022 1926 298Ophthalmate 047 Amino acid 0023 1457 2901Homocitrulline 077 Amino acid 0024 832 1901


Table 1 Continued

Metabolite name Ratio (smalllarger) Class Adj P RI Mass5-Methylcytidine 113 Nucleotide 0025 1388 258N-Formylmethionine 089 Amino acid 0029 1541 1761Bilirubin (EE) 050 Cofactors and vitamins 0031 4625 5852X-17299 083 Unnamed 0031 12659 2292X-18156 079 Unnamed 0031 1392 2721Palmitoyl sphingomyelin 084 Lipid 0032 2524 3113X-16945 173 Unnamed 0036 34579 351Cysteine-glutathione disulfide 081 Amino acid 0038 821 42714-Vinylphenol sulfate 129 Xenobiotics 0040 3323 1991Erythritol 087 Xenobiotics 0040 15175 217Dihomolinolenate (203n3 or 3n6) 119 Lipid 0043 5600 3054Anthranilate 136 Amino acid 0049 3213 1381Lysine 075 Amino acid 0049 18367 3172Threitol 086 Carbohydrate 0049 1513 2171Threonate 074 Cofactors and vitamins 0049 15607 2921Ratios of median transformed values Benjamini-Hochberg adjusted 119875 values metabolite biological class retention index (RI) and mass (Da) are shown X- metabolites represent distinct chemical entities of discrete molecular formula and structure but do not currently match a named biochemical in ourreference library

Table 2 Clinical measures with adjusted 119875 value lt 005 between small dogs and dogs of larger body size

Clinical measure Mean small SEM small Mean larger SEM larger Adj PDEXA tissue (gm) 913512 40187 25392 56982 134119864 minus 18

DEXA lean (gm) 688476 30856 1794289 49191 134119864 minus 18

DEXA bone mineral content (gm) 37958 1599 100906 2488 134119864 minus 18

Weight (gm) 948615 42158 3176872 130221 22119864 minus 16

DEXA fat (gm) 225042 14525 744906 42725 291119864 minus 16

DEXA total mass (kg) 951 042 2640 059 127119864 minus 11

Bone density (gmcm2) 065 001 078 001 307119864 minus 10

Serum creatinine (mgdL) 064 002 086 002 780119864 minus 07

Serum creatine kinase (IUL) 26388 3351 15404 2137 504119864 minus 05

Serum potassium (mmolL) 431 005 465 005 933119864 minus 04

Serum total bilirubin (mgdL) 010 001 013 001 002Serum aspartate transaminase (UL) 3568 199 2791 107 002Serum gamma-glutamyltransferase (gdL) 693 043 594 036 002Serum total antioxidant status (mmolL) 149 003 160 002 003Serum T3 (nmolL) 106 004 094 003 004Protein digestibility (percentage) 8800 038 8600 057 001Mean standard error of the mean (SEM) and adjusted P values are shown DEXA dual-energy X-ray absorptiometry T3 total triiodothyronine

or it can be ingested [25]Most creatine is phosphorylated andstored as phosphocreatine in skeletal muscle where it is usedto replenish ATP concentrations Creatine is recycled intocreatinine which is then excreted by the kidney Creatininelevels were lower in small dogs

Homocitrulline concentrations were lower in larger dogsHomocitrulline is formed by the carbamylation of lysineresidues and results in loss of the biological activity of lysine[26] Triiodothyronine (T3) was higher in small dogs T3is a thyroid hormone that affects basal metabolic rate andincreases O2 metabolic consumption affecting both fatty acidand carbohydrate metabolism Pantothenic acid (vitaminB5) an essential component of coenzyme A was higher in

small dogs Bone mineral density was lower in small dogsconsistent with the results of others [27]

35 The Fecal Microbiome Differed between Dogs of DifferentBody Size The fecal microbiome was analyzed to determineif small dogs had differences in bacterial populations com-pared to larger dogs Since bacterial populations can changein as little as one day in response to a macronutrient change[28] and all dogs were fed identical diets fecal samples weretaken after 5 weeks based on the assumption that bacterialpopulations had normalized 16S analysis identified 6 bacteria(119875 value lt 005) at the genus level that differed between smalldogs and larger dogs Of these Bacteroides Faecalibacterium


Table 3 Metabolite module preservation and ability to distinguishbetween small dogs and dogs of larger body size

Module Size 119885-scoreBrown 70 2061Green 42 1397Yellow 63 938Turquoise 82 752Red 21 576Grey 72 422Black 19 411Blue 80 151119885-scores associated with each metabolite module Greater 119885-scores depictgreater preservation when the reference is changed from small to largerdogsThus modules with greater119885-scores have a lower ability to distinguishbetween groups

0

5

10

15

20

25

30

Bacteroides Collinsella Lactobacillus Faecalibacterium

Mea

n re

lativ

efre

quen

cy (

) + S

TD

Small body sizeLarger body size

lowast

lowast

lowast

lowastlowast

Figure 1 Fecal microbiota differences (genus level) between smalldogs and dogs of larger body size Microbiota differences with 119875value lt 005 and relative frequencies greater than 1 are shownlowastlowast119875 lt 001 lowast119875 lt 005

(higher in small dogs) and Collinsella and Lactobacillus(higher in larger dogs) had the highest mean proportiondifference (mean relative frequency gt 1) (Figure 1)

36 Plasma Metabolites and Clinical Measures Associate witha Kidney Function Visualization with PCA performed usingonly selected clinical or metabolite parameters simultane-ously confirmed clear discrimination between small andlarger dogs (Figures 2(a) and 2(b)) In order to understandrelationships between metabolites and clinical parametersmetabolite small dog modules were first identified withWGCNA using the 449 metabolites (Figure 3) 8 moduleswere identified (Table 3) The blue module containing 64named metabolites (Supplementary Table 3) had the high-est ability to distinguish between small dogs and largerdogs (lowest 119885-score and thus lowest preservation whenthe reference group was changed) A correlation analysiswas then performed between the clinical parameters andmetabolomics modules eigengenes (Figure 4) Age (negative)creatinine and bilirubin (both positive) among other clinicalparameters showed significant correlations (Figure 4) with

bluemodulemetabolitesMetabolites and clinical parameterswere analyzed for associations with kidney function Greaterthan 30 of the metabolites (Supplementary Table 4) andnearly all blue module associated clinical parameters (Sup-plementary Table 5) have associations with kidney function

4 Discussion

Although Monodrsquos dictum that anything true of E coli isalso true of the elephant describes well the commonalityof regulatory and biochemical reactions across the tree oflife subtle and important differences in transcriptional andmetabolic processes occur between species and within indi-viduals of the same species Analysis of plasma metabolitesand the microbiome revealed differences based on body sizebetween small and larger dogs Hierarchical clustering of thefinal preprocessed metabolites identified metabolites withsimilar concentrations (ie the blue module) that had thehighest ability to distinguish between small and larger dogsThis module contained 64 named metabolites in differentmetabolic classes (amino acid nucleotides carbohydratesxenobiotics and cofactors see Supplementary Table 3)

Small dogs have lower plasma levels of multiple antiox-idants including total antioxidant status urate glutathionemetabolites and bilirubin as compared to larger dogs sug-gesting a higher mass-specific metabolic rate [3] in tissuesLower levels of antioxidants may be an adaptation to ahigher production of free radicals because of the higherbasal metabolic rate in small dogs Bilirubin exerts itsmost potent antioxidant effects against lipid oxidation whilewater-soluble urate and glutathione have much more potentantioxidant effects on protein [29] which when consideredtogether indicated a systemic difference between small andlarger dogs

Urate concentrations were higher in larger dogs com-pared with small dogs Urate has both anti- and prooxidantcharacteristics Urate utilizes glutathione to reduce brainfree radicals by increasing cysteine uptake via EAAT-1transporters in neurons of the hippocampus [30] Urate hasspecifically demonstrated protective effects against peroxide[31] 1-methyl-4-phenyl-pyridinium [32] the reaction prod-ucts of peroxynitrite and CO2 CO3

minus and NO2 [33] as wellas 6-hydroxydopamine (6-OHDA) [34] Appropriate uratelevels have protective effects against oxidative diseases suchas Alzheimerrsquos Disease [35] Parkinsonrsquos disease [36] andMultiple Sclerosis [37]

However urate can also be prooxidant A 1mgdLincrease in serum urate concentrations has been associatedwith a significant increased incidence of hypertension [38]Higher urate concentrations have also been shown to predictworsening of renal disease in patients with renal failure[39] and affect glomerular filtration rate in healthy studyparticipants [40] Proper regulation of urate concentration isthus important to mediate its anti- or prooxidant properties

Glutathione is present in all cells in high concentrationsand acts as a buffer in redox reactions GSH is the mostprevalent antioxidant in the liver is stored in its reducedstate and protects hepatocytes against oxidative damageGSH is involved in maintaining thiol disulfide balance


PC 1 (175)

PC 2

(11

7)

6

4

2

0

minus2

minus4

minus6

6 8420minus2minus4minus6

BEA FOX T SCHNZR

LABSETSIBRottweiler

SmallOther

(a)

BEA FOX T SCHNZR

LABSETSIB

0 2 4PC 1 (222)

PC 2

(18

4)

SmallOther

2

1

0

minus2

minus2

minus1

minus3

(b)

Figure 2 Principle component analysis using selected metabolites (a) and clinical parameters (b) between small dogs and dogs of larger(other) body size Note that Rottweilers were not considered in the PCA generated with clinical parameters as they are missing DEXA-related parameters along with thyroid hormones T3 and T4 Body size is indicated by triangle (small) or circle (larger other) LAB LabradorRetriever SET English Setter BEA Beagle FOX T Small Fox Terrier SIB Siberian Husky SCHNZR Miniature Schnauzer

10

09

08

07

06

05

04

Hei

ght

Module colors

Figure 3 Metabolite dendrogram and module identification Hier-archical cluster tree of the 449 metabolites color-coded accordingto the modules identified using small dogs as the reference

peroxide detoxification leukotriene biosynthesis and aminoacid transport and has been shown to play a role in multiplecellular processes such as transcription proliferation andapoptosis [41] Cardiac disease is associated with decreasedGSH levels in dogs [42] Compared with healthy dogs GSHconcentrations in clinically ill dogs are significantly decreasedin erythrocytes and GSH depletion correlates with severityof illness and mortality [43] We showed here that multiplemetabolites of GSH metabolism were lower in the plasmaof small dogs suggesting utilization for GSH production

However the true response of the GSH system in small dogsis not known since oxidative states of the GSH were notmeasured in this study

We have shown that bilirubin concentrations were lowerin small dogs Bilirubin represents a lipophilic cytoprotec-tant antioxidant which is complementary to water-solubleantioxidants such as GSH [29] The clinical implicationsof low bilirubin in small dogs are unclear although lowerconcentrations suggest increased metabolic consumptionand the possibility of ongoing oxidative damage in small dogs

Small dogs had lower levels of multiple amino acidsincluding the essential amino acids phenylalanine tyrosineand lysine Arginine was an exception since it was found athigher levels in small dogs We previously determined thatprotein digestibility was higher in small dogs suggesting thatmetabolic differences produced the lower levels of aminoacids in small dogs

Phenylalanine is involved in the synthesis of tyrosinewhich is then used as a precursor for the synthesis ofadrenaline noradrenaline and dopamine [44] Tyrosine canbe fermented in the large intestine resulting in the microbialformation of p-cresol and indoxyl (a phenolic compound)which after hepatic sulfation become p-cresyl sulfate andphenol sulfate [24 45] Concentrations of both of thesecompounds were higher in small dogs suggesting that pheny-lalanine and tyrosine were lower due to fermentation andsulfation perhaps through increased microbial metabolism


minus1minus08minus06minus04minus020020406081

Age

yea

rs

Seru

mU

reaN

itrog

enSe

rum

TSH

Seru

mT

rigly

cerid

esSe

rum

Tot

alP

rote

inSe

rum

Tot

alB

iliru

bin

Seru

mT

AS

Seru

mT

4Se

rum

T3

Seru

mS

odiu

mSe

rum

Pot

assiu

mSe

rum

Pho

spho

rus

Seru

mM

agne

sium

Seru

mL

DL

Cho

leste

rol

Seru

mL

DH

Seru

mIn

sulin

Seru

mIg

GSe

rum

IgE

Seru

mIg

ASe

rum

HD

LC

hole

stero

lSe

rum

Glu

cose

Seru

mG

lobu

linSe

rum

GG

TSe

rum

Cre

atin

ine

Seru

mC

ortis

olSe

rum

CK

Seru

mC

hole

stero

lSe

rum

Chl

orid

eSe

rum

Cal

cium

Seru

mA

STSe

rum

Apo

lipro

tein

ASe

rum

ALT

Seru

mA

lkal

ineP

hosp

hata

seSe

rum

Alb

umin

Plu

sD

EXA

Tot

alM

ass

DEX

AT

issue

Fat

DEX

AT

issue

DEX

AR

egio

nFa

tD

EXA

Lea

nD

EXA

Fat

DEX

AB

oneM

iner

alC

onte

ntD

EXA

Bon

eDen

sity

CBC

WBC

CBC

RBC

CBC

PLT

CBC

Neu

troph

il

CBC

MCV

CBC

MCH

CCB

CM

CHCB

CLy

mph

ocyt

eCB

CH

GB

CBC

HCT

CBC

Eosin

ophi

lCB

CBa

nds

VitD

25O

HVi

tD1

25O

HPe

tWei

ght

Seru

mP

arat

horm

one

MEbrownMEred

MEblackMEblue

MEturquoiseMEgreen

MEyellowMEgrey

Figure 4 Correlations betweenmetabolite modules and clinical parameters Significant associations (119875 lt 005) between metabolite modulesand clinical parameters using small dogs as reference are indicated by filled circles Strength of Spearman correlations detailed by the scaleon the right

Levels of certain microbial populations affect formation of p-cresyl sulfate indicative of differences in the gut microflorabetween small and larger dogs [45] 16S analysis revealedhigher levels of Bacteroides in small dogs Bacteroides fragilishas been shown to produce phenols from tyrosine [45]Previous studies have shown differences between fecal versusilleal protein digestibility which takes into account microbialcontributions to amino acid metabolism [46 47] consistentwith the results presented here

We observed higher levels of arginine and lower levelsof lysine in small dogs Lysine and arginine share thecationic amino acid transporter system (CAT) mechanismand concentrations of one competitively inhibit transport ofthe other which has been observed in mammalian cells [4849]The clinical implications of differences in concentrationsof these amino acids cannot be interpreted with the currentdata although arginine supplementation is known to bebeneficial in wound healing and is essential for maintainingintestinal integrity [50] Additionally the lower levels ofplasma glutamine in small dogsmay be due to absorption intoenterocytes since enterocytes use glutamine as their primaryfuel source [51]

Creatine concentrations in plasma were lower in largerdogs In addition to dietary source creatine can be syn-thesized endogenously and is stored as phosphocreatine inmuscles as an ATP buffer Creatine is excreted as creatinine inurine and often serves as a marker of kidney function Dogswith increased bodyweight have increased urinary creatinineexcretion suggesting increased creatine turnover consistentwith the higher levels of creatinine in larger dogs noted inour study [52] However creatinine may also be associatedwith increased muscle mass or muscle volume Sighthoundshave moremuscle volume than breeds of similar body weightwith concomitant increased creatinine concentrations whencomparedwith other breeds [53 54] Reduced concentrationsof creatine might be associated with increased storage asphosphocreatine increased usage in skeletal muscle andconsequent increased creatinine excretion

Plasma homocitrulline was higher in larger dogs Ele-vated homocitrulline concentrations have been correlatedwith the progression of renal disease [55 56] Homocitrullineconcentration is inversely associatedwith estimated glomeru-lar filtration rate [55 57] Kidney disease has a prevalence

of 05ndash15 in the canine population [58] In a retrospectivestudy in Sweden an average of 158 cases of kidney diseasewere diagnosed per 10000 dog years at risk (DYAR) witha mortality of 97 deaths per 10000 DYAR [59] Of thebreeds exceeding the mean incidence of kidney disease 23are considered breeds of larger body size However the threebreeds with the lowest incidence of mortality due to kidneydisease were all small breeds This is especially interestingbecause a different survey-based study found that smallerdogs are at greater risk for kidney disease with every decreaseof 10 kg in bodyweight a 50 increased risk of kidney diseasewas found [60]

Many other metabolites in the blue module were asso-ciated with kidney function (Supplementary Table 4) Otherclinical parameters correlated with metabolites in this mod-ule also have associations with kidney function (Supplemen-tary Table 5) Based on these data thismetabolitemodule andits clinical correlates may contribute to a kidney metabolitenetwork Many of the differences noted here between smalland larger dogs can be attributed to functional differencesrather than disease since the animals used in this study didnot have clinical kidney conditions However no predispo-sitions are known between the small and large breed dogpopulations but more research needs to be done here todetermine the clinical significance

5 Conclusions

We have described here metabolic differences between smalldogs and dogs of larger body sizes This included thedifference in circulating metabolites clinical parameters andmicrobiota from dogs in a diet and environment-controlledstudy Small dogs had a lower antioxidant status as measuredby multiple metabolites and clinical parameters Differenceswere also shown in circulating amino acids some of whichcould be tied to variations in specific bacteria of the micro-biota Additionally analysis of small dog metabolites andclinical parameters reflected a network which strongly asso-ciates with kidney functionThis analysis represents a uniqueand initial view of metabolic differences between body sizeswithin a mammalian species These differences reflect notonly morphometric induced variability but also metabolic-specific genetic differences associated with the creation of


breeds due to artificial selection More will need to be donein order to identify other unique metabolic characteristicsof small dogs including studies representing more breedsbelonging to the body size classes of Canis lupus familiaris

Abbreviations

AST Aspartate transaminaseDEXA Dual-energy X-ray absorptiometryDYAR Dog years at riskGCMS Gas chromatographymass spectrometryGGT Gamma-glutamyltransferaseGSH GlutathioneLCMS Liquid chromatographytandem mass

spectrometryOTU Operational taxonomic unitsPCA Principal component analysisRF Random forestT3 TriiodothyronineT4 ThyroxineTAS Total antioxidant statusWGCNA Weighted gene coexpression network analysis

Ethical Approval

TheNestle PurinaAnimal Care andUseCommittee approvedthe study protocol

Disclosure

Present address of Jim Kaput is Vydiant Inc Gold RiverCA R Middleton C Petzinger-Germain and A Beloshapkaare employees of Nestle Purina Research J Carayol is anemployee of Nestle Institute of Health Sciences and J Kaputwas employed by Nestle Institute of Health Sciences duringthe project work reflected in this manuscript

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this article

Acknowledgments

The authors would like to thank Rachel Anderson PatriciaTurpin Cathy Chase Aaron Parker and Carolyn Cupp fortheir help with conducting the animal trial and samplecollection They thank Qinghong Li Jeff Labuda and ZiadRamadan for their help with the fecal microbiome analysisThey thank Wendell Kerr and Xuemei Si for their help withthe clinical statistics analysisThis work was funded by NestlePurina

References

[1] C L Turner and D Christian ldquoHealth Risks in Small DogsrdquoSupplement to Compendium on Continuing Education for thePracticing Veterinarian vol 24 p 76 2002

[2] J M Fleming K E Creevy and D E L Promislow ldquoMortalityin north american dogs from 1984 to 2004 an investigation

into age- size- and breed-related causes of deathrdquo Journal ofVeterinary Internal Medicine vol 25 no 2 pp 187ndash198 2011

[3] A G Jimenez ldquoPhysiological underpinnings in life-historytrade-offs inmanrsquosmost popular selection experiment the dogrdquoJournal of Comparative Physiology B Biochemical Systemic andEnvironmental Physiology vol 186 no 7 pp 813ndash827 2016

[4] V J Adams K M Evans J Sampson and J LWood ldquoMethodsand mortality results of a health survey of purebred dogs in theUKrdquo J Small Anim Pract vol 51 no 10 pp 512ndash524 2010

[5] Q Li L M Freeman J E Rush et al ldquoVeterinary medicine andmulti-omics research for future nutrition targets metabolomicsand transcriptomics of the common degenerative mitral valvedisease in dogsrdquo OMICS A Journal of Integrative Biology vol19 no 8 pp 461ndash470 2015

[6] A M Evans C D DeHaven T Barrett M Mitchell andE Milgram ldquoIntegrated nontargeted ultrahigh performanceliquid chromatographyelectrospray ionization tandem massspectrometry platform for the identification and relative quan-tification of the small-molecule complement of biological sys-temsrdquoAnalytical Chemistry vol 81 no 16 pp 6656ndash6667 2009

[7] C D DeHaven A M Evans H Dai and K A LawtonldquoOrganization of GCMS and LCMS metabolomics data intochemical librariesrdquo J Cheminformatics vol 2 pp 9ndash21 2010

[8] L K Karr-Lilienthal C M Grieshop J K Spears et alldquoEstimation of the proportion of bacterial nitrogen in caninefeces using diaminopimelic acid as an internal bacterialmarkerrdquoJournal of Animal Science vol 82 no 6 pp 1707ndash1712 2004

[9] J Reeder and R Knight ldquoRapidly denoising pyrosequencingamplicon reads by exploiting rank-abundance distributionsrdquoNature Methods vol 7 no 9 pp 668-669 2010

[10] R C Edgar B J Haas J C Clemente C Quince and RKnight ldquoUCHIME improves sensitivity and speed of chimeradetectionrdquo Bioinformatics vol 27 no 16 pp 2194ndash2200 2011

[11] T Z DeSantis P Hugenholtz N Larsen et al ldquoGreengenesa chimera-checked 16S rRNA gene database and workbenchcompatible with ARBrdquo Applied and Environmental Microbiol-ogy vol 72 no 7 pp 5069ndash5072 2006

[12] Q Wang G M Garrity J M Tiedje and J R Cole ldquoNaiveBayesian classifier for rapid assignment of rRNA sequences intothe new bacterial taxonomyrdquoAppl EnvironMicrobiol vol 73 pp5261ndash5267 2007

[13] M Hubert P J Rousseeuw and K V Branden ldquoROBPCA anew approach to robust principal component analysisrdquo Techno-metrics vol 47 no 1 pp 64ndash79 2005

[14] V Todorov and P Filzmoser ldquoAn object-oriented framework forrobust multivariate analysisrdquo Journal of Statistical Software vol32 no 3 pp 1ndash47 2009

[15] E Archer rfPermute Estimate Permutation p-Values for Ran-dom Forest Importance Metrics R package version 215 2016httpsCRANR-projectorgpackage=rfPermute

[16] L Breiman ldquoMachine Learningrdquo vol 45 2001[17] E Saccenti H C J Hoefsloot A K Smilde J A Westerhuis

and M M W B Hendriks ldquoReflections on univariate andmultivariate analysis of metabolomics datardquoMetabolomics vol10 no 3 pp 361ndash374 2014

[18] P Langfelder and S Horvath ldquoWGCNA an R package forweighted correlation network analysisrdquo BMC Bioinformaticsvol 9 article 559 2008

[19] Y Benjamini and Y Hochberg ldquoControlling the false discoveryrate a practical and powerful approach to multiple testingrdquoJournal of the Royal Statistical Society Series B (StatisticalMethodology) vol 57 pp 289ndash300 1995


[20] P Langfelder R Luo M C Oldham and S Horvath ldquoIs MyNetwork Module Preserved and Reproduciblerdquo PLoS ComputBiol vol 7 Article ID 1001057 p 10 2011

[21] R Core Team R A language and environment for statisticalcomputing R Foundation for Statistical Computing ViennaAustria 2016 httpswwwR-projectorg

[22] D E Baranano M Rao C D Ferris and S H SnyderldquoBiliverdin reductase a major physiologic cytoprotectantrdquo Pro-ceedings of the National Acadamy of Sciences of the United Statesof America vol 99 no 25 pp 16093ndash16098 2002

[23] M Oda Y Satta O Takenaka and N Takahata ldquoLoss of urateoxidase activity in hominoids and its evolutionary implica-tionsrdquo Molecular Biology and Evolution vol 19 no 5 pp 640ndash653 2002

[24] W R Wikoff A T Anfora and J Liu ldquoMetabolomics analysisreveals large effects of gut microflora on mammalian bloodmetabolitesrdquo Proceedings of the National Acadamy of Sciencesof the United States of America vol 106 no 10 pp 3698ndash37032009

[25] M G Bemben and H S Lamont ldquoCreatine supplementationand exercise performance Recent findingsrdquo Sports Medicinevol 35 no 2 pp 107ndash125 2005

[26] ZWang S J Nicholls E R Rodriguez et al ldquoProtein carbamy-lation links inflammation smoking uremia and atherogenesisrdquoNature Medicine vol 13 no 10 pp 1176ndash1184 2007

[27] C J Cupp and G Czarnecki-Maulden ldquoEffect of breed and sizeof dog on body compositionrdquo J An Sci vol 82 supplement 1 p244 2004

[28] L A David C F Maurice R N Carmody et al ldquoDiet rapidlyand reproducibly alters the human gut microbiomerdquo Naturevol 505 no 7484 pp 559ndash563 2014

[29] T W Sedlak M Saleh D S Higginson B D Paul K R Juluriand S H Snyder ldquoBilirubin and glutathione have complemen-tary antioxidant and cytoprotective rolesrdquo Proceedings of theNational Acadamy of Sciences of the United States of Americavol 106 no 13 pp 5171ndash5176 2009

[30] K Aoyama N Matsumura M Watabe F Wang K Kikuchi-Utsumi and T Nakaki ldquoCaffeine and uric acid mediate glu-tathione synthesis for neuroprotectionrdquo Neuroscience vol 181pp 206ndash215 2011

[31] B N Ames R Cathcart E Schwiers and P HochsteinldquoUric acid provides an antioxidant defense in humans againstoxidant- and radical-caused aging and cancer a hypothesisrdquoProceedings of the National Acadamy of Sciences of the UnitedStates of America vol 78 no 11 pp 6858ndash6862 1981

[32] S Cipriani C A Desjardins T C Burdett Y Xu K Xu andM A Schwartzchild ldquoUrate and its transgenic depletion mod-ulate neuronal vulnerability in a cellular model of Parkinsonsdiseaserdquo PLoS One vol 7 Article ID e37331 2012

[33] G L Squadrito R Cueto A E Splenser et al ldquoReaction ofuric acidwith peroxynitrite and implications for themechanismof neuroprotection by uric acidrdquo Archives of Biochemistry andBiophysics vol 376 no 2 pp 333ndash337 2000

[34] L Gong Q-L Zhang N Zhang et al ldquoNeuroprotection byurate on 6-OHDA-lesioned rat model of Parkinsonrsquos diseaseLinking to AktGSK3120573 signaling pathwayrdquo Journal of Neuro-chemistry vol 123 no 5 pp 876ndash885 2012

[35] T-S Kim C-U Pae S-J Yoon et al ldquoDecreased plasmaantioxidants in patients with Alzheimerrsquos diseaserdquo InternationalJournal of Geriatric Psychiatry vol 21 no 4 pp 344ndash348 2006

[36] J W Davis A Grandinetti C I Waslien G W Ross L RWhite and D M Morens ldquoObservations on serum uric acidlevels and the risk of idiopathic Parkinsonrsquos diseaserdquo AmericanJournal of Epidemiology vol 144 no 5 pp 480ndash484 1996

[37] D C Hooper G S Scott A Zborek et al ldquoUric acid aperoxynitrite scavenger inhibits CNS inflammation blood-CNS barrier permeability changes and tissue damage in amouse model of multiple sclerosisrdquoThe FASEB Journal vol 14no 5 pp 691ndash698 2000

[38] P C Grayson S Young Kim M Lavalley and H K ChoildquoHyperuricemia and incident hypertension a systematic reviewand meta-analysisrdquo Arthritis Care amp Research vol 63 no 1 pp102ndash110 2011

[39] G Bellomo S Venanzi C Verdura P Saronio A Esposito andM Timio ldquoAssociation of uric acid with change in kidney func-tion in healthy normotensive individualsrdquo American Journal ofKidney Diseases vol 56 no 2 pp 264ndash272 2010

[40] C-Y Hsu C Iribarren C E McCulloch J Darbinian and AS Go ldquoRisk factors for end-stage renal disease - 25-year follow-uprdquo JAMA Internal Medicine vol 169 no 4 pp 342ndash350 2009

[41] E V Kalinina N N Chernov and M D Novichkova ldquoRole ofglutathione glutathione transferase and glutaredoxin in regu-lation of redox-dependent processesrdquo Biochemistry (Moscow)vol 79 no 13 pp 1562ndash1583 2014

[42] L M Freeman J E Rush P E Milbury and J B BlumbergldquoAntioxidant status and biomarkers of oxidative stress in dogswith congestive heart failurerdquo Journal of Veterinary InternalMedicine vol 19 no 4 pp 537ndash541 2005

[43] K R Viviano S N Lavergne L Goodman et al ldquoGlutathionecysteine and ascorbate concentrations in clinically ill dogs andcatsrdquo Journal of Veterinary Internal Medicine vol 23 no 2 pp250ndash257 2009

[44] P F Fitzpatrick ldquoThe aromatic amino acid hydroxylasesrdquoAdvances in Enzymology and Related Areas ofMolecular Biologyvol 74 pp 235ndash294 2000

[45] E Bone A Tamm and M Hill ldquoThe production of urinaryphenols by gut bacteria and their possible role in the causationof large bowel cancerrdquo American Journal of Clinical Nutritionvol 29 no 12 pp 1448ndash1454 1976

[46] M Fuller ldquoDetermination of protein and amino acid digestibil-ity in foods including implications of gut microbial amino acidsynthesisrdquo British Journal of Nutrition vol 108 no 2 pp S238ndashS246 2012

[47] P Reeds G Schaafsma D Tome and V Young ldquoCriteria andsignificance of dietary protein sources in humans Summaryof the workshop with recommendationsrdquo J Nutr vol 130 pp1874Sndash1876S 2000

[48] R L OrsquoKane J R Vina I Simpson R Zaragoza A Mokashiand R A Hawkins ldquoCationic amino acid transport acrossthe blood-brain barrier is mediated exclusively by system y+rdquoAmerican Journal of Physiology Endocrinology and MetabolismClinics of North America vol 291 pp E412ndashE419 2009

[49] B Stieger G Stange J Biber and H Murer ldquoTransport of l-lysine by rat renal brush border membrane vesiclesrdquo PflugersArchiv - European Journal of Physiology vol 397 no 2 pp 106ndash113 1983

[50] K Singh L A CoburnD P Barry J-L Boucher R Chaturvediand K T Wilson ldquoL-arginine uptake by cationic amino acidtransporter 2 is essential for colonic epithelial cell restitutionrdquoAmerican Journal of Physiology-Gastrointestinal and Liver Phys-iology vol 302 no 9 pp G1061ndashG1073 2012


[51] S T OrsquoDwyer R J Smith T L Hwang and D W WilmoreldquoMaintenance of Small Bowel Mucosa with Glutamine-Enriched Parenteral Nutritionrdquo Journal of Parenteral andEnteral Nutrition vol 13 no 6 pp 579ndash585 1989

[52] S A Center EWilkinson C A Smith H Erb and RM Lewisldquo24-Hour urine proteincreatinine ratio in dogs with protein-losing nephropathiesrdquo Journal of the American VeterinaryMedical Association vol 187 no 8 pp 820ndash824 1985

[53] W E Feeman III C G Couto and T L Gray ldquoSerum creati-nine concentrations in retired racing greyhoundsrdquo VeterinaryClinical Pathology vol 32 no 1 pp 40ndash42 2003

[54] M Hillpo ldquoSome haematological and clinical-chemical param-eters of sight hounds (Afghan hound saluki and whippet)rdquoNordisk Veterinaeligrmedicin vol 38 no 3 pp 148ndash155 1986

[55] W H W Tang K Shrestha Z Wang et al ldquoProtein car-bamylation in chronic systolic heart failure Relationship withrenal impairment and adverse long-term outcomesrdquo Journal ofCardiac Failure vol 19 no 4 pp 219ndash224 2013

[56] L M Kraus L Gaber C R Handorf H Marti Krais Jr andA P ldquoCarbamylation of glomerular and tubular proteins inpatients with kidney failure a potential mechanism of ongoingrenal damagerdquo Swiss Medical Weekly vol 131 pp 139ndash145 2001

[57] A S Levey J P Bosch J B Lewis T Greene N Rogers and DRoth ldquoAmore accuratemethod to estimate glomerular filtrationrate from serum creatinine a new prediction equationrdquo Annalsof Internal Medicine vol 130 no 6 pp 461ndash470 1999

[58] D J Polzin ldquoChronic kidney diseaserdquo in Textbook of VeterinaryInternal Medicine S J Ettinger and E C Feldman Eds pp1990ndash2021 Elsevier Saunders St Louis Missouri MO USA7th edition 2010

[59] L Pelander I Ljungvall A Egenvall H Syme J Elliott and JHaggstrom ldquoIncidence of andmortality from kidney disease inover 600000 insured Swedish dogsrdquoVeterinary Record vol 176no 25 p 656 2015

[60] P C Bartlett J W Van Buren A D Bartlett and C ZhouldquoCase-control study of risk factors associated with feline andcanine chronic kidney diseaserdquo Veterinary Medicine Interna-tional vol 2010 Article ID 957570 9 pages 2010

Submit your manuscripts athttpswwwhindawicom

Stem CellsInternational

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014


MEDIATORSINFLAMMATION

of


Behavioural Neurology

EndocrinologyInternational Journal of



Disease Markers


BioMed Research International

OncologyJournal of



Oxidative Medicine and Cellular Longevity


PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of



Computational and Mathematical Methods in Medicine

OphthalmologyJournal of


Diabetes ResearchJournal of



Research and TreatmentAIDS


Gastroenterology Research and Practice


Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom


kibble diet for 5 weeks Small dogs (34 individuals BeagleSmall Fox Terrier and Miniature Schnauzer) had a meanweight of 93 kg (range of 61ndash156 kg) Larger dogs (49 indi-viduals Labrador Retriever English Setter Siberian Huskyand Rottweiler) had a mean weight of 315 kg (range of184ndash544 kg) Small dogs had a mean age of 68 years (rangeof 24ndash133 years) while larger dogs had a mean age of 62years (range of 22ndash98 years) All dogs except Rottweilerswere housed in the same location Samples were handled andprocessed in the same manner to avoid technical variabilityor bias Plasma-EDTA and serum samples were taken afterovernight fasting during the fifth week of feeding Fecalsamples were collected during the fifth week of feedingPlasma serum and fecal samples not immediately analyzedwere frozen at minus80∘C

22 Canine Plasma Metabolites Metabolite profiling wasperformed as described previously [5] In summary metabo-lites from each blood sample were extracted and analyzedby GCMS (Thermo Fischer DSQ mass spectrometer) andLCMS (Thermo Fischer LTQ mass spectrometers) Wecarried out chromatographic separation followed by full-scanMS to record and quantify all detectable ions in the samples[6] All metabolites with known chemical structure wereidentified by matching the ionsrsquo chromatographic retentionindex andMS fragmentation signatureswith reference libraryentries created from authentic standard metabolites [7] Thereported masses within the supplemental table represent therespective masses of the ion features utilized to identifyeach molecule These ion features could be the mass ofthe parent molecule the mass of an ion featurefragmentof the molecule or an adduct (eg sodium adduct) ofthe parental molecule or an adduct of an ion fragmentAdditional library entries were added for ions that were notcovered by the standards based on their unique ion signatures(chromatographic and mass spectral) so these ions couldthen be routinely detected and quantified For quality controland run-day performance analysis labeled internal standardswere spiked into all samples at different stages of the dataacquisition process The median relative standard deviationswere 7 and 12 for the internal standards and endogenousbiochemicals 589 detected in total respectively

We identified 589 metabolites in plasma prior to removalof some for low percentage presence across all breeds Ofthese 401 biochemicals matched a named structure in thereference library (named) The remaining 188 biochemicalsrepresented distinct chemical entities that represent a singlemolecule of discretemolecular formula and structure but thatdo not currently match a named chemical in the referencelibrary (unnamed)

23 Canine Clinical Parameters Most clinical parameterswere analyzed in all dogs Some anthropometric analysesusing dual-energy X-ray absorptiometry (DEXA) and thy-roid hormones triiodothyronine (T3) and thyroxine (T4)were evaluated only in 34 small dogs and 35 larger dogs (notassessed in Rottweilers) Serum creatinine creatine kinasepotassium total bilirubin total antioxidant status (TAS)

aspartate transaminase (AST) gamma-glutamyltransferase(GGT) T3 and T4 were measured using the Cobas c311 ore411 clinical chemistry analyzer according to manufacturerrsquosdirections Protein digestibility was determined based onamount of protein in food consumed amount in feces andcorrected for microbial nitrogen [8] DEXA was performedaccording to manufacturerrsquos directions

24 Gut Microbiota Composition The sequences for 16Samplicon PCR forward and reverse primers for the variableregions V4 to V6 (V456) were 51015840AGGCCAGCAGCCGCG-GTAA and 51015840GCCRRCACGAGCTGACGAC respectivelyThe pyrosequencing was performed using Roche 454 GS-FLX Pyrosequencer 489290 sequences were generated for98 samples (83 samples were used in this analysis) Dataquality control and sequence trimming were performedusing QIIMErsquos python script ldquosplit librariesrdquo [9] with defaultsettings except the following parameters (i) no barcodemismatcheswere allowed (ii)maximum sequence lengthwasset to 520 bp and (iii) a sliding window of 50 nucleotideswas used with average quality score ge 25 Pyrosequencingerror was removed using flowgram clustering The chimericsequences were detected and removed using UCHIME [10]A total of 265401 high quality sequences were obtainedwith the average of 3198 sequences per sample for the83 samples used in this analysis The cleaned sequenceswere then clustered into operational taxonomic units (OTU)using a closed reference-based OTU picking method withsimilarity threshold of 97 [10 11] where the refer-ence data file was obtained from the greengenes website(httpgreengeneslblgov August 2013 release) [11] A con-sensus taxonomic assignment for each OTU was performedusing the ribosomal database project naıve Bayesian classifier[12] at a minimum confidence interval of 80 Welchrsquos 119905-testwas used to calculate 119875 values

25 Imputation of Missing Value and Outlier DetectionParameters (metabolites or clinical) missing more than 20values across all breeds were discarded while missing valueswere imputed in cases where less than 20 values wereabsent Imputed metabolites were randomly determinedfrom a uniform distribution between 0 and the lowestmeasured value Imputed clinical parameters were replacedby the breed-specific median value of corresponding clinicalparameter

Outlier detection was performed using robust principalcomponent analysis (PCA) as described previously [13] andimplemented in the rrcov package for R [14] PCA wasperformed separately for metabolites and clinical variablesOne small dog (Small Fox Terrier) was identified as an outlierand removed from subsequent metabolomics analyses Afterpreprocessing 449 metabolites (of which 131 were unnamedchemicals) were included in the final metabolomics datasetNo clinical outliers were detected

26 Evaluation ofVariable Importance Theability ofmetabo-lomics and clinical variables to distinguish between bodysizes was evaluated using random forest (RF) with the







3 Results










Table 1 Continued






Weight (gm) 948615 42158 3176872 130221 22119864 minus 16

DEXA fat (gm) 225042 14525 744906 42725 291119864 minus 16














0

5

10

15

20

25

30


Mea

n re

lativ

efre

quen

cy (

) + S

TD


lowast

lowast

lowast

lowastlowast





4 Discussion








PC 1 (175)

PC 2

(11

7)

6

4

2

0

minus2

minus4

minus6


BEA FOX T SCHNZR

LABSETSIBRottweiler

SmallOther

(a)

BEA FOX T SCHNZR

LABSETSIB

0 2 4PC 1 (222)

PC 2

(18

4)

SmallOther

2

1

0

minus2

minus2

minus1

minus3

(b)


10

09

08

07

06

05

04

Hei

ght

Module colors









Age

yea

rs

Seru

mU

reaN

itrog

enSe

rum

TSH

Seru

mT

rigly

cerid

esSe

rum

Tot

alP

rote

inSe

rum

Tot

alB

iliru

bin

Seru

mT

AS

Seru

mT

4Se

rum

T3

Seru

mS

odiu

mSe

rum

Pot

assiu

mSe

rum

Pho

spho

rus

Seru

mM

agne

sium

Seru

mL

DL

Cho

leste

rol

Seru

mL

DH

Seru

mIn

sulin

Seru

mIg

GSe

rum

IgE

Seru

mIg

ASe

rum

HD

LC

hole

stero

lSe

rum

Glu

cose

Seru

mG

lobu

linSe

rum

GG

TSe

rum

Cre

atin

ine

Seru

mC

ortis

olSe

rum

CK

Seru

mC

hole

stero

lSe

rum

Chl

orid

eSe

rum

Cal

cium

Seru

mA

STSe

rum

Apo

lipro

tein

ASe

rum

ALT

Seru

mA

lkal

ineP

hosp

hata

seSe

rum

Alb

umin

Plu

sD

EXA

Tot

alM

ass

DEX

AT

issue

Fat

DEX

AT

issue

DEX

AR

egio

nFa

tD

EXA

Lea

nD

EXA

Fat

DEX

AB

oneM

iner

alC

onte

ntD

EXA

Bon

eDen

sity

CBC

WBC

CBC

RBC

CBC

PLT

CBC

Neu

troph

il

CBC

MCV

CBC

MCH

CCB

CM

CHCB

CLy

mph

ocyt

eCB

CH

GB

CBC

HCT

CBC

Eosin

ophi

lCB

CBa

nds

VitD

25O

HVi

tD1

25O

HPe

tWei

ght

Seru

mP

arat

horm

one

MEbrownMEred

MEblackMEblue

MEturquoiseMEgreen

MEyellowMEgrey








5 Conclusions




Abbreviations



Ethical Approval


Disclosure




Acknowledgments


References





































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of






















3 Results










Table 1 Continued






Weight (gm) 948615 42158 3176872 130221 22119864 minus 16

DEXA fat (gm) 225042 14525 744906 42725 291119864 minus 16














0

5

10

15

20

25

30


Mea

n re

lativ

efre

quen

cy (

) + S

TD


lowast

lowast

lowast

lowastlowast





4 Discussion








PC 1 (175)

PC 2

(11

7)

6

4

2

0

minus2

minus4

minus6


BEA FOX T SCHNZR

LABSETSIBRottweiler

SmallOther

(a)

BEA FOX T SCHNZR

LABSETSIB

0 2 4PC 1 (222)

PC 2

(18

4)

SmallOther

2

1

0

minus2

minus2

minus1

minus3

(b)


10

09

08

07

06

05

04

Hei

ght

Module colors









Age

yea

rs

Seru

mU

reaN

itrog

enSe

rum

TSH

Seru

mT

rigly

cerid

esSe

rum

Tot

alP

rote

inSe

rum

Tot

alB

iliru

bin

Seru

mT

AS

Seru

mT

4Se

rum

T3

Seru

mS

odiu

mSe

rum

Pot

assiu

mSe

rum

Pho

spho

rus

Seru

mM

agne

sium

Seru

mL

DL

Cho

leste

rol

Seru

mL

DH

Seru

mIn

sulin

Seru

mIg

GSe

rum

IgE

Seru

mIg

ASe

rum

HD

LC

hole

stero

lSe

rum

Glu

cose

Seru

mG

lobu

linSe

rum

GG

TSe

rum

Cre

atin

ine

Seru

mC

ortis

olSe

rum

CK

Seru

mC

hole

stero

lSe

rum

Chl

orid

eSe

rum

Cal

cium

Seru

mA

STSe

rum

Apo

lipro

tein

ASe

rum

ALT

Seru

mA

lkal

ineP

hosp

hata

seSe

rum

Alb

umin

Plu

sD

EXA

Tot

alM

ass

DEX

AT

issue

Fat

DEX

AT

issue

DEX

AR

egio

nFa

tD

EXA

Lea

nD

EXA

Fat

DEX

AB

oneM

iner

alC

onte

ntD

EXA

Bon

eDen

sity

CBC

WBC

CBC

RBC

CBC

PLT

CBC

Neu

troph

il

CBC

MCV

CBC

MCH

CCB

CM

CHCB

CLy

mph

ocyt

eCB

CH

GB

CBC

HCT

CBC

Eosin

ophi

lCB

CBa

nds

VitD

25O

HVi

tD1

25O

HPe

tWei

ght

Seru

mP

arat

horm

one

MEbrownMEred

MEblackMEblue

MEturquoiseMEgreen

MEyellowMEgrey








5 Conclusions




Abbreviations



Ethical Approval


Disclosure




Acknowledgments


References





































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of




















Table 1 Continued






Weight (gm) 948615 42158 3176872 130221 22119864 minus 16

DEXA fat (gm) 225042 14525 744906 42725 291119864 minus 16














0

5

10

15

20

25

30


Mea

n re

lativ

efre

quen

cy (

) + S

TD


lowast

lowast

lowast

lowastlowast





4 Discussion








PC 1 (175)

PC 2

(11

7)

6

4

2

0

minus2

minus4

minus6


BEA FOX T SCHNZR

LABSETSIBRottweiler

SmallOther

(a)

BEA FOX T SCHNZR

LABSETSIB

0 2 4PC 1 (222)

PC 2

(18

4)

SmallOther

2

1

0

minus2

minus2

minus1

minus3

(b)


10

09

08

07

06

05

04

Hei

ght

Module colors









Age

yea

rs

Seru

mU

reaN

itrog

enSe

rum

TSH

Seru

mT

rigly

cerid

esSe

rum

Tot

alP

rote

inSe

rum

Tot

alB

iliru

bin

Seru

mT

AS

Seru

mT

4Se

rum

T3

Seru

mS

odiu

mSe

rum

Pot

assiu

mSe

rum

Pho

spho

rus

Seru

mM

agne

sium

Seru

mL

DL

Cho

leste

rol

Seru

mL

DH

Seru

mIn

sulin

Seru

mIg

GSe

rum

IgE

Seru

mIg

ASe

rum

HD

LC

hole

stero

lSe

rum

Glu

cose

Seru

mG

lobu

linSe

rum

GG

TSe

rum

Cre

atin

ine

Seru

mC

ortis

olSe

rum

CK

Seru

mC

hole

stero

lSe

rum

Chl

orid

eSe

rum

Cal

cium

Seru

mA

STSe

rum

Apo

lipro

tein

ASe

rum

ALT

Seru

mA

lkal

ineP

hosp

hata

seSe

rum

Alb

umin

Plu

sD

EXA

Tot

alM

ass

DEX

AT

issue

Fat

DEX

AT

issue

DEX

AR

egio

nFa

tD

EXA

Lea

nD

EXA

Fat

DEX

AB

oneM

iner

alC

onte

ntD

EXA

Bon

eDen

sity

CBC

WBC

CBC

RBC

CBC

PLT

CBC

Neu

troph

il

CBC

MCV

CBC

MCH

CCB

CM

CHCB

CLy

mph

ocyt

eCB

CH

GB

CBC

HCT

CBC

Eosin

ophi

lCB

CBa

nds

VitD

25O

HVi

tD1

25O

HPe

tWei

ght

Seru

mP

arat

horm

one

MEbrownMEred

MEblackMEblue

MEturquoiseMEgreen

MEyellowMEgrey








5 Conclusions




Abbreviations



Ethical Approval


Disclosure




Acknowledgments


References





































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















Table 1 Continued






Weight (gm) 948615 42158 3176872 130221 22119864 minus 16

DEXA fat (gm) 225042 14525 744906 42725 291119864 minus 16














0

5

10

15

20

25

30


Mea

n re

lativ

efre

quen

cy (

) + S

TD


lowast

lowast

lowast

lowastlowast





4 Discussion








PC 1 (175)

PC 2

(11

7)

6

4

2

0

minus2

minus4

minus6


BEA FOX T SCHNZR

LABSETSIBRottweiler

SmallOther

(a)

BEA FOX T SCHNZR

LABSETSIB

0 2 4PC 1 (222)

PC 2

(18

4)

SmallOther

2

1

0

minus2

minus2

minus1

minus3

(b)


10

09

08

07

06

05

04

Hei

ght

Module colors









Age

yea

rs

Seru

mU

reaN

itrog

enSe

rum

TSH

Seru

mT

rigly

cerid

esSe

rum

Tot

alP

rote

inSe

rum

Tot

alB

iliru

bin

Seru

mT

AS

Seru

mT

4Se

rum

T3

Seru

mS

odiu

mSe

rum

Pot

assiu

mSe

rum

Pho

spho

rus

Seru

mM

agne

sium

Seru

mL

DL

Cho

leste

rol

Seru

mL

DH

Seru

mIn

sulin

Seru

mIg

GSe

rum

IgE

Seru

mIg

ASe

rum

HD

LC

hole

stero

lSe

rum

Glu

cose

Seru

mG

lobu

linSe

rum

GG

TSe

rum

Cre

atin

ine

Seru

mC

ortis

olSe

rum

CK

Seru

mC

hole

stero

lSe

rum

Chl

orid

eSe

rum

Cal

cium

Seru

mA

STSe

rum

Apo

lipro

tein

ASe

rum

ALT

Seru

mA

lkal

ineP

hosp

hata

seSe

rum

Alb

umin

Plu

sD

EXA

Tot

alM

ass

DEX

AT

issue

Fat

DEX

AT

issue

DEX

AR

egio

nFa

tD

EXA

Lea

nD

EXA

Fat

DEX

AB

oneM

iner

alC

onte

ntD

EXA

Bon

eDen

sity

CBC

WBC

CBC

RBC

CBC

PLT

CBC

Neu

troph

il

CBC

MCV

CBC

MCH

CCB

CM

CHCB

CLy

mph

ocyt

eCB

CH

GB

CBC

HCT

CBC

Eosin

ophi

lCB

CBa

nds

VitD

25O

HVi

tD1

25O

HPe

tWei

ght

Seru

mP

arat

horm

one

MEbrownMEred

MEblackMEblue

MEturquoiseMEgreen

MEyellowMEgrey








5 Conclusions




Abbreviations



Ethical Approval


Disclosure




Acknowledgments


References





































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of



















0

5

10

15

20

25

30


Mea

n re

lativ

efre

quen

cy (

) + S

TD


lowast

lowast

lowast

lowastlowast





4 Discussion








PC 1 (175)

PC 2

(11

7)

6

4

2

0

minus2

minus4

minus6


BEA FOX T SCHNZR

LABSETSIBRottweiler

SmallOther

(a)

BEA FOX T SCHNZR

LABSETSIB

0 2 4PC 1 (222)

PC 2

(18

4)

SmallOther

2

1

0

minus2

minus2

minus1

minus3

(b)


10

09

08

07

06

05

04

Hei

ght

Module colors









Age

yea

rs

Seru

mU

reaN

itrog

enSe

rum

TSH

Seru

mT

rigly

cerid

esSe

rum

Tot

alP

rote

inSe

rum

Tot

alB

iliru

bin

Seru

mT

AS

Seru

mT

4Se

rum

T3

Seru

mS

odiu

mSe

rum

Pot

assiu

mSe

rum

Pho

spho

rus

Seru

mM

agne

sium

Seru

mL

DL

Cho

leste

rol

Seru

mL

DH

Seru

mIn

sulin

Seru

mIg

GSe

rum

IgE

Seru

mIg

ASe

rum

HD

LC

hole

stero

lSe

rum

Glu

cose

Seru

mG

lobu

linSe

rum

GG

TSe

rum

Cre

atin

ine

Seru

mC

ortis

olSe

rum

CK

Seru

mC

hole

stero

lSe

rum

Chl

orid

eSe

rum

Cal

cium

Seru

mA

STSe

rum

Apo

lipro

tein

ASe

rum

ALT

Seru

mA

lkal

ineP

hosp

hata

seSe

rum

Alb

umin

Plu

sD

EXA

Tot

alM

ass

DEX

AT

issue

Fat

DEX

AT

issue

DEX

AR

egio

nFa

tD

EXA

Lea

nD

EXA

Fat

DEX

AB

oneM

iner

alC

onte

ntD

EXA

Bon

eDen

sity

CBC

WBC

CBC

RBC

CBC

PLT

CBC

Neu

troph

il

CBC

MCV

CBC

MCH

CCB

CM

CHCB

CLy

mph

ocyt

eCB

CH

GB

CBC

HCT

CBC

Eosin

ophi

lCB

CBa

nds

VitD

25O

HVi

tD1

25O

HPe

tWei

ght

Seru

mP

arat

horm

one

MEbrownMEred

MEblackMEblue

MEturquoiseMEgreen

MEyellowMEgrey








5 Conclusions




Abbreviations



Ethical Approval


Disclosure




Acknowledgments


References





































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















PC 1 (175)

PC 2

(11

7)

6

4

2

0

minus2

minus4

minus6


BEA FOX T SCHNZR

LABSETSIBRottweiler

SmallOther

(a)

BEA FOX T SCHNZR

LABSETSIB

0 2 4PC 1 (222)

PC 2

(18

4)

SmallOther

2

1

0

minus2

minus2

minus1

minus3

(b)


10

09

08

07

06

05

04

Hei

ght

Module colors









Age

yea

rs

Seru

mU

reaN

itrog

enSe

rum

TSH

Seru

mT

rigly

cerid

esSe

rum

Tot

alP

rote

inSe

rum

Tot

alB

iliru

bin

Seru

mT

AS

Seru

mT

4Se

rum

T3

Seru

mS

odiu

mSe

rum

Pot

assiu

mSe

rum

Pho

spho

rus

Seru

mM

agne

sium

Seru

mL

DL

Cho

leste

rol

Seru

mL

DH

Seru

mIn

sulin

Seru

mIg

GSe

rum

IgE

Seru

mIg

ASe

rum

HD

LC

hole

stero

lSe

rum

Glu

cose

Seru

mG

lobu

linSe

rum

GG

TSe

rum

Cre

atin

ine

Seru

mC

ortis

olSe

rum

CK

Seru

mC

hole

stero

lSe

rum

Chl

orid

eSe

rum

Cal

cium

Seru

mA

STSe

rum

Apo

lipro

tein

ASe

rum

ALT

Seru

mA

lkal

ineP

hosp

hata

seSe

rum

Alb

umin

Plu

sD

EXA

Tot

alM

ass

DEX

AT

issue

Fat

DEX

AT

issue

DEX

AR

egio

nFa

tD

EXA

Lea

nD

EXA

Fat

DEX

AB

oneM

iner

alC

onte

ntD

EXA

Bon

eDen

sity

CBC

WBC

CBC

RBC

CBC

PLT

CBC

Neu

troph

il

CBC

MCV

CBC

MCH

CCB

CM

CHCB

CLy

mph

ocyt

eCB

CH

GB

CBC

HCT

CBC

Eosin

ophi

lCB

CBa

nds

VitD

25O

HVi

tD1

25O

HPe

tWei

ght

Seru

mP

arat

horm

one

MEbrownMEred

MEblackMEblue

MEturquoiseMEgreen

MEyellowMEgrey








5 Conclusions




Abbreviations



Ethical Approval


Disclosure




Acknowledgments


References





































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of


















Age

yea

rs

Seru

mU

reaN

itrog

enSe

rum

TSH

Seru

mT

rigly

cerid

esSe

rum

Tot

alP

rote

inSe

rum

Tot

alB

iliru

bin

Seru

mT

AS

Seru

mT

4Se

rum

T3

Seru

mS

odiu

mSe

rum

Pot

assiu

mSe

rum

Pho

spho

rus

Seru

mM

agne

sium

Seru

mL

DL

Cho

leste

rol

Seru

mL

DH

Seru

mIn

sulin

Seru

mIg

GSe

rum

IgE

Seru

mIg

ASe

rum

HD

LC

hole

stero

lSe

rum

Glu

cose

Seru

mG

lobu

linSe

rum

GG

TSe

rum

Cre

atin

ine

Seru

mC

ortis

olSe

rum

CK

Seru

mC

hole

stero

lSe

rum

Chl

orid

eSe

rum

Cal

cium

Seru

mA

STSe

rum

Apo

lipro

tein

ASe

rum

ALT

Seru

mA

lkal

ineP

hosp

hata

seSe

rum

Alb

umin

Plu

sD

EXA

Tot

alM

ass

DEX

AT

issue

Fat

DEX

AT

issue

DEX

AR

egio

nFa

tD

EXA

Lea

nD

EXA

Fat

DEX

AB

oneM

iner

alC

onte

ntD

EXA

Bon

eDen

sity

CBC

WBC

CBC

RBC

CBC

PLT

CBC

Neu

troph

il

CBC

MCV

CBC

MCH

CCB

CM

CHCB

CLy

mph

ocyt

eCB

CH

GB

CBC

HCT

CBC

Eosin

ophi

lCB

CBa

nds

VitD

25O

HVi

tD1

25O

HPe

tWei

ght

Seru

mP

arat

horm

one

MEbrownMEred

MEblackMEblue

MEturquoiseMEgreen

MEyellowMEgrey








5 Conclusions




Abbreviations



Ethical Approval


Disclosure




Acknowledgments


References





































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of


















Abbreviations



Ethical Approval


Disclosure




Acknowledgments


References





































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
































































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of





















of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
















Documents

ResearchArticle Metabolic Differences between Dogs of ...downloads.hindawi.com/journals/jnme/2017/4535710.pdf · N-Formylmethionine 0.89 Aminoacid 0.029 1541 176.1 Bilirubin(E,E)