Abstract
Neutering is a significant risk factor for obesity in cats. The
mechanisms that promote neuter-associated weight gain are not well
understood but following neutering, acute changes in energy expenditure
and energy consumption have been observed. Metabolic profiling (GC-MS
and UHPLC-MS-MS) was used in a longitudinal study to identify changes
associated with age, sexual development and neutering in male cats fed
a nutritionally-complete dry diet to maintain an ideal body condition
score. At eight time points, between 19 and 52 weeks of age, fasted
blood samples were taken from kittens neutered at either 19 weeks of
age (Early Neuter (EN), n = 8) or at 31 weeks of age (Conventional
Neuter (CN), n = 7). Univariate and multivariate analyses were used to
compare plasma metabolites (n = 370) from EN and CN cats. Age was the
primary driver of variance in the plasma metabolome, including a
developmental change independent of neuter group between 19 and 21
weeks in lysolipids and fatty acid amides. Changes associated with
sexual development and its subsequent loss were also observed, with
differences at some time points observed between EN and CN cats for 45
metabolites (FDR p<0.05). Pathway Enrichment Analysis also identified
significant effects in 20 pathways, dominated by amino acid, sterol and
fatty acid metabolism. Most changes were interpretable within the
context of male sexual development, and changed following neutering in
the CN group. Felinine metabolism in CN cats was the most significantly
altered pathway, increasing during sexual development and decreasing
acutely following neutering. Felinine is a testosterone-regulated,
felid-specific glutathione derivative secreted in urine. Alterations in
tryptophan, histidine and tocopherol metabolism observed in
peripubertal cats may be to support physiological functions of
glutathione following diversion of S-amino acids for urinary felinine
secretion.
Introduction
Neutering is recommended for cats by veterinarians for population
welfare reasons as it reduces unwanted pregnancies, but it also has
benefits for the individual, including a reduction in the risk of
certain reproductive disorders and diseases [[34]1, [35]2] and unwanted
aggressive behaviours [[36]3]. However, these have to be balanced
against the management of some potentially undesirable consequences for
the individual as neutering is a significant risk factor for obesity,
which is itself associated with multiple health concerns (diabetes,
dyslipidemia and osteoarthritis) [[37]4, [38]5]. In cats, evidence
indicates that an acute post-neuter increased food intake in ad libitum
environments is a major driver of increased percentage body fat and
body weight that persist through life and may have health consequences.
Offering options to prevent weight gain associated with neutering
requires an understanding of the different factors that may underpin
the post-neuter dysregulation of self-regulated food intake. The
importance of such data to the welfare of cats is evident when
considering that the vast majority of cats (80–92%) in Europe and the
US over 6 months old are neutered [[39]6, [40]7].
The impact of neutering on weight is considered a consequence of two
factors, a reduction in energy expenditure and increased consumption
when fed ad libitum [[41]8–[42]15]. Adult cats can gain weight soon
after neutering when fed an amount to maintain a pre-neuter stable body
weight and it has been estimated that a reduction in intake of between
13–27% is required to maintain the pre-neuter body weight
[[43]8–[44]10]. Similarly, post-neuter changes in energy expenditure
have also been suggested in other species [[45]11]. Evidence also
exists that cats consume more if fed ad libitum [[46]12, [47]13].
Irrespective of whether energy consumption or expenditure is the major
driver of neuter-associated weight gain, weight gain is likely to be a
consequence of the disruption in the cat’s endocrine milieu. Peptides
regulating hunger and satiety feeding behaviours have been investigated
in cats [[48]10, [49]14, [50]15], but using different methods and in
cats of different ages, under different feeding regimens and sampled
over different time periods. As such, interpretation requires caution
and the regulatory role of these hunger and satiety-regulating hormones
in instigating any change in food intake/reduced energy expenditure has
yet to be fully elucidated.
Oestrogen is a major regulator of energy intake in cats, and injection
of estradiol (E2) following neutering is sufficient to prevent
increased food intake and weight gain in both males and females
[[51]16, [52]17]. Whilst loss of oestrogen-dependent energy regulation
may be the primary cause of energy imbalance following neutering in
females, neutering is also a predisposition for obesity in male cats
and the mechanism is less clear. If sex hormones are responsible for
changing energy regulation and intake behaviour, it is possible that
neutering before sexual development occurs would avoid this regulatory
dominance and subsequent acute response in the post-neuter phase.
Traditionally, cats are neutered around 6 to 7 months old [[53]18], but
early neutering (before or at 4 months old) is commonly performed in
the US for animal welfare population control [[54]19] and also appears
to be safe [[55]20]. However, some evidence indicate that regardless of
the age at which it is performed, neutering is a significant risk
factor for obesity [[56]14, [57]21, [58]22].
Many studies investigating the effect of neutering use adult cats and
allow ad libitum feeding. However, most cats are neutered whilst under
one year old and still growing. The current NRC feeding guidelines for
kittens (NRC 2006) are considered to be inappropriately high and
feeding to an ideal body condition score is recommended as a more
appropriate method of feeding kittens [[59]13]. The current study aimed
to establish the total energy requirements to maintain an ideal body
condition score during growth up to one year old in male kittens. The
impact of neutering was investigated and the study included a number of
physiological measures (such as intake, body weight, body composition,
spontaneous physical activity, clinical biochemistry). As kittens were
fed to maintain an ideal body condition score, the opportunity for
excessive weight and fat mass gain was reduced, which enabled factors
that may drive acute neuter-dependent changes to be assessed (for
example gut hormone, faecal microbiome and plasma metabolic profile
analysis). The metabolic profiling data analysis and interpretation for
male cats in that study is reported in detail here.
Materials and Methods
Animal maintenance and diets
The metabolic profiling study reported here refers to a cohort of 16
domestic short-haired male kittens (from 13 litters) recruited on to a
trial feeding a commercially available diet, that measured food intake,
body weight, body condition score, activity levels, hunger and satiety
hormones, faecal microbiome, diet digestibility and metabolic profiles
at different stages through to one year old. Kittens were housed in
purpose-built, environmentally-enriched housing at the WALTHAM Centre
for Pet Nutrition, and all housing, care and procedures were in keeping
with the requirements of the Animals (Scientific Procedures) Act 1986
and the study approved by WALTHAM’s Animal Welfare and Ethical Review
Body.
Kittens had free access to fresh water and were fed from a single batch
of a nutritionally complete [[60]23], commercial dry diet formulated to
support kittens through growth [Royal Canin Kitten, Aimargues, France]
for a minimum of 4 weeks before the first sample. Kittens were
individually fed to maintain an ideal body condition score (based on
the S.H.A.P.E.^™ 7-point scale [[61]24]) with weekly assessments to
determine whether any changes in intake were required.
Study design
Kittens were housed in a single social group and allocated to two
groups based on age when they were to be neutered, with only one litter
member represented in each group. Neutering was performed as part of
normal veterinary practice at WALTHAM and occurred at one of two time
points, defined as early (EN), at 19 weeks old and as conventional
(CN), at 31 weeks old, with 8 kittens in each respective group. One
kitten was removed from this study (CN group) as we were unable to
obtain a blood sample in accordance with our welfare policy.
Food intake (g) was measured daily and body weight (kg) and body
condition score (7-point scale) weekly. Spontaneous physical activity
levels were assessed (average count for 24 hour periods over three
consecutive days) using Actical devices (Philips Respironics) when cats
were 19, 25, 31, 37, 43 and 52 weeks old.
Blood sampling and peptide hormone analysis
Fasted (>16 hours) blood samples were collected from the jugular vein
on up to eight occasions (at 19, 21, 25, 31, 33, 37, 43 and 52 weeks
old, and prior to surgery in weeks 19 and 31). Blood (1ml) for
metabolite profiling was placed in chilled EDTA tubes, mixed by
inversion and incubated on ice (maximum 30 min) before centrifugation
(1,000g, 10 min and 4°C). Plasma samples (~0.5ml) were collected and
stored (-80°C) until transfer on dry ice to Metabolon Inc. (Durham, NC,
USA), where they were stored (-80°C) until analysis.
To measure peptide hormones (insulin, ghrelin, leptin and
Glucose-dependent Insulinotropic Peptide (GIP)), a Multispecies Gut
Hormone Milliplex assay validated for feline samples (Merck Millipore,
Watford, UK) was used according to the manufacturer’s protocol. Blood
(0.5ml), collected in chilled EDTA tubes containing a DPP-IV inhibitor
(5μl, cat# DPP4-010 Merck Millipore, Nottingham, UK) and protease
inhibitor cocktail (5μl, cat# P2714 Sigma, Poole, UK), was centrifuged
as above. Plasma was collected, snap frozen on dry ice and stored at
-80°C within 30 minutes of sampling until analysis. Assays, conducted
in duplicate, involved microspheres (with standards, controls and
samples (25μl)), incubated at 4°C under agitation in a 96-well
microtiter filter plate for 18hr. The plates were washed and detection
antibody was added for 30 min at room temperature,
streptavidin–phycoerythrin was then added for a further 30 min and,
after washing, signal was detected on the Luminex-200 Integrated System
(Luminex Corporation, Austin, TX, USA) according to manufacturer’s
protocol.
Metabolite profiling
Metabolite profiling was provided by Metabolon Inc. (Durham, NC, USA)
using Ultra High Performance Liquid chromatography/Mass
Spectrometry/Mass Spectrometry (UHPLC/MS/MS) and Gas chromatography/
Mass Spectrometry (GC/MS). Fractionation and derivisation of samples
and detection technologies have been reported previously
[[62]25–[63]27]. For quality assurance purposes, additional samples
were included with each day’s analysis. These randomly distributed
samples included extracts of a pool of well-characterized human plasma,
extracts of a pool created from a small aliquot of all plasma samples
(note that this also includes plasma samples from a total of 43
kittens, including females and not reported here), and process blanks.
Data extraction, metabolite identification and metabolite
quantification were undertaken using proprietary software.
Data set analysis and normalisation
To enable statistical analysis in samples where metabolites were not
detected, the minimum value of that metabolite that had been detected
was imputed. Prior to analysis, all data were log[10] transformed. Each
individual metabolite response ([64]S1 Table) was analysed by linear
mixed effects models (LMM) with neuter status, age and their
interaction as fixed effects and cat as a random effect. Models could
not be fitted to six metabolites (X-12763, sucrose, atenolol,
2-oxindole-3-acetate, 12-HEPE and 1,1-kestotetraose) which were
singular values (e.g. all 0) for male cats.
Planned contrasts were performed comparing the following: between
neuter status, at each age; between successive time points, for each
neuter status; between 19 weeks and other ages, for each neuter status
and between 31 weeks and ages >31 weeks, for the conventional neuter
status. The coefficients and variance-covariance matrix of each LMM
were used, along with a normal approximation to the degrees of freedom,
to calculate each comparison and their subsequent confidence intervals
and p-values using simultaneous inference [[65]28, [66]29]. The
Benjamini–Hochberg procedure [[67]30] was then used to adjust the
p-values for each contrast to maintain a 5% false discovery rate (FDR)
across the 364 metabolites identified.
To account for changes in intake relative to mass through growth,
energy intake (calculated as kcal/kgBW^0.67 [[68]23]) data were also
analysed by the same form of LMM as for the metabolites. Comparisons
between neuter groups at each week were performed using a family wise
error rate of 5%.
Statistical analyses were performed in R v 3.2.2 using the libraries
nlme for LMM, multcomp for simultaneous inference and padjust for FDR
adjustments. Means and fold changes are reported with 95% confidence
intervals (CI).
Principal component analysis (PCA) was performed using the R package
‘pcaMethods’ with single value decomposition [[69]31]. Data were
log[10]transformed and standardised prior to analysis. Ellipses were
added to the PCA scores plot using the R package ‘vegan’ to illustrate
95% confidence intervals [[70]32]. Correlation coefficient analysis was
performed for both neuter groups across all time points.
Pathway enrichment analysis
Permutation testing was then performed for each contrast to identify
pathways (designated by Metabolon Inc. proprietary software) containing
more significant metabolite changes than would be expected by chance.
The number of metabolites in each pathway and the subset with a
significant contrast were calculated. One thousand random subsets of
the number of significant metabolites were then taken (to represent
random significant metabolites) and the number found in each pathway
calculated. The probability of a pathway containing more significant
metabolite groups than would be expected by chance was calculated as
the percentage of subsets where the random number in each pathway was
greater or equal to the number of significant metabolites in each
pathway.
Results and Discussion
The impact of neutering and development on physiological parameters
No significant increase in mean average daily energy intake (measured
as kcal/kg body weight^0.67) was observed in male kittens neutered at
19 weeks compared to the CN group that remained entire to 31 weeks old.
However, a significant difference was observed between the two groups
in weeks 34–36 and weeks 38–41 (CN group being greater, up to 36kcal/kg
body weight^0.67 with 95% CI (9, 62), [71]S1 Fig). Epidemiological data
indicated that, irrespective of neuter age, neutering is associated
with increased food intake and propensity for weight gain. This study
showed no intrinsic effect of neutering on energy intake relative to
metabolic body weight in male cats. However, the increase in energy
intake relative to metabolic body weight (compared to the EN cats)
observed between weeks 3–10 post-procedure in CN cats is consistent
with other post-neuter responses observed in adult male cats [[72]15].
These data suggest that neutering males in the early stages of sexual
development may reduce acute feeding behaviour changes.
Neutering is unlikely to have altered energy expenditure through
changes in activity as spontaneous physical activity reduced by 25% for
both groups, with no significant effect of neuter group at any time
point. Peptide hormones (ghrelin, GIP, insulin and leptin)
concentrations did not differ significantly between groups at any time
point (data not shown), nor did faecal genera [[73]33]. Albeit from a
small cohort, these data suggest that when fed to maintain an ideal
body condition score, neutering males in the early stages of sexual
development has minimal impact across a spectrum of physiological
functions.
Age is the primary driver of variance in the male fasted plasma metabolome
Metabolic profiling detected 370 metabolites, of which 189 were
consistently detectable in all samples. To determine the main drivers
of variance in the plasma metabolome, multivariate analysis was
performed using Principal Component Analysis (PCA) ([74]Fig 1). Age was
the primary driver of variance in the first two principal components
(PC), though differences between neuter groups, observable at week 31,
indicated some effect of neutering. However, the groups converged
within twelve weeks of neutering the CN group, indicating that
neutering age had no persistent impact on the plasma metabolome.
Fig 1. Principal Component Analysis of metabolic profiles from males
indicating the impact of age on variance in the plasma metabolome.
[75]Fig 1
[76]Open in a new tab
PCA of plasma metabolome samples from males, labelled by neuter group
and age, indicate that age is the primary driver of variance between
samples. The PCA scores plot of metabolites (with 95% confidence
ellipses by neuter group at 19, 31 and 43 weeks) illustrates the
divergence between groups at week 31.
Univariate analysis of metabolites that changed (FDR corrected p<0.05)
between weeks 19 and 21 identified two groups of metabolites that
decreased in both groups and remained low over the course of the study,
indicative of a discrete developmental change ([77]Table 1, with
examples in [78]Fig 2). All 4 fatty acid (FA) amides and 13 of 16 acyl
glycerophosphocholines (acylGPCs) detected decreased in both groups
(p<0.001). In mice, gene expression analysis over the
pre-pubertal-to-early adult developmental phase identified changes
indicative of the switch from liver growth to specialised functions,
such as bile production [[79]34]. The decline in FA amides and acylGPCs
here may be due to a similar acute developmental switch and is
supported by previously reported differences in lipid metabolism
between kittens of 20 weeks and 32 weeks old [[80]35].
Table 1. Metabolite data used to support a discrete developmental change that
ended between 19 and 21 weeks old.
Early Neuter:Age21-Age19 Conventional Neuter:Age21-Age19
Metabolite Fold change Confidence interval (95%) FDR p-value Fold
change Confidence interval (95%) FDR p-value
Fatty Acid, Amide oleamide 0.31 (0.2,0.47) <0.0001 0.2 (0.12,0.31)
<0.0001
palmitic amide 0.17 (0.1,0.27) <0.0001 0.14 (0.08,0.24) <0.0001
stearamide 0.04 (0.02,0.1) <0.0001 0.06 (0.02,0.16) <0.0001
linoleamide (18.2n6) 0.25 (0.17,0.37) <0.0001 0.33 (0.21,0.51) <0.0001
Lysolipid 1-palmitoylglycerophosphocholine 0.36 (0.27,0.48) <0.0001
0.41 (0.3,0.55) <0.0001
2-palmitoylglycerophosphocholine [81]^* 0.56 (0.43,0.73) 0.0006 0.35
(0.26,0.46) <0.0001
1-heptadecanoylglycerophosphocholine 0.21 (0.11,0.38) <0.0001 0.11
(0.06,0.2) <0.0001
1-stearoylglycerophosphocholine 0.26 (0.18,0.37) <0.0001 0.27
(0.18,0.39) <0.0001
2-stearoylglycerophosphocholine [82]^* 0.3 (0.19,0.47) <0.0001 0.13
(0.08,0.21) <0.0001
1-oleoylglycerophosphocholine 0.39 (0.29,0.52) <0.0001 0.4 (0.3,0.55)
<0.0001
2-oleoylglycerophosphocholine [83]^* 0.35 (0.24,0.5) <0.0001 0.36
(0.25,0.53) <0.0001
1-linoleoylglycerophosphocholine 0.74 (0.62,0.88) 0.0106 0.64
(0.53,0.77) <0.0001
1-eicosadienoylglycerophosphocholine [84]^* 0.29 (0.17,0.48) <0.0001
0.19 (0.11,0.34) <0.0001
1-eicosatrienoylglycerophosphocholine [85]^* 0.4 (0.3,0.54) <0.0001
0.37 (0.27,0.5) <0.0001
1-arachidoylglycerophosphocholine 0.19 (0.11,0.33) <0.0001 0.21
(0.11,0.37) <0.0001
1-arachidonoylglycerophosphocholine [86]^* 0.76 (0.65,0.89) 0.0119 0.61
(0.52,0.72) <0.0001
[87]Open in a new tab
Metabolites that altered significantly (FDR corrected p<0.05) between
weeks 19 and 21 of age in both neuter groups with fold-change in means
with 95% Confidence Intervals. All metabolites belonged to two groups
of lipids, fatty acid amides and glycerophosphocholine lysolipids.
*Putative identification: no standard metabolite tested.
Fig 2. Examples of metabolites which decline between 19 and 21 weeks of age.
[88]Fig 2
[89]Open in a new tab
Changes in the average abundance of metabolites for which significant
changes were observed between 19 and 21 weeks of age in males in both
neuter groups, CN (red) and EN (black), all of which were present in
only 2 lipid metabolite subgroups (see [90]Table 2 for details). Scaled
intensity is relative to the normalised pool of all samples (error bars
represent 95% CI).
Neutering per se had little acute effect on the plasma metabolome
Neutering, at any age, is reported to be associated with an increased
risk of weight gain. To determine if neutering had a similar effect on
metabolism irrespective of age, the metabolic profiles were analysed
between the samples from the final pre-neuter time point and the first
post-neuter time point two weeks later. Only retinoate and
trans-4-hydroxyproline changed in both EN and CN cats (1.47- and 1.7-
fold increase and 0.77- and 0.67-fold change respectively), indicating
that any acute neuter-related changes were mostly resolved by two weeks
post-procedure or were dominated by factors related to the different
metabolic status of the groups prior to neutering.
Metabolic differences are associated with changes in male sexual development
Univariate analysis determined metabolites differing between groups at
each comparable time point ([91]Table 2). No significant differences
were observed between the groups at 19 weeks old, when both were
entire, nor at 21 weeks, indicating no acute detectable effect on the
metabolome 2 weeks post-neutering. Eight metabolites differed between
the groups at week 25, 33 at week 31 and 19 within 2 weeks of neutering
in the CN group. Only 2 metabolites were significantly different 12
weeks post-operation (week 43). These univariate analyses are
consistent with PCA and indicate that despite dynamic differences as a
consequence of sexual development in the CN cats, there is little
evidence to suggest the age when neutered (19 and 31 weeks old)
resulted in long-term effects on the plasma metabolome.
Table 2. Metabolites differing at some stage between neuter groups.
Ranking Subpathway Metabolite 19 Weeks 21 Weeks 25 weeks 31 weeks 33
weeks 37 weeks 43 weeks 52 weeks
1 Dipeptide felinylglycine [92]^* 0.92 1.68
[MATH: 3.52 :MATH]
[MATH: 8.08 :MATH]
[MATH: 4.56 :MATH]
[MATH: 2.31 :MATH]
1.42 1.11
2 Feline metabolism gamma-glutamylfelinylglycine [93]^* 0.91 1.47
[MATH: 2.94 :MATH]
[MATH: 7.24 :MATH]
[MATH: 4.04 :MATH]
[MATH: 2.1 :MATH]
1.4 1.06
3 Feline metabolism felinine [94]^* 0.84 1.35
[MATH: 2.1 :MATH]
[MATH: 4.48 :MATH]
[MATH: 2.89 :MATH]
1.78 1.35 0.97
4 Tryptophan metabolism[95]^a kynurenine 0.98 1.06
[MATH: 0.74 :MATH]
[MATH: 0.58 :MATH]
[MATH: 0.71 :MATH]
0.86 0.96 0.93
5 Fatty acid, dihydroxy 2-hydroxydecanoic acid 0.91 0.89
[MATH: 0.65 :MATH]
[MATH: 0.52 :MATH]
[MATH: 0.63 :MATH]
1.02 1.16 1.47
6 Feline metabolism N-acetylfelinine [96]^* 0.93 1.3 1.77
[MATH: 4.64 :MATH]
[MATH: 2.92 :MATH]
1.91 1.22 0.98
7 Endocannabinoid [97]^a N-stearoyl taurine 1.03 1.09 2.02
[MATH: 3.7 :MATH]
[MATH: 4.27 :MATH]
[MATH: 3.17 :MATH]
2.01 2.13
8 Tryptophan metabolism[98]^a tryptophan 1.08 1.12 0.97
[MATH: 0.74 :MATH]
0.85 0.94 1.05 1.03
9 Fatty acid, dicarboxylate[99]^a eicosanodioate 1.16 1.17 0.91
[MATH: 0.61 :MATH]
[MATH: 0.72 :MATH]
0.96 1.05 1
10 Lysolipid[100]^a 1-docosahexaenoylglycerophosphocholine[101]^* 1.05
0.78 0.78
[MATH: 0.59 :MATH]
0.83 0.96 0.95 1.14
11 Cysteine, methionine, SAM, taurine metabolism N-acetylmethionine 1
0.92 0.7
[MATH: 0.58 :MATH]
[MATH: 0.64 :MATH]
0.76 0.91 0.86
12 Pyrimidine metabolism, thymine containing thymidine 0.85 0.92 1.63
[MATH: 3.24 :MATH]
1.65 1.07 1.17 1.18
13 Tocopherol metabolism alpha-tocopherol 1.08 1.21 1.24
[MATH: 1.5 :MATH]
1.12 1.04 1.18 1.09
14 Sphingolipid palmitoyl sphingomyelin 1.08 1.31
[MATH: 1.43 :MATH]
[MATH: 1.49 :MATH]
0.95 0.95 1.06 1.02
15 Histidine metabolism histidine 0.98 0.93 0.89
[MATH: 0.83 :MATH]
0.97 0.96 0.99 1.04
16 Lysolipid[102]^a 1-palmitoylglycerophosphoethanolamine 0.95 0.89
0.66
[MATH: 0.59 :MATH]
[MATH: 0.67 :MATH]
1.13 1.03 0.76
17 Sterol cholesterol 1.09 1.29
[MATH: 1.33 :MATH]
[MATH: 1.37 :MATH]
1.01 1.04 1.13 1.08
18 Dipeptide derivative anserine 1.02 0.96 1.14
[MATH: 1.41 :MATH]
1.3 1.15 1.01 0.93
19 Lysolipid[103]^a 1-docosapentaenoylglycerophosphocholine[104]^* 1.32
0.79 0.79
[MATH: 0.56 :MATH]
0.96 0.96 1.24 1.09
20 Dipeptide derivative carnosine 0.95 0.89 0.86
[MATH: 0.77 :MATH]
1.06 1.01 0.96 0.89
21 Valine, leucine and isoleucine metabolism 2-methylbutyrylcarnitine
(C5) 0.97 1.11 0.86
[MATH: 0.62 :MATH]
0.81 0.98 1.08 1.11
22 Lysolipid[105]^a 1-oleoylglycerophosphoethanolamine 0.87 1.23 1.11
[MATH: 2.48 :MATH]
0.8 1.28 1.5 0.81
23 Alanine and aspartate metabolism N-acetylaspartate (NAA) 2.02 1.22
1.71
[MATH: 3.57 :MATH]
1.85 1.13 1.03 1.63
24 Chemical[106]^a 2-ethylhexanoate 1.03 1.53 1.57
[MATH: 1.87 :MATH]
0.91 1.26 1.14 1.1
25 Glycerolipid metabolism glycerophosphorylcholine (GPC) 1.02 1.14 1.1
[MATH: 1.36 :MATH]
0.93 0.92 1.05 0.89
26 Long chain fatty acid[107]^a cis-vaccenate (18:1n7) 1.02 1.18 1.21
[MATH: 1.44 :MATH]
1.09 1.06 1.22 1.21
27 Urea cycle; arginine-, proline-, metabolism[108]^a citrulline 1.04
1.07 0.77
[MATH: 0.66 :MATH]
0.78 0.92 0.88 1.05
28 Essential fatty acid[109]^a eicosapentaenoate (EPA; 20:5n3) 1.04
0.92 0.88
[MATH: 0.69 :MATH]
0.8 1.04 1.01 1.32
29 Pyrimidine metabolism, cytidine containing 5-methylcytidine 1 1.02
0.9
[MATH: 0.71 :MATH]
[MATH: 0.68 :MATH]
0.82 0.98 0.79
30 Benzoate metabolism[110]^a 2-aminobutyrate 1.11 1.06 0.95
[MATH: 0.73 :MATH]
0.83 1.06 1.11 0.82
31 Benzoate metabolism[111]^a 4-vinylphenol sulfate 0.62 0.83 1.13
[MATH: 2.2 :MATH]
0.85 0.67 0.9 1.02
32 Glutathione metabolism[112]^a 5-oxoproline 1.02 1.04 1.01
[MATH: 0.83 :MATH]
0.88 0.93 1.02 1.02
33 Tryptophan metabolism[113]^a indolepropionate 0.8 1.05 0.77
[MATH: 0.51 :MATH]
[MATH: 0.5 :MATH]
0.65 0.98 1.02
34 Essential fatty acid[114]^a docosahexaenoate (DHA) 22.6n3. 0.94 0.96
0.96 0.79
[MATH: 0.76 :MATH]
0.98 0.85 0.98
35 Fructose, mannose, galactose, starch, and sucrose metabolism[115]^a
mannose 1.04 1.18
[MATH: 1.39 :MATH]
1.24 1.01 1.13 1.14 1.07
36 Pyrimidine metabolism, cytidine containing 2'-deoxycytidine 1 0.99
1.02 0.84
[MATH: 0.74 :MATH]
0.83 0.99 0.94
37 Creatine metabolism creatine 1.27 1.25 1.23 1.58
[MATH: 2.45 :MATH]
1.54 1.55 1.3
38 Glycine, serine and threonine metabolism N-acetylthreonine 0.9 1.08
0.92 0.97 0.89 0.89 0.96
[MATH: 0.67 :MATH]
39 Glutathione metabolism[116]^a glutathione, oxidized (GSSG) 0.88 0.9
0.96 0.79
[MATH: 1.77 :MATH]
1.34 0.9 1.06
40 Fatty acid, monohydroxy 2-hydroxypalmitate 1.08 0.96 1.06 0.87
[MATH: 0.73 :MATH]
0.82 0.77 1.1
41 Urea cycle; arginine-, proline-, metabolism[117]^a
trans-4-hydroxyproline 0.91 1.13 1.02 1.07
[MATH: 0.67 :MATH]
0.82 0.88 0.78
42 Vitamin A metabolism retinoate 1.08 0.68 0.88 1.07
[MATH: 1.88 :MATH]
1.49 1.26 1.2
43 Food component/Plant thymol sulfate 1.05 1.19 1.07 0.95 0.87 1.08
[MATH: 1.59 :MATH]
1.13
44 Purine metabolism, adenine containing[118]^a N1-methyladenosine 1.07
1.07 0.88 0.89 0.92 0.89
[MATH: 1.36 :MATH]
0.92
45 Glycine, serine and threonine metabolism serine 1.05 1.14 1.21 0.97
0.76
[MATH: 0.68 :MATH]
0.89 0.94
[119]Open in a new tab
Fold-change values of the 45 named metabolites identified as
significantly different (FDR corrected p<0.05) at some stage between
the two neuter groups (highlighted in red, up in CN; highlighted in
green, down in CN). A further 16 unknown metabolites also met this
significance cut-off, with all differences between 25–37 weeks and 11
significantly different at week 31. The list is sorted by decreasing
significance values at week 31, the time point with the largest number
of significant differences.
Metabolites in bold belong to metabolic subpathways found to have more
significant metabolite groups than would be expected by chance between
the two neuter groups at some time point (see text).
^a indicates subpathways that contained more significant metabolites
than would be expected by chance within at least one of the neuter
groups between timepoints.
*Putative identification: no standard metabolite tested.
An objective was to detect changes in fasted plasma samples as a
consequence of neutering that may implicate a fundamental change in
metabolism responsible in initiating previously observed post-neuter
weight gain in cats [[120]8, [121]10, [122]13]. No substantial evidence
was found to suggest that neutering per se causes a change in metabolic
regulation. Instead, evidence indicated that the primary
differentiating driver was sexual development and changes subsequent to
neutering in the CN cats. For clarification, we refer to differences
between the EN and CN groups between 19 and 31 weeks old as associated
with sexual development, differences in CN post-neuter as associated
with consequences of sexual development (CN cats), whilst differences
consistent within both EN and CN groups over time were associated with
age/development.
To characterise the consequences of neutering following sexual
development, metabolites that changed in the CN group from 31 weeks old
and subsequent sampling points were identified ([123]S1 Table). Many of
the 85 metabolites were involved in similar areas of metabolism (39
metabolic pathways), with changes predominantly related to amino acid
and lipid metabolism. To gain a broader understanding of the pathways
that were most affected over time within and between groups, a Pathway
Set Enrichment analysis was undertaken ([124]Table 3). These results
are described below.
Table 3. Metabolic pathways that differ at some stage between or within
neuter groups.
Pathways that are over-represented with significant contrasts between
the two groups in at least one time point comparison at least one time
point within EN group at least one time point within CN group
Dipeptide Y Y
Feline metabolism Y Y
Tryptophan metabolism Y
Endocannabinoid Y
Fatty acid, dicarboxylate Y
Lysolipid Y Y
Dipeptide derivative Y Y Y
Chemical Y Y
Long chain fatty acid Y Y
Urea cycle; arginine-, proline-, metabolism Y Y
Essential fatty acid Y Y
Benzoate metabolism Y
Fatty acid, amide Y Y
Glutathione metabolism Y
Glycine, serine and threonine metabolism Y Y
Fatty acid, monohydroxy Y
Food component/Plant Y Y
Purine metabolism, adenine containing Y
Fatty acid metabolism[125]^a Y
Krebs cycle Y
[126]Open in a new tab
Twenty pathways were found to contain more significant metabolite
groups than would be expected by chance, for contrasts between groups
and within groups, ranked to be consistent with the metabolites in
[127]Table 2.
^aPathways for which no metabolite met the univariate significant
criterion used between the two neuter groups.
Felinine metabolism and associated metabolites
All detected metabolites of felinine metabolism were significantly
affected in CN cats (FDR corrected p<0.05) ([128]Table 2, ranking (R)
R2, R3 & R5), as was the dipeptide felinylglycine ([129]Table 2, R1).
These all increased in sexually maturing cats, and following neutering
they decreased, until similar to EN cats by 12 weeks post-neuter
([130]Fig 3a–3d, [131]Table 2).
Fig 3. Impact of development and neutering on felinine-associated
metabolites.
[132]Fig 3
[133]Open in a new tab
Changes in the average abundance of metabolites of the felinine pathway
and a related dipeptide in the two groups (CN (red) and EN (black)).
Scaled intensity is relative to the normalised pool of all samples
(error bars represent 95% confidence intervals). *Putative
identification: no standard metabolite tested. These four metabolites
were highly correlated (r>0.95) in the CN group of males cats.
Felinine is found predominantly in the urine of sexually mature male
cats, and may have a role in territorial marking and conspecific
recognition [[134]36]. Whilst there is some debate regarding the
synthesis pathway of felinine itself, it is likely that the felinine
precursor, γ-glutamylfelinylglycine (γ-GFG), derived from glutathione
and the cholesterol precursor isopentenyl pyrophosphate, is produced in
the liver [[135]37]. γ-GFG is believed to be absorbed in the kidneys,
where enzymatic activities involving γ-glutamyltransferases and
N-acetyl transferases result in felinine and N-acetyl felinine
synthesis [[136]36]. As felinine and N-acetyl felinine were not
detected in serum previously [[137]37], their identification in this
study may result from different methodologies and study design.
Urinary felinine is detected from 2.5–3 months of age and increases
with age, predominantly in entire male cats [[138]36]. Urinary felinine
is regulated by testosterone, with neutered male cats producing
approximately 3–5 fold less than entire males [[139]36] and increasing
urinary felinine in response to testosterone supplementation [[140]38].
Whilst testosterone was not assayed here, the felinine-related data
were consistent with previous reports where testosterone was detected
by 5 months of age and neutering resulted in a parallel fall in plasma
testosterone and urinary felinine [[141]38]. The similar profiles from
metabolites within the same pathway, interpretable with known
physiological changes in sexual development in the cat over a prolonged
period, provide confidence in interpretability of metabolite pools in
fasted plasma.
Tryptophan metabolism
Tryptophan ([142]Table 2, R8 & [143]Fig 4), and the tryptophan-related
metabolites kynurenine ([144]Table 2, R4 & [145]Fig 4) and
indolepropionate ([146]Table 2, R33) were lower in EN cats compared to
CN cats at week 31, (26% decrease with 95%CI (17%, 35%), 42% decrease
(33%, 50%) and 51% decrease (18%, 68%) respectively). Furthermore,
these and two other tryptophan-related metabolites (indoleacetate and
3-indoxyl sulfate) differed in CN cats between 31 and 43 weeks ([147]S1
Table). These are consistent with sexual development impacting
tryptophan metabolism and neutering reverting the effect. Changes in
tryptophan metabolism during human adolescence have been identified
[[148]39] and in kynurenine with castration in rats [[149]40]. The
reduced pools of both tryptophan and kynurenine may indicate that
synthesis of other tryptophan derivatives (such as serotonin or
melatonin) are required during male sexual development (see below).
Fig 4. Impact of development and neutering on tryptophan and sterol
metabolism.
[150]Fig 4
[151]Open in a new tab
Changes in the average abundance of sterol- and tryptophan-associated
metabolites with significant increases in CN compared to EN cats during
sexual development ((CN (red) and EN (black)). Scaled intensity is
relative to the normalised pool of all samples (error bars represent
95% CI).
Sterol metabolism
There is a positive association between total cholesterol and the
highest testosterone:estradiol ratio in male humans [[152]41] and
testosterone replacement also positively correlates with plasma
cholesterol [[153]42]. Consistent with cholesterol’s role as a
precursor for testosterone, total cholesterol ([154]Table 2, R17;
[155]Fig 4) increased significantly in CN cats during sexual
development (1.33 fold higher 95%CI (1.13, 1.57)) and declined rapidly
within 2 weeks of neutering, to a similar level in EN cats. Palmitoyl
sphingomyelin, a sphingolipid associated with cholesterol in human
blood metabolite profiling [[156]43], was also effected by neutering in
CN cats ([157]Table 2, R14; [158]Fig 4) with a similar profile to
cholesterol (1.49 fold higher, 95%CI (1.22, 1.81)). Sphingomyelins are
especially abundant in epididymosomes, the small membranous vesicles
secreted by epithelial cells within the luminal compartment of the
epididymis [[159]44]. Further research is required to determine any
specific role for palmitoyl sphingomyelin in male sexual
maturation/spermatogenesis in cats.
Histidine and related dipeptides
Histidine, and two histidine-containing dipeptides, carnosine
(β-alanyl-l-histidine) and anserine (β-alanyl-N-methylhistidine),
differed between CN and EN cats at 31 weeks ([160]Table 2, R15, R20 &
R18 respectively). Compared to EN cats, histidine and carnosine
decreased in CN cats during sexual development (17% lower, with 95%CI
(9%, 24%) and 23% lower, with 95%CI (11%, 33%) respectively) and
rapidly increased within 2 weeks post-neuter to a similar level as EN
cats ([161]Fig 5). Unlike these, the anserine pool increased during
sexual development (differing to EN cats by 1.41-fold, with 95% CI
(1.18, 1.69)) and remained relatively stable from 31 weeks of age.
These data are consistent with upregulation of anserine synthesis for a
sexual development-related requirement, with concomitant depleted pools
of histidine and carnosine and, following neutering, with loss of
sexual development-related anserine synthesis, resulting in carnosine
and histidine being regulated to levels observed in EN males. These
data are consistent with evidence of testosterone influencing muscle
carnosine in mice [[162]45, [163]46] and decreased muscle carnosine in
adulthood, including shortly after puberty in humans [[164]45]. As both
carnosine and anserine have anti-oxidant properties [[165]47], it is
possible that the dipeptide differences seen in sexually maturing cats
relate to a requirement for alternative anti-oxidants to compensate for
the supply of glutathione for felinine production and secretion.
Fig 5. Impact of development and neutering on histidine-associated
metabolites.
[166]Fig 5
[167]Open in a new tab
Changes in the average abundance of histidine and histidine-derived
muscle-associated amino acid derivatives. Both histidine and carnosine
decrease significantly in CN compared to EN cats during sexual
development and increase to levels similar to EN cats within 2 weeks of
neutering (CN (red) and EN (black)). Anserine, the final product
detected in this pathway increases significantly in CN cats during
sexual development and remains at a stable level, whilst EN cats show a
steady increase throughout development. Scaled intensity is relative to
the normalised pool of all samples (error bars represent 95% CI).
S-amino acid derivatives, glutathione and the synthesis of alternative
anti-oxidants during sexual development
The highly ranked metabolite N-acetylmethionine ([168]Table 2, R11;
[169]Fig 6) is a sulphur amino acid derivative and the inverse
relationship to felinine may be a consequence of partitioning sulphur
amino acids toward felinine production. Whilst there was no difference
in plasma glutathione (glutathione, oxidised GSSG, [170]Table 2, R39;
[171]S2 Fig) between the groups during sexual development, at 33 weeks
there was an acute increase in glutathione (1.77 fold higher, 95% CI
(1.26, 2.49)) in the CN group compared with the EN group (and a
1.66-fold increase compared to CN 2 weeks previously; 95% CI (1.2,
2.3)). We propose that the glutathione pool was being maintained during
sexual development, but with a greater flux driven toward felinine
synthesis, with a rapid increase post-neuter following loss of felinine
synthesis as glutathione synthesis outstripped demand.
Fig 6. Impact of development and neutering on S-amino acid-associated
metabolism.
[172]Fig 6
[173]Open in a new tab
Changes in the average abundance of metabolites associated with the
glutathione subpathway that differ significantly between neuter groups
(CN (red) and EN (black)). Scaled intensity is relative to the
normalised pool of all samples (error bars represent 95%CI).
Changes to other glutathione-related metabolites reflect the major
impact of felinine production on S-amino acid metabolism during sexual
development. 5-oxoproline ([174]Table 2, R32; [175]Fig 6), part of the
γ-glutamyl cycle that enables glutathione-dependent uptake of amino
acids into cells [[176]48], is released by erythrocytes [[177]49] and
changes in plasma pools reflect S amino acids and glycine availability
[[178]50]. 5-Oxoproline decreased during sexual development (down 17%,
95% CI (6%, 27%) in CN cats compared to EN cats at 31 weeks) and
increased following neutering (by 1.2-fold, 95% CI (1.11, 1.37) in week
43 compared to week 31 in CN, [179]S2 Table). The changes are
consistent with glutathione synthesis increasing during sexual
development to support felinine production and, after neutering, the
increased glutathione pool led to an increased pool of 5-oxoproline.
Furthermore, glycine ([180]S2 Table, R35; [181]S2 Fig), a substrate for
glutathione synthesis, decreased in CN cats during the acute
post-neuter period.
Other metabolites with changes associated with sexual development
Retinoic acid regulates over 500 genes [[182]51], drives spermatogonial
differentiation and the release of spermatids from the seminiferous
epithelium [[183]52]. Whilst there was no difference between the groups
during sexual development, an acute post-neuter increase in retinoate
(1.7-fold, 95% CI (1.34, 2.16) between weeks 31 and 33 in CN and
[184]Fig 7) led to a difference between groups in week 33 ([185]Table
2, R43). Similar to glutathione, this post-neuter increase suggests
that retinoate synthesis and use was elevated during sexual
development, and that post-neuter, an initial increase was observed
before regulatory feedback resulted in levels observed in EN cats.
Fig 7. Impact of neutering on other metabolites associating with sexual
development.
[186]Fig 7
[187]Open in a new tab
Changes in the average abundance of metabolites associated with sexual
development in male cats identified as significantly different between
EN and CN cats (CN (red) and EN (black)). Scaled intensity is relative
to the normalised pool of all samples (error bars represent 95%CI).
Metabolites showing similar profiles to felinine metabolite pools in
the CN group may be similarly regulated to support sexual development.
Thymidine ([188]Table 2, R12; [189]Fig 7) and N-acetylglycine ([190]S2
Fig, [191]S2 Table) were positively correlated with felinine
metabolites. As thymidine is required for DNA synthesis, the increase
may represent greater availability for DNA synthesis during
spermatogenesis. Other nucleotide derivatives were also statistically
different between neuter groups ([192]Table 2 R30; R37). There is no
report to our knowledge as to the possible role for N-acetylglycine in
sexual development but as a product of glycine N-acyltransferase
activity it may reflect an increased role for this phase II
detoxification enzyme during sexual development, when glutathione
production is supporting felinine synthesis. Furthermore, other
N-acetylamino acids differed significantly during sexual development
supporting the proposed increased NAT activity, regulated by
testosterone (examples in [193]S2 Fig, N-acetylaspartate ([194]Table 2,
R23); N-acetylyglycine ([195]S2 Table).
Testosterone enhances N-acetyl transferase (NAT) activity, upregulating
melatonin production in the Harderian gland of Syrian hamsters, with
castrated males having similar NAT activity to females and testosterone
implants in castrated males restoring NAT activty [[196]53]. Melatonin
is a highly effective antioxidant [[197]54] and also enhances the
rate-limiting step in glutathione synthesis, γ-glutamylcysteine
synthase [[198]55]. Recent evidence indicates that decreased levels of
melatonin and increased levels of advanced oxidation protein products
in seminal plasma are associated with human male infertility [[199]56].
The reductions in tryptophan and kynurenine observed here may be a
consequence of a testosterone-regulated increase in melatonin to
protect sperm viability, providing valuable anti-oxidant protection
whilst supporting glutathione production for felinine production.
Therefore, it is worth noting that anti-oxidant α-tocopherol
([200]Table 2, R14; [201]S2 Fig) also increased through sexual
development and declined rapidly following neutering. This may indicate
that α-tocopherol is raised to maintain plasma anti-oxidant function
whilst glutathione is directed toward felinine synthesis.
The endocannabinoid N-stearoyl taurine differed between EN and CN cats
from weeks 31 to 37 ([202]Table 2, R7, [203]Fig 7), increasing through
sexual development up to a 4-fold increase relative to EN cats in week
33. Unlike other metabolites that increased with sexual development,
N-stearoyl taurine declined slower and dropped between week 37 and 42
(fold change of 0.34, 95%CI (0.22, 0.53)). This may indicate a
secondary response to loss of sexual development. Little is known of
the physiological role of N-acyltaurines but it has been speculated
that they may function as endocrine-like signalling molecules
[[204]57].
Summary
Previously, we have characterised factors (such as breed, gender, the
individual, dietary supplementation and environment) that influence
metabolic profiles in both cats and dogs [[205]58–[206]62]. Here,
metabolic profiling has provided insights into the potential effect of
development, neutering and age at time of neutering on metabolism in
male kittens. Age was the major driver of variance in the plasma
metabolome, with particularly striking developmental effects between
weeks 19 and 21, when a significant proportion of FA amides and
acylGCPs decreased. To our knowledge such acute changes in these
metabolites with adolescence has not been reported. However, evidence
consistent with changes in liver functionality in late adolescence
exists and may indicate that in cats, liver maturation finishes between
19 and 21 weeks of age.
The objective was to investigate whether metabolic profiles changed due
to neuter-dependent changes in energy intake, using EN cats with CN
cats as a control group. Instead, the differences reflected sexual
development to 31 weeks of age. After neutering at 31 weeks it was
possible to compare the effect of age when neutered on metabolism.
Whilst a post-procedure change in energy intake was observed in CN
cats, the metabolome was dominated by changes that can be ascribed to
the consequences of neutering on S-amino acid utilisation rather than
energy metabolism, reflecting the dominance of sexual development and
its’ loss.
As understanding the effect of neutering, rather than sexual
development, had been the primary objective, testosterone assays were
not performed and the process of sexual development can only be
ascribed based on age and the known relationship between testosterone
and felinine metabolism. Many metabolites that changed with sexual
development were related to amino acid metabolism and can be
contextualised within a network to support anti-oxidant status. Our
interpretation of the data is that sexual development results in
felinine production, considered important in territorial marking.
Felinine production may not only have been selected due to the odorous
characteristics of its breakdown products, but may also communicate
“male mating quality/individual fitness value” through secretion of
such a valuable resource [[207]63]. S-amino acids are especially
important in the synthesis of glutathione anti-oxidant and taurine,
(the sole bile acid conjugate in cats), for which there is a dietary
requirement. It is likely that a strong selection pressure exists to
retain such an important class of compounds, so to secrete them as an
honest signal [[208]64] may require a compensation in metabolism
(alterations in anti-oxidants derived from tryptophan, histidine and
tocopherol metabolism) to secure sufficient functionality to maintain
cat health status. The physiological compromises to maintain S-amino
acid balance is supported by preliminary findings indicating that
entire males of long-haired cat breeds may have reduced urinary
felinine due to the increased requirement for cysteine in hair growth
[[209]65].
In summary, the major effect on the plasma metabolic profile was age.
The acute effect of neutering per se showed little consistent effect on
the plasma metabolome, whilst the impact of sexual development, and
subsequent loss following neutering did. Statistically significant data
were consistent with current understanding of male cat metabolism and
also provided insights into changes through adolescence in the presence
and absence of sexual development that may also be relevant to other
species.
Supporting Information
S1 Fig. Energy intake.
The weekly mean daily energy intake (kcal/kgBW^0.67) for each neuter
group, with means and 95% confidence intervals. Contrasts with
family-wise p-values < 0.05 are denoted by *.
(TIFF)
[210]Click here for additional data file.^ (134.6KB, tiff)
S2 Fig. Changes in the average abundance of metabolites associated with
anti-oxidant functions and N-acetyltranserase activity.
The two groups (CN (red) and EN (black)) are shown with scaled
intensity relative to the normalised pool of all samples (error bars
represent 95% CI).
(TIFF)
[211]Click here for additional data file.^ (247KB, tiff)
S1 Table. Individual metabolite data.
Dataset used for analysis.
(XLSX)
[212]Click here for additional data file.^ (400.3KB, xlsx)
S2 Table. Metabolites that differ post-neutering in CN cats.
Metabolites with fold-changes that were significantly different to the
31 week sample in subsequent weeks for CN. The table is ranked to be
consistent with the metabolites in [213]Table 2. ^aPathways for which
no metabolite met the univariate significant criterion used between the
two neuter groups at week 31.
(XLSX)
[214]Click here for additional data file.^ (22.2KB, xlsx)
Acknowledgments