Faecal Microbiota of Cats with Insulin-Treated Diabetes Mellitus

Microorganisms within the gastrointestinal tract significantly influence metabolic processes within their mammalian host, and recently several groups have sought to characterise the gastrointestinal microbiota of individuals affected by metabolic disease. Differences in the composition of the gastrointestinal microbiota have been reported in mouse models of type 2 diabetes mellitus, as well as in human patients. Diabetes mellitus in cats has many similarities to type 2 diabetes in humans. No studies of the gastrointestinal microbiota of diabetic cats have been previously published. The objectives of this study were to compare the composition of the faecal microbiota of diabetic and non-diabetic cats, and secondarily to determine if host signalment and dietary factors influence the composition of the faecal microbiota in cats. Faecal samples were collected from insulin-treated diabetic and non-diabetic cats, and Illumina sequencing of the 16S rRNA gene and quantitative PCR were performed on each sample. ANOSIM based on the unweighted UniFrac distance metric identified no difference in the composition of the faecal microbiota between diabetic and non-diabetic cats, and no significant differences in the proportions of dominant bacteria by phylum, class, order, family or genus as determined by 16S rRNA gene sequencing were identified between diabetic and non-diabetic cats. qPCR identified a decrease in Faecalibacterium spp. in cats aged over ten years. Cat breed or gender, dietary carbohydrate, protein or fat content, and dietary formulation (wet versus dry food) did not affect the composition of the faecal microbiota. In conclusion, the composition of the faecal microbiota was not altered by the presence of diabetes mellitus in cats. Additional studies that compare the functional products of the microbiota in diabetic and non-diabetic cats are warranted to further investigate the potential impact of the gastrointestinal microbiota on metabolic diseases such as diabetes mellitus in cats

Agreeing language in veterinary endocrinology (ALIVE): diabetes mellitus - a modified Delphi-method-based system to create consensus disease definitions

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Agreeing Language in Veterinary Endocrinology (ALIVE): Diabetes mellitus - a modified Delphi-method-based system to create consensus disease definitions

[No abstract

Options for monitoring diabetic cats

The key to successful long-term management of diabetes in cats is individualization of advice to suit cat and owner. A relationship based on trust and cooperation between veterinarian and client leads invariably to the most satisfactory outcome. Success requires knowledge of the options for monitoring diabetic cats, selection and adaptation of appropriate techniques for each individual case, and provision of ongoing support and guidance for owners. The ongoing treatment of a diabetic cat can be one of the more rewarding experiences of feline practice, and many diabetic cats and their owners come to occupy a special place within the clinic environment. This chapter provides a comprehensive overview of the current options for monitoring diabetes in cats and guidelines for application of the techniques to clinical cases

Evaluation of beta-cell sensitivity to glucose and first-phase insulin secretion in obese dogs

Objective—To compare beta-cell sensitivity to glucose, first-phase insulin secretion, and glucose tolerance between dogs with naturally occurring obesity of > 2 years’ duration and lean dogs. Animals—17 client-owned obese or lean dogs. Procedures—Frequently sampled IV glucose tolerance tests were performed with minimal model analysis on 6 obese dogs and matched controls. Glucagon stimulation tests were performed on 5 obese dogs and matched controls. Results—Obese dogs were half as sensitive to the effects of insulin as lean dogs. Plasma glucose concentrations after food withholding did not differ significantly between groups; plasma insulin concentrations were 3 to 4 times as great in obese as in lean dogs. Obese dogs had plasma insulin concentrations twice those of lean dogs after administration of glucose and 4 times as great after administration of glucagon. First-phase insulin secretion was greater in obese dogs. Conclusions and Clinical Relevance—Obese dogs compensated for obesity-induced insulin resistance by secreting more insulin. First-phase insulin secretion and beta-cell glucose sensitivity were not lost despite years of obesity-induced insulin resistance and compensatory hyperinsulinemia. These findings help explain why dogs, unlike cats and humans, have not been documented to develop type 2 diabetes mellitus

Use of a meal challenge test to estimate peak postprandial triglyceride concentrations in dogs

Objective - To develop a standardized meal challenge test by assessing associations between food-withheld preprandial (ie, fasting) and postprandial triglyceride concentrations, determining the most appropriate sampling time to detect the peak concentration (highest postprandial concentration), and estimating reference intervals for fasting and postprandial concentrations in healthy dogs. Animals - 12 lean healthy mixed-breed dogs. Procedures - Dogs were fed a dry commercially available diet (fat, 31% metabolizable energy) for 3 weeks. After food was withheld for 23 to 24 hours, plasma triglyceride concentrations were measured 1 and 0.083 hours before and 1, 2, 3, 4, 5, 6, 9, and 12 hours after feeding of a standardized challenge meal (median amount eaten, 63 kcal/kg [127 kcal/ kg]). Correlation and agreement between concentrations at peak and other time points were assessed by use of correlation coefficients and Bland-Altman limits of agreement. Reference intervals were calculated by use of a robust method. Results - Fasting and peak triglyceride concentrations were not closely associated. The highest concentration among samples obtained 2, 5, and 6 hours after meal consumption had closest agreement with peak concentration. In 5 of 12 dogs, concentrations 12 hours after eating were still significantly above baseline concentration (mean of each dog's fasting concentrations). Conclusions and Clinical Relevance - Fasting triglyceride concentration could not be used to accurately predict peak concentration. When estimating peak concentration, multiple samples should be collected 2, 5, and 6 hours after consumption of a standardized meal. Food may need to be withheld for > 12 hours when assessing fasting concentrations in healthy dogs

Evaluation of day-to-day variability of serial blood glucose concentration curves in diabetic dogs

Objective - To evaluate day-to-day variability of serial blood glucose concentration curves in dogs with diabetes mellitus. Design - Prospective clinical study. Animals - 10 dogs with diabetes mellitus. Procedure - Paired 12-hour serial blood glucose concentration curves performed during 2 consecutive days were obtained on 3 occasions from each dog. Dogs received the same dose of insulin and meal every 12 hours on both days. For each pair of curves, comparison was made between the results of days 1 and 2. Results - Mean absolute difference (without regard to sign) between days 1 and 2 for each parameter was significantly > 0, disproving the hypothesis that there is minimal day-to-day variability of serial blood glucose concentration curves when insulin dose and meals are kept constant. Coefficient of variation of the absolute difference between days 1 and 2 for each parameter ranged from 68 to 103%. Evaluation of the paired curves led to an opposite recommendation for adjustment of the insulin dose on day 2, compared with day 1, on 27% of occasions. Disparity between dosage recommendations was more pronounced when glucose concentration nadir was < 180 mg/dL (10 mmol/L) on 1 or both days. In this subset of 20 paired curves, an opposite recommendation for dosage adjustment was made on 40% of occasions. Conclusions and Clinical Relevance - There is large day-to-day variation in parameters of serial blood glucose concentration curves in diabetic dogs. Day-to-day variability of serial blood glucose concentration curves has important clinical implications, particularly in dogs with good glycemic control

Quality of life and response to treatment in cats with hypersomatotropism: the owners’ point of view

The aim of this study was to collect clinical information from owners of cats with hypersomatotropism (HS) distributed worldwide, assessing the impact of HS and its treatments on cats' quality of life (QoL) and survival time.Fil: Corsini, Andrea. Università di Parma; Italia. Universidad de Bologna; ItaliaFil: Niessen, Stijn J. M.. University of London. Royal Veterinary College; Reino UnidoFil: Miceli, Diego Daniel. Universidad de Buenos Aires. Facultad de Ciencias Veterinarias; ArgentinaFil: Caney, Sarah. Midlothian Innovation Centre; Reino UnidoFil: Zeugswetter, Florian K.. Veterinarmedizinische Universitat Wien; AustriaFil: Sieber Ruckstuhl, Nadja S.. Universitat Zurich; SuizaFil: Arenas, Carolina. Anicura Hospital Veterinario Valencia Sur; EspañaFil: Fleeman, Linda M. Animal Diabetes Australia; AustraliaFil: Leal, Rodolfo O. Universidade de Lisboa; Portugal. Universidade de Lisboa. Facultade de Medicina Veterinária; PortugalFil: Battellino, Martina. Universidad de Bologna; ItaliaFil: Fracassi, Federico. Universidad de Bologna; Itali

Quantitative PCR evaluation of the faecal microbiota in diabetic versus non-diabetic cats.

<p>Values are expressed as means ± standard deviation of the log amount of DNA (fg) per 10 ng of isolated total DNA. Differences in mean values between diabetic and non-diabetic cats were determined by 2-sided t-tests. P values <0.05 were considered significant.</p><p>Quantitative PCR evaluation of the faecal microbiota in diabetic versus non-diabetic cats.</p

Median percentage of bacterial orders identified in diabetic and non-diabetic cats.

<p>Median percentage of bacterial orders identified in diabetic and non-diabetic cats.</p