Received: 17 November 2022 Accepted: 5 July 2023 DOI: 10.1111/jvim.16813 STANDARD ARTICLE Association of serum and fecal microRNA profiles in cats with gastrointestinal cancer and chronic inflammatory enteropathy Louise Brogaard 1 | Janne G. Lyngby2 | Annemarie T. Kristensen2 | 1 2 3 Merete Fredholm | Charlotte R. Bjørnvad | Silke Salavati Schmitz | Ellen Skancke4 | Joanna S. Morris | Nana Dupont2 5 | David Argyle3 | 6,7 8 9 Armand Sánchez | Anette Spohr | Kasper Graarup-Hansen | Lise N. Nielsen2 | Susanna Cirera1 1 Department of Veterinary and Animal Sciences, University of Copenhagen, Frederiksberg, Denmark 2 Department of Veterinary Clinical Sciences, University of Copenhagen, Frederiksberg, Denmark 3 Hospital for Small Animals, Royal (Dick) School of Veterinary Studies, The Roslin Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Midlothian, UK 4 Department of Companion Animal Clinical Sciences, Norwegian University of the Life Sciences, Oslo, Norway 5 College of Medical, Veterinary, and Life Sciences, School of Veterinary Medicine, University of Glasgow, Glasgow, UK 6 Department of Animal Medicine and Surgery, School of Veterinary Sciences, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain 7 Centre for Research in Agricultural Genomics, The Spanish National Research Council (CSIC), Institute of Agrifood Research and Technology (IRTA), Autonomous University of Barcelona (UAB), and University of Barcelona (UB), Barcelona, Spain 8 Evidensia Faxe Animal Hospital, Faxe, Denmark 9 Evidensia Karlslunde Animal Hospital, Greve, Denmark Correspondence Janne G. Lyngby, Department of Veterinary Abstract Clinical Sciences, University of Copenhagen, Background: Differentiation of gastrointestinal cancer (GIC) from chronic inflamma- Dyrlægevej 16, 1870 Frederiksberg C, Denmark. tory enteropathies (CIE) in cats can be challenging and often requires extensive diag- Email: janne.lyngby@sund.ku.dk nostic testing. MicroRNAs (miRNAs) have promise as non-invasive biomarkers in Present address serum and feces for diagnosis of GIC. Louise Brogaard, Department of Hypothesis/Objectives: Cats with GIC will have serum and fecal miRNA profiles that Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark. differ significantly from healthy cats and cats with CIE. Identify serum and fecal miR- NAs with diagnostic potential for differentiation between cats with GIC and CIE as Funding information Teknologi og Produktion, Det Frie compared to healthy cats. Forskningsråd, Grant/Award Number: DFF- Animals: Ten healthy cats, 9 cats with CIE, and 10 cats with GIC; all client-owned. 6111-00124 Methods: Cats were recruited for an international multicenter observational prospec- tive case-control study. Serum and feces were screened using small RNA sequencing Abbreviations: %CV, coefficient of variance; ANOVA, analysis of variance; AUC, area under the curve; CE, chronic enteropathy; CI, confidence interval; CIE, chronic inflammatory enteropathy; CPM, counts per million; DLH, Domestic longhair; DSH, Domestic shorthair; FCEAI, feline chronic enteropathy activity index; FNCB, fine needle cytological biopsy; fPLI, feline pancreatic lipase immunoreactivity; GI, gastrointestinal; GIC, gastrointestinal cancer; IBD, inflammatory bowel disease; LCL, large-cell lymphoma; LR, likelihood ratio; miRNA, microRNA; noPAP, not containing poly(A) polymerase; SCL, small-cell lymphoma; small RNAseq, small RNA sequencing; TLI, trypsin-like immunoreactivity; tT4, Total T4; qPCR, quantitative real-time PCR; ROC, receiver operating characteristic; SAA, serum amyloid A; UCPH, University of Copenhagen; WSAVA, World Small Animal Veterinary Association. Louise Brogaard and Janne G. Lyngby have contributed equally as first authors. Lise N. Nielsen and Susanna Cirera have contributed equally as last authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. © 2023 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals LLC on behalf of American College of Veterinary Internal Medicine. 1738 wileyonlinelibrary.com/journal/jvim J Vet Intern Med. 2023;37:1738–1749. BROGAARD ET AL. 1739 for miRNAs that differed in abundance between cats with GIC and CIE, and healthy cats. Diagnostic biomarker potential of relevant miRNAs from small RNA sequencing and the literature was confirmed using reverse transcription quantitative real-time PCR (RT-qPCR). Results: Serum miR-223-3p was found to distinguish between cats with GIC and CIE with an area under the curve (AUC) of 0.9 (95% confidence interval [CI], 0.760-1.0), sensitivity of 90% (95% CI, 59.6-99.5%), and specificity of 77.8% (95% CI, 45.3-96.1%). Serum miR-223-3p likewise showed promise in differentiating a sub- group of cats with small cell lymphoma (SCL) from those with CIE. No fecal miRNAs could distinguish between cats with GIC and CIE. Conclusion and Clinical Importance: Serum miR-223-3p potentially may serve as a noninvasive diagnostic biomarker of GIC in cats, in addition to providing a much needed tool for the differentiation of CIE and SCL. KEYWORDS biomarker, CIE, lymphoma, miRNA, qPCR, small RNA sequencing 1 | I N T RO DU CT I O N and their ubiquitous involvement in cancer development and progres- sion.10,11 Likewise, several miRNAs are abundant in GIC and chronic Chronic inflammatory enteropathy (CIE) is increasingly common in enteropathies in dogs.12,13 MiRNAs already have been successfully cats, and is a diagnosis of exclusion based on clinical signs, diagnostics, measured in feces from healthy cats,14 but their potential as non- elimination of other gastrointestinal (GI) diseases, and GI histopathol- invasive diagnostic biomarkers in serum and feces for differentiation 1,2 ogy indicating inflammatory infiltration. The clinical signs of persis- between GIC and CIE in cats remains to be investigated. tent or recurring weight loss, dysrexia, vomiting, or diarrhea for To investigate serum and fecal miRNAs in cats as non-invasive ≥3 weeks duration are non-specific and do not differentiate between diagnostic biomarkers for the differentiation between GIC and CIE as CIE and gastrointestinal cancer (GIC).2 compared to healthy cats, we first aimed to use small RNA sequencing Gastrointestinal cancer accounts for up to 8% to 13.5% of tumors (small RNAseq) combined with known published data from the human in cats, and the most common location is the small intestine.3,4 Lym- and veterinary medical literature to identify relevant miRNAs. Sec- phoma is the most prevalent intestinal cancer, followed by adenocar- ondly, we aimed to establish these relevant miRNAs as a panel for cinoma and mast cell tumors.1,3,5-7 Abdominal ultrasound examination reverse transcription quantitative real-time PCR (RT-qPCR) to differ- and fine needle cytological biopsy (FNCB) are invaluable diagnostic entiate cats with GIC and CIE from healthy cats. We hypothesized tools, but only 68% of FNCB from GI lesions in cats and dogs were that serum and fecal miRNA profiles from cats with GIC would be sig- clinically useful, and 66% of useful cytological samples were in com- nificantly different from those of healthy cats and cats with CIE. plete agreement with histopathology.7 Hence, histopathology still may be required for a diagnosis, and additional diagnostic assessment such as immunohistochemistry or clonality testing can be necessary 2 | M A T E R I A L S A N D M ET H O D S to reach a final diagnosis and more accurately determine tumor immu- nophenotype and differentiate between CIE and GIC, because doing 2.1 | Study design and ethics approval 2,8,9 so can be challenging in individual cases. Diagnostic evaluation is expensive and potentially invasive, emphasizing the need for reliable This study was an international multicenter prospective observational non-invasive biomarkers to diagnose these conditions in order to initi- case-control study conducted from 2018 to 2020 at the University of ate specific treatments and improve patient quality of life and Copenhagen (UCPH). In addition to UCPH participating international survival. academic centers included: University of Edinburgh, Norwegian Uni- MicroRNAs (miRNAs) represent a promising array of non-invasive versity of Life Sciences, and University of Glasgow. Each institution diagnostic biomarkers in cats. They are small non-coding RNAs that obtained their own local ethical approval (#2017-9 + 2017-12; contribute to post-transcriptional regulation of gene expression by VERC#41.18; 14/04723-72; Ref 05a/18). The study was approved by binding to and repressing translation of their target messenger RNA the Animal Experiments Inspectorate under the Ministry of Food, transcripts. In humans, miRNAs have shown great potential as bio- Agriculture, and Fisheries of Denmark, Danish Veterinary and Food markers because of their stability and accessibility in serum and feces, Administration (case #2017-15-0201-01353). Owners provided 1740 BROGAARD ET AL. informed consent before enrollment. Cats with GIC and CIE were serum biochemistry, serum amyloid A (SAA) concentration, recruited at UCPH, the University of Edinburgh, the Norwegian Uni- FIV/FeLV testing, urinalysis, fecal flotation (Fecalyzer, Vetoquinol, versity of Life Sciences, University of Glasgow, or at Evidensia Karl- Lure, France), and Giardia/Cryptosporidium screening (Immunocard slunde Animal Hospital, Denmark, or Evidensia Faxe Animal Hospital, STAT! Crypto/Giardia, Meridian Bioscience, San Diego, CA). These Denmark. All healthy cats were recruited at UCPH. A study investigat- diagnostic tests could be performed by the study investigators, ing miRNA in feces and serum from dogs using the same methodology other veterinarians at the same referral hospital, or by a referring 12 has previously been published by this group. veterinarian. Serum cobalamin and folate concentrations were mea- sured at the clinician's discretion. Cats in the GIC and CIE groups had feline chronic enteropathy 2.2 | Cat recruitment activity index (FCEAI) score determined,16 and if endoscopy was per- formed, the final FCEAI was reported. Duration of disease was defined Client-owned cats were prospectively recruited into 1 of 3 groups: as the number of days from first clinical signs to the first visit for study GIC, CIE, and healthy cats (Figure 1). All cats included in the study participation, and was based on the history from the owner and medical were either directly seen by, or had their medical records evaluated records. In addition, cats in the GIC and CIE groups had abdominal by 1 board-certified internist (JGL) to assess their eligibility for final ultrasonography and endoscopy or laparotomy with biopsies for histo- enrollment into the study. logic assessment performed. A reference laboratory performed the his- For inclusion, cats in all 3 groups had to be ≥1 year of age topathological assessment, and inflammatory alterations were graded and > 2 kg in body weight. Cats in all 3 groups underwent routine using the World Small Animal Veterinary Association (WSAVA) standard- diagnostic evaluation including history, physical examination, fecal ization grading system.17,18 Clonality testing, immunohistochemistry, or 15 score based on the Purina 7-point fecal scoring system, CBC, both were performed at the clinician's discretion. In addition, cats in the GIC group required a histopathological diagnosis of GIC. For cats with a GIC diagnosis, full staging, including thoracic imaging and FNCB of regional lymph nodes, was encouraged. No specific exclusion criteria existed for the GIC group, and cats in this group were allowed to have co-morbidities and receive medica- tions and supplements. Cats in the CIE group were included if they had chronic GI signs, defined as persistent or recurrent vomiting, diarrhea, dys- rexia, or abdominal pain for ≥2-3 weeks, if other causes of GI signs had been systematically ruled out, and if they had a histopathologi- cal diagnosis of mucosal inflammation.2 For CIE cats only, to rule out other causes of enteropathy, additional diagnostic tests were performed at the clinician's discretion, based on current recommen- dations.2 These included ≥1 diet trials a minimum of 2 weeks in duration using a hydrolyzed or novel protein diet, serum total T4 (tT4) concentration, serum trypsin-like immunoreactivity (TLI), and serum feline pancreatic lipase immunoreactivity (fPLI). Cats with CIE were excluded if they had food-responsive enteropathy, antibiotic-responsive enteropathy, protein-losing enteropathy, or if they had received antimicrobials, corticosteroids, or other immuno- modulatory drugs within the previous 6 weeks, anthelmintics within F I G U R E 1 Cat recruitment and workflow. 25 cats (10 healthy, the previous 4 weeks, or nonsteroidal anti-inflammatory drugs 8 CIE cats, 7 GIC cats) were recruited prior to the initial small RNAseq within the previous 2 weeks. Cats in the CIE group were allowed screening was performed. Serum was included in small RNAseq from to have co-morbidities. all 25 cats, whereas feces was included in small RNAseq from 23 cats Healthy cats were included, if they were deemed healthy, without (feces not obtained from 1 CIE and 1 GIC cat). Following this, 1 additional CIE cat and 3 additional GIC cats were recruited for the any clinically relevant abnormalities on the above-mentioned diagnos- study for a total number of 29 cats (10 healthy, 9 CIE cats, and tic tests in addition to serum tT4 concentration. Cats were excluded 10 GIC cats). These additional cats were only included in the RT-qPCR from the healthy group if there was any known disease or suspicion analysis, not small RNAseq. Serum was obtained from all 29 cats. of disease. This determination was made based on history, physical Feces was obtained from 26 cats (1 CIE cat and 2 GIC cats did not examination, the diagnostic tests mentioned above, or episodes of GI supply feces); additionally, cDNA synthesis from fecal RNA from 2 of signs within 2 months of enrollment. In addition, healthy cats were the CIE cats was unsuccessful, leaving 6 CIE cats in the qPCR analysis of fecal miRNAs. CIE, chronic inflammatory enteropathy; GIC, excluded if they had received antimicrobials, corticosteroids, or other gastrointestinal cancer; Small RNAseq, small RNA sequencing. immunomodulatory drugs within the previous 6 weeks, anthelmintics BROGAARD ET AL. 1741 within the previous 4 weeks, or nonsteroidal anti-inflammatory drugs The qPCR was carried out using the high-throughput platform Bio- within the previous 2 weeks. mark HD (Fluidigm, San Francisco, California) and the 96.96 Dynamic Array integrated fluidic circuit chip format (Fluidigm, San Francisco, California). All details on RT-qPCR analysis can be found in File S1 and 2.3 | Sample collection in Table S1.12-14,19-47 Blood was collected at the first visit by the investigators of the study and processed within 30 min of sampling. Serum samples were ali- 2.7 | Data analyses quoted into 0.5 mL cryotubes and initially frozen at 20 C to mimic a standard household freezer available in most veterinary clinics. 2.7.1 | Clinical data Within 1 hour of defecation, fecal samples were collected and ali- quoted (approximately 1 g per aliquot) into cryotubes, which then were The data was analyzed using GraphPad Prism (version 9.3.1). Normal- frozen at 20 C. Clients were provided detailed written and verbal ity was assessed using the Shapiro–Wilk test. Numerical data was instruction and the necessary supplies for at-home fecal sample collec- expressed as median and range, or as number of animals and percent- 17,18 tion if feces were not collected while the cats were in the hospital. age. For continuous variables in general (eg, age, body weight) all All frozen serum and fecal samples were transferred from 20 C to 3 groups were compared using the Kruskal–Wallis test, and, if signifi- 80 C and kept at this temperature until batched RNA isolation. cantly different, a 2-stage linear step-up procedure of Benjamini, Krie- ger, and Yekutieli was applied to correct for multiple comparisons. When assessing disease-related continuous variables (eg, duration of 2.4 | RNA isolation disease, serum cobalamin, serum folate, serum SAA) a pair-wise com- parison between CIE and GIC using the Mann-Whitney test was used. The miRNeasy Mini Kit (Qiagen, Hilden, Germany) was used for isolation Fisher's exact or Chi-squared tests were used to compare categorical 14 of total RNA from 100 mg feces as described previously. Total RNA data. A P value <.05 was considered significant. was isolated from 200 μL serum using the miRNeasy Micro Kit (Qiagen, Hilden, Germany) without including the accompanying C. elegans miR- 39 spike-in extraction control. Concentration yield and purity of each 2.7.2 | Small RNAseq data RNA sample were assessed by measuring the 260 nm/280 nm and 260 nm/230 nm absorbance ratios on a NanoDrop ND-1000 Spectro- Open source bioinformatics tools were used for small RNAseq photometer (Thermo Scientific, Hvidovre, Denmark). The RNA was data analysis. All details can be found in File S1.48-54 stored at 80 C until batch analysis could be performed. 2.7.3 | qPCR data 2.5 | Small RNAseq screening Quality control and processing of qPCR data was carried out using the The NEBNext Small RNA Library Prep Set for Illumina (New England Fluidigm Real-Time PCR Analysis software (v.4.7.1, Fluidigm) and Biolabs, Ipswich, MA) was used for small RNAseq library preparation GenEx Pro software (v.7.1.1.118, MultiD Analyses AB), as described of fecal and serum samples using 6 μL total RNA from each sample. previously.12 One-way analysis of variance (ANOVA) was used to All samples obtained from cats that had been enrolled in the study up identify significant differences in serum and fecal miRNA amounts to this point were included in the small RNAseq screening. Library among GIC, CIE, and healthy cats, and among SCL, CIE, and healthy preparation and sequencing was carried out by a sequencing service cats (P < .05) using GraphPad Prism (v.9.2.0, GraphPad). For miRNAs provider (Genomics Unit, Center for Genomic Regulation, Barcelona with P < .05, the Tukey–Kramer post-hoc test was used for subse- Biomedical Research Park, Barcelona, Spain) using the Illumina HiSeq quent pairwise comparisons among the 3 groups. MiRNA fold changes 2500 system to produce 50 bp single-end reads. Small RNAseq raw were determined as the ratio of the average miRNA amounts in the data was supplied to the authors as fastq files. 2 groups being compared. The diagnostic performance of individual miRNAs in relation to discriminating between GIC and CIE cats was analyzed if a miRNA was present at significantly different amounts in 2.6 | RT-qPCR identification of miRNA biomarker GIC relative to CIE cats. The ability of miRNAs to discriminate candidates between GIC and CIE cats or GIC and healthy cats was evaluated using receiver operating characteristic (ROC) curve analysis in Graph- Samples from all cats included in the small RNAseq screening in addi- Pad Prism. Using the maximum value of Youden's index as cutoff, tion to 1 CIE cat and 3 additional GIC cats that were subsequently diagnostic performance of miRNAs was evaluated by computing sen- enrolled in the study (10 healthy, 9 CIE cats, and 10 GIC cats) were sitivity, specificity, and positive and negative likelihood ratios (LR used in RT-qPCR biomarker candidate identification (see Figure 1). +, LR ). 1742 BROGAARD ET AL. TABLE 1 Cat characteristics. Group characteristic Healthy CIE GIC P valueα Total number, n 10 9 10 Cat characteristics Age in months, median (range) 44 (19-133) 103 (44-149) 111 (34-202) <.05 Gender, n female/male 6/4 4/5 3/7 .40 a Body weight in kg, median (range) 4.7 (2.9-6.4) 5.5 (2.9-6.7) 4.46 (2.9-5.2) .16 Breeds, n DSH, 5 DSH, 5 DSH, 7 Birman, 3 NFC, 2 NFC, 1 DLH, 1 DLH, 1 Maine coon, 1 Rag doll, 1 Toyger cat, 1 Bengal cross, 1 Clinical parameters Disease duration in days, median (range) NA 180 (5–1080) 30 (0–540) .14 Clinical signs, n (%) NA -Vomiting NA 8/9 (89%) 4/10 (40%) .06 -Diarrhea NA 4/9 (44%) 4/10 (40%) >.99 -Weight loss NA 3/9 (33%) 7/10 (70%) .18 -Dysrexia NA 5/9 (56%) 7/10 (70%) .65 -GI bleeding NA 5/9 (56%) 5/10 (50%) >.99 Clinicopathological parameters Serum cobalamin concentration in pmol/L, median 879 (603-2283) 876 (111–1323) 267 (152–1226) .22 (range)a Serum folate concentration in nmol/L, median (range)a NA 39.3 (13.2–98.3) 28.3 (19.6-49.8) .03 a SAA concentration mg/L, median (range) 0 (0-0.2) 0.3 (0-126.7) 0.4 (0-104.9) .88 Note: “Cat characteristics” (ie, age, gender, and body weight) are compared between GIC, CIE, and healthy cats. Descriptive statistics are based on multiple comparisons for the “clinical parameters” (ie, duration of disease and clinical signs) and “clinicopathological parameters” (ie, serum cobalamin, serum folate, serum amyloid A), as the healthy cats are not included in the statistical comparisons even if median and range are listed. α, Significant difference between groups (P < .05) is indicated with boldface values. Abbreviations: CIE, chronic inflammatory enteropathy; DLH, Domestic longhair; DSH, Domestic shorthair; GI, gastrointestinal; GIC, gastrointestinal cancer; NFC, Norwegian forest cat; SAA, serum amyloid A. a Data missing on 1 cat. 3 | RESULTS cobalamin concentrations <250 pmol/L and 5/9 GIC cats had serum cobalamin concentrations <400 pmol/L. Hypofolatemia was seen in 3.1 | Cat characteristics 4/9 cats defined as serum folate concentration < 25.2 nmol/L and 1 cat had hyperfolatemia defined as serum folate concentration Twenty-nine cats were enrolled from 2018 to 2020. Cat characteris- > 49.0 nmol/L. All cats but 1 (9/10) had known FIV/FeLV status and tics are presented in Table 1. were all negative. Ten cats were included in the GIC group. Four of these cats had Abdominal ultrasound examination was performed in 9/10 GIC received medical treatment when sampled for the study. The treat- cats. Four cats had a focal mass (2 jejunal, 1 colon, and 1 localized to a ments included meloxicam (n = 1), cannabidiol drops (n = 1), chloram- non-specified small intestinal segment). Two cats had diffuse gastric bucil and prednisolone (n = 1), and metronidazole and robenacoxib wall thickening with loss of normal wall layering, and 2 cats had dif- (n = 1). Two cats had odontoclastic resorptive lesions, 1 cat had a his- fuse small intestinal wall thickening of the mucosa and muscularis tory of giardiasis, and 1 cat had a history of focal seizures- and facial layers. One cat had hyperechoic mucosal stippling in the jejunum, but twitching. Weight loss and dysrexia were the most prevalent clinical no other findings were noted in the GI tract. signs, seen in 70% of cats. Median duration of disease was 30 days One cat had thoracic radiographs performed with no evidence of (range 0-540 days). metastases. Six GIC cats had endoscopic biopsies performed, and the All but 1 GIC cat (9/10) had serum cobalamin and folate concen- remaining 4 cats had full thickness biopsies performed at laparotomy. trations measured. The median serum cobalamin concentration was In the 6 cats that had endoscopic biopsies, the median FCEAI score 267 pmol/L (range, 152-1226 pmol/L). Four of 9 GIC cats had serum was 8.5 (range, 0-14). Eight cats were diagnosed with lymphoma, BROGAARD ET AL. 1743 including SCL (n = 4), high grade small-intermediate cell lymphoma duration of disease, clinical signs, serum cobalamin concentration, and (n = 1), and large-cell lymphoma (LCL; n = 3). Two LCL were B-cell, serum SAA concentration were found among groups (Table 1). transmural, and located in the stomach or jejunum, respectively. The third LCL was transmural, located in the small intestine, and was CD20, PAX5, CD3, and c-KIT negative on immunohistochemistry, but was 3.2 | RNA isolation consistent with T-cell lymphoma on clonality testing. The small to inter- mediate T-cell lymphoma was a transmural solitary lesion originating Total RNA was isolated from cat feces and serum for use in small from the jejunum. Of the cats with mucosal SCL, 3 were of T-cell, and RNAseq and RT-qPCR. For serum, RNA was obtained from 29 samples 1 of B-cell origin. Lastly, 2 cats had a colonic papillary adenocarcinoma (healthy, n = 10; CIE, n = 9; GIC, n = 10). For feces, RNA was and rectal carcinoma with sebaceous differentiation, respectively. obtained from 26 samples (healthy, n = 10; CIE, n = 8; GIC, n = 8). Disease involvement elsewhere or metastases were not cytologi- See also Figure 1. Results on RNA concentration and purity are sum- cally or histologically confirmed in any cat. However, 1 cat with marized in Table 2. All samples were considered to be of acceptable colonic adenocarcinoma had local lymphadenopathy visualized on quality for inclusion in further analysis. ultrasound examination and during laparotomy, and the tumor was transmural and expanded into the abdomen. Nine cats with CIE were enrolled. Two of these cats had a 3.3 | Small RNAseq screening of cat serum concurrent cardiac murmur, 3 had a dermatological problem with and feces pruritus, alopecia or both and 1 cat had a history of spontaneous pneumothorax. All 9 cats had clinical signs of enteritis alone or in 3.3.1 | Serum combination with gastritis or colitis. Median duration of disease was 180 days (range, 5-1080 days). The most prevalent clinical Small RNAseq was performed on 25 serum samples (healthy, signs were vomiting (89%) and dysrexia (56%). Serum tT4 concen- n = 10; CIE, n = 8; GIC, n = 7; Figure 1). Small RNAseq of serum trations were normal or low in all CIE cats, and all cats were FIV/ yielded an average of 9.7 M reads per sample. For serum samples, FeLV negative. Serum TLI was assessed in 8/9 cats and was nor- 99.2% of reads passed quality control and adapter trimming and, mal in 4 and above normal in 4. Serum feline pancreatic lipase of these, 63.8% of reads mapped to the F. catus genome. Of the concentration was assessed in 8/9, being normal in 4, between mapped reads in serum, 2.2% mapped to known or novel cat 3.6-5.3 μg/L in 2, and > 5.4 μg/L in 1 cat. Serum folate and cobala- miRNA sequences. Serum miRNA abundance is summarized in min concentrations were assessed in all 9 CIE cats. The median Figure 2A. Comparison of average serum miRNA amounts showed serum cobalamin concentration was 876 pmol/L (range, that miR-1224, miR-320a-3p, and miR-296-3p were present in sig- 111-1323 pmol/L), and 3/9 CIE cats had serum cobalamin concen- nificantly lower amounts in GIC cats compared to CIE cats, miR- trations <250 pmol/L or <400 pmol/L. The median serum folate 27a-5p was present in significantly higher amounts in GIC cats concentration was 39.3 nmol/L (range, 13.2-98.3 nmol/L), and compared to healthy cats, and miR-320a-3p was present in signifi- hypofolatemia, defined as serum folate concentration < 25.2 nmol/ cantly lower amounts in CIE cats compared to healthy cats after L, was seen in 1/9 cats. Hyperfolatemia, defined as a serum folate correcting for multiple testing (Table S2 and Figure S1). Details on concentration > 49.0 nmol/L, was seen in 2/9 cats. small RNAseq results can be found in Tables S3 and S4. MiRDeep2 All 9 CIE cats had endoscopic biopsies performed, but 2 did not identified several putative novel cat miRNAs in the small RNAseq have ileal biopsy specimens obtained because of anesthetic complica- data. These putative novel miRNAs were included in DESeq2 anal- tions (n = 1) and difficulty passing the endoscope beyond the ileocolic ysis (Table S2) and are further summarized in Table S5. valve (n = 1). The median FCEAI score was 8 (range, 4-13). Histopath- ologic diagnoses in this group were mild-moderate or moderate lym- phoplasmacytic enteritis (n = 5), mild-moderate or moderate 3.3.2 | Feces lymphocytic and eosinophilic enterocolitis (n = 2), and mild or mild- moderate lymphocytic enterocolitis (n = 2). Small RNAseq was performed on 23 fecal samples (healthy, n = 10; Ten healthy cats were enrolled. No clinically relevant abnormali- CIE, n = 7; GIC, n = 6; Figure 1). Small RNAseq of feces yielded an ties were noted on any of the diagnostic tests, including urinalysis, average of 10.9 M reads per sample. For fecal samples, 99.6% of reads fecal testing, FIV/FeLV testing, tT4, and serum cobalamin concentra- passed quality control and adapter trimming and, of these, 18.7% of tion. Serum folate concentrations were measured in 3 cats, but were reads mapped to the F. catus genome. Of the mapped reads in feces, within the normal reference range in these cats. 0.07% mapped to known or novel cat miRNA sequences. Fecal Significant differences in age among all 3 groups were found and miRNA abundance is summarized in Figure 2B. When comparing aver- remained significant between healthy cats and cats with GIC on post- age fecal miRNA amounts in the 3 groups of cats, statistical analyses hoc analysis with GIC cats being older (P = .02). Cats with GIC had showed that no miRNAs were present in statistically significant significantly lower serum folate concentrations compared to those amounts in any comparisons (ie, GIC vs. CIE cats, GIC vs. healthy cats, with CIE (P = .03), but no significant differences in sex, body weight, or CIE vs. healthy cats) when correcting for multiple testing (Table S2 1744 BROGAARD ET AL. TABLE 2 RNA isolation: Median and Group RNA concentration (ng/μl) A260/280 ratio A260/230 ratio range. Serum Healthy cats 11.9 (7.1-37.6) 1.3 (1.1-1.4) 0.37 (.10–.62) CIE cats 13.1 (8.2-35.7) 1.3 (.95-1.5) 0.22 (.08–.42) GIC cats 11.2 (6.2-22.4) 1.3 (1.1–1-5) 0.23 (.10–.39) All cats 12.0 (6.2-37.6) 1.3 (.95–1.5) 0.29 (.08–.62) Feces Healthy cats 249.6 (66.0-398.8) 2.0 (1.8-2.1) 1.6 (.45-1.9) CIE cats 152.0 (56.3-791.0) 1.9 (1.4-2.0) 0.78 (.30-2.0) GIC cats 344.5 (162.6-1069.4) 2.0 (1.8–2.1) 1.5 (.53-2.1) All cats 258.2 (56.3-1069.4) 2.0 (1.2-2-1) 1.5 (.30-2.1) F I G U R E 3 Relative expression levels of miR-197-3p, miR-223-3p, and miR-320a-3p in healthy cats, cats with CIE, and cats with GIC. P values from Tukey's post-hoc test. Boxes extend from 25th to 75th percentile; whiskers extend to minimum and maximum values; horizontal red lines indicate median value. For the GIC groups, white triangles highlight the 4 cats diagnosed with SCL. (Table S6). Of these, let-7f-5p, let-7i-5p, and miR-21-5p were found suitable for data normalization based on evaluation using NormFinder55 F I G U R E 2 (A) The most abundant of the detected miRNAs in cat and geNorm.56 A significant difference was found for 3 miRNAs in serum were miR-486-5p, miR-320a-3p, miR-92a-3p, miR-423-5p, and miR-191–5p, accounting for a total of 59.4% of all miRNA reads. 1-way ANOVA (miR-223-3p, miR-197-3p, and miR-320a-3p) among (B) The most abundant of the detected miRNAs in cat feces were the 3 groups of cats (Figure 3 and Table 3). Of these, only miR-223-3p miR-21-5p, miR-378-3p, miR-194-5p, miR-192-5p, and miR-215-5p, was present in significantly different quantities in GIC and CIE cats by accounting for a total of 57.2% of all miRNA reads. Tukey-Kramer's post hoc test (Figure 3 and Table 3), and miR-223-3p likewise was present in significantly higher quantities in GIC compared and Figure S1). Details on fecal small RNAseq results and putative to healthy cats. No difference however was found for miR-223-3p novel cat miRNAs can be found in Tables S3–S5. between CIE and healthy cats. MiR-197-3p was significantly different between GIC and healthy cats, and miR-320a-3p was significantly dif- ferent between CIE and healthy cats, but neither were significantly dif- 3.4 | qPCR identification of cat miRNA biomarkers ferent between GIC and CIE cats (Figure 3 and Table 3). that differentiate GIC from CIE 3.4.1 | Serum 3.4.2 | Feces Forty-seven of the 91 assayed miRNAs (representing 52 of the Twenty-three of the 91 assayed miRNAs (representing 26 of the 96 included primer pairs) were quantifiable by qPCR in cat serum 96 included primer pairs) were quantifiable by qPCR in cat feces BROGAARD ET AL. 1745 TABLE 3 qPCR identification of serum miRNA biomarker candidates for differentiation between cats with GIC and CIE, and cats with SCL and CIE. Comparisons RNAseq-qPCR All GIC vs. CIE All GIC vs. healthy CIE vs. healthy correlation miRNA Pa FC (±95%CI) Pb FC (±95%CI) Pb FC (±95%CI) Pb (Pearson's r) Serum miR-223-3p .002 3.2 (±1.3) .002 2.4 (±1.0) .02 .76 (±.39) .57 NA miR-197-3p .02 1.5 (±.34) .15 1.7 (±.24) .02 1.2 (±1.6) .62 r = .42, P = .05 miR-320a-3p .04 .50 (±.19) .17 .95 (±.36) .74 1.9 (±.83) .04 r = .44, P = .03 Feces None SCL vs. CIE SCL vs. healthy CIE vs. healthy Serum miR-223-3p .008 3.9 (±1.6) .006 3.0 (±1.3) .03 .76 (±.39) .58 NA miR-320a-3p .04 .34 (±.11) .13 .65 (±.21) .98 1.9 (±.83) .06 r = .45, P = .04 Feces miR-148b-3p .03 .36 (±.34) .02 .45 (±.43) .05 1.23 (±.31) .72 r = .39, P = .14 Note: CI, confidence interval, NA, not available—miR-223-3p not quantified with small RNAseq. a One-way ANOVA. b Tukey-Kramer's post hoc test. Statistically significant changes are highlighted with bold font. 3.5 | Diagnostic performance of serum miR- 223-3p for differentiation of GIC from CIE or healthy cats The ROC curve analysis was carried out for miR-223-3p to evaluate its diagnostic potential in serum. For the differentiation between GIC and CIE, this analysis yielded an AUC of 0.90 (95% CI, 0.76-1.0; Fig- ure 4). Using the maximum value of Youden's index, sensitivity and specificity were determined to be 90.0% (95% CI, 59.6-99.5%) and 77.8% (95% CI, 45.3-96.1%), respectively. Positive likelihood ratio was found to be 4.1 (95% CI, 1.2-14.0) and LR- was found to be 0.13 (95% CI, 0.019-0.85). For differentiation between GIC and healthy cats, this analysis yielded an AUC of 0.87 (95% CI, 0.693-1.0), sensi- tivity of 90.0% (95% CI, 59.6-99.5%), specificity of 90.0% (95% CI, 59.6-99.5%), LR+ of 9.0 (95% CI, 1.4-58.4), and LR- of 0.11 (95% F I G U R E 4 ROC curve for miR-223-3p for distinguishing all GIC CI, 0.017-0.72; Figure S2). from CIE cats. AUC, area under the curve; FPR, false positive rate; LR, likelihood ratio; Sn, sensitivity; Sp, specificity; TPR, true positive rate. 95% Cis, AUC 0.760-1.0; Sn, 59.6%-99.5%; Sp, 45.3%-96.1%; LR+, 1.2-14.0; LR , 0.019-0.85. 3.6 | qPCR identification of cat miRNA biomarkers that differentiate SCL from CIE (Table S6). Of these, let-7a-5p and miR-192-5p were found suitable 3.6.1 | Serum for data normalization based on evaluation using NormFinder55 and geNorm.56 The qPCR results showed that cDNA synthesis from 2 fecal All quantified miRNAs were evaluated for their ability to distinguish RNA samples (both CIE) had been unsuccessful, and these had to be among SCL, CIE, and healthy cats. In 1-way ANOVA, significant taken out of the analysis, leaving 6 CIE cats for the remaining analysis. difference among these 3 groups was seen for miR-223-3p and miR- Statistical analysis showed no significant differences in fecal miRNA 320a-3p (Figure 5 and Table 3), but significant differences in Tukey- amounts among the 3 groups of cats for any of the quantified miRNAs Kramer's post-hoc test were only seen for miR-223-3p between SCL (1-way ANOVA), and therefore no further investigation of fecal and CIE cats, as well as between SCL and healthy cats. No investiga- miRNA biomarker potential was conducted. tion of diagnostic performance of miR-223-3p in relation to 1746 BROGAARD ET AL. between SCL and CIE or healthy cats was made because of the low sample size for feces from SCL cats (n = 3). 4 | DI SCU SSION Our study is the first to examine serum and fecal miRNAs as potential biomarker candidates for the differentiation of GIC, CIE, and healthy cats. Although fecal miRNAs could not differentiate these conditions in our study groups, serum miR-223-3p was present in significantly different quantities and was able to distinguish GIC from CIE as well as healthy cats with high sensitivity and specificity. These findings lay the potential foundation for the development of a novel assay in cats for detection and differentiation of GIC from both CIE and F I G U R E 5 Serum quantities of miR-223-3p and miR-320a-3p in healthy cats. cats with SCL and CIE and healthy cats. Horizontal red lines represent In cats, serum amounts of miR-223-3p were significantly higher in median values. P value from Tukey–Kramer post hoc test after one- GIC relative to CIE cats. In this context, it is relevant to note that way ANOVA. when comparing only SCL and CIE cats, serum amounts of miR- 223-3p still were high in SCL cats, suggesting that miR-223-3p might have the potential to differentiate these conditions. In our study, serum miR-223-3p could distinguish between cats with GIC and CIE with an AUC of 0.90 (95% CI, 0.760-1.0). A previous study reported similar performance with an AUC of 0.92 for this miRNA in feces for differentiating between GIC and CIE dogs.12 MiR-223-3p was included in our study because it was previously found to be a poten- tial fecal biomarker candidate for differentiation between GIC and CIE in dogs.12 Another study determined miR-223-3p to be present in lower amounts in serum and colonic mucosa of dogs with CIE com- pared to healthy dogs,13 supporting the notion of it as a marker of only GIC in dogs and cats. In our study, miR-223-3p serum amounts were slightly lower in cats with CIE compared with healthy cats, but this difference was not significant. Diagnostic performance of miR- 223-3p in GI disease in humans has been evaluated in the context of cancer or inflammatory bowel disease (IBD) in relation to differentia- tion from healthy individuals, but to the best of our knowledge never F I G U R E 6 Fecal quantities of miR-148b-3p in cats with SCL and in relation to differentiation between the 2 diseases. However, quan- CIE and healthy cats. Horizontal red lines represent median values. tities of serum and fecal miR-223-3p have been shown to be P value from Tukey–Kramer post hoc test after one-way ANOVA. increased in patients with GIC or IBD compared to healthy individuals. Likewise, good discriminatory ability of miR-223-3p in plasma or feces has been reported both between healthy individuals and GIC distinguishing between SCL and CIE or healthy cats was made patients42,57 and between healthy individuals and IBD patients.29,44 because of the low sample size for serum from SCL cats (n = 4). Consequently, miR-223-3p might not be able to discriminate between these conditions in humans, as it appears able to in cats and dogs. Analysis of feces yielded no miRNAs that were significantly differ- 3.6.2 | Feces ent among the GIC, CIE, and healthy cats, neither using small RNAseq nor RT-qPCR. However, when comparing only SCL cats to CIE and In contrast to the results of the comparison of all GIC cats to CIE and healthy cats, miR-148b-3p was significantly lower in SCL than in both healthy cats (Section 3.4), 1 miRNA was significantly different in CIE and healthy cats. This result however should be interpreted with 1-way ANOVA when comparing only SCL, CIE, and healthy cats, caution because of the small sample size for fecal samples from SCL cats namely miR-148b-3p (Figure 6 and Table 3). In Tukey-Kramer's post (n = 3). Additionally, the relevance for miR-148b-3p as a biomarker for hoc test, miR-148b-3p was significantly different between SCL and discrimination of SCL and CIE requires further investigation. Our reason- CIE cats, as well as between SCL and healthy cats. No investigation of ing for including miR-148b-3p in our analysis was its possible potential diagnostic performance of miR-148b-3p in relation to distinguishing as an endogenous qPCR normalizer based on our small RNAseq BROGAARD ET AL. 1747 screening (Tables S1 and S2) as well as literature findings showing it to All types of malignant neoplasia were eligible for inclusion, but be significantly different in serum of dogs with GIC and CIE14 and in only cats with lymphomas and carcinomas were enrolled and hence serum of human colorectal cancer patients and healthy controls.43 only these cancer types were investigated. These findings are consis- Despite the consistency of finding miR-223-3p to be a biomarker tent with the current literature because lymphoma and carcinomas candidate for the differentiation of GIC and CIE in cats as it also previ- are the most prevalent GI tumors.3 Therefore, our findings do not nec- ously has been in dogs,12 there is a discrepancy regarding sample essarily apply to cats with other tumor types such as mast cell tumors matrix. In a previous study, miR-223-3p proved a good fecal bio- or mesenchymal tumors.3 marker candidate, whereas GIC and CIE cats had no differences in Because only 1 cat with GIC had thoracic radiography performed, fecal miR-223-3p amounts.12 In contrast, serum miR-223-3p amounts pulmonary neoplasia or other pathology cannot be ruled out in the in dogs with GIC and CIE were not significantly different, contrary to remaining cats, even though none of the cats with GIC had a history of our findings in cats. Evidently, care should be taken to not extrapolate clinical signs relating to the respiratory system at the time of inclusion. findings on biomarker suitability between these species. There are a A subset of cats had comorbidities, received medications or both. number of reasons why assessing fecal miRNAs might be subject to The effect of these comorbidities and medications are unknown both more variation, thus limiting their diagnostic use. Feces is generally for the CIE and GIC groups, but could cause alterations of the micro- easy to obtain from indoor cats, but it proved challenging to ensure biota that could affect the fecal miRNA.64 A number of diseases, collection of newly evacuated feces (<1 hour), because many of the including stable hypertrophic cardiomyopathy, have shown distinct enrolled cats defecated at night or while alone, especially cats that deregulated miRNAs, but none of the investigated miRNAs were sig- normally were allowed outdoor access. However, evaluating a more nificant in our study.65 diverse group of cats with different subtypes of CIE and GIC is war- In conclusion, we identified miR-223-3p as a potential serum bio- ranted. Dysrexic cats produced only small amounts of fecal material, marker candidate for the differentiation of cats with GIC and CIE from and it likewise proved challenging to collect feces if the fecal score healthy cats. Additionally, serum miR-223-3p showed potential in dif- was 6-7. A prolonged time from defecation to collection as well as ferentiating cats with SCL from those with CIE and healthy cats. presence of hair or undigested plant material within the fecal content could have influenced the quality of the RNA isolated from fecal ACKNOWLEDG MENT material and therefore the present fecal miRNA results. Furthermore, Funding provided by the Independent Research Fund Denmark— outdoor cats with potential access to birds or small rodents were Technology and Production, “Fondet for sygdomsbekæmpelse hos allowed in our study. In humans, diet-derived xenomiRs have been vore familiedyr” (“Fund for Disease Control in our Companion Ani- detected in blood and feces, but this occurrence has not mals”), and “Agria och SKK Forskningsfond” (“Agria and SKK Research been assessed in cats, and hence it is unknown if specific meat-rich Fund”). We thank master's students Ann E. Hovland, Cecilie S. D. diets or ingestion of prey can influence the fecal or serum miRNA pro- Due, Freja K. Nielsen, and Christina Piper. Also, a great thank you to 58,59 files in cats. The difficulties relating to fecal miRNA quantification Mette Rasmussen as well as the other veterinary nurses at all partici- have been described previously.12 Only 27% of the miRNA primer pating institutions that have assisted with this study. Thank you to pairs (26/96) included in qPCR analysis in our study were successful Louise Bochsen, and other staff at the Veterinary Diagnostic Labora- in feces, compared with 54% (52/96) in serum. Proper storage is cru- tory, Denmark, in addition to laboratory technicians Tina B. N. Mahler cial to achieving high quality RNA from any sample, and the less con- and Minna B. Jakobsen. trolled method of owner-conducted at-home feces collection applied in our study might have contributed to suboptimal conditions for pre- CONFLIC T OF INTER E ST STATEMENT venting RNA degradation. We found that serum provided a more reli- Authors declare no conflict of interest. able sample type for the identification of GIC biomarkers in cats, and is a commonly applied minimally-invasive sample type for biomarker DATA AVAILABILITY STAT EMEN T measurement, including miRNA biomarkers.12,34,38,60 All small RNA sequencing data will be available from the Sequencing A limitation of our study is the relatively small sample size. Read Archive (https://www.ncbi.nlm.nih.gov/sra) upon final publica- Because ours was the first study to detect miRNAs in serum and feces tion of the manuscript (BioProject ID: PRJNA844553). from healthy cats and cats with CIE and GIC, future investigation assessing the role of miR-223-3p in a larger study group would be OF F-LABEL ANTIMI CROBIAL DECLARATION indicated. All CIE cats and the majority of GIC cats had endoscopic Authors declare no off-label use of antimicrobials. biopsies performed, and 2/9 CIE cats did not have ileal biopsy speci- mens obtained. Previously, it was believed that ileal biopsy specimens INSTITU TIONAL ANIMAL C AR E AND USE COMMITTEE were critical to obtaining the correct diagnosis, but such may not be (IACUC) OR OTHER APPROVAL DECLARATION the case.61–63 Histopathologic scoring and interobserver variation Approved by the local ethics committees (University of Copenhagen: remain challengeing 62,63 and the final diagnoses on some CIE or SCL #2017-9 + 2017-12; Norwegian University of Life Sciences: cats could have been misinterpreted, but immunohistochemistry and 14/04723-72, University of Glasgow: Ref 05a/18, University of Edin- clonality testing were performed when relevant and available. burgh: VERC#41.18) at all involved institutions as well as by the 1748 BROGAARD ET AL. Animal Experiments Inspectorate under the Ministry of Food, Agricul- 13. Konstantinidis AO, Pardali D, Adamama-Moraitou KK, et al. Colonic ture, and Fisheries of Denmark, Danish Veterinary and Food Adminis- mucosal and serum expression of microRNAs in canine large intestinal inflammatory bowel disease. BMC Vet Res. 2020;16(1):69. doi:10. tration (case #2017-15-0201-01353). 1186/s12917-020-02287-6 14. Lyngby JG, Kristensen AT, Fredholm M, Nielsen LN, Cirera S. Evalua- HUMAN ETHICS APPROVAL DECLARATION tion of fecal microRNA stability in healthy cats. Vet Clin Pathol. 2019; Authors declare human ethics approval was not needed for this study. 48(3):455-460. doi:10.1111/vcp.12757 15. Purina fecal scoring chart. https://www.purinainstitute.com/sites/g/ files/auxxlc381/files/2021-04/fecal-chart.pdf ORCID 16. Jergens AE, Crandell JM, Evans R, Ackermann M, Miles KG, Wang C. A Louise Brogaard https://orcid.org/0000-0003-4571-6822 clinical index for disease activity in cats with chronic enteropathy. J Vet Janne G. 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