Identification of novel genetic variants associated with feline cardiomyopathy using targeted next-generation sequencing

doi:10.21203/rs.3.rs-3943358/v1

Cardiomyopathies are the most common heritable heart diseases in cats and humans. This study aimed to identify novel genetic variants in cats with hypertrophic cardiomyopathy (HCM) and restrictive cardiomyopathy (RCM) using a targeted panel of genes associated with human cardiomyopathy. Cats were phenotyped for HCM/RCM by echocardiography or port-mortem examination. DNA was extracted from residual blood, and targeted next-generation sequencing was performed on two separate feline cohorts: an across-breed cohort (23 healthy cats and 21 HCM-affected pedigree or Domestic Shorthair cats), and a within-breed cohort of Birman pedigree cats (14-healthy, 8 HCM-affected, and 6 RCM-affected). Genome analysis toolkit for best practice was used for variant discovery. Genomic association analyses (including the covariates breed, age and sex) were conducted to identify genetic variants of interest. We identified genetic variants associated with HCM and RCM susceptibility in candidate genes based on the human literature. Novel variants of interest were identified in the sarcomeric genes ACTC1, ACTN2, MYH7, TNNT2 and the non-sarcomeric gene CSRP3. The Birman pedigree breed demonstrated shared genetic variants across the HCM and RCM phenotypes, suggesting that the same variants could be associated with both HCM and RCM phenotypes, as proposed in humans.

Health sciences/Cardiology

Biological sciences/Genetics

Biological sciences/Genetics/Genomics

Cardiomyopathies are diseases of the myocardium that can lead to a range of functional and structural abnormalities of the heart. Cardiomyopathies in both humans and cats are associated with elevated risks of congestive heart failure, cardioembolic events, and sudden cardiac death^1–3. Subcategorization of cardiomyopathies is based on the underlying disease cause, cardiac morphology and function, clinical presentation, and signs.

Hypertrophic cardiomyopathy (HCM) is defined in both humans and cats as presence of a hypertrophied left ventricle (LV) in the absence of abnormal loading conditions capable of producing a similar degree of hypertrophy (such as other cardiac or systemic diseases)^3,4. Human HCM is the most common genetic cardiovascular disease, affecting 0.2% of the world population (1 in 500 individuals)⁵. The inheritance pattern in 60% of cases is autosomal dominant⁶. Nevertheless, more recent findings propose that human HCM follows a more complex mode of inheritance⁷ with reports of genotype-positive/phenotype-negative individuals and a higher estimated population prevalence of 0.5% (1 in 200 individuals)⁸. Among domesticated animals, cats are particularly predisposed to HCM, with an estimated prevalence of 15% reported in the general cat population⁹.

In humans, HCM has a well-characterized genetic basis with more than 1500 variants described so far¹⁰. In up to 60% of human cases, HCM is caused by variants in genes encoding the cardiac sarcomeric proteins that form the cardiac contractile unit, thus HCM is generally considered a ‘disease of the sarcomere’¹¹. Variants in the genes encoding beta-myosin heavy chain (MYH7) and myosin-binding protein C (MYBPC3) account for the majority of cases in humans (around 70% of patients with sarcomeric variants)^11,12. Less commonly affected genes include cardiac troponin-I (TNNI3) and cardiac troponin-T (TNNT2), α-tropomyosin (TPM1), myosin light chain (regulatory MYL2 and essential MYL3) and cardiac actin (ACTC)^11–13.

To date, four variants associated with feline HCM susceptibility have been reported within specific cat breeds. Three of these variants were exonic and located in sarcomeric genes: MYBPC3 in the Maine Coon¹⁴ and Ragdoll cats,¹⁵ and MYH7 in a non-pedigree domestic shorthair cat (DSH)¹⁶. One variant reported in Sphynx cats was in the non-sarcomeric Alstrom syndrome 1 (ALMS1) gene¹⁷, which is associated with cardiac development and cell regulation¹⁸. One further intronic (splicing) variant within the sarcomeric TNNT2 gene was associated with HCM in the Maine Coon breed¹⁹, however a more recent study found that this variant was present in high frequencies across multiple cat breeds, suggesting that it might not have any significant association with HCM²⁰. As yet, no additional variants have been identified.

In humans, HCM is most commonly associated with exonic sarcomeric gene variants. These variants cause variable degrees of left ventricular hypertrophy (LVH) and different cardiomyopathy phenotypes within the same family^21,22. Individuals sharing the same causative variant may variously exhibit a HCM, RCM or dilated cardiomyopathy (DCM) phenotype^21,22. This pleiotropy leading to varying disease severity/expression in cardiomyopathies suggests that factors beyond the sarcomeric variant itself may influence disease expression, such as modifier genes, environmental factors, and epigenetic modifiers^13,23. The non-coding genome is an emerging area of study for HCM, with regulatory variants now identified in human HCM^24,25. For most variants the exact underlying molecular mechanisms linking genotype to phenotype remain unclear.

There are numerous similarities between human and feline HCM, highlighting the potential value of using cats as a model to study the human disease. In both species, the disease is spontaneous and with similar natural histories and wide phenotypic spectra. They also share genetic homology: mutations for HCM found in humans have also been identified in Maine Coon and Ragdoll cats. Studies of feline HCM could uncover further shared genetic variants, disease mechanisms and therapeutic targets. A better understanding of the genetic factors causing disease and influencing disease severity in cats could help with diagnosis and management of the disease.

Our main aim was to identify novel genetic variants for HCM susceptibility within and across cat breeds. Our secondary aim was to investigate different forms of cardiomyopathies (HCM and RCM) within a cohort of related and unrelated Birman cats to identify family-specific variants and explore possible co-occurrence of cardiomyopathies within feline families.

HCM has been reported to affect both pedigree and non-pedigree cats, with some breeds displaying a greater predisposition to the disease than others. We initially investigated the disease across multiple pedigree and non-pedigree cats to capture associations across a spectrum of cat breeds. In the second study we focussed on cats of the Birman breed, since Birmans are recognized as a breed with a familial tendency to developing HCM (unpublished observations). We primarily focussed on investigating HCM, since this is the most common cardiomyopathy observed in cats, but we also included Birman cats with RCM. We aimed to determine whether shared HCM/RCM phenotype causative variants exist in Birman cats as they do in humans^21,22.

Descriptive statistics of the studied cat populations

Descriptive statistics of the clinical and echocardiographic characteristics of the Across-breeds cat cohort (n=44) and Birman cat cohort (n=28) are summarised in Table 1 and Table 2, respectively. Due to sample limitations, we included 2 DSH control cats with a left ventricular wall thickness (LVWT) = 5.5mm. Both cats were from a geriatric population (³9 years old) with no previous signs of heart disease, all other cats included in the control population had a LVWT <5.5mm.

Genetic variant discovery and statistical analyses

The 18 candidate genes studied are listed in Table 3.

Study 1: Across-breeds

Targeted next generation sequencing analysis revealed the presence of a total of 4025 variants, single nucleotide variants (SNVs) (3400) and indels (666) in the 18 candidate genes in the Across-breeds cohort. Details of the identified genetic variants are presented in Figure 1.

Chi-squared comparisons

The annotation of the identified variants detected 8 high impact variants, including the known Ragdoll missense variant R820W in MYBPC3¹⁵, which was included as a positive control. However, none of these variants had a significantly different prevalence between cases and controls when analyzed both within and across the cat breeds.

Comparisons using the Chi-squared (χ²) test of the allelic and genotypic frequencies of the identified variants with a predicted moderate or modifier effect on the encoded protein identified a total of 160 variants with a significant (P£0.05) difference between HCM cases and controls. 157 of these variants were intronic: 91/157 had a higher prevalence in cases, with 8/157 being present only in cases (see Supplementary Table 1 for full list of variants with a statistically significant difference). Four of these variants remained significant after correcting for multiple testing: one intronic variant (X:101006474, T>C, P=0.0002) in Lysosomal associated membrane protein (LAMP2) gene, one 3’UTR (F1:42194903 G>GGT, P=0.025) located in TNNT2 gene and two missense variants (B3:76167563, C>T, L88F, P=0.003; D1:76804158, T>C, I45V, P=0.004) located within the novel gene ENSFCAG00000040035 (overlapping MYH7) and Cysteine and Glycine Rich Protein (CSRP3) gene respectively. The intronic SNV in LAMP2 was only present in control cats. The 3’UTR variant located in TNNT2 had a significantly higher genotypic frequency in controls. According to the Softberry FPROM human promotor predictor analysis close to this 3’UTR SNV there are two promotors. However, this SNV did not directly overlap with these promotor predictions.

The two missense variants were present in both case and control cats with a higher prevalence in controls and were located within the novel gene ENSFCAG00000040035 (overlapping MYH7) (B3:76167563 L88F) and CSRP3 gene (D1:7680415 I45V) respectively. The CSRP3 gene missense variant has a reported ‘sorting intolerant from tolerant’ (SIFT) score of 0.34, which is considered ‘tolerated’.

Genomic association analysis

The genomic association analysis for the Across-breeds cohort which included age, sex and breed as covariates revealed the presence of one intronic variant within TNNT2 (present only in cases (n = 5) (F1:42199381 CA>C)) significantly associated with HCM (P=0.0006). The Softberry NSITE analysis predicted that this variant affected the motifs that were able to bind to the nearby transcription factor binding sites (TFBS), with 3 additional motifs identified in the intronic sequence compared to the control cat population sequence (see supplementary table 8). The Manhattan plot presenting the results of the genomic association analysis for HCM susceptibility in the Across-breeds cat cohort is shown in Figure 2.

Study 2: Birman cats

The targeted next generation sequencing analysis of the Birman cat cohort revealed the presence of 2298 genetic variants, SNVs (1921) and indels (395) across the candidate genes. Details of the identified genetic variants are presented in Figure 3.

Chi-squared comparisons

The annotation of the genetic variants revealed 5 high impact variants within the Birman cohort, however their frequency was not significantly different between case and control cats. When variants with a predicted moderate or modifier effect were compared using the χ² test, 177 variants were identified with significantly different frequencies (P£0.05) between cases (HCM and RCM) and controls. Among these variants was a missense SNV located in ENSFCAG00000040035 gene-Glu22Gln (B3:76167365, G>C, E22Q, P=0.04) more prevalent in cases (heterozygous in 5 HCM, 3 RCM). This missense variant is synonymous for a variant within MYH7 gene and overlaps with a microRNA (miR-208B- ENSFCAG00000018043) which has been previously reported to play a role in heart disease²⁶. Moreover, one 3’UTR SNV (D1:76785090, C>A, P=0.03) within CSRP3 gene was found only in control cats; the Softberry analysis did not reveal any further overlapping of this 3’UTR SNV with promoter regions. Further, 14 intronic variants located in Actin alpha cardiac muscle 1 (ACTC1), MYH7 and TNNT2 genes were more prevalent in cases.

When cases were restricted to cats with HCM, the χ² comparisons revealed 153 variants that were significantly different (P£0.05) between cases and controls. Of these 153 variants, 117 had a higher prevalence in cases, with 78 intronic variants present only in cats with HCM (mainly spanning the genes ACTC1 and Actinin Alpha 2 (ACTN2)).

Full details of the identified variants in the HCM and RCM analyses and the HCM analyses are presented in Supplementary Tables 3 and 4, respectively.

Genomic association analyses

I. Genomic Analysis: HCM Cases (n=8) and Controls (n=14)

When cases were restricted to just HCM, the genomic association analysis which included age and sex as covariates identified 24 intronic variants with a significant association with disease susceptibility. These intronic variants were located within ACTN2 (D2:12374576 C>T), MYH7 (B3:76168426 G>A) and ACTC1 (B3:70080970 T>TC) genes and had a higher frequency in the case population aside from one intronic variant associated to controls in ACTN2 (D2:12407434 GGGGT>G). The Manhattan plot presenting these results is shown in Figure 4.

II. Genomic Analysis: HCM and RCM Cases (n=14) and Controls (n=14)

The genomic association analysis of the merged HCM and RCM phenotypes revealed the presence of 9 intronic variants within CSRP3 gene and 1 intronic variant within MYH7 with a statistically significant to the disease. The Manhattan plot presenting these results is shown in Figure 5.

Human Comparison & Functional Impact Analysis

The significant missense SNV that we identified in Birman cats (B3:76167365) corresponds to the protein change pE22Q with a SIFT score of 0.4. The protein orthologue approach confirmed the presence of an E amino acid in the protein ortholog alignment for humans (14:23415004, Human GRCh38 position). According to the Clinical Variants (ClinVar) archive, an E>Q protein change human variant at position 14:23413845 has an association with HCM and DCM that does not overlap with the variant identified in cats, but it is relatively close to the human position identified from the region comparison approach 14:23415004.

We aimed to identify novel genetic variants associated with HCM and RCM in Birman cats, as well as across pedigree breeds and DSH cats and performed two studies using a targeted cardiomyopathy gene panel and with meticulously phenotyped cats. Although there are a few shared genetic variants associated with HCM resistance or susceptibility across cat breeds, the genetic architecture of the disease seems to be breed-specific.

Moreover, our studies identified high impact variants within sarcomeric genes that were present at similar frequencies in both HCM cases and healthy controls. Similarly, several missense variants were present in both cases and controls, with no significant differences between the groups. These findings indicate that studies with appropriate sample sizes of cases and controls are required for the identification of truly causative HCM variants in cats. Nevertheless, we did identify a missense variant located on a novel gene ENSFCAG00000040035, which overlaps with MYH7 and a microRNA (miR-208). This missense variant had a significantly higher prevalence in HCM cases (P = 0.048) in our Birman cat cohort. The function of ENSFCAG00000040035 gene is unknown, but MYH7 is a sarcomeric gene that encodes the protein beta myosin heavy chain; a key protein component of the sarcomere involved in contractile function²⁷. Of increased interest is the presence of this variant within miR-208 (overlapping with ENSFCAG00000040035 and MYH7), which is expressed in cardiac tissue and regulates the production of beta myosin heavy chain during cardiomyocyte development²⁸. MicroRNAs (miRNA) are non-coding RNA sequences which are crucial in biochemical pathway regulation including during the heart’s development²⁹. According to previous studies, genetic variants in miRNA genes can have profound effects on miRNA functionality at all levels, including miRNA transcription, maturation, and target specificity, and as such they can also contribute to disease^30–32. Therefore miR-208 might prove to be an important biomarker in feline cardiac disease, especially since it has already been linked to myocardial infarction, hypertensive heart disease^33,34 and dilated cardiomyopathy in humans³⁵. Relationships between miRNAs and cardiac conditions such as left ventricular hypertrophy and fibrosis have already been shown across studies^36,37, including evidence for other miRNAs that overlap with the MYH7 gene serving as biomarkers for human HCM^38,39. Nevertheless, the role of microRNAs in feline HCM remains largely unknown. There is only one previous study that compared serum miRNA of a healthy control cat cohort (n = 12) with a HCM cohort (with stage C (disease progression is causing noticeable clinical signs of heart disease)) (n = 11). In that study, 7 human HCM-associated miRNAs (causing cardiac tissue damage and disturbed blood flow) were upregulated in the HCM cat cohort,⁴⁰ suggesting that miRNAs might also play a role in feline HCM and could potentially be useful biomarkers as in humans. The miR-208 was not among the upregulated miRNAs within their cat cohort, suggesting our miR-208 variant may be specific to Birman pedigree cats. Further studies in Birman cats are needed to validate these results and confirm the potential role of miR-208 or/and ENSFCAG00000040035 in feline HCM susceptibility.

Recent studies suggest intronic variants might play a more significant role in HCM susceptibility than previously thought^41,42. Whole genome sequencing studies of human HCM have found pathogenic intronic variants that were causing disruption of splicing and TFBS⁴¹. In our study, we identified several intronic variants significantly associated with HCM susceptibility in cats, both across cat breeds and in the Birman cohort. Of particular interest was the intronic variant in TNNT2 (position F1:42199381) which was present only in HCM cases in the Across-breeds cat study. Softberry analysis predicted that this intronic variant affects the number of motifs in or around the TFBS which has the potential to influence the binding of transcription factors, and consequently gene regulation. Several variants in TNNT2 gene are associated with human HCM⁴³. TNNT2 encodes cardiac troponin-T (cTnT) a cardiac specific protein forming part of the troponin complex associated with thin filaments. This protein plays a crucial role in cardiomyocyte contraction and relaxation through its interaction with actin and tropomyosin⁴⁴. Further studies are needed to confirm whether this intronic variant plays a regulatory role and contributes to HCM susceptibility since Softberry tools currently provide predictions based on the human (and not the feline) genome assembly. Moreover, we found several intronic variants associate with HCM susceptibility both in the Across-breeds and Birman cat studies, but it is difficult to assess if they have a pathological impact. Further genomic and functional genomic studies with larger sample sizes are needed to shed light on the role of intronic variants in feline HCM susceptibility.

We investigated RCM alongside HCM in Birman cats following previous unpublished observations of cats within the same family being diagnosed with different cardiomyopathy phenotypes, as has been observed in affected human families⁴⁵. There are significant similarities in disease presentation between HCM and RCM, with both conditions leading to diastolic dysfunction and increased end diastolic pressure⁴⁵, predisposing cats to heart failure. RCM in cats shares similar histological features to HCM, thus it has been proposed that RCM could be part of the spectrum of HCM⁴⁶. An intronic variant in the CSRP3 gene was significantly associated with the combined group of HCM and RCM cases. The CSRP3 gene encodes the muscle LIM protein (MLP) of functional importance for calcium handling and signalling in cardiomyocytes⁴⁷. Variants within this gene have been identified as causative for both human HCM and dilated cardiomyopathy^48,49. Within our Birman cat cohort, the intronic variant was more prevalent in the control population and may have a protective role. Our results indicate the potential presence of shared protective variants against the phenotypic expression of RCM/HCM phenotype within Birman cats. To identify whether our intronic variant is playing a protective role and the exact mechanism behind this, further molecular and functional studies would need to be conducted, alongside validation in another case-control study of Birman cats. It would be useful if further studies in Birman cats were to include related cats exhibiting varying cardiomyopathies. Our Birman cohort included related cats, but these consisted of only 4 cats in the control population and 2 HCM cats.

Genetic similarities identified between the human and feline cardiomyopathies point to the usefulness of cats as a translational model of human disease. Preclinical feline models of HCM have already shown promising results, with the myosin inhibitor MYK-461 (mavacamten) reducing left ventricular outflow tract (LVOT) obstruction in Maine coon cats with HCM⁵⁰. Collaborations between human and veterinarian researchers have the potential to unravel the genetic background of cardiomyopathies, with beneficial outcomes possible for both.

In this study, we identified several high- or moderate-impact variants in sarcomeric and other candidate HCM genes that were not causative, since they were not unique to cats with HCM. As with human patients, in some cats with HCM a genetic cause cannot be identified by following a candidate gene approach and focusing only on exonic variants. In this study we identified several intronic variants statistically associated with HCM susceptibility or protection, but due to the poor annotation of regulatory elements in the cat genome it is difficult to assess their potential role in HCM. Moreover, we identified in Birman cats an exonic variant of interest located in a gene of unknown function (ENSFCAG00000040035) that overlaps with the key sarcomeric gene MYH7 and a myocardium related microRNA (miR-208). Further studies are needed to characterise the role of this variant in HCM susceptibility within this breed and assess if microRNAs play a role in HCM susceptibility in cats as in humans.

Ethical approval

Ethical approval was received by the Clinical Research Ethical Review Board of the Royal Veterinary College (URN.2019.1942-3, URN 2016 1515, URN 2015-1378), the study followed all relevant guidelines and regulations. The study is reported in adherence to ARRIVE (https://arriveguidelines.org) guidelines.

Study population

Cats were recruited into the study following routine or invited echocardiographic screening for heart disease or following post-mortem examination conducted at the Royal Veterinary College (RVC). Of the cats included in the study (total n = 72), 2 HCM cats in the Birman cohort and 11 HCM cats in the Across-breeds cohort were diagnosed at necropsy. All other cats were diagnosed via echocardiography. Cats without evidence of HCM or other cardiac disease (confirmed via echocardiography) and above the age of 9 years old were used as controls. Cats of any age with a confirmed HCM phenotype were used as cases. Among the Birman cohort 2 control cats were littermates, 2 control cats shared the same dam, and 2 HCM cats shared the same dam.

Our work included two studies: i) An Across-breeds cat study, totalling 44 phenotyped cats (controls = 23, HCM = 21) representing 21 non-pedigree cats (DSH) and pedigree breeds (4 Bengal, 8 British shorthair, 1 British longhair, 6 NFC, 3 Ragdoll, and 1 Maine coon). Among the HCM cases we included a Ragdoll cat confirmed homozygous for the HCM-associated MYBPC3 variant (R820W); ii) A Birman pedigree cat study, totalling 28 phenotyped Birman cats (controls = 14, cases = 17, including 8 cats with HCM, and 6 cats with RCM).

Phenotyping

The cardiac phenotype was defined by echocardiography and/or gross pathology and histopathology with owner consent. Echocardiography was performed by a board-certified veterinary cardiologist, or by a cardiology resident under the supervision of a board-certified veterinary cardiologist, using a Vivid E9 or Vivid I ultrasound machine (GE Systems, Hatfield, Hertfordshire, UK) with a 7.5 or 12 MHz phased-array transducer. Standard echocardiographic views were acquired, and video loops recorded⁹. All studies were measured off-line using dedicated echocardiographic software (EchoPac, GE Systems, Hatfield, Hertfordshire, UK).

On echocardiography, the thickness of the left ventricular free wall (LVFW) and interventricular septum (IVS) was measured by a leading edge to leading edge technique from a 2D right parasternal long-axis (RPLA) 4- or 5-chambered view and a short-axis view at the papillary muscle level (RPSA). The thickest end-diastolic segment was averaged over 3 different cardiac cycles in each view (RPLA and RPSA). End-diastolic frames were defined as the first frame after mitral valve closure in RPLA and as the time point in the cardiac cycle of greatest left ventricular internal diameter in RPSA⁹. The greatest end-diastolic wall thickness of these measured views (RPLA septal, RPLA free wall, RPSA septal, RPSA free wall) was defined as LVWT and used for data analysis. Left atrial linear dimensions were measured as left atrial to aortic ratio (LA/Ao ratio) and left atrial diameter (LAD). The LA/Ao was measured as the ratio of the left atrium to aorta measured in 2D from a RPSA view at the heart base, in the frame after aortic valve closure⁵¹. The LAD was measured as the cranial-caudal LA dimension from a RPLA 4-chambered view, in the frame before mitral valve opening⁵². Left ventricular (LVFS%) fractional shortening was measured by M-Mode from a right parasternal short-axis at the papillary muscle. Systolic anterior motion of the mitral valve (SAM) was assessed on colour Doppler and 2D echo from a right parasternal long-axis 5 chamber view.

HCM was defined as LVWT ³5.5 mm at end-diastole. Cases with concurrent disease that could contribute to LVH were excluded from the study. These conditions included systemic hypertension (systolic blood pressure >160mmHg)⁵³, aortic stenosis or hyperthyroidism⁵⁴. Healthy cats (control group) were defined as having a LVWT <5.5 mm and aged ³9 years old to minimise inclusion of cats with late onset HCM. Necropsy examinations were performed by a single trained observer, and HCM was defined as a hypertrophied LV in the presence of myofiber disarray and interstitial/replacement fibrosis on histopathology⁵⁵.

In the Birman cat cohort, in addition to HCM cases we also included RCM cases, defined as the presence of left or biatrial enlargement (left and/or right atrial diameter in RPLA view>16 mm), LVWT £5.5 mm and normal left ventricular systolic function (LVFS%>30%).

Blood and tissue collection and DNA extraction

Myocardial samples collected at necropsy were received from Birman breeders following death with suspicion of heart disease. For the Across-breeds cats, liver samples were obtained following routine necropsy examinations at the RVC. Residual blood (derived from clinical testing) was used for this project from blood collected by either a qualified veterinarian or veterinary nurse following echocardiography (using the same equipment and expert for each diagnosis) to exclude systemic diseases that can affect the heart and to measure cardiac biomarkers. DNA was extracted from whole blood/liver/myocardial samples using two commercial kits: DNeasy Blood and Tissue Kit (Qiagen®) and GeneJet Whole Blood Genomic DNA Purification Mini Kit (Thermo Scientific®) according to the manufacturers’ instructions. DNA quality and quantity were assessed using Denovix DS-11 Series spectrophotometer and Invitrogen Qubit 4 Fluorometer, respectively.

Feline HCM gene panel and Targeted Next Generation Sequencing (tNGS)

We developed a gene panel for feline HCM and RCM based on candidate genes previously implicated in human cardiomyopathies (Table 3). This feline panel was equivalent to the Illumina TruSight Cardio Panel⁵⁶ which is applied in suspected cases of human cardiomyopathy. In the first study (Across-breeds cohort) we included a panel of 18 candidate genes (Table 3). The same panel was used in the second study (Birman cohort) with the exclusion of two metabolic genes. These two genes were excluded due to limited variation, with no exonic variation being identified in these genes from the first study.

Targeted Next Generation Sequencing Analysis

The raw sequencing data (FASTQ files) were assessed for quality control using FASTQC (v10.1)⁵⁷ and trimmed to exclude adapter sequencing using Trimmomatic (v0.36)⁵⁸ prior to mapping the reads on Felis Catus v9.0 genome assembly⁵⁹ using the BWA aligner⁶⁰. The matching variant file for the Felis Catus v9.0 genome assembly (Ensembl release version 95)⁶¹ was sorted against the reference dictionary to obtain known variant sites using Picard toolkit (v2.21.7)⁶². The reads were indexed, and duplicates removed using SAMTOOLS (v1.3)⁶³. Base recalibration and variant calling to detect SNVs and indel variants were performed with the GATK (v.3.8) software⁶⁴ using HaplotypeCaller⁶⁵. Joint VCF files were created for cases and controls (for each study separately). Two separate VCF files for the Birman cases were created: one including both HCM and RCM cases and another only HCM. We ran a grouped analysis for cats with HCM and RCM phenotypes, as RCM has been suggested to be part of the HCM spectrum, i.e., these two phenotypes might represent diverse expressions of the same disease^45,46,66,67. The SNV locations were obtained from Felis Catus v9.0 genome assembly using the Ensembl genome browser release version 95⁶⁸. SNV annotation was performed using the Ensembl variant effect predictor (VEP) tool⁶⁹.

The data from each study were analysed separately. Allelic and genotypic frequencies of genetic (SNV and Indel) variants with a predicted high, moderate, or modifier functional impact according to VEP were compared between cases and controls to assess if there are statistically significant differences between the two groups. The Chi-squared test (χ2), with a significance level set at P£0.05 was used in this respect. A correction for multiple testing (0.05 divided by number of genes tested) was also applied.

To identify if any of the SNVs of interest in 3’UTR and other non-coding regions were located within a putative regulatory region we further interrogated these SNVs using Softberry software⁷⁰. Specifically, to identify potential functional roles of our SNVs of interest we used BEDTools⁷¹ to extract SNV sequences 1500bp either side of our SNV and ran comparisons against the corresponding 3000bp sequence extracted from our sample containing the reference allele. These 3000bp sequences were inputted into Softberry tools FPROM promotor predictor to look for predicted promotor regions in our significant 3’UTR SNVs and the NSITE tool to search for regulatory motifs in our 3’UTR and intronic regions⁷².

Genomic association studies

A bed genotypic file was generated from the VCF file for cases and controls using the PLINK software (v1.90)^73–75. Each of the datasets was subjected to quality control (qc) measures using the following thresholds: call rate <90%, minor allele frequency <0.05 and Hardy-Weinberg equilibrium P<10^-6. A genomic relationship matrix was created for all animals using the GEMMA (v0.98.1) algorithm⁷⁶. GEMMA was used to run the genomic association analyses for HCM susceptibility using a mixed model where the genomic relationship matrix was added as a random effect to account for possible population stratification and age, sex, and breed as fixed effects in the first study (Across-breeds cat cohort), and lambda correction applied to the P-values. The same model with the exclusion of breed as a fixed effect was used in the second study (Birman cat cohort). The significance level was set at P£0.05 and a Bonferroni correction for multiple testing was applied. Python3⁷⁷ in Jupyter notebook⁷⁸ (for Mac OS) was used to create Manhattan plots to present the genomic analyses results.

Feline and Human Comparisons

To investigate whether the SNVs of interest identified for feline HCM susceptibility were equivalent or close to previously identified variants in humans, a relevant comparison was performed. Initially, a region comparison approach was used to compare the cat (Felis Catus v9.0) and human (GRCh38.p13) assembly by inputting the cat SNV position into Ensembl’s region comparison tool⁶⁸. The output of this analysis provides the predicted equivalent coordinate in the human assembly per feline SNV.

Moreover, a protein orthologue approach was applied by extracting the relevant amino acid sequence alignments for Felis Catus v9.0 and Human GRCh38.p13 genome assemblies using the Ensembl ortholog comparison tool⁶⁸ in ClustalW format for missense SNVs of interest. The equivalent human protein position for each missense SNV was identified through these sequence comparisons before identifying the correct international union of pure and applied chemistry (IUPAC) coding. After the equivalent human genome position was identified, ClinVar database⁷⁹ was used to search for human SNVs that have been previously reported close to the equivalent feline SNVs of interest.

ACTC	Cardiac actin
ACTN2	Actinin Alpha 2
ALSM1	Alstrom syndrome 1
ARVC	Arrhythmogenic right ventricular cardiomyopathy
CSRP3	Cysteine and Glycine Rich Protein 3
DCM	Dilated cardiomyopathy
DSH	Domestic shorthair
HCM	Hypertrophic cardiomyopathy
LA/Ao	Left atrium to aorta ratio
LAD	Left atrial diameter
LV	Left ventricle
LVH	Left ventricular hypertrophy
LVWT	Left ventricular wall thickness at end-diastole
MYBPC3	myosin-binding protein C
MYH7	beta-myosin heavy chain
MYL2	Regulatory myosin light chain
MYL3	Essential myosin light chain
NFC	Norwegian Forest Cat
RCM	Restrictive cardiomyopathy
SNV	single nucleotide polymorphisms
tNGS	targeted next-generation sequencing
TNNI3	Cardiac troponin I
TNNT2	cardiac troponin-T
TPM1	α-tropomyosin

Data Availability

The datasets generated and analysed during the study are available in the Sequence Read Archive (SRA) repository, BioProject ID PRJNA1083230.

Acknowledgements

The authors acknowledge the financial support provided by the Biotechnology and Biological Sciences Research Council (BBSRC) studentship. Funding was provided via the UKRI funder award reference 1903448. The authors acknowledge the Petplan Charitable Trust for making the research possible through funding provided to projects S18-6930731 and S190735-774. The authors also acknowledge the Winn Feline Foundation and the Birman Cat Club for their continued support of the research.

The authors express gratitude to the team at the Queen Mother hospital for Animals at the Royal Veterinary College. The authors thank Petros Syrris (University College London) for their guidance on human hypertrophic cardiomyopathy and Lois Wilkie (Royal Veterinary College) for performing the post-mortem examinations on cats included in the study and providing in-depth pedigree information of the Birman cat cohort. The authors acknowledge Oliver Foreman (Animal Health Trust) for their help with devising the original candidate gene panel and co-ordinates.

Author Contributions

Jade Raffle (JR): Collected clinical data on study participants, performed the bioinformatic and statistical analysis and interpretation of the sequencing datasets, and prepared the manuscript.

Jose Novo Matos (JNM): Provided expertise on feline cardiology, recruited the study participants, and performed the sample DNA extractions for submission to outsourced sequencing, contributed to data collection and study design, and assisted in revising the manuscript.

Androniki Psifidi (AP): Provided expertise on clinical genetics, guidance on the research design and data interpretation and assisted in revising the manuscript.

Virginia Luis Fuentes (VLF): Provided expertise on feline cardiology, conducted echocardiographic assessments for the study, research design and data interpretation and assisted in revising the manuscript.

David J Connolly (DJC): Provided expertise on feline cardiology, conducted echocardiographic assessments for the study, research design and data interpretation and assisted in revising the manuscript.

Perry Elliott (PE): Provided guidance on the human cardiology genomic background and the development of the feline targeted HCM panel.

Richard Piercy (RP): Contributed to securing funding and experimental design alongside reviewing the manuscript and providing feedback.

AP, VLF, DJC, RP: conceived and designed the genetic study of HCM resistance and secured funding.

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Table 1. Descriptive statistics of clinical and echocardiographic characteristics of the Across-breeds cohort aiming to identify genetic variants for HCM susceptibility using a targeted cardiomyopathy gene panel.

	Controls (n = 23)	HCM (n = 21)
Age (years)	12 [9 – 17]	6.9 [1.8 - 20]
Weight (Kg)	4.2 [2.41 – 5.65]	4.8 [3 – 8.55]
Sex: males (%)	8 (35%)	14 (67%)
Echocardiography
LVWT (mm)	4.8 [4 – 5.5]	7.6 [5.7 – 11.6]
LAD (mm)	14.1 [11.5 - 17]	19.15 [11.2 - 31]
LA/Ao	1.25 [1 – 1.5]	1.8 [1.12 – 2.7]

Results are presented as median [range] for each variable for the Hypertrophic cardiomyopathy (HCM) and control cats. Abbreviations: LAD, left atrial diameter; LA/Ao, left atrium to aorta ratio; LVWT, left ventricular wall thickness at end-diastole.

Table 2. Descriptive statistics of clinical and echocardiographic characteristics of the Birman cat study aiming to identify genetic variants for HCM susceptibility using a cardiomyopathy targeted gene panel.

	Controls (n = 14)	HCM (n = 8)	RCM (n = 6)
Age (years)	11.3 [9.2 - 17]	8.35 [1.4 – 16.4]	8.25 [4 – 17.9]
Weight (Kg)	3.53 [2.63 – 5.2]	4.15 [3.5 – 5.2]	4.4 [3.54 – 5.2]
Sex: males (%)	3 (21%)	6 (75%)	3 (50%)
Echocardiography
LVWT (mm)	4.4 [2.8 – 4.8]	6 [5.5 – 8.4]	5.1 [4.8 – 5.2]
LAD (mm)	13.5 [11.4 – 15.4]	14 [12 – 19.4]	21.9 [16 – 27.3]
LA/Ao	1.4 [1.3 - 1.6]	1.3 [1 – 1.8]	2 [1.8 – 2.9]

Results are presented as median [range] for each variable for the cardiomyopathies (HCM, RCM) and control cats. Abbreviations: LAD, left atrial diameter; LA/Ao, left atrium to aorta ratio; LVWT, left ventricular wall thickness at end-diastole.

Table 3. Feline cardiomyopathy target gene panel. Gene names and gene positions based on FelCat9 assembly. *genes exclusive to the 18-gene panel for Cohort (i) Across-breeds Cat tNGS Study; ˆgenes are exclusive to the 16-gene panel Cohort (ii) Birman Pedigree Cat Study.

Gene Acronym	Gene Name	Chromosome	Start Position	End Position
MYL3	Myosin light chain 3	A2	16290210	16296259
TNNC1	Troponin C1	A2	21044756	21047572
PRKAG2*	Protein Kinase AMP-Activated Non-Catalytic Subunit Gamma 2	A2	165581663	165842537
CAV3ˆ	Caveolin-3	A2	50098852	50115062
PDLIM3*	PDZ and LIM domain protein 3	B1	16445054	16474763
PLN	Phospholamban	B2	109748495	109748653
MYH7	Myosin heavy chain gene	B3	76134518	76188380
TPM1	Tropomyosin 1	B3	43987226	44036037
ACTC1	Actin alpha cardiac muscle 1	B3	70080059	70085659
MYH6	Myosin Heavy Chain 6	B3	76134518	76188380
MYBPC3	Myosin Binding Protein C	D1	101324989	101341953
CSRP3	Cysteine and Glycine Rich Protein 3	D1	76776148	76804617
ACTN2	Actinin Alpha 2	D2	12369479	12442749
MYL2	Myosin light chain 2	D3	8973170	8980956
TCAP	Telethonin	E1	40752572	40753322
TNNI3	Troponin I3, Cardiac Type)	E2	3439821	3450055
TNNT2	Troponin T2	F1	42194772	42209527
GLA	Galactosidase	X	83631654	83639229
LAMP2*	Lysosomal associated membrane protein	X	100973530	101012558

No competing interests reported.

SupplementaryDataFiletNGSManuscript231108.xlsx

Identification of novel genetic variants associated with feline cardiomyopathy using targeted next-generation sequencing

Status:

Version 1

Abstract

Figures

Introduction

Results

Descriptive statistics of the studied cat populations

Genetic variant discovery and statistical analyses

The 18 candidate genes studied are listed in Table 3.

Study 1: Across-breeds

Study 2: Birman cats

Discussion

Conclusion

Materials and Methods

Ethical approval

Study population

Phenotyping

Blood and tissue collection and DNA extraction

Feline HCM gene panel and Targeted Next Generation Sequencing (tNGS)

Targeted Next Generation Sequencing Analysis

Genomic association studies

Feline and Human Comparisons

Abbreviations

Declarations

Data Availability

Acknowledgements

Author Contributions

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1