Introduction:Dysregulated immune responses are central to progression of sepsis and closely associated with impaired cellular metabolism. However, most existing studies have focused on late-stage sepsis, leaving metabolic alterations during earlier stages of infection poorly characterised. This study aimed to determine whether immune cell metabolic impairment is already present during uncomplicated infection, prior to the development of sepsis, and to evaluate its potential as an early indicator of immune dysfunction and risk of progression. Materials and methods:Forty patients with sepsis (fulfilling Sepsis-3 criteria) and 27 patients with uncomplicated infection were recruited from the emergency department along with 20 healthy volunteers. Whole blood samples were collected to assess gene expression, cytokine levels, and cellular metabolic functions, including mitochondrial respiration, oxidative stress, and apoptosis in immune cells. Results:Mitochondrial respiration was significantly impaired in immune cells from both uncomplicated infection and sepsis patients compared with healthy controls (p < 0.05), with more pronounced impairment in established sepsis. Downregulation of BCL2 and BBC3 gene expression was observed in sepsis patients (p < 0.05), but not in uncomplicated infection, potentially contributing to differences in the severity of metabolic impairment. Impaired mitochondrial respiration was significantly associated with increased mitochondrial oxidative stress (p < 0.05), which was elevated in uncomplicated infection and further increased in sepsis. Oxidative stress levels also correlated with tumour necrosis factor-α (r = 0.330) and the expression of CYCS, TP53, SLC25A24, and TSPO (rs = -0.4926, -0.4422, 0.4382, and 0.4835, respectively). Despite these metabolic alterations, no significant differences in immune cell apoptosis were observed between uncomplicated infection and sepsis patients. Conclusions:Immune cell metabolic dysfunction is present in patients with uncomplicated infection before the clinical onset of sepsis. Early mitochondrial dysfunction and oxidative stress may represent promising targets for further investigation as early biomarkers of immune dysfunction and sepsis risk.

Respiratory infections pose significant challenges to global health, impacting millions of individuals annually. Understanding the molecular mechanisms underlying the pathogenicity of these infections is crucial for developing effective interventions. RNA sequencing provides insights into a patient's global transcriptome changes, facilitating the identification of host gene signatures in response to infection and potential therapeutic targets. Here we present an extensive whole blood transcriptome dataset from a demographically diverse cohort of 502 patients with infections including COVID-19, seasonal coronavirus, influenza A or influenza B, sepsis, septic shock, and co-infections (Viral/Viral, Bacterial/Viral, Bacterial/Viral/Fungal, Viral/Fungal, Viral/ Viral/Fungal). The cohort size and depth of data showcase its potential to unravel respiratory infection pathogenesis for the development of better diagnostics, treatments, and preventive strategies for respiratory infections and future global health crises.

Sub-Saharan Africa is experiencing the highest mortality rates for several cancer types. While cancer research globally has entered the genomic era and advanced the deployment of precision oncology, Africa has largely been excluded and has received few benefits from tumour profiling. Through a thorough literature review, we identified only five whole cancer genome databases that include patients from Sub-Saharan Africa, covering four cancer types (breast, esophageal, prostate, and Burkitt lymphoma). Irrespective of cancer type, these studies report higher tumour genome instability, including African-specific cancer drivers and mutational signatures, suggesting unique contributory mechanisms at play. Reviewing bioinformatic tools applied to African databases, we carefully select a workflow suitable for large-scale African resources, which incorporates cohort-level data and a scalable design for time and computational efficiency. Using African genomic data, we demonstrate the scalability achieved by high-level parallelism through physical data or genomic interval chunking strategies. Furthermore, we provide a rationale for improving current workflows for African data, including the adoption of more genomic techniques and the prioritisation of African-derived datasets for diverse applications. Together, these enhancements and genomic scaling strategies serve as practical computational guidance, lowering technical barriers for future large-scale African-inclusive research and ultimately helping to reduce the disparity gap in cancer mortality rates across Sub-Saharan Africa.

The overall prognosis of acute myeloid leukemia (AML) remains dismal, largely because of the inability of current therapies to kill leukemia stem cells (LSCs) with intrinsic resistance. Loss of the stress sensor growth arrest and DNA damage-inducible 45 alpha (GADD45A) is implicated in poor clinical outcomes, but its role in LSCs and AML pathogenesis is unknown. Here, we define GADD45A as a key downstream target of G protein-coupled receptor (LGR)4 pathway and discover a regulatory role for GADD45A loss in promoting leukemia-initiating activity and oxidative resistance in LGR4/HOXA9-dependent AML, a poor prognosis subset of leukemia. Knockout of GADD45A enhances AML progression in murine and patient-derived xenograft (PDX) mouse models. Deletion of GADD45A induces substantial mutations, increases LSC self-renewal and stemness in vivo, and reduces levels of reactive oxygen species (ROS), accompanied by a decreased response to ROS-associated genotoxic agents (eg, ferroptosis inducer RSL3) and acquisition of an increasingly aggressive phenotype on serial transplantation in mice. Our single-cell cellular indexing of transcriptomes and epitopes by sequencing analysis on patient-derived LSCs in PDX mice and subsequent functional studies in murine LSCs and primary AML patient cells show that loss of GADD45A is associated with resistance to ferroptosis (an iron-dependent oxidative cell death caused by ROS accumulation) through aberrant activation of antioxidant pathways related to iron and ROS detoxification, such as FTH1 and PRDX1, upregulation of which correlates with unfavorable outcomes in patients with AML. These results reveal a therapy resistance mechanism contributing to poor prognosis and support a role for GADD45A loss as a critical step for leukemia-initiating activity and as a target to overcome resistance in aggressive leukemia.

BACKGROUND:Viral respiratory tract infections are frequently complicated by secondary bacterial infections. This study aimed to use machine learning to predict the risk of bacterial superinfection in SARS-CoV-2-positive individuals. METHODS:In this prospective, multicentre, observational cohort study done in nine centres in six countries (Australia, Indonesia, Singapore, Italy, Czechia, and France) blood samples and RNA sequencing were used to develop a robust model of predicting secondary bacterial infections in the respiratory tract of patients with COVID-19. Eligible participants were older than 18 years, had known or suspected COVID-19, and symptoms of a recent respiratory infection. A control cohort of participants without COVID-19 who were older than 18 years and with no infection symptoms was also recruited from one Australian centre. In the pre-analysis phase, data were filtered to include only individuals with complete blood transcriptomics and patient data (ie, age, sex, location, and WHO severity score at the time of sample collection). The dataset was then divided randomly (4:1) into a training set (80%) and a test set (20%). Gene expression data in the training set and control cohort were used for differential expression analysis. Differentially expressed genes, along with WHO severity score, location, age, and sex, were used for feature selection with least absolute shrinkage and selection operator (LASSO) in the training set. For LASSO analysis, samples were excluded if gene expression data were not obtained at study admission, no longitudinal clinical information was available, a bacterial infection at the time of study admission was present, or a fungal infection in the absence of a bacterial infection was detected. LASSO regression was performed using three subsets of predictor variables: patient data alone, gene expression data alone, or a combination of patient data and gene expression data. The accuracy of the resultant models was tested on data from the test set. FINDINGS:Between March, 2020, and October, 2021, we recruited 536 SARS-CoV-2-positive individuals and between June, 2013, and January, 2020, we recruited 74 participants into the control cohort. After prefiltering analysis and other exclusions, samples from 158 individuals were analysed in the training set and 47 in the test set. The expression of seven host genes (DAPP1, CST3, FGL2, GCH1, CIITA, UPP1, and RN7SL1) in the blood at the time of study admission was identified by LASSO as predictive of the risk of developing a secondary bacterial infection of the respiratory tract more than 24 h after study admission. Specifically, the expression of these genes in combination with a patient's WHO severity score at the time of study enrolment resulted in an area under the curve of 0·98 (95% CI 0·89-1·00), a true positive rate (sensitivity) of 1·00 (95% CI 1·00-1·00), and a true negative rate (specificity) of 0·94 (95% CI 0·89-1·00) in the test cohort. The combination of patient data and host transcriptomics at hospital admission identified all seven individuals in the training and test sets who developed a bacterial infection of the respiratory tract 5-9 days after hospital admission. INTERPRETATION:These data raise the possibility that host transcriptomics at the time of clinical presentation, together with machine learning, can forward predict the risk of secondary bacterial infections and allow for the more targeted use of antibiotics in viral infection. FUNDING:Snow Medical Research Foundation, the National Health and Medical Research Council, the Jack Ma Foundation, the Helmholtz-Association, the A2 Milk Company, National Institute of Allergy and Infectious Disease, and the Fondazione AIRC Associazione Italiana per la Ricerca contro il Cancro.

Antibiotic overuse has promoted the spread of antimicrobial resistance (AMR) with significant health and economic consequences. Genome sequencing reveals the widespread presence of antimicrobial resistance genes (ARGs) in diverse microbial environments. Hence, surveillance of resistance reservoirs, like the rarely explored oral microbiome, is necessary to combat AMR. Here, we characterise the development of the paediatric oral resistome and investigate its role in dental caries in 221 twin children (124 females and 97 males) sampled at three time points over the first decade of life. From 530 oral metagenomes, we identify 309 ARGs, which significantly cluster by age, with host genetic effects detected from infancy onwards. Our results suggest potential mobilisation of ARGs increases with age as the AMR associated mobile genetic element, Tn 916 transposase was co-located with more species and ARGs in older children. We find a depletion of ARGs and species in dental caries compared to health. This trend reverses in restored teeth. Here we show the paediatric oral resistome is an inherent and dynamic component of the oral microbiome, with a potential role in transmission of AMR and dysbiosis.

Background Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infected individuals display a wide spectrum of disease severity, as defined by the World Health Organization (WHO). One of the main factors underlying this heterogeneity is the host immune response, with severe COVID-19 often associated with a hyperinflammatory state. Aim Our current study aimed to pinpoint the specific genes and pathways underlying differences in the disease spectrum and outcomes observed, through in-depth analyses of whole blood transcriptomics in a large cohort of COVID-19 participants. Results All WHO severity levels were well represented and mild and severe disease displaying distinct gene expression profiles. WHO severity levels 1-4 were grouped as mild disease, and signatures from these participants were different from those with WHO severity levels 6-9 classified as severe disease. Severity level 5 (moderate cases) presented a unique transitional gene signature between severity levels 2-4 (mild/moderate) and 6-9 (severe) and hence might represent the turning point for better or worse disease outcome. Gene expression changes are very distinct when comparing mild/moderate or severe cases to healthy controls. In particular, we demonstrated the hallmark down-regulation of adaptive immune response pathways and activation of neutrophil pathways in severe compared to mild/moderate cases, as well as activation of blood coagulation pathways. Conclusions Our data revealed discrete gene signatures associated with mild, moderate, and severe COVID-19 identifying valuable candidates for future biomarker discovery.

Patients with preexisting metabolic disorders such as diabetes are at a higher risk of developing severe coronavirus disease 2019 (COVID-19). Mitochondrion, the very organelle that controls cellular metabolism, holds the key to understanding disease progression at the cellular level. Our current study aimed to understand how cellular metabolism contributes to COVID-19 outcomes. Metacore pathway enrichment analyses on differentially expressed genes (encoded by both mitochondrial and nuclear deoxyribonucleic acid (DNA)) involved in cellular metabolism, regulation of mitochondrial respiration and organization, and apoptosis, was performed on RNA sequencing (RNASeq) data from blood samples collected from healthy controls and patients with mild/moderate or severe COVID-19. Genes from the enriched pathways were analyzed by network analysis to uncover interactions among them and up- or downstream genes within each pathway. Compared to the mild/moderate COVID-19, the upregulation of a myriad of growth factor and cell cycle signaling pathways, with concomitant downregulation of interferon signaling pathways, were observed in the severe group. Matrix metallopeptidase 9 (MMP9) was found in five of the top 10 upregulated pathways, indicating its potential as therapeutic target against COVID-19. In summary, our data demonstrates aberrant activation of endocrine signaling in severe COVID-19, and its implication in immune and metabolic dysfunction.

Purpose Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness. Methods We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients. Results We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients. Conclusion These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.

Squamous cell carcinoma is the most common head and neck malignancy arising from the oral mucosa and the skin. The histologic and immunohistochemical features of oral squamous cell carcinoma (OSCC) and head and neck cutaneous squamous cell carcinoma (HNcSCC) are similar, making it difficult to identify the primary site in cases of metastases. With the advent of immunotherapy, reliable distinction of OSCC and HNcSCC at metastatic sites has important treatment and prognostic implications. Here, we investigate and compare the genomic landscape of OSCC and HNcSCC to identify diagnostically useful biomarkers. Whole-genome sequencing data from 57 OSCC and 41 HNcSCC patients were obtained for tumor and matched normal samples. Tumor mutation burden (TMB), Catalogue of Somatic Mutations in Cancer (COSMIC) mutational signatures, frequent chromosomal alterations, somatic single nucleotide, and copy number variations were analyzed. The median TMB of 3.75 in primary OSCC was significantly lower (P < .001) than that of 147.51 mutations/Mb in primary HNcSCC. The COSMIC mutation signatures were significantly different (P <.001) between OSCC and HNcSCC. OSCC showed COSMIC single-base substitution (SBS) mutation signature 1 and AID/APOBEC activityeassociated signature 2 and/or 13. All except 1 HNcSCC from hairbearing scalp showed UV damageeassociated COSMIC SBS mutation signature 7. Both OSCC and HNcSCC demonstrated a predominance of tumor suppressor gene mutations, predominantly TP53. The most frequently mutated oncogenes were PIK3CA and MUC4 in OSCC and HNcSCC, respectively. The metastases of OSCC and HNcSCC demonstrated TMB and COSMIC SBS mutation signatures similar to their primary counterparts. The combination of high TMB and UV signature in a metastatic keratinizing squamous cell carcinoma suggests HNcSCC as the primary site and may also facilitate decisions regarding immunotherapy. HNcSCC and OSCC show distinct genomic profiles despite histologic and immunohistochemical similarities. Their genomic characteristics may underlie differences in behavior and guide treatment decisions in recurrent and metastatic settings. (c) 2023 United States & Canadian Academy of Pathology. Published by Elsevier Inc. All rights reserved.

Knowledge of the mechanisms underpinning the development of protective immunity conferred by mRNA vaccines is fragmentary. Here, we investigated responses to coronavirus disease 2019 (COVID-19) mRNA vaccination via high-temporal resolution blood transcriptome profiling. The first vaccine dose elicited modest interferon and adaptive immune responses, which peaked on days 2 and 5, respectively. The second vaccine dose, in contrast, elicited sharp day 1 interferon, inflammation, and erythroid cell responses, followed by a day 5 plasmablast response. Both post-first and post-second dose interferon signatures were associated with the subsequent development of antibody responses. Yet, we observed distinct interferon response patterns after each of the doses that may reflect quantitative or qualitative differences in interferon induction. Distinct interferon response phenotypes were also observed in patients with COVID-19 and were associated with severity and differences in duration of intensive care. Together, this study also highlights the benefits of adopting high-frequency sampling protocols in profiling vaccine-elicited immune responses.

BACKGROUND: Determining the risk of developing severe acute pancreatitis (AP) on presentation to hospital is difficult but vital to enable early management decisions that reduce morbidity and mortality. The objective of this study was to determine global gene expression profiles of patients with different acute pancreatitis severity to identify genes and molecular mechanisms involved in the pathogenesis of severe AP. STUDY DESIGN: AP patients (n = 87) were recruited within 24 hours of admission to the Emergency Department and were confirmed to exhibit at least 2 of the following features: (1) abdominal pain characteristic of AP, (2) serum amylase and/or lipase more than 3-fold the upper laboratory limit considered normal, and/or (3) radiographically demonstrated AP on CT scan. Severity was defined according to the Revised Atlanta classification. Thirty-two healthy volunteers were also recruited and peripheral venous blood was collected for performing RNA-Seq. RESULTS: In severe AP, 422 genes (185 upregulated, 237 downregulated) were significantly differentially expressed when compared with moderately severe and mild cases. Pathway analysis revealed changes in specific innate and adaptive immune, sepsis-related, and surface modification pathways in severe AP. Data-driven approaches revealed distinct gene expression groups (endotypes), which were not entirely overlapping with the clinical Atlanta classification. Importantly, severe and moderately severe AP patients clustered away from healthy controls, whereas mild AP patients did not exhibit any clear separation, suggesting distinct underlying mechanisms that may influence severity of AP. CONCLUSION: There were significant differences in gene expression affecting the severity of AP, revealing a central role of specific immunological pathways. Despite the existence of patient endotypes, a 4-gene transcriptomic signature (S100A8, S100A9, MMP25, and MT-ND4L) was determined that can predict severe AP with an accuracy of 64%.

Background African ancestry is a significant risk factor for advanced prostate cancer (PCa). Mortality rates in sub-Saharan Africa are 2.5-fold greater than global averages. However, the region has largely been excluded from the benefits of whole genome interrogation studies. Additionally, while structural variation (SV) is highly prevalent, PCa genomic studies are still biased towards small variant interrogation. Methods Using whole genome sequencing and best practice workflows, we performed a comprehensive analysis of SVs for 180 (predominantly Gleason score ≥ 8) prostate tumours derived from 115 African, 61 European and four ancestrally admixed patients. We investigated the landscape and relationship of somatic SVs in driving ethnic disparity (African versus European), with a focus on African men from southern Africa. Results Duplication events showed the greatest ethnic disparity, with a 1.6- (relative frequency) to 2.5-fold (count) increase in African-derived tumours. Furthermore, we found duplication events to be associated with CDK12 inactivation and MYC copy number gain, and deletion events associated with SPOP mutation. Overall, African-derived tumours were 2-fold more likely to present with a hyper-SV subtype. In addition to hyper-duplication and deletion subtypes, we describe a new hyper-translocation subtype. While we confirm a lower TMPRSS2-ERG fusion-positive rate in tumours from African cases (10% versus 33%), novel African-specific PCa ETS family member and TMPRSS2 fusion partners were identified, including LINC01525, FBXO7 , GTF3C2 , NTNG1 and YPEL5 . Notably, we found 74 somatic SV hotspots impacting 18 new candidate driver genes, with CADM2 , LSAMP , PTPRD , PDE4D and PACRG having therapeutic implications for African patients. Conclusions In this first African-inclusive SV study for high-risk PCa, we demonstrate the power of SV interrogation for the identification of novel subtypes, oncogenic drivers and therapeutic targets. Identifying a novel spectrum of SVs in tumours derived from African patients provides a mechanism that may contribute, at least in part, to the observed ethnic disparity in advanced PCa presentation in men of African ancestry.

Modulation of individual macronutrients or caloric density is known to regulate host resistance to infection in mice. However, the impact of diet composition, independent of macronutrient and energy content, on infection susceptibility is unclear. We show that two laboratory rodent diets, widely used as standard animal feeds and experimental controls, display distinct abilities in supporting mice during influenza infection. Mice placed on the highly processed AIN93G showed increased mortality to infection compared with those on a grain-based chow diet, suggesting a detrimental role for highly processed food in host defense. We further demonstrate that the heightened susceptibility of AIN93G-fed mice was associated with the failure in homeostasis restoration mediated by the cytokine interferon (IFN)-γ. Our findings show that diet composition calibrates host survival threshold by regulating adaptive homeostasis and highlights a pivotal role for extrinsic signals in host phenotype and outcome of host-pathogen interaction.

Prostate cancer is characterized by considerable geo-ethnic disparity. African ancestry is a significant risk factor, with mortality rates across sub-Saharan Africa of 2.7-fold higher than global averages 1 . The contributing genetic and non-genetic factors, and associated mutational processes, are unknown 2 , 3 . Here, through whole-genome sequencing of treatment-naive prostate cancer samples from 183 ancestrally (African versus European) and globally distinct patients, we generate a large cancer genomics resource for sub-Saharan Africa, identifying around 2 million somatic variants. Significant African-ancestry-specific findings include an elevated tumour mutational burden, increased percentage of genome alteration, a greater number of predicted damaging mutations and a higher total of mutational signatures, and the driver genes NCOA2 , STK19 , DDX11L1 , PCAT1 and SETBP1 . Examining all somatic mutational types, we describe a molecular taxonomy for prostate cancer differentiated by ancestry and defined as global mutational subtypes (GMS). By further including Chinese Asian data, we confirm that GMS-B (copy-number gain) and GMS-D (mutationally noisy) are specific to African populations, GMS-A (mutationally quiet) is universal (all ethnicities) and the African–European-restricted subtype GMS-C (copy-number losses) predicts poor clinical outcomes. In addition to the clinical benefit of including individuals of African ancestry, our GMS subtypes reveal different evolutionary trajectories and mutational processes suggesting that both common genetic and environmental factors contribute to the disparity between ethnicities. Analogous to gene–environment interaction—defined here as a different effect of an environmental surrounding in people with different ancestries or vice versa—we anticipate that GMS subtypes act as a proxy for intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies.

INTRODUCTION:Oral squamous cell carcinoma (OSCC) in the young (<50 years), without known carcinogenic risk factors, is on the rise globally. Whole genome duplication (WGD) has been shown to occur at higher rates in cancers without an identifiable carcinogenic agent. We aimed to evaluate the prevalence of WGD in a cohort of OSCC patients under the age of 50 years.METHODS:Whole genome sequencing (WGS) was performed on 28 OSCC patients from the Sydney Head and Neck Cancer Institute (SHNCI) biobank. An additional nine cases were obtained from The Cancer Genome Atlas (TCGA).RESULTS:WGD was seen in 27 of 37 (73%) cases. Non-synonymous, somatic TP53 mutations occurred in 25 of 27 (93%) cases of WGD and were predicted to precede WGD in 21 (77%). WGD was significantly associated with larger tumor size (p = 0.01) and was frequent in patients with recurrences (87%, p = 0.36). Overall survival was significantly worse in those with WGD (p = 0.05).CONCLUSIONS:Our data, based on one of the largest WGS datasets of young patients with OSCC, demonstrates a high frequency of WGD and its association with adverse pathologic characteristics and clinical outcomes. TP53 mutations also preceded WGD, as has been described in other tumors without a clear mutagenic driver.

Additional file 2: Table S4. Summary of gene fusions identified from SVs. Table S5. SV calls resulting in gene fusions.

Congenital sensorineural deafness (CSD) has been reported to affect up to 30% of Dalmatian dogs world-wide and while unilaterally deaf dogs can live a close to normal life, dogs suffering bilateral deafness are frequently euthanized. Extreme-white coat patterning as encoded by the gene Melanocyte Inducing Transcription Factor (MITF) has long been postulated as the major risk factor for CSD in the Dalmatian breed. While attempts to identify causative risk variants associated with CSD have been numerous, no genome-wide association study has positively identified MITF as a risk locus for either bilateral or unilateral deafness in the Dalmatian breed to date. In this study, we identified an association with CSD on CFA20 in the vicinity of MITF within Australian Dalmatian dogs. Although not genome-wide significant, the association signal was validated by reanalysing publicly available data and merging the wider data resource with the local data to improve statistical power. The merged data, representing three major global populations of Dalmatian dogs, enabled us to identify a single, well-defined genome-wide significant risk haplotype for CSD. The haplotype was formed by three genome-wide significant associated markers (BICF2G630233852T>C, BICF2G630233861T>C, BICF2G630233888G>A) on CFA20 with 62% of bilaterally deaf dogs homozygous for the risk haplotype (CCA), while 30% of bilaterally deaf and 45% of hearing dogs carried one copy of the risk haplotype. Animals homozygous or heterozygous for the low-risk haplotype were less likely to be unilaterally deaf. While the association between the risk haplotype and deafness is incomplete, animals homozygous for the risk haplotype were 10-times more likely to be bilaterally deaf. Although the underlying causative variants are yet to be discovered, results from this study can now assist with reducing deafness in Dalmatian dogs.