Whole genome sequencing of a German cohort to understand host genetics in COVID-19

Background/Objectives: The disease course upon SARS-CoV-2 infection is highly variable and comprises a range from asymptomatic infection to severe (and even lethal) COVID-19. Genetic factors substantially contribute to this variability, as evidenced by epidemiological studies and recent results from genome-wide association studies (GWAS) as well as sequencing-based approaches. The host genetics group of the German COVID-19 OMICs Initiative (DeCOI) has been founded with the aim to identify additional genetic variants that influence COVID-19 severity through whole genome sequencing (WGS) analyses. Method(s): Until January 2022, WGS has been performed on approximately 1200 individuals affected by COVID-19. Result(s): The most recent data freeze comprised 952 individuals. In this dataset, no carrier of a deleterious protein-altering variant has been detected in TLR7, which is the only conclusive risk gene for severe COVID-19. Applying a gene-based association test of rare variants to the subcohort of European individuals (n = 752, mean age: 56 years, females: 44%), including 199 severely affected individuals, we did not observe any significant association after correction for multiple testing. Exome-wide association analysis of common variants in this subcohort replicated the GWAS-locus on chromosome 3. Conclusion(s): With this ongoing work, we are contributing to international efforts to elucidate the host genetics of COVID-19, also by sharing our summary statistics for meta-analyses. Currently, we are sequencing additional severely affected individuals and we are refining analytical strategies, which will also include the joint analysis of common and rare variants at genomewide scale.

A comprehensive review on technological advances in alternate drug discovery process:Drug repurposing

The traditional de novo drug discovery is time consuming, costly and in some instances the drugs will fail to treat the disease which result in a huge loss to the organization. Drug repurposing is an alternative drug discovery process to overcome the limitations of the De novo drug discovery process. Ithelps for the identification of drugs to the rare diseases as well as in the pandemic situationwithin short span of time in a cost-effective way. The underlying principle of drug repurposing is that most of the drugs identified on a primary purpose have shown to treat other diseases also. One such example is Tocilizumab is primarily used for rheumatoid arthritis and it is repurposed to treat cancer and COVID-19. At present, nearly30% of the FDA approved drugs to treat various diseases are repurposed drugs. The drug repurposing is either drug-centric or disease centric and can be studied by using both experimental and in silico studies. The in silico repurpose drug discovery process is more efficient as it screens thousands of compounds from the diverse libraries within few days by various computational methods like Virtual screening, Docking, MD simulations,Machine Learning, Artificial Intelligence, Genome Wide Association Studies (GWAS), etc. with certain limitations.These limitationscan be addressed by effective integration of advanced technologies to identify a novel multi-purpose drug.Copyright © 2023, Association of Biotechnology and Pharmacy. All rights reserved.

A survival genome-wide association study to identify variants associated with COVID-19 risk of death

Background/Objectives: SARS-CoV-2 infection clinical manifestations hugely vary among patients, ranging from no symptoms, to life-threatening conditions. This variability is also due to host genetics: COVID-19 Host Genetics Initiative identified six loci associated with COVID-19 severity in a previous case-control genome-wide association study. A different approach to investigate the genetics of COVID-19 severity is looking for variants associated with mortality, e.g. by analyzing the association between genotypes and time-to-event data. Method(s): Here we perform a case-only genome-wide survival analysis, of 1,777 COVID-19 patients from the GEN-COVID cohort, 60 days after infection/hospitalization. Case-only studies has the advantage of eliminating selection biases and confounding related to control subjects. Patients were genotyped using Illumina Infinium Global Screening Arrays. PLINK software was used for data quality check and principal component analysis. GeneAbel R package was used for survival analysis and age, sex and the first four principal components were used as covariates in the Cox proportional hazard model. Result(s): We found four variants associated with COVID-19 patient survival at a nominal P < 1.0 x 10-6. Their minor alleles were associated with a higher mortality risk (i.e. hazard ratios (HR)>1). In detail, we observed: HR=1.03 for rs28416079 on chromosome 19 (P=1.34 x 10-7), HR=1.15 for rs72815354 on chromosome 10 (P=1.66 x 10-7), HR=2.12 for rs2785631 on chromosome 1 (P=5.14 x 10-7), and HR=2.27 for rs2785631 on chromosome 5 (P=6.65 x 10-7). Conclusion(s): The present results suggest that germline variants are COVID-19 prognostic factors. Replication in the remaining HGI COVID-19 patient cohort (EGAS00001005304) is ongoing at the time of submission.

Genetic associations from the Long COVID-19 Host Genetics Initiative contribute to understanding of the genetics of prolonged symptoms in COVID-19

Background/Objectives: One of the most remarkable features of SARS-CoV-2 infection is that a large proportion of individuals are asymptomatic while others experience progressive, even lifethreatening acute respiratory distress syndrome, and some suffer from prolonged symptoms (long COVID). The contribution of host genetics to susceptibility and severity of infectious disease is well-documented, and include rare monogenic inborn errors of immunity as well as common genetic variation. Studies on genetic risk factors for long COVID have not yet been published. Method(s): We compared long COVID (1534) to COVID-19 patients (96,692) and population controls (800,353) using both questionnaire and EHR- based studies. First meta-analysis of 11 GWAS studies from 8 countries did not show genome-wide significant associations. Result(s): Testing 24 variants earlier associated to COVID-19 susceptibility or severity by COVID-19 Host Genetics Initiative showed genetic variation in rs505922, an intronic variant in ABO blood group gene, to be associated with long COVID compared to population controls (OR = 1.16, 95% CI: 1.07-1.27, p = 0.033). (Within-COVID analysis gave similar OR, but was not significant after conservative Bonferroni correction (OR = 1.17, 95% CI: 1.06-1.30, p = 092)). Conclusion(s): The first data freeze of the Long COVID Host Genetics Initiative suggests that the O blood group is associated with a 14% reduced risk for long COVID. The following data freezes with growing sample sizes will possibly elucidate long COVID pathophysiology and pave the way for possible treatments for long lasting COVID symptoms.

Genetic overlap study between idiopathic pulmonary fibrosis and COVID-19

Background/Objectives: Genetic factors influence COVID-19 susceptibility and outcomes, including the development of pulmonary fibrosis (i.e. lung scarring). Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease and the most common cause of pulmonary fibrosis in the general population. Genome-wide association studies (GWAS) of COVID-19 and IPF revealed genes associated with both diseases, suggesting these share genetic risk factors. Here we performed a genetic overlap study between COVID-19 and IPF. Method(s): Summary statistics from an IPF 5-way meta-GWAS and from the COVID-19 Host Genetics initiative GWAS metaanalysis (v6) were used. We performed genetic correlation analyses and assessed individual genetic signals to identify those variants shared between both traits. We conducted colocalisation analyses to determine whether the same causal variant was driving both traits. Finally, the association of overlapping variants with gene expression was assessed and a phenome-wide association study was performed. Result(s): There was a positive genetic correlation between severe COVID-19 and IPF. We found four genetic loci with likely shared causal variants between both traits, including one novel risk locus at 7q22.1 that colocalised with decreased ZKSCAN1 and TRIM4 expression in blood. The other three loci colocalised with MUC5B, ATP11A and DPP9 expression. The locus associated with increased ATP11A expression was also associated with higher Hb1AC levels, a biomarker used in diabetes. Conclusion(s): Results suggest there are shared biological processes driving IPF and severe COVID-19 phenotypes.

Germline rare variants of lectin pathway genes predispose to asymptomatic SARS-CoV-2 infection in elderly individuals

Background/Objectives: Emerging evidence suggests that complement system infection-dependent hyperactivation may worsen COVID-19 outcome. We investigated the role of predicted high impact variants -referred as Qualifying Variants (QVs) -of complement system genes in predisposing asymptomatic COVID-19 in elderly individuals, known to be more susceptible to severe disease. Method(s): Exploiting Whole-Exome Sequencing (WES) data and 56 complement system genes, we performed a gene-based collapsing test between 164 asymptomatic subjects (age >= 60 y.o.) and 56,885 European individuals from the gnomAD database. We replicated this test comparing the same asymptomatic individuals with 147 hospitalized COVID-19 patients. Result(s): We found an enrichment of QVs in three genes (MASP1, COLEC10 and COLEC11), which belong to the lectin pathway, in the asymptomatic cohort. Moreover, individuals with QVs showed lower serum levels of Masp1 and of prothrombin activity compared to controls while no differences were observed for CH50 and AH50 levels that measure the activity of classical and alternative complement pathways, respectively. Finally, integrative analyses of genome-wide association study and expression quantitative loci traits data showed a correlation between polymorphisms associated with asymptomatic COVID-19 and decreased expression of MASP1, COLEC11 and COLEC10 genes in lung tissue. Conclusion(s): This study suggests that rare genetic variants can protect from severe COVID-19 by mitigating the activation of lectin pathway and prothrombin activity.

Identification of genetic determinants of COVID-19 severity by exome sequencing

Background/Objectives: The severity of the symptoms of coronavirus disease 2019 (COVID-19) has been associated to age, comorbidity, and male sex. Besides virus characteristics, host genetic factors influence the infection outcome. Different genome-wide association studies and meta-analyses investigated the contribution of common variants, whereas the role of rare variants just started to be elucidated. Our goal is to determine the contribution of rare variants to the development of severe COVID-19 in the Italian population. Method(s): We compared the genetic background of 215 severe COVID-19 patients with 1764 individuals from the general population. Rare variants (minor allele frequency <1%) from wholeexome sequencing data were retrieved using a bioinformatics variant discovery pipeline. We tested the impact of rare variants (classified according to their predicted effect on the gene product) both using a burden test design, and an iterative machine learning (ML) approach. Result(s): We identified a total of 690,000 rare variants in the entire examined population. Among them, 250 were associated with COVID-19 severity at a nominal P < 0.05. Gene-based burden test revealed a gene with an excess of loss-of-function mutations at P < 0.05. Finally, the ML approach, analysing all the 690,000 rare variants, identified the best combination of variants that is able to predict COVID-19 severity in our cohort. Conclusion(s): Our work provides new insights on the genetic signature of COVID-19 in the Italian population. The most informative rare variants could be exploited to define individuals' risk profiles to COVID-19 severity for the Italian population.

A systematical association analysis of 25 common virus infection and genetic susceptibility of COVID-19 infection.

OBJECTIVES: Previous studies identified a number of diseases were associated with 2019 coronavirus disease (COVID-19). However, the associations between these diseases related viral infections and COVID-19 remains unknown now. METHODS: In this study, we utilized single nucleotide polymorphisms (SNPs) related to COVID-19 from genome-wide association study (GWAS) and individual-level genotype data from the UK biobank to calculate polygenic risk scores (PRS) of 487,409 subjects for eight COVID-19 clinical phenotypes. Then, multiple logistic regression models were established to assess the correlation between serological measurements (positive/negative) of 25 viruses and the PRS of eight COVID-19 clinical phenotypes. And we performed stratified analyses by age and gender. RESULTS: In whole population, we identified 12 viruses associated with the PRS of COVID-19 clinical phenotypes, such as VZV seropositivity for Varicella Zoster Virus (Unscreened/Exposed_Negative: ß = 0.1361, P = 0.0142; Hospitalized/Unscreened: ß = 0.1167, P = 0.0385) and MCV seropositivity for Merkel Cell Polyomavirus (Unscreened/Exposed_Negative: ß = -0.0614, P = 0.0478). After age stratification, we identified seven viruses associated with the PRS of eight COVID-19 clinical phenotypes. After gender stratification, we identified five viruses associated with the PRS of eight COVID-19 clinical phenotypes in the women group. CONCLUSION: Our study findings suggest that the genetic susceptibility to different COVID-19 clinical phenotypes is associated with the infection status of various common viruses.

Molecular genetics and genomics of the ABO blood group system

The A and B oligosaccharide antigens of the ABO blood group system are produced from the common precursor, H substance, by enzymatic reactions catalyzed by A and B glycosyltransferases (AT and BT) encoded by functional A and B alleles at the ABO genetic locus, respectively. In 1990, my research team cloned human A, B, and O allelic cDNAs. We then demonstrated this central dogma of ABO and opened a new era of molecular genetics. We identified four amino acid substitutions between AT and BT and inactivating mutations in the O alleles, clarifying the allelic basis of ABO. We became the first to achieve successful ABO genotyping, discriminating between AA and AO genotypes and between BB and BO, which was impossible using immunohematological/serological methods. We also identified mutations in several subgroup alleles and also in the cis-AB and B(A) alleles that specify the expression of the A and B antigens by single alleles. Later, other scientists interested in the ABO system characterized many additional ABO alleles. However, the situation has changed drastically in the last decade, due to rapid advances in next-generation sequencing (NGS) technology, which has allowed the sequencing of several thousand genes and even the entire genome in individual experiments. Genome sequencing has revealed not only the exome but also transcription/translation regulatory elements. RNA sequencing determines which genes and spliced transcripts are expressed. Because more than 500,000 human genomes have been sequenced and deposited in sequence databases, bioinformaticians can retrieve and analyze this data without generating it. Now, in this era of genomics, we can harness the vast sequence information to unravel the molecular mechanisms responsible for important biological phenomena associated with the ABO polymorphism. Two examples are presented in this review: the delineation of the ABO gene evolution in a variety of species and the association of single nucleotide variant (SNV) sites in the ABO gene with diseases and biological parameters through genome-wide association studies (GWAS).Copyright © Annals of Blood. All rights reserved.

Genetic correlation, causal relationship, and shared loci between vitamin D and COVID-19: A genome-wide cross-trait analysis.

Observational studies have shown that vitamin D supplementation reduces the risk of COVID-19 infection, yet little is known about the shared genomic architectures between them. Leveraging large-scale genome-wide association study (GWAS) summary statistics, we investigated the genetic correlation and causal relationship between genetically determined vitamin D and COVID-19 using linkage disequilibrium score regression and Mendelian randomization (MR) analyses, and conducted a cross-trait GWAS meta-analysis to identify the overlapping susceptibility loci of them. We observed a significant genetic correlation between genetically predicted vitamin D and COVID-19 (rg = -0.143, p = 0.011), and the risk of COVID-19 infection would decrease by 6% for every 0.76 nmol L-1 increase of serum 25 hydroxyvitamin D (25OHD) concentrations in generalized MR (OR = 0.94, 95% CI: 0.89-0.99, p = 0.019). We identified rs4971066 (EFNA1) as a risk locus for the joint phenotype of vitamin D and COVID-19. In conclusion, genetically determined vitamin D is associated with COVID-19. Increased levels of serum 25OHD concentration may benefit the prevention and treatment of COVID-19.

Federated Learning for Healthcare Domain - Pipeline, Applications and Challenges

Federated learning is the process of developing machine learning models over datasets distributed across data centers such as hospitals, clinical research labs, and mobile devices while preventing data leakage. This survey examines previous research and studies on federated learning in the healthcare sector across a range of use cases and applications. Our survey shows what challenges, methods, and applications a practitioner should be aware of in the topic of federated learning. This paper aims to lay out existing research and list the possibilities of federated learning for healthcare industries.© 2022 Copyright held by the owner/author(s).

A genome wide association study of chronic spontaneous urticaria risk and heterogeneity.

BACKGROUND: Chronic spontaneous urticaria (CSU) is a dermatologic condition that is characterized by spontaneous, pruritic hives and/or angioedema that persist for six weeks or longer with no identifiable trigger. Anti-histamines and second line therapies such as omalizumab are effective for some CSU patients, but others remain symptomatic with significant impact on quality of life. This variable response to treatment and autoantibodies levels across patients highlight clinically heterogeneous subgroups. OBJECTIVE: We aimed to highlight pathways involved in CSU by investigating the genetics of CSU risk and subgroups. METHODS: We performed a genome-wide association study (GWAS) of 679 CSU patients and 4,446 controls and a GWAS of Chronic Urticaria (CU) index, which measures IgG autoantibodies levels, by comparing 447 CU-index low to 183 CU-index high patients. We also tested whether polygenic scores for autoimmune-related disorders associate with CSU risk and CU-index. RESULTS: We identified two loci significantly associated with disease risk. The strongest association maps to position 56 of HLA-DQA1 (P=1.69x10-9), where the arginine residue was associated with increased risk (OR=1.64). The second association signal colocalizes with expression-quantitative trait loci for ITPKB in whole blood (probabilitycolocalization=0.997). The arginine residue at position 56 of HLA-DQA1 was also associated with increased risk of CU-index high (P=6.15x10-5, OR=1.86), while the ITKPB association was not (P=0.64). Polygenic scores for three autoimmune-related disorders (hypothyroidism, type-1 diabetes, and vitiligo) are associated with CSU risk and CU-index (P<2.34x10-3, OR>1.72). CONCLUSION: This GWAS of CSU identifies two genome-wide significant loci and highlights the shared genetics between CU-index and autoimmune disorders.

Transcriptome Profiling in Autoimmune Diseases

Autoimmune diseases are a group of different inflammatory disorders characterized by systemic or localized inflammation, affecting approximately 0.1–1% of the general population. Several studies suggest that genetic risk loci are shared between different autoimmune diseases and pathogenic mechanisms may also be shared. The strategy of performing differential gene expression profiles in autoimmune disorders has unveiled new transcripts that may be shared among these disorders. Microarray technology and bioinformatics offer the most comprehensive molecular evaluations and it is widely used to understand the changes in gene expression in specific organs or in peripheral blood cells. The major goal of transcriptome studies is the identification of specific biomarkers for different diseases. It is believed that such knowledge will contribute to the development of new drugs, new strategies for early diagnosis, avoiding tissue autoimmune destruction, or even preventing the development of autoimmune disease. In this review, we primarily focused on the transcription profiles of three typical autoimmune disorders, including type 1 diabetes mellitus (destruction of pancreatic islet beta cells), systemic lupus erythematosus (immune complex systemic disorder affecting several organs and tissues), and multiple sclerosis (inflammatory and demyelinating disease of the nervous system). © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2014, 2022.

Drug repurposing against COVID-19 by GWAS

This note is prepared by the authors of a recent publication on shared genetic architecture of drug response based on summary statistics from genome-wide association studies (GWAS) to propose a drug repurposing approach for the treatment of coronavirus COVID-19. The authors proposed that in silico studies may be preceded by analyzing shared genetic architecture of drug response based on existing GWAS.Copyright © 2020, Health Biotechnology and Biopharma.

Causal effects of COVID-19 on cancer risk: A Mendelian randomization study.

In contemporary literature, little attention has been paid to the association between coronavirus disease-2019 (COVID-19) and cancer risk. We performed the Mendelian randomization (MR) to investigate the causal associations between the three types of COVID-19 exposures (critically ill COVID-19, hospitalized COVID-19, and respiratory syndrome coronavirus 2 (SARS-CoV-2) infection) and 33 different types of cancers of the European population. The results of the inverse-variance-weighted model indicated that genetic liabilities to critically ill COVID-19 had suggestive causal associations with the increased risk for HER2-positive breast cancer (odds ratio [OR] = 1.0924; p-value = 0.0116), esophageal cancer (OR = 1.0004; p-value = 0.0226), colorectal cancer (OR = 1.0010; p-value = 0.0242), stomach cancer (OR = 1.2394; p-value = 0.0331), and colon cancer (OR = 1.0006; p-value = 0.0453). The genetic liabilities to hospitalized COVID-19 had suggestive causal associations with the increased risk for HER2-positive breast cancer (OR = 1.1096; p-value = 0.0458), esophageal cancer (OR = 1.0005; p-value = 0.0440) as well as stomach cancer (OR = 1.3043; p-value = 0.0476). The genetic liabilities to SARS-CoV-2 infection had suggestive causal associations with the increased risk for stomach cancer (OR = 2.8563; p-value = 0.0019) but with the decreasing risk for head and neck cancer (OR = 0.9986, p-value = 0.0426). The causal associations of the above combinations were robust through the test of heterogeneity and pleiotropy. Together, our study indicated that COVID-19 had causal effects on cancer risk.

Combined effects of inflammation and coronavirus disease 2019 (COVID-19) on the risks of anxiety and depression: A cross-sectional study based on UK Biobank.

Infection-induced perturbation of immune homeostasis could promote psychopathology. Psychiatric sequelae have been observed after previous coronavirus outbreaks. However, limited studies were conducted to explore the potential interaction effects of inflammation and coronavirus disease 2019 (COVID-19) on the risks of anxiety and depression. In this study, first, polygenic risk scores (PRS) were calculated for eight COVID-19 clinical phenotypes using individual-level genotype data from the UK Biobank. Then, linear regression models were developed to assess the effects of COVID-19 PRS, C-reactive protein (CRP), systemic immune inflammation index (SII), and their interaction effects on the Generalized Anxiety Disorder-7 (GAD-7, 104 783 individuals) score and the Patient Health Questionnaire-9 (PHQ-9, 104 346 individuals) score. Several suggestive interactions between inflammation factors and COVID-19 clinical phenotypes were detected for PHQ-9 score, such as CRP/SII × Hospitalized/Not_Hospitalized in women group and CRP × Hospitalized/Unscreened in age >65 years group. For GAD-7 score, we also found several suggestive interactions, such as CRP × Positive/Unscreened in the age ≤65 years group. Our results suggest that not only COVID-19 and inflammation have important effects on anxiety and depression but also the interactions of COVID-19 and inflammation have serious risks for anxiety and depression.

Genetic Liability to Cannabis Use Disorder and COVID-19 Hospitalization.

BACKGROUND: Vulnerability to COVID-19 hospitalization has been linked to behavioral risk factors, including combustible psychoactive substance use (e.g., tobacco smoking). Paralleling the COVID-19 pandemic crisis have been increasingly permissive laws for recreational cannabis use. Cannabis use disorder (CUD) is a psychiatric disorder that is heritable and genetically correlated with respiratory disease, independent of tobacco smoking. We examined the genetic relationship between CUD and COVID-19 hospitalization. METHODS: We estimated the genetic correlation between CUD (case: n = 14,080; control: n = 343,726) and COVID-19 hospitalization (case: n = 9373; control: n = 1,197,256) using summary statistics from genome-wide association studies. Using independent genome-wide association studies conducted before the pandemic, we controlled for several covariates (i.e., tobacco use phenotypes, problematic alcohol use, body mass index, fasting glucose, forced expiratory volume, education attainment, risk taking, attention-deficit/hyperactivity disorder, Townsend deprivation index, chronic obstructive pulmonary disease, hypertension, and type 2 diabetes) using genomic structural equation modeling. Genetic causality between CUD and COVID-19 hospitalization was estimated using latent causal variable models. RESULTS: Genetic vulnerability to COVID-19 was correlated with genetic liability to CUD (r G  = 0.423 [SE = 0.0965], p = 1.33 × 10-6); this association remained when accounting for genetic liability to related risk factors and covariates (b = 0.381-0.539, p = .012-.049). Latent causal variable analysis revealed causal effect estimates that were not statistically significant. CONCLUSIONS: Problematic cannabis use and vulnerability to serious COVID-19 complications share genetic underpinnings that are unique from common correlates. While CUD may plausibly contribute to severe COVID-19 presentations, causal inference models yielded no evidence of putative causation. Curbing excessive cannabis use may mitigate the impact of COVID-19.

The Genetics of Primary Biliary Cholangitis: A GWAS and Post-GWAS Update.

Primary biliary cholangitis (PBC) is a chronic, progressive cholestatic liver disease in which the small intrahepatic bile ducts are destroyed by autoimmune reactions. Among autoimmune diseases, which are polygenic complex traits caused by the combined contribution of genetic and environmental factors, PBC exhibits the strongest involvement of genetic heritability in disease development. As at December 2022, genome-wide association studies (GWASs) and associated meta-analyses identified approximately 70 PBC susceptibility gene loci in various populations, including those of European and East Asian descent. However, the molecular mechanisms through which these susceptibility loci affect the pathogenesis of PBC are not fully understood. This study provides an overview of current data regarding the genetic factors of PBC as well as post-GWAS approaches to identifying primary functional variants and effector genes in disease-susceptibility loci. Possible mechanisms of these genetic factors in the development of PBC are also discussed, focusing on four major disease pathways identified by in silico gene set analyses, namely, (1) antigen presentation by human leukocyte antigens, (2) interleukin-12-related pathways, (3) cellular responses to tumor necrosis factor, and (4) B cell activation, maturation, and differentiation pathways.

Zooanthroponotic transmission of SARS-CoV-2 and host-specific viral mutations revealed by genome-wide phylogenetic analysis.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a generalist virus, infecting and evolving in numerous mammals, including captive and companion animals, free-ranging wildlife, and humans. Transmission among non-human species poses a risk for the establishment of SARS-CoV-2 reservoirs, makes eradication difficult, and provides the virus with opportunities for new evolutionary trajectories, including the selection of adaptive mutations and the emergence of new variant lineages. Here, we use publicly available viral genome sequences and phylogenetic analysis to systematically investigate the transmission of SARS-CoV-2 between human and non-human species and to identify mutations associated with each species. We found the highest frequency of animal-to-human transmission from mink, compared with lower transmission from other sampled species (cat, dog, and deer). Although inferred transmission events could be limited by sampling biases, our results provide a useful baseline for further studies. Using genome-wide association studies, no single nucleotide variants (SNVs) were significantly associated with cats and dogs, potentially due to small sample sizes. However, we identified three SNVs statistically associated with mink and 26 with deer. Of these SNVs, ~⅔ were plausibly introduced into these animal species from local human populations, while the remaining ~⅓ were more likely derived in animal populations and are thus top candidates for experimental studies of species-specific adaptation. Together, our results highlight the importance of studying animal-associated SARS-CoV-2 mutations to assess their potential impact on human and animal health.