Association Analysis Research Articles

Comprehensive Analysis of Gallstone Composition and Association with Risk Factors in Bangladesh: Insights into the burden and outlook for prevention and management.

Comprehensive Analysis of Gallstone Composition and Association with Risk Factors in Bangladesh: Insights into the burden and outlook for prevention and management.

To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice.

To develop recommendations regarding the use of weights to reduce selection bias for commonly performed analyses using electronic health record (EHR)-linked biobank data. We mapped diagnosis (ICD code) data to standardized phecodes from 3 EHR-linked biobanks with varying recruitment strategies: All of Us (AOU; n = 244071), Michigan Genomics Initiative (MGI; n = 81243), and UK Biobank (UKB; n = 401167). Using 2019 National Health Interview Survey data, we constructed selection weights for AOU and MGI to represent the US adult population more. We used weights previously developed for UKB to represent the UKB-eligible population. We conducted 4 common analyses comparing unweighted and weighted results. For AOU and MGI, estimated phecode prevalences decreased after weighting (weighted-unweighted median phecode prevalence ratio [MPR]: 0.82 and 0.61), while UKB estimates increased (MPR: 1.06). Weighting minimally impacted latent phenome dimensionality estimation. Comparing weighted versus unweighted phenome-wide association study for colorectal cancer, the strongest associations remained unaltered, with considerable overlap in significant hits. Weighting affected the estimated log-odds ratio for sex and colorectal cancer to align more closely with national registry-based estimates. Weighting had a limited impact on dimensionality estimation and large-scale hypothesis testing but impacted prevalence and association estimation. When interested in estimating effect size, specific signals from untargeted association analyses should be followed up by weighted analysis. EHR-linked biobanks should report recruitment and selection mechanisms and provide selection weights with defined target populations. Researchers should consider their intended estimands, specify source and target populations, and weight EHR-linked biobank analyses accordingly.

Genome-wide association analyses of breast cancer in women of African ancestry identify new susceptibility loci and improve risk prediction.

We performed genome-wide association studies of breast cancer including 18,034 cases and 22,104 controls of African ancestry. Genetic variants at 12 loci were associated with breast cancer risk (P < 5 × 10-8), including associations of a low-frequency missense variant rs61751053 in ARHGEF38 with overall breast cancer (odds ratio (OR) = 1.48) and a common variant rs76664032 at chromosome 2q14.2 with triple-negative breast cancer (TNBC) (OR = 1.30). Approximately 15.4% of cases with TNBC carried six risk alleles in three genome-wide association study-identified TNBC risk variants, with an OR of 4.21 (95% confidence interval = 2.66-7.03) compared with those carrying fewer than two risk alleles. A polygenic risk score (PRS) showed an area under the receiver operating characteristic curve of 0.60 for the prediction of breast cancer risk, which outperformed PRS derived using data from females of European ancestry. Our study markedly increases the population diversity in genetic studies for breast cancer and demonstrates the utility of PRS for risk prediction in females of African ancestry.

Soil microbial identity explains home-field advantage for litter decomposition.

Unraveling the mechanisms of home-field advantage (HFA) is essential to gain a complete understanding of litter decomposition processes. However, knowledge of the relationships between HFA effects and microbial communities is lacking. To examine HFA effects on litter decomposition, we identified the microbial communities and conducted a reciprocal transplant experiment, including all possible combinations of soil and litter, between sites at two elevations in cool-temperate forests. Soil origin, rather than HFA, was an important factor in controlling litter decomposition processes. Microbiome-wide association analyses identified litter fungi and bacteria specific to the source soil, which completely differed at a low taxonomic level between litter types. The relative abundance of these microbes specific to source soil was positively correlated with litter mass loss. The results indicated that the unique relationships between plant litter and soil microbes through plant-soil linkages drive litter decomposition processes. In the short term, soil disturbances resulting from land-use changes have the potential to disrupt the effect of soil origin and hinder the advancement of litter decomposition. These findings contribute to an understanding of HFA mechanisms and the impacts of land-use change on decomposition processes in forest ecosystems.

Genetic variability, correlation and path analysis in the BC2F2 population of groundnut

The present study was carried out in the backcross population of groundnut involving TMV 7 and ICG 15419. Allele-specific primers were used to screen the population for high oleic acid and a total of 11 yield-contributing traits were included in this study. The number of primary and secondary branches had higher estimates of PCV and GCV whereas pod yield per plant had moderate PCV but low GCV. Along with the variability parameters, plant height, number of primary and secondary branches, pod width, 100 pod weight, oleic acid content and linoleic acid content had good estimates of heritability and genetic advance as a percent of the mean, whereas pod yield per plant had moderate and low, heritability and GAM respectively, with a negatively significant skewed distribution. Association analysis exhibited a positive correlation between the number of primary branches, number of secondary branches, pod length and 100 pod weight with pod yield per plant and it was evident that oleic acid was indirectly proportional to linoleic acid content. Hundred pod weights had the highest direct effect on pod yield per plant. Selection based on traits with a better relationship with pod yield per plant and moderate to high estimates of PCV, GCV, heritability and genetic advancement would help in accelerating the groundnut improvement program. High oleic, low linolenic lines of BC2F2 with better pod yield would be forwarded to the next generation.

Large-scale transcriptomic and genomic analyses reveal a novel functional gene SERPINB6 for chicken carcass traits

BackgroundCarcass traits are crucial indicators of meat production efficiency. However, the molecular regulatory mechanisms associated with these traits remain unclear.ResultsIn this study, we conducted comprehensive transcriptomic and genomic analyses on 399 Tiannong partridge chickens to identify key genes and variants associated with carcass traits and to elucidate the underlying regulatory mechanisms. Based on association analyses with the elastic net (EN) model, we identified 12 candidate genes (AMY1A, AP3B2, CEBPG, EEF2, EIF4EBP1, FGFR1, FOXD3, GOLM1, LOC107052698, PABPC1, SERPINB6 and TBC1D16) for 4 carcass-related traits, namely live weight, dressed weight, eviscerated weight, and breast muscle weight. SERPINB6 was identified as the only overlapping gene by 3 analyses, EN model analysis, weighted gene co-expression network analysis and differential expression analysis. Cell-level experiments confirmed that SERPINB6 promotes the proliferation of chicken DF1 cells and primary myoblasts. Further expression genome-wide association study and association analysis indicated that rs317934171 is the critical site that enhances SERPINB6 expression. Furthermore, a dual-luciferase reporter assay proved that gga-miR-1615 targets the 3′UTR of SERPINB6.ConclusionsCollectively, our findings reveal that SERPINB6 serves as a novel gene for chicken carcass traits by promoting fibroblast and myoblast proliferation. Additionally, the downstream variant rs317934171 regulates SERPINB6 expression. These results identify a new target gene and molecular marker for the molecular mechanisms of chicken carcass traits.

Association Analysis Between Intratumoral and Peritumoral MRI Radiomics Features and Overall Survival of Neoadjuvant Therapy in Rectal Cancer.

The use of peritumoral features to determine the survival time of patients with rectal cancer (RC) is still imprecise. To explore the correlation between intratumoral, peritumoral and combined features, and overall survival (OS). Retrospective. One hundred sixty-six RC patients (53 women, 113 men; average age: 55 ± 12 years) who underwent radical resection after neoadjuvant therapy. 3 T; T2WI sagittal, T1WI axial, T2WI axial with fat suppression, and high-resolution T2WI axial sequences, enhanced T1WI axial and sagittal sequences with fat suppression. Radiologist A segmented 166 patients, and radiologist B randomly segmented 30 patients. Intratumoral and peritumoral features were extracted, and features with good stability (ICC ≥0.75) were retained through intra-observer analysis. Seven classifiers, including Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Random Forest (RF), Extremely randomized trees (ET), eXtreme Gradient Boosting (XGBoost), and LightGBM (LGBM), were applied to select the classifier with the best performance. Next, the Rad-score of best classifier and the clinical features were selected to establish the models, thus, nomogram was built to identify the association with 1-, 3-, and 5-year OS. LASSO, regression analysis, ROC, DeLong method, Kaplan-Meier curve. P < 0.05 indicated a significant difference. Only Node (irregular tumor nodules in the surrounding mesentery) and ExtraMRF (lymph nodes outside the perirectal mesentery) were significantly different in 20 clinical features. Twelve intratumoral, 3 peritumoral, and 14 combined features related to OS were selected. LR, SVM, and RF classier showed the best efficacy in the intratumoral, peritumoral, and combined model, respectively. The combined model (AUC = 0.954 and 0.821) had better survival association than the intratumoral model (AUC = 0.833 and 0.813) and the peritumoral model (AUC = 0.824 and 0.687). The proposed peritumoral model with radiomics features may serve as a tool to improve estimated survival time. 3 TECHNICAL EFFICACY: Stage 4.

Sweet corn association panel and genome-wide association analysis reveal loci for chilling-tolerant germination

Sweet corn is highly susceptible to the deleterious effects of low temperatures during the initial stages of growth and development. Employing a 56K chip, high-throughput single-nucleotide polymorphism (SNP) sequencing was conducted on 100 sweet corn inbred lines. Subsequently, six germination indicators—germination rate, germination index, germination time, relative germination rate, relative germination index, and relative germination time—were utilized for genome-wide association analysis. Candidate genes were identified via comparative analysis of homologous genes in Arabidopsis and rice, and their functions were validated using quantitative real-time polymerase chain reaction (qRT-PCR). The results revealed 35,430 high-quality SNPs, 16 of which were significantly correlated. Within 50 kb upstream and downstream of the identified SNPs, 46 associated genes were identified, of which six were confirmed as candidate genes. Their expression patterns indicated that Zm11ΒHSDL5 and Zm2OGO likely play negative and positive regulatory roles, respectively, in the low-temperature germination of sweet corn. Thus, we determined that these two genes are responsible for regulating the low-temperature germination of sweet corn. This study contributes valuable theoretical support for improving sweet corn breeding and may aid in the creation of specific germplasm resources geared toward enhancing low-temperature tolerance in sweet corn.

Integrating meta‐analysis of genome‐wide association study with Pig Genotype‐Tissue Expression resources uncovers the genetic architecture for age at first farrowing in pigs

AbstractAge at first farrowing (AFF) is a reproductive trait with low heritability and high importance in the pig industry. To enhance the statistical power of genome‐wide association study (GWAS) and further explore the genetic nature of AFF, we first conducted GWAS meta‐analysis using three Yorkshire populations, and then integrated the Pig Genotype‐Tissue Expression (PigGTEx) resources to interpret their potential regulatory mechanism. Additionally, we compared the AFF in pig with the age at first birth (AFB) of human using GWAS summary statistics. We detected 18 independent variants in GWAS meta‐analysis and 8 genes in gene‐based association analysis significantly associated with AFF. By integrating the PigGTEx resource, we conducted transcriptome‐wide association study (TWAS) and colocalization analysis on 34 pig tissues. In TWAS, we detected 18 significant gene‐tissue pairs, such as DCAF6 in uterus and CREG1 in blood. In colocalization, we found 111 potential candidate tissue‐gene pairs, such as GJD4 and LYPLAL1. We found that the homologous gene, CHST10, might be the potential candidate gene between humans in AFB and pigs in AFF. In conclusion, integrating GWAS meta‐analysis and PigGTEx resources is a meaningful way to decipher the genetic architecture of complex traits. We found that DCAF6, CREG1, GJD4, and LYPLAL1 are candidate genes with high reliability for AFF in swine. The comparative analysis showed that CHST10 might play a potentially critical role in AFB/AFF across human and pigs.

Causal association of circulating metabolites with diabetic retinopathy: a bidirectional Mendelian randomization analysis

IntroductionThe retina is a highly metabolically active tissue, and there is a lack of clarity about the relationship between metabolites and diabetic retinopathy (DR). This study used two-sample bidirectional Mendelian randomization (MR) analyses to identify causal relationships between metabolites and DR.MethodsGenetic variants were selected from the open-access Genome-Wide Association Studies (GWAS) summary database as proxies for the 1400 most recently published metabolites. MR analysis was performed to examine associations between these metabolite traits and DR. Single nucleotide polymorphism (SNP) data that were significantly associated with exposure were screened through association analysis. Validated instrumental variables (IVs) were obtained by removing SNPs with linkage disequilibrium (LD) and F-statistic values below 10. MR analyses were performed using the inverse variance weighted (IVW) method as the primary approach. The robustness of the results was verified by sensitivity analyses, including assessments of heterogeneity, horizontal pleiotropy, and the leave-one-out method.ResultsIn the IVW approach and in the primary analysis of several sensitivity analyses, genetically determined glycolithocholate sulfate levels, androstenediol (3 beta, 17 beta) monosulfate (1) levels, 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4) levels, 1-oleoyl-2-arachidonoyl-GPE (18:1/20:4) levels, 1-oleoyl-2-linoleoyl-GPE (18:1/18:2) levels, X-26109 levels, N6-methyllysine levels, (N6,N6-dimethyllysine levels), and (N2-acetyl,N6,N6-dimethyllysine levels) were negatively associated with the risk of DR. 5-hydroxymethyl-2-furoylcarnitine levels and the glutamate-to-alanine ratio were positively associated with the risk of DR. No reverse causal association was found between DR and metabolites.DiscussionThis MR study suggests that nine metabolites may have a protective effect in DR, while two metabolites may be associated with an increased risk of DR. However, further research is needed to confirm these findings. Supplementation with beneficial metabolites may reduce DR risk and could potentially be a novel therapeutic approach to DR treatment.

Fundamentals for predicting transcriptional regulations from DNA sequence patterns.

Cell-type-specific regulatory elements, cataloged through extensive experiments and bioinformatics in large-scale consortiums, have enabled enrichment analyses of genetic associations that primarily utilize positional information of the regulatory elements. These analyses have identified cell types and pathways genetically associated with human complex traits. However, our understanding of detailed allelic effects on these elements' activities and on-off states remains incomplete, hampering the interpretation of human genetic study results. This review introduces machine learning methods to learn sequence-dependent transcriptional regulation mechanisms from DNA sequences for predicting such allelic effects (not associations). We provide a concise history of machine-learning-based approaches, the requirements, and the key computational processes, focusing on primers in machine learning. Convolution and self-attention, pivotal in modern deep-learning models, are explained through geometrical interpretations using dot products. This facilitates understanding of the concept and why these have been used for machine learning for DNA sequences. These will inspire further research in this genetics and genomics field.

Untargeted serum metabolic profiling of diabetes mellitus among Parkinson’s disease patients

Type 2 diabetes mellitus (T2DM) is a common comorbidity among Parkinson’s disease (PD) patients. Yet, little is known about dysregulated pathways that are unique in PD patients with T2DM. We applied high-resolution metabolomic profiling in serum samples of 636 PD and 253 non-PD participants recruited from Central California. We conducted an initial discovery metabolome-wide association and pathway enrichment analysis. After adjusting for multiple testing, in positive (or negative) ion mode, 30 (25) metabolic features were associated with T2DM in both PD and non-PD participants, 162 (108) only in PD participants, and 32 (7) only in non-PD participants. Pathway enrichment analysis identified 17 enriched pathways associated with T2DM in both the PD and non-PD participants, 26 pathways only in PD participants, and 5 pathways only in non-PD participants. Several amino acid, nucleic acids, and fatty acid metabolisms were associated with T2DM only in the PD patient group suggesting a possible link between PD and T2DM.

Predictive genome-wide association and economic analyses of pooled DNA in a commercial feedlot setting

Understanding the genetic profile of cattle allows producers to make predictions of performance and disease. However, it is often fiscally and logistically unfeasible for commercial cattle producers to individually genotype animals. As such, our objec­tive was to utilize prospectively-pooled DNA from commercial feedlot cattle for a genome-wide association study (GWAS) of ec­onomically-important carcass traits and measure the economic efficiency of this technique.

Genetic Diversity and Genome-Wide Association Analysis of the Hulled/Naked Trait in a Barley Collection from Shanghai Agricultural Gene Bank

Genetic Diversity and Genome-Wide Association Analysis of the Hulled/Naked Trait in a Barley Collection from Shanghai Agricultural Gene Bank

Gut microbiota, blood metabolites, and left ventricular diastolic dysfunction in US Hispanics/Latinos

BackgroundLeft ventricular diastolic dysfunction (LVDD) is an important precursor of heart failure (HF), but little is known about its relationship with gut dysbiosis and microbial-related metabolites. By leveraging the multi-omics data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a study with population at high burden of LVDD, we aimed to characterize gut microbiota associated with LVDD and identify metabolite signatures of gut dysbiosis and incident LVDD.ResultsWe included up to 1996 Hispanic/Latino adults (mean age: 59.4 years; 67.1% female) with comprehensive echocardiography assessments, gut microbiome, and blood metabolome data. LVDD was defined through a composite criterion involving tissue Doppler assessment and left atrial volume index measurements. Among 1996 participants, 916 (45.9%) had prevalent LVDD, and 212 out of 594 participants without LVDD at baseline developed incident LVDD over a median 4.3 years of follow-up. Using multivariable-adjusted analysis of compositions of microbiomes (ANCOM-II) method, we identified 7 out of 512 dominant gut bacterial species (prevalence > 20%) associated with prevalent LVDD (FDR-q < 0.1), with inverse associations being found for Intestinimonas_massiliensis, Clostridium_phoceensis, and Bacteroide_coprocola and positive associations for Gardnerella_vaginali, Acidaminococcus_fermentans, Pseudomonas_aeruginosa, and Necropsobacter_massiliensis. Using multivariable adjusted linear regression, 220 out of 669 circulating metabolites with detection rate > 75% were associated with the identified LVDD-related bacterial species (FDR-q < 0.1), with the majority being linked to Intestinimonas_massiliensis, Clostridium_phoceensis, and Acidaminococcus_fermentans. Furthermore, 46 of these bacteria-associated metabolites, mostly glycerophospholipids, secondary bile acids, and amino acids, were associated with prevalent LVDD (FDR-q < 0.1), 21 of which were associated with incident LVDD (relative risk ranging from 0.81 [p = 0.001, for guanidinoacetate] to 1.25 [p = 9 × 10−5, for 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4)]). The inclusion of these 21 bacterial-related metabolites significantly improved the prediction of incident LVDD compared with a traditional risk factor model (the area under the receiver operating characteristic curve [AUC] = 0.73 vs 0.70, p = 0.001). Metabolite-based proxy association analyses revealed the inverse associations of Intestinimonas_massilliensis and Clostridium_phoceensis and the positive association of Acidaminococcus_fermentans with incident LVDD.ConclusionIn this study of US Hispanics/Latinos, we identified multiple gut bacteria and related metabolites linked to LVDD, suggesting their potential roles in this preclinical HF entity.E59jTaJp--U2oUtePgjZu8Video

Rare MED12L variants is associated with susceptibility to guttate psoriasis in the Han Chinese Population.

According to the common disease/rare variant (CDRV) hypothesis, it is important to study the role of rare variants in complex diseases. The association of rare variants with psoriasis has been demonstrated, but the association between rare variants and specific clinical subtypes of psoriasis has not been investigated. Gene-based and gene-level meta-analyses were performed on data extracted from our previous study data sets(2,483 patients with guttate psoriasis and 8,292 patients with non-guttate psoriasis) for genotyping. Then, haplotype analysis was performed for rare loss-of-function variants located in MED12L, and protein function prediction was performed for MED12L. Gene-based analysis at each stage had a moderate significance threshold (P < 0.05). A chi-square test was then conducted on the three potential genes, and the merged gene-based analysis was used to confirm the results. We also conducted association analysis and meta-analysis for functional variants located on the identified gene. Through these gene-level analyses, we determined that MED12L is a guttate psoriasis susceptibility gene (P=9.99x10-5), and the single-nucleotide polymorphism (SNP) with the strongest association was rs199780529 (P_combine=1x10-3, P_meta=2x10-3). In our study, a guttate psoriasis-specific subtype-associated susceptibility gene was confirmed in a Chinese Han population. These findings contribute to a better genetic understanding of different subtypes of psoriasis.

Assessment of genotypic variability and genome‐wide association analysis of cooking time and canning quality traits in common bean (Phaseolus vulgaris L.)

AbstractDeveloping improved common bean varieties with short cooking time (CT) and good canning quality traits (CQTs) is very key for accelerating bean consumption among the urban and middle‐class population. The objective of this study was to assess the genotypic variability and identify single nucleotide polymorphism (SNP) markers associated with CT and CQTs in common bean. A total of 250 common bean accessions were evaluated under field conditions for two seasons using alpha lattice design with two replications. Three months post‐harvest, the dry bean grains were evaluated for CT and CQTs. Significant variation was observed among the 250 common bean accessions tested for both traits. CT ranged from 51 to 215 min, with 11 genotypes cooking in less than 60 min. The percentage total CQTs' score ranged from 41% to 84% with 31 genotypes scoring 76% and above. Forty‐seven significant GWAS signals were detected for CT on chromosomes Pv01, Pv04, Pv05 and Pv11 and CQTs on Pv01, Pv02, Pv03, Pv04, Pv05, Pv06, Pv07, Pv08, Pv10 and Pv11, respectively. Positional candidate genes including Phvul.005G161200 on chromosome Pv05, Phvul.007G2803001 and Phvul.007G280700 on chromosome Pv07 were associated with seed coat colour retention of the canned beans. Besides their usefulness in breeding research, the identified bean genotypes with shorter CT and good CQTs could enhance bean consumption and processing industries.

Association Analysis of Essential Tremor-Associated Genetic Variants in Sporadic Late-Onset Parkinson's Disease.

Parkinson's disease (PD) and Essential tremor (ET) are the two most common tremor diseases with recognized genetic pathogenesis. The overlapping clinical features suggest they may share genetic predispositions. Our previous study systematically investigated the association between rare coding variants in ET-associated genes and early-onset PD (EOPD), and found the suggestive association between teneurin transmembrane protein 4 (TENM4) and EOPD. In the current research, we explored the potential genetic interplay between ET-associated genetic loci/genes and sporadic late-onset PD (LOPD). We performed whole-genome sequencing in the 1962 sporadic LOPD cases and 1279 controls from mainland China. We first used logistic regression analysis to test the top 16 SNPs identified by the ET genome-wide association study for the association between ET and LOPD. Then we applied the optimized sequence kernel association testing to explore the rare variant burden of 33 ET-associated genes in this cohort. We did not observe a significant association between the included SNPs with LOPD. We also did not discover a significant burden of rare deleterious variants of ET-associated genes in association with LOPD risk. Our results do not support the role of ET-associated genetic loci and variants in LOPD. 1962 cases and 1279 controls were recruited to study the potential genetic interplay between ET-associated genetic loci/variants and sporadic LOPD.No significant association between the ET-associated SNPs and LOPD were observed.No significant burden of rare deleterious variants of ET-associated gene in LOPD risk were found.

Gene association analysis to determine the causal relationship between immune-mediated inflammatory diseases and frozen shoulder.

Multiple studies have indicated a potential correlation between immune-mediated inflammatory diseases (IMIDs) and Frozen shoulder (FS). To explore the genetic causal relationship between IMIDs and FS using 2-sample Mendelian randomization (MR) analysis. Genome-wide association study (GWAS) summary data for FS were obtained from Green's study, while data for 10 IMIDs were sourced from the FinnGen Consortium. The MR analysis was performed using inverse variance weighting, MR Egger, and weighted median methods. IVW, as the primary MR analysis technique, was complemented with other sensitivity analyses to validate the robustness of the results. Additionally, reverse MR analysis was further conducted to investigate the presence of reverse causal relationships. In the forward MR analysis, genetically determined 4 IMIDs are causally associated with FS: rheumatoid arthritis (odds ratio [OR] (95% confidence interval [95% CI]) = 1.05 [1.02-1.09], P < .01); type 1 diabetes (OR [95% CI] = 1.06 [1.03-1.09], P < .01); hypothyroidism (OR [95% CI] = 1.07 [1.01-1.14], P = .02); and Celiac disease (OR [95% CI] = 1.02 [1.01-1.04], P = .01). However, no causal relationship was found between 6 IMIDs (autoimmune hyperthyroidism, Crohn disease, ulcerative colitis, psoriasis, sicca syndrome and systemic lupus erythematosus) and FS. Sensitivity analyses did not detect any heterogeneity or horizontal pleiotropy. In the reverse MR analysis, no causal relationship was observed between FS and IMIDs. In conclusion, this MR study suggests a potential causal relationship between rheumatoid arthritis, type 1 diabetes, hypothyroidism, and Celiac disease in the onset and development of FS. Nevertheless, more basic and clinical research will be needed in the future to support our findings.

Genomic epidemiology of Staphylococcus aureus from the Iberian Peninsula highlights the expansion of livestock associated-CC398 towards wildlife

Staphylococcus aureus is a versatile pathobiont, exhibiting a broad host range, including humans, other mammals, and avian species. Host specificity determinants, virulence, and antimicrobial resistance genes are often shared by strains circulating at the animal-human interface. While transmission dynamics studies have shown strain exchange between humans and livestock, knowledge of the source, genetic diversification, and transmission drivers of S. aureus in wildlife lag behind.In this work, we explore a wide array of S. aureus genomes from different sources in the Iberian Peninsula to understand population structure, gene content and niche adaptation at the human-livestock-wildlife nexus. Through Bayesian inference, we address the hypothesis that S. aureus strains in wildlife originate from humanized landscapes, either from contact with humans or through interactions with livestock. Phylogenetic reconstruction applied to whole genome sequence data was completed with a dataset of 450 isolates featuring multiple clones from the 1990–2022 period and a subset of CC398 strains representing the 2008–2022 period. Phylodynamic signatures of S. aureus from the Iberian Peninsula suggest widespread circulation of most clones among humans before jumping to other hosts. The number of transitions of CC398 strains within each host category (human, livestock, wildlife) was high (88.26 %), while the posterior probability of transitions from livestock to wildlife was remarkably high (0.99). Microbial genome-wide association analysis did not evidence genome rearrangements nor biomarkers suggesting S. aureus niche adaptation to wildlife, thus supporting recent spill overs. Altogether, our findings indicate that S. aureus isolates collected in the past years from wildlife most likely represent multiple introduction events from livestock. The clonal origin of CC398 and its potential to disseminate and evolve through different animal host species are highlighted, calling for management practices at the livestock-wildlife axis to improve biosecurity and thus restrict S. aureus transmission and niche expansion along gradients of human influence.