Cluster Of Single Nucleotide Polymorphisms Research Articles

A region on chromosome 16 is associated with Doberman Pinscher dilated cardiomyopathy

Doberman Pinschers are known for their increased susceptibility to dilated cardiomyopathy (DCM) relative to other domestic dogs. This makes the Doberman Pinscher a key model for gene-disease investigations. We conducted a genome-wide association study (GWAS) leveraging a database of genetic profiles obtained through collaboration with the Doberman Diversity Project (DDP). We worked in parallel to increase the depth and power of the DDP database. We exchanged direct correspondences with listed breeders and owners to establish health updates for participant dogs. In total, our study included data on 216, 184 single nucleotide polymorphisms (SNPs) in 46 cases and 3226 population control Doberman Pinschers. Using a generalized linear mixed model and saddlepoint approximation to correct for unbalanced group sizes, we identified a cluster of SNPs associated with DCM on chromosome 16.

Analysis of genetic signatures of virulence and resistance in foodborne Staphylococcus aureus isolates from Algeria

Staphylococcus aureus, a frequent commensal of the human microbiota, also frequently associated with various infections. This study aimed to genetically characterize foodborne methicillin resistant S. aureus (MRSA) in Oran, Algeria. From a total of 474 food matrices, 30 MRSA strains were isolated and characterized using whole genome sequencing (WGS) and bioinformatics. The genomes were assessed for antimicrobial resistance and virulence genes, sequence and spa types and single nucleotide polymorphism (SNP) to establish their relationship. The prevalence of S. aureus was 34.38% with MRSA accounting for 18.40%. MRSA strains showed high resistance to penicillinG, ampicillin and tetracycline. However, inconsistencies were noted between phenotypic and genotypic resistance for methicillin, aminoglycosides, and phenicolates, with mecA gene identified in three isolates. The isolates revealed eight different sequence types (predominantly ST97 and ST45) and eleven spa types (mainly t230 and t8503), correlating with SNP clusters except for isolates belonging to ST7200.86.66% of isolates harboured at least one enterotoxin gene underscores their potential public health threat. This investigation highlights the genetic heterogeneity among S. aureus regarding virulence and antimicrobial resistance, shedding light into food safety in Algeria and the ease of using WGS approach to rapidly characterize bacterial pathogens in community environments.

Predicting regulatory mutations and their target genes by new computational integrative analysis: A study of follicular lymphoma

Mutations in DNA regulatory regions are increasingly being recognized as important drivers of cancer and other complex diseases. These mutations can regulate gene expression by affecting DNA-protein binding and epigenetic profiles, such as DNA methylation in genome regulatory elements. However, identifying mutation hotspots associated with expression regulation and disease progression in non-coding DNA remains a challenge. Unlike most existing approaches that assign a mutation score to individual single nucleotide polymorphisms (SNP), a mutation block (MB)-based approach was introduced in this study to assess the collective impact of a cluster of SNPs on transcription factor-DNA binding affinity, differential gene expression (DEG), and nearby DNA methylation. Moreover, the long-distance target genes of functional MBs were identified using a new permutation-based algorithm that assessed the significance of correlations between DNA methylation at regulatory regions and target gene expression. Two new Python packages were developed. The Differential Methylation Region (DMR-analysis) analysis tool was used to detect DMR and map them to regulatory elements. The second tool, an integrated DMR, DEG, and SNP analysis tool (DDS-analysis), was used to combine the omics data to identify functional MBs and long-distance target genes. Both tools were validated in follicular lymphoma (FL) cohorts, where not only known functional MBs and their target genes (BCL2 and BCL6) were recovered, but also novel genes were found, including CDCA4 and JAG2, which may be associated with FL development. These genes are linked to target gene expression and are significantly correlated with the methylation of nearby DNA sequences in FL. The proposed computational integrative analysis of multiomics data holds promise for identifying regulatory mutations in cancer and other complex diseases.

Genome-Wide Genetic Analysis of Dropout in a Controlled Exercise Intervention in Sedentary Adults With Overweight or Obesity and Cardiometabolic Disease.

Despite the benefits of exercise, many individuals are unable or unwilling to adopt an exercise intervention. The purpose of this analysis was to identify putative genetic variants associated with dropout from exercise training interventions among individuals in the STRRIDE trials. We used a genome-wide association study approach to identify genetic variants in 603 participants initiating a supervised exercise intervention. Exercise intervention dropout occurred when a subject withdrew from further participation in the study or was otherwise lost to follow-up. Exercise intervention dropout was associated with a cluster of single-nucleotide polymorphisms with the top candidate being rs722069 (T/C, risk allele = C) (unadjusted p = 2.2 × 10-7, odds ratio = 2.23) contained within a linkage disequilibrium block on chromosome 16. In Genotype-Tissue Expression, rs722069 is an expression quantitative trait locus of the EARS2, COG7, and DCTN5 genes in skeletal muscle tissue. In subsets of the STRRIDE genetic cohort with available muscle gene expression (n = 37) and metabolic data (n = 82), at baseline the C allele was associated with lesser muscle expression of EARS2 (p < .002) and COG7 (p = .074) as well as lesser muscle concentrations of C2- and C3-acylcarnitines (p = .026). Our observations imply that exercise intervention dropout is genetically moderated through alterations in gene expression and metabolic pathways in skeletal muscle. Individual genetic traits may allow the development of a biomarker-based approach for identifying individuals who may benefit from more intensive counseling and other interventions to optimize exercise intervention adoption. STRRIDE I = NCT00200993; STRRIDE AT/RT = NCT00275145; STRRIDE-PD = NCT00962962.

Diversity and distribution of sodium channel mutations in Aedes albopictus (Diptera: Culicidae).

There is growing interest in insecticide resistance in the mosquito, Aedes albopictus (Skuse), as its potential for spreading diseases is increasing as urbanization and control efforts intensify. Here we review the presence and diversity of mutations in the voltage-sensitive sodium channel (Vssc) gene associated with pyrethroid resistance and report on additional surveys of these mutations in new populations with an analysis of their spread. The known diversity of these mutations has increased in recent years including the identification of 26 non-synonymous mutations, although phenotypic data associating mutations with resistance remain limited. We provide data on mutations in several new locations including those in Timor Leste, Indonesia, and Vanuatu. We use population genomic data from ddRAD analyses of target populations with the 1534C mutation to identify single nucleotide polymorphisms (SNPs) associated with the mutant to test for clustering of SNPs based on the presence of the 1534C mutation rather than population origin. Our findings suggest spread of resistance alleles via genetic invasion, which is further supported by patterns from a genome-wide principal components analysis. These data point to movement of resistance alleles across wide areas with likely impacts on local control options.

T2T reference genome assembly and genome-wide association study reveal the genetic basis of Chinese bayberry fruit quality.

Chinese bayberry (Myrica rubra or Morella rubra; 2n = 16) produces fruit with a distinctive flavor, high nutritional, and economic value. However, previous versions of the bayberry genome lack sequence continuity. Moreover, to date, no large-scale germplasm resource association analysis has examined the allelic and genetic variations determining fruit quality traits. Therefore, in this study, we assembled a telomere-to-telomere (T2T) gap-free reference genome for the cultivar 'Zaojia' using PacBio HiFi long reads. The resulting 292.60Mb T2T genome, revealed 8 centromeric regions, 15 telomeres, and 28 345 genes. This represents a substantial improvement in the genome continuity and integrity of Chinese bayberry. Subsequently, we re-sequenced 173 accessions, identifying 6 649 674 single nucleotide polymorphisms (SNPs). Further, the phenotypic analyses of 29 fruit quality-related traits enabled a genome-wide association study (GWAS), which identified 1937 SNPs and 1039 genes significantly associated with 28 traits. An SNP cluster pertinent to fruit color was identified on Chr6: 3407532 to 5 153 151bp region, harboring two MYB genes (MrChr6G07650 and MrChr6G07660), exhibiting differential expression in extreme phenotype transcriptomes, linked to anthocyanin synthesis. An adjacent, closely linked gene, MrChr6G07670 (MLP-like protein), harbored an exonic missense variant and was shown to increase anthocyanin production in tobacco leaves tenfold. This SNP cluster, potentially a quantitative trait locus (QTL), collectively regulates bayberry fruit color. In conclusion, our study presented a complete reference genome, uncovered a suite of allelic variations related to fruit-quality traits, and identified functional genes that could be harnessed to enhance fruit quality and breeding efficiency of bayberries.

Genomic diversity of Salmonella enterica isolated from raw chicken at retail establishments in Mexico

The genomic diversity of circulating non-typhoidal Salmonella in raw chicken was investigated in three states of central Mexico. A total of 192 S. enterica strains from chicken meat samples collected at supermarkets, fresh markets, and butcher shops were analyzed by whole-genome sequencing. The serovar distribution, occurrence of genes encoding for antimicrobial resistance, metal resistance, biocide resistance, plasmids and virulence factors, and clonal relatedness based on single nucleotide polymorphism (SNP) analysis were investigated. Serovars Infantis, Schwarzengrund and Enteritidis predominated among twenty identified. The distribution of serovars and proportion of AMR genes was different according to the state, year, season, and retail establishment (p < 0.001). Genes encoding metals resistance were identified in all the strains. A total of 145 virulence genes were identified and strains were classified into 32 virulotypes; serovars Infantis, Typhimurium, and Enteritidis showed the highest number of virulence genes. The strains matched 34 SNP clusters in the NCBI Pathogen Detection server and 59 %, which corresponded to Infantis, Schwarzengrund, Saintpaul, and Enteritidis, were associated with five major clusters and matched with chicken, environmental and clinical isolates from at least three countries. These results provide useful information to understand the epidemiology of Salmonella, conduct microbial risk assessment, and design risk-based control measures.

1791. Use of pathogen genomics to monitor global emergence of extensively drug-resistant Salmonella Serotype Typhi

Abstract Background Whole-genome sequencing (WGS) has transformed surveillance and outbreak detection. However, its use to complement resource-intensive epidemiologic investigations of emerging pathogens is limited. Here using WGS data of S. Typhi, we investigate the global spread of an emerging pathogen. Methods We used NCBI pathogen detection to search for SNP clusters of ceftriaxone-resistant S. Typhi (CRT) reported in the US and the National Antimicrobial Monitoring System (NARMSNOW) to analyze antibiotic-resistant trends of S. Typhi. Results Pathogen Detection Outbreaks of CRT infections were first reported in the US in 2018. We found that the US CRT isolates formed two distinct clusters linked to travel destinations, having close genetic relatedness with those found in Pakistan or Iraq. Specifically, three US CRT isolates (linked to travel to Iraq) only differed from 10 Iraq isolates (2021-2022) by an average of 3 SNPs (Figure). Further, two US CRT isolates (linked to travel to Pakistan) only differed from one Pakistan isolate (2022) by an average of 5 SNPs. NARMS Now Using 2012-2022 NARMS Now data, we analyzed trends in decreased susceptibility to ciprofloxacin (DSC) and resistance to ≥3 antibiotics recommended for treatment (MDR) among S. Typhi. We also compared the resistance trend pre-pandemic and after 2020. Our analysis included a total of 3,633 S. Typhi isolates. The percentage of DSC isolates increased from 68.5% (2012) to 85.1% (2022), while the percentage of MDR isolates increased from 8.9% to 20.1%. The 3-year (2017-2019) pre-pandemic DSC average was 77.5% and 80.5% after (2020-2022). For MDR isolates, it was 12.4% and 21.8%. Close genetic relatedness between three US outbreak associated ceftriaxone-resistant Typhi strains (linked to travel to Iraq; highlighted in red) and 10 strains isolated in Iraq (highlighted in red). Note the strains are collected in different years. The single nucleotide polymorphism (SNP) tree is automatically generated in the NCBI Pathogen Detection database when sequencing data are submitted to the database. The average SNP distance for the red highlighted isolates in the tree is three (SNP distance range 0∼9). Conclusion The SNP clusters indicate the likely international spread of resistant S. Typhi strains in travelers. Resistance to ciprofloxacin is increasing as is resistance to multiple antimicrobials. Travel restrictions imposed during the pandemic did not appreciatively alter resistance trends. These findings indicate the need for global cooperation in addressing antimicrobial resistance and emerging pathogens. Disclosures All Authors: No reported disclosures

Evaluation of Density-Based Spatial Clustering for Identifying Genomic Loci Associated with Ischemic Stroke in Genome-Wide Data.

The genetic architecture of ischemic stroke (IS), which is one of the leading causes of death worldwide, is complex and underexplored. The traditional approach for associative gene mapping is genome-wide association studies (GWASs), testing individual single-nucleotide polymorphisms (SNPs) across the genomes of case and control groups. The purpose of this research is to develop an alternative approach in which groups of SNPs are examined rather than individual ones. We proposed, validated and applied to real data a new workflow consisting of three key stages: grouping SNPs in clusters, inferring the haplotypes in the clusters and testing haplotypes for the association with phenotype. To group SNPs, we applied the clustering algorithms DBSCAN and HDBSCAN to linkage disequilibrium (LD) matrices, representing pairwise r2 values between all genotyped SNPs. These clustering algorithms have never before been applied to genotype data as part of the workflow of associative studies. In total, 883,908 SNPs and insertion/deletion polymorphisms from people of European ancestry (4929 cases and 652 controls) were processed. The subsequent testing for frequencies of haplotypes restored in the clusters of SNPs revealed dozens of genes associated with IS and suggested the complex role that protocadherin molecules play in IS. The developed workflow was validated with the use of a simulated dataset of similar ancestry and the same sample sizes. The results of classic GWASs are also provided and discussed. The considered clustering algorithms can be applied to genotypic data to identify the genomic loci associated with different qualitative traits, using the workflow presented in this research.

Single Nucleotide Polymorphisms Associated With Motor Recovery in Patients With Nondisabling Stroke: GWAS Study.

Despite notable advances in genetic understanding of stroke recovery, most studies focus only on candidate genes. To date, only 2 genome-wide association studies (GWAS) have focused on stroke outcomes, but they were limited to the modified Rankin Scale (mRS). The mRS maps poorly to biological processes. Therefore, we performed a GWAS to discover single nucleotide polymorphisms (SNPs) associated with motor recovery poststroke. We used the Vitamin Intervention for Stroke Prevention (VISP) data set of 2,100 genotyped participants with nondisabling stroke. We included only participants who had motor impairment at randomization. Participants with a recurrent stroke during the trial were excluded. Genotyped data underwent strict quality control and imputation. The GWAS used logistic regression models with generalized estimating equations to leverage the repeated NIH Stroke Scale motor score measurements spanning 6 time points over 24 months. The primary outcome was a decrease in the motor drift score of ≥1 vs <1 at each time point. Our model estimated the odds ratio (OR) of motor improvement for each SNP after adjusting for age, sex, race, days from stroke to visit, initial motor score, VISP treatment arm, and principal components. A total of 488 (64%) participants with a mean (SD) age of 66±11 years were included in the GWAS. Although no associations reached genome-wide significance (p < 5 × 10-8), our analysis detected 115 suggestive associations (p < 5 × 10-6). Notably, we found multiple SNP clusters near genes with plausible neuronal repair biology mechanisms. The CLDN23 gene had the most convincing association with rs1268196-T as its most significant SNP (OR 0.32; 95% CI 0.21-0.48; p value 6.19 × 10-7). CLDN23 affects blood-brain barrier integrity, neurodevelopment, and immune cell transmigration. We identified novel suggestive genetic associations with the first-ever motor-specific poststroke recovery GWAS. The results seem to describe a distinct stroke recovery phenotype compared with prior genetic stroke outcome studies that use outcome measures, such as the mRS. Replication and further mechanistic investigation are warranted. In addition, this study demonstrated a proof-of-principle approach to optimize statistical efficiency with longitudinal data sets for genetic discovery.

Application of quasimetagenomics methods to define microbial diversity and subtype Listeria monocytogenes in dairy and seafood production facilities.

Microorganisms frequently colonize surfaces within food production facilities. Detection of Listeria monocytogenes in this setting relies on culture-dependent methods, but the complex dynamics of bacterial interactions within these environments and their impact on pathogen detection remain largely unexplored. To address this challenge, we applied both 16S rRNA and shotgun quasimetagenomic (enriched microbiome) sequencing of swab culture enrichments from five seafood and seven dairy production environments. Utilizing 16S rRNA amplicon sequencing, we observed variability between 355 samples taken from these 12 production facilities and a distinctive microbiome for each environment. With shotgun quasimetagenomic sequencing, we were able to assemble L. monocytogenes metagenome-assembled genomes (MAGs) from 28 of the 32 culture-positive samples. We compared these MAGs to their corresponding whole-genome sequencing assemblies, which resulted in two polyphyletic clades consisting of L. monocytogenes lineages I and II with 13,195 and 25,556 single-nucleotide polymorphism sites, respectively. The remaining four MAGs did not produce sufficient genome coverage. To understand and establish limits for pathogen detection and subtyping using shotgun quasimetagenomics, these same data sets were downsampled in slilico to produce a titration series of abundances of L. monocytogenes and analyzed. Pathogen detection was achieved for all downsampled data sets, even those with only 3× genome coverage. This study contributes to the understanding of microbial diversity within food production environments and presents insights into the level of genome coverage needed in a metagenome sequencing data set to detect, subtype, and source track a foodborne pathogenIMPORTANCEIn developed countries, the human diet is predominated by food commodities, which have been manufactured, processed, and stored in a food production facility. Little is known about the application of metagenomic sequencing approaches for detecting foodborne pathogens, such as L. monocytogenes, and characterizing microbial diversity in food production ecosystems. In this work, we investigated the utility of 16S rRNA amplicon and quasimetagenomic sequencing for the taxonomic and phylogenetic classification of Listeria culture enrichments of environmental swabs collected from dairy and seafood production facilities. We demonstrated that single-nucleotide polymorphism (SNP) analyses of L. monocytogenes metagenome-assembled genomes (MAGs) from quasimetagenomic data sets can achieve similar resolution as culture isolate whole-genome sequencing. To further understand the impact of genome coverage on MAG SNP cluster resolution, an in silico downsampling approach was employed to reduce the percentage of target pathogen sequence reads, providing an initial estimate of required MAG coverage for subtyping resolution of L. monocytogenes.

Triglyceride-rich lipoprotein remnants, low-density lipoproteins, and risk of coronary heart disease: a UK Biobank study.

The strength of the relationship of triglyceride-rich lipoproteins (TRL) with risk of coronary heart disease (CHD) compared with low-density lipoprotein (LDL) is yet to be resolved. Single-nucleotide polymorphisms (SNPs) associated with TRL/remnant cholesterol (TRL/remnant-C) and LDL cholesterol (LDL-C) were identified in the UK Biobank population. In a multivariable Mendelian randomization analysis, TRL/remnant-C was strongly and independently associated with CHD in a model adjusted for apolipoprotein B (apoB). Likewise, in a multivariable model, TRL/remnant-C and LDL-C also exhibited independent associations with CHD with odds ratios per 1 mmol/L higher cholesterol of 2.59 [95% confidence interval (CI): 1.99-3.36] and 1.37 [95% CI: 1.27-1.48], respectively. To examine the per-particle atherogenicity of TRL/remnants and LDL, SNPs were categorized into two clusters with differing effects on TRL/remnant-C and LDL-C. Cluster 1 contained SNPs in genes related to receptor-mediated lipoprotein removal that affected LDL-C more than TRL/remnant-C, whereas cluster 2 contained SNPs in genes related to lipolysis that had a much greater effect on TRL/remnant-C. The CHD odds ratio per standard deviation (Sd) higher apoB for cluster 2 (with the higher TRL/remnant to LDL ratio) was 1.76 (95% CI: 1.58-1.96), which was significantly greater than the CHD odds ratio per Sd higher apoB in cluster 1 [1.33 (95% CI: 1.26-1.40)]. A concordant result was obtained by using polygenic scores for each cluster to relate apoB to CHD risk. Distinct SNP clusters appear to impact differentially on remnant particles and LDL. Our findings are consistent with TRL/remnants having a substantially greater atherogenicity per particle than LDL.

A nomogram based on genotypic and clinicopathologic factors to predict the non-sentinel lymph node metastasis in Chinese women breast cancer patients.

Sentinel lymph node biopsy (SLNB) is the standard treatment for breast cancer patients with clinically negative axilla. However, axillary lymph node dissection (ALND) is still the standard care for sentinel lymph node (SLN) positive patients. Clinical data reveals about 40-75% of patients without non-sentinel lymph node (NSLN) metastasis after ALND. Unnecessary ALND increases the risk of complications and detracts from quality of life. In this study, we expect to develop a nomogram based on genotypic and clinicopathologic factors to predict the risk of NSLN metastasis in SLN-positive Chinese women breast cancer patients. This retrospective study collected data from 1,879 women breast cancer patients enrolled from multiple centers. Genotypic features contain 96 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility, therapy and prognosis. SNP genotyping was identified by the quantitative PCR detection platform. The genetic features were divided into two clusters by the mutational stability. The normalized polygenic risk score (PRS) was used to evaluate the combined effect of each SNP cluster. Recursive feature elimination (RFE) based on linear discriminant analysis (LDA) was adopted to select the most useful predictive features, and RFE based on support vector machine (SVM) was used to reduce the number of SNPs. Multivariable logistic regression models (i.e., nomogram) were built for predicting NSLN metastasis. The predictive abilities of three types of model (based on only clinicopathologic information, the integrated clinicopathologic and all SNPs information, and integrated clinicopathologic and significant SNPs information) were compared. Internal and external validations were performed and the area under ROC curves (AUCs) as well as a series of evaluation indicators were assessed. 229 patients underwent SLNB followed by ALND and without any neo-adjuvant therapy, 79 among them (34%) had a positive axillary NSLN metastasis. The LDA-RFE identified the characteristics including lymphovascular invasion, number of positive SLNs, number of negative SLNs and two SNP clusters as significant predictors of NSLN metastasis. Furthermore, the SVM-RFE selected 29 significant SNPs in the prediction of NSLN metastasis. In internal validation, the median AUCs of the clinical and all SNPs combining model, the clinical and 29 significant SNPs combining model, and the clinical model were 0.837, 0.795 and 0.708 respectively. Meanwhile, in external validation, the AUCs of the three models were 0.817, 0.815 and 0.745 respectively. We present a new nomogram by combining genotypic and clinicopathologic factors to achieve higher sensitivity and specificity comparing with traditional clinicopathologic factors to predict NSLN metastasis in Chinese women breast cancer. It is recommended that more validations are required in prospective studies among different patient populations.

Predicting late-stage age-related macular degeneration by integrating marginally weak SNPs in GWA studies.

Introduction: Age-related macular degeneration (AMD) is a progressive neurodegenerative disease and the leading cause of blindness in developed countries. Current genome-wide association studies (GWAS) for late-stage age-related macular degeneration are mainly single-marker-based approaches, which investigate one Single-Nucleotide Polymorphism (SNP) at a time and postpone the integration of inter-marker Linkage-disequilibrium (LD) information in the downstream fine mappings. Recent studies showed that directly incorporating inter-marker connection/correlation into variants detection can help discover novel marginally weak single-nucleotide polymorphisms, which are often missed in conventional genome-wide association studies, and can also help improve disease prediction accuracy. Methods: Single-marker analysis is performed first to detect marginally strong single-nucleotide polymorphisms. Then the whole-genome linkage-disequilibrium spectrum is explored and used to search for high-linkage-disequilibrium connected single-nucleotide polymorphism clusters for each strong single-nucleotide polymorphism detected. Marginally weak single-nucleotide polymorphisms are selected via a joint linear discriminant model with the detected single-nucleotide polymorphism clusters. Prediction is made based on the selected strong and weak single-nucleotide polymorphisms. Results: Several previously identified late-stage age-related macular degeneration susceptibility genes, for example, BTBD16, C3, CFH, CFHR3, HTARA1, are confirmed. Novel genes DENND1B, PLK5, ARHGAP45, and BAG6 are discovered as marginally weak signals. Overall prediction accuracy of 76.8% and 73.2% was achieved with and without the inclusion of the identified marginally weak signals, respectively. Conclusion: Marginally weak single-nucleotide polymorphisms, detected from integrating inter-marker linkage-disequilibrium information, may have strong predictive effects on age-related macular degeneration. Detecting and integrating such marginally weak signals can help with a better understanding of the underlying disease-development mechanisms for age-related macular degeneration and more accurate prognostics.

Genomic analyses of drug-resistant Salmonella enterica serovar Heidelberg strains isolated from meat and related sources between 2013 and 2017 in the south region of Brazil.

Salmonella enterica serovar Heidelberg (S. Heidelberg) is a zoonotic, ubiquitous, and worldwide-distributed pathogen, responsible for gastroenteritis in humans caused by the consumption of contaminated food. In this study, 11 S. Heidelberg strains isolated from chicken and bovine meat, drag swab, and animal feed between 2013 and 2017 in states of the southern region of Brazil were characterized by whole-genome sequencing (WGS) analyses. Antimicrobial resistance against 18 antimicrobials was determined by disk-diffusion and ciprofloxacin's minimum inhibitory concentration by Etest®. The search for resistance and virulence genes, plasmids, Salmonella Pathogenicity Islands (SPIs) plus multi-locus sequence typing (MLST), and single-nucleotide polymorphisms (SNPs) analyses was conducted using WGS data. All strains harbored resistance genes fosA7, aac(6')-Iaa, sul2, tet(A), blaCMY-2, mdsA, and mdsB, and point mutations in gyrA and parC. All strains showed a phenotypic multidrug-resistant profile, with resistant or intermediate resistant profiles against 14 antimicrobials tested. Plasmids ColpVC, IncC, IncX1, and IncI1-I(Alpha) were detected. Virulence genes related to adherence, macrophage induction, magnesium uptake, regulation, and type III secretion systems plus 10 SPIs were detected. All strains were assigned to ST15 and belonged to two SNP clusters showing high similarity to isolates from the United Kingdom, Chile, Germany, the Netherlands, China, South Africa, and South Korea. In conclusion, the presence of multidrug-resistant S. Heidelberg strains in Brazil showing a global genomic relationship may alert for the necessity of stronger surveillance measures by food safety and public health authorities to limit its spread to humans and animals through foods.

Multigraph Cluster Analysis of AD Candidate Genes via Human Brain Mapping

AbstractBackgroundBrain imaging genetics examines associations between imaging quantitative traits (QTs) and genetic factors such as single nucleotide polymorphisms (SNPs) to provide important insights into the pathogenesis of Alzheimer’s diseases (AD). Given the high dimensionality, the individual level SNP‐QT signals typically have small effect sizes and are hard to be detected and replicated. To overcome this limitation, this work proposes a new approach to identify high‐level imaging genetic associations through applying multi‐graph clustering to SNP‐QT association maps.MethodsParticipants include 255 cognitive normal (CN) and 218 late mild cognitive impairment (LMCI) subjects from the ADNI data. Linear regression is performed to regress regional AV‐45 measures on each of the 54 AD SNPs to obtain a brain association map across 116 AAL‐ROIs. To quantify the similarity between each SNP pair, 5 scoring functions are used to calculate 5 different similarity measures between the respective brain maps of the two SNPs. Each scoring function yields a similarity graph of all 54 SNPs. Multigraph min‐max clustering is applied to 5 different graphs simultaneously to group similar SNPs together. Functional annotation is performed on each SNP cluster and the corresponding average brain association map to provide high level interpretations.ResultsFigure 1 shows the genetic effect on regional AV‐45 measures for each pair of SNP and ROI. The multi‐graph clustering result is shown in Figure 2, where 54 AD‐related SNPs are clustered into two groups. Figure 3a shows the results of Enrichr Elsevier pathway analysis. SNP group 1 is associated with pathways such as amyloid beta clearance, while SNP group 2 is associated with pathways including amyloid beta formation and APP processing in AD. Figure 3b shows the NeuroSynth annotation of the average brain effect maps associated with the two SNP clusters, respectively.ConclusionWe proposed an approach that transforms individual level imaging genetic associations (SNP vs ROI) to high‐level associations (i.e., SNP cluster vs brain association map), and applied it to an LMCI study. These high‐level findings have the potential to provide valuable insights into relevant genetic pathways and brain circuits, which can help form new hypotheses for more detailed imaging and genetics studies in independent cohorts.

A human iPSC-array-based GWAS identifies a virus susceptibility locus in the NDUFA4 gene and functional variants.

SummaryPopulation-based studies to identify disease-associated risk alleles typically require samples from a large number of individuals. Here, we report a human-induced pluripotent stem cell (hiPSC)-based screening strategy to link human genetics with viral infectivity. A genome-wide association study (GWAS) identified a cluster of single-nucleotide polymorphisms (SNPs) in a cis-regulatory region of the NDUFA4 gene, which was associated with susceptibility to Zika virus (ZIKV) infection. Loss of NDUFA4 led to decreased sensitivity to ZIKV, dengue virus, and SARS-CoV-2 infection. Isogenic hiPSC lines carrying non-risk alleles of SNPs or deletion of the cis-regulatory region lower sensitivity to viral infection. Mechanistic studies indicated that loss/reduction of NDUFA4 causes mitochondrial stress, which leads to the leakage of mtDNA and thereby upregulation of type I interferon signaling. This study provides proof-of-principle for the application of iPSC arrays in GWAS and identifies NDUFA4 as a previously unknown susceptibility locus for viral infection.

Bloodstream Infections in Patients with Rectal Colonization by Carbapenem-Resistant Enterobacteriaceae: A Prospective Cohort Study.

PurposeCarbapenem-resistant Enterobacteriaceae (CRE) infection has become a concerning threat, especially in hospital settings; however, its phenotypic characterization, association with rectal colonization and subsequent bloodstream infections (BSI) remain to be clarified. This study aimed to investigate the incidence and risk factors of CRE infection in rectal CRE carriers and to understand the clonality of carbapenem-resistant Klebsiella pneumoniae (CRKP) strains and their association with subsequent BSI in these patients.Patients and MethodsThis was a prospectively designed cohort study. Hospitalized patients treated at our institution from April 2019 to October 2020 with intestinal CRE carriage were screened at admission and weekly thereafter until death or discharge from the hospital. Stool and blood samples were obtained for strain growth and mass spectrometry. The colonization and clinical infection isolates were analyzed by antimicrobial susceptibility testing to identify CRE. The clonality of the CRE strains and their corresponding clinical infection strains was studied by whole-genome sequencing to explore the mechanism of drug resistance and evaluate possible transmission. CRE-associated risk factors were analyzed in combination with epidemiological data.ResultsOf the 1203 patients, 85 were colonized by CRE and 21 developed CRE infection, of whom 13 developed CRE bloodstream infection (BSI). Ninety-one CRE strains were isolated from the rectal specimens of the 85 patients. Tracheotomy and chemotherapy in the past three months were independent risk factors for CRE infection in intestinal CRE carriers. ST11-KL64 (92.3%, 24/26) was the most dominant capsule and multilocus sequence typing (MLST) type among clonal CRKP isolates. Single-nucleotide polymorphism clustering showed homology of representative colonization and infection CRKP strain pairs (n=13) in the same patient. One group of leading clones was endemic in surgical intensive care units (ICUs). Twenty-four CRKP strains carried β-lactamase K. pneumonia carbapenemase 2, and 73.1% (19 strains) of CRKP carried mucoid phenotype regulator genes A2 and iucABCD.ConclusionIn summary, intestinal CRE colonization was detectable at an elevated rate among hospitalized patients and prevalent in ICU patients, with potential rapid horizontal transmission, providing evidence that CRE BSI infection in hospitalized patients might be due to their colonized strains and indicates the correlation between intestinal colonization and BSI.

Mining High-Level Imaging Genetic Associations via Clustering AD Candidate Variants with Similar Brain Association Patterns.

Brain imaging genetics examines associations between imaging quantitative traits (QTs) and genetic factors such as single nucleotide polymorphisms (SNPs) to provide important insights into the pathogenesis of Alzheimer’s disease (AD). The individual level SNP-QT signals are high dimensional and typically have small effect sizes, making them hard to be detected and replicated. To overcome this limitation, this work proposes a new approach that identifies high-level imaging genetic associations through applying multigraph clustering to the SNP-QT association maps. Given an SNP set and a brain QT set, the association between each SNP and each QT is evaluated using a linear regression model. Based on the resulting SNP-QT association map, five SNP–SNP similarity networks (or graphs) are created using five different scoring functions, respectively. Multigraph clustering is applied to these networks to identify SNP clusters with similar association patterns with all the brain QTs. After that, functional annotation is performed for each identified SNP cluster and its corresponding brain association pattern. We applied this pipeline to an AD imaging genetic study, which yielded promising results. For example, in an association study between 54 AD SNPs and 116 amyloid QTs, we identified two SNP clusters with one responsible for amyloid beta clearances and the other regulating amyloid beta formation. These high-level findings have the potential to provide valuable insights into relevant genetic pathways and brain circuits, which can help form new hypotheses for more detailed imaging and genetics studies in independent cohorts.

Dissemination of Multiple Drug-Resistant Shigella flexneri 2a Isolates Among Pediatric Outpatients in Urumqi, China.

Multiple drug-resistant (MDR) Shigella isolates have been reported worldwide. Between May 2017 and September 2018, 55 Shigella flexneri 2a isolates were collected from 3322 stool samples of 0-10-year-old outpatients with diarrhea at the Children's Hospital of Urumqi, China. All isolates were characterized using serotyping, antimicrobial susceptibility testing, and whole-genome sequencing. A total of 54 of 55 (98.2%) isolates exhibited MDR phenotypes and had accumulated multiple resistance determinants, particularly of fluoroquinolones and cephalosporins preferred for shigellosis treatment: point mutations in quinolone resistance-determining regions (QRDRs) of topoisomerases (GyrA (S83L, D87N) and ParC (S80I) [n = 9]; GyrA (S83L) and ParC (S80I) [n = 45]) and acquisition of qnrS1 (n = 3) and blaCTX-M (n = 8). Over 70% of isolates acquired two point mutations of GyrA (S83L) and ParC (S80I) in QRDRs and 11 highly resistant isolates accumulated three point mutations in QRDRs or acquired qnrS1. Four S. flexneri 2a isolates from three single-nucleotide polymorphism clusters exhibited coresistance to ciprofloxacin, cefotaxime, or azithromycin (AZM), which are used as first- and second-line shigellosis treatment antimicrobials in clinics. Our data indicated that fluoroquinolones should be terminated in shigellosis treatment for outpatients in Urumqi. The transferable antimicrobial resistance determinants have been identified for third-generation cephalosporins and AZM. Novel strategies are urgently required for developing empirical medication to reduce the antimicrobial selective pressure and prevent dissemination of MDR S. flexneri 2a isolates.