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PubMed2026

Evaluation of Oxford nanopore sequencing for antimicrobial resistance surveillance in Salmonella: comparison with phenotypic antimicrobial susceptibility in a large-scale study.

UNLABELLED: Salmonella is a major zoonotic foodborne pathogen, and antimicrobial resistance (AMR) in Salmonella presents a significant public health challenge. Compared with conventional antimicrobial susceptibility testing (AST), whole-genome sequencing (WGS) provides a more rapid and comprehensive approach to AMR characterization, thereby informing antimicrobial selection and supporting public health surveillance. In this study, Oxford Nanopore Technology (ONT)-based WGS was performed on 1,490 Salmonella isolates collected through nationwide surveillance in Taiwan in 2025. Genotypic resistance inferred from WGS data was compared with phenotypic AST results to assess the performance of ONT-WGS. Overall, WGS-inferred resistance showed high concordance with phenotypic resistance for most antimicrobials. However, major genotype-phenotype discordance was observed, attributed to four categories: (i) breakpoint-dependent classification, (ii) reduced or absent phenotypic expression of resistance genes, (iii) minimum inhibitory concentration (MIC) modulation by ramAp, and (iv) absence of known AMR determinants. Notable discrepancies included tigecycline resistance without known genetic determinants, nalidixic acid resistance linked to ramAp-mediated MIC elevation, and a high prevalence of colistin resistance (35.7%) in S. Enteritidis, with most resistant isolates lacking identifiable AMR determinants. Additionally, a significant proportion of ESBL- and AmpC-producing isolates were classified as susceptible or intermediate to cefotaxime and ceftazidime under CLSI criteria, highlighting the potential for misclassification and treatment failure. These findings demonstrate that ONT-WGS enables accurate and comprehensive AMR characterization by directly identifying resistance determinants and avoiding potential misclassification associated with breakpoint-based AST interpretations. When interpreted appropriately, WGS can support better antimicrobial selection and serve as a valuable alternative to conventional susceptibility testing. IMPORTANCE: Accurate prediction of antimicrobial resistance is essential for appropriate therapy and effective surveillance of Salmonella. However, discordance between genotype-based predictions and phenotypic antimicrobial susceptibility testing (AST) can complicate clinical interpretation. In this nationwide study of 1,490 Salmonella isolates, we show that Oxford Nanopore Technology-based whole-genome sequencing (ONT-WGS) provides rapid and comprehensive detection of antimicrobial resistance determinants with high concordance to phenotypic AST. We further identify four major mechanisms underlying genotype-phenotype discordance, including breakpoint-dependent classification, reduced or absent phenotypic expression of resistance genes, minimum inhibitory concentration (MIC) modulation by ramAp, and the absence of known AMR determinants. These findings demonstrate how WGS can complement conventional AST, improve interpretation of challenging susceptibility results, and strengthen genomic surveillance of emerging antimicrobial-resistant Salmonella.

Microbial Sensitivity Tests↗

PubMed2026

Hybrid genome assembly and phenotypic assays reveal carbohydrate metabolism diversity in Lacticaseibacillus strains.

Investigation of carbohydrate metabolism in lactic acid bacteria is essential for the rational selection of strains for fermentation processes, particularly in emerging applications involving non-conventional substrates or building of synthetic microbial consortia. However, establishing robust genotype-phenotype relationships remains challenging, as gene presence alone often fails to explain observed metabolic traits without considering the genomic context and regulatory architecture. In the present study, we combined hybrid genome assembly (Illumina and Oxford Nanopore) with high-throughput phenotype profiling (Biolog GENIII and PM2A) to investigate carbohydrate utilization in five Lacticaseibacillus strains. Phenotypic assays revealed clear intra- and inter-specific variability in substrate utilization. We therefore investigated whether such differences could be attributed to the organization and regulatory context of carbohydrate-associated loci, rather than to gene presence alone. Functional annotation based on COG and CAZyme databases revealed candidate genomic regions potentially involved in carbohydrate metabolism. Comparative analysis between predicted and experimentally observed substrate usage highlighted specific loci associated with carbohydrate utilization profile. The trehalose (tre) operon was conserved across all strains, while at least two distinct cellobiose-associated loci were detected in each genome. Despite the presence of these loci, L. paracasei strains were unable to metabolize cellobiose, a phenotype likely linked to the presence of a downstream TetR-type transcriptional repressor within the cellobiose (cel) operon. Additionally, a genomic region uniquely found in L. rhamnosus strains was associated with gentiobiose utilization, consistent with phenotypic observations. Overall, these findings highlight the importance of integrating phenotypic validation with complete genome context to support the identification of candidate structural and regulatory determinants of carbohydrate utilization in lactic acid bacteria. KEY POINTS: • Phenotype microarrays reveal metabolic traits of interest in isolated strains. • Regulatory context is key to understanding carbohydrate metabolism differences. • Basis of subspecies-dependent cellobiose metabolism in L. paracasei is provided.

Carbohydrate Metabolism↗

PubMed2025

Predicting natural variation in the yeast phenotypic landscape with machine learning.

Most organismal traits result from the complex interplay of many genetic and environmental factors, making their prediction difficult. Here, we used machine learning (ML) models to explore phenotype predictions for 223 traits measured across 1011 genome-sequenced Saccharomyces cerevisiae strains isolated worldwide. We benchmarked a ML pipeline with multiple linear and non-linear models to predict phenotypes from genotypes and gene expression, and determined gradient boosting machines as the best-performing model. Gene function disruption scores and gene presence/absence emerged as best predictors, suggesting a considerable contribution of the accessory genome in controlling phenotypes. The prediction accuracy broadly varied among phenotypes, with stress resistance being easier to predict compared to growth across nutrients. ML identified relevant genomic features linked to phenotypes, including high-impact variants with established relationships to phenotypes, despite these being rare in the population. Near-perfect accuracies were achieved when other phenomics data mostly in similar conditions were used, suggesting that useful information can be conveyed across phenotypes. Overall, our study underscores the power of ML to interpret the functional outcome of genetic variants.

Genetic Variation↗

PubMed2025

Genotype-phenotype correlations with autism spectrum disorder-related traits in noonan syndrome and noonan syndrome with multiple lentigines: a cross-sectional study.

BACKGROUND: Noonan syndrome (NS) and Noonan syndrome with multiple lentigines (NSML) are neurodevelopmental conditions caused by genetic variants leading to upregulated signaling in the RAS-MAPK pathway. While previous research has focused on genetic variability in cognitive and cardiac phenotypes, behavioral phenotypes, and their correlations across genetic variants and within the PTPN11 gene remain poorly characterized. METHODS: This study included 121 individuals with NS (PTPN11: 88, SOS1: 18, RAF1: 6, KRAS: 2, RIT1: 3, NRAS: 2, LZTR1: 2, SOS2: 1) and seven individuals with NSML (PTPN11), compared to age- and sex-matched typically developing (TD) (N = 71). Behavioral questionnaires assessed social responsiveness and ASD-related traits (using SRS-2), and emotional problems (using CBCL) to identify genetic variant-specific behavioral profiles. Biochemical profiling of SHP2 activity in PTPN11-associated NS variants examined genotype-phenotype relationships. RESULTS: Compared to TD individuals, those with PTPN11-associated NS, NSML, and SOS1-associated NS exhibited clinically elevated scores, indicating increased ASD-related behaviors, poorer social functioning, and heightened emotional problems. Genetic variant comparisons revealed that individuals with PTPN11-associated NS and NSML exhibited greater ASD-related challenges than those with RAF1. Individuals with NSML exhibit elevated attention problems compared to all other genetic groups. Logistic regression results suggested each one-unit increase in SHP2 fold activation for PTPN11-associated NS corresponded to a 64% higher likelihood of markedly elevated restricted and repetitive behaviors, suggesting genotype-phenotype links. LIMITATIONS: Small sample sizes for rarer variants, leading to unequal group sizes across subgroups, with PTPN11 variants comprising most of the NS group. Future research should address these sampling constraints and conduct functional studies to clarify variant impacts. Longitudinal assessments could elucidate behavioral phenotype trajectories. CONCLUSIONS: This study underscores the importance of genetic variant-specific research to understand unique behavioral phenotypes in NS and NSML. Our findings indicate a higher risk for ASD-related symptoms in PTPN11-associated NS and NSML compared to other variants. Additionally, individuals with PTPN11-associated NS and higher SHP2 fold activation exhibited greater impairments in restricted and repetitive behaviors, suggesting SHP2 activation variations may contribute to phenotypic variability. By linking ASD-related symptoms to biochemical predictors in PTPN11-associated NS, this study may inform future targeted treatment approaches.

Humans↗

PubMed1977

The dissociation of the surface architecture described by enhanced lectin agglutinability and the transformed phenotype expressed as anchorage independence.

Using a series of cold-sensitive variants of chemically transformed BHK-21 cells, revertants to the normal phenotype derived from a dimethyl-nitrosamine transformed clone of BHK-21 as well as revertants to the normal phenotype derived from polyoma transformed BHK-21 cells we have demonstrated that the surface phenotype described by enhanced agglutinability with Con A and WGA can be dissociated from the transformed phenotype described by anchorage independence (growth in semisolid medium). Specifically we have demonstrated that the surface characteristic of enhanced agglutinability may be found in a variety of cell lines which fail to display to grow in agar. Our work clearly shows that the two phenotypes described are not concomitantly controlled and tends to suggest that the phenotype of enhanced lectin agglutinability may be dissociated from the transformed phenotype.

Agar↗

PubMed2026

Comparative genomics reveals genotype-phenotype concordance and cryptic resistomes in clinical Pseudomonas aeruginosa.

BACKGROUND: Pseudomonas aeruginosa (P. aeruginosa) is a major pathogen because of its adaptability. It shows rapid evolution of multidrug resistance (MDR). Phenotype-based diagnostics often fail to detect silent resistance determinants and early adaptive changes. This study integrates phenotypic profiling with whole-genome sequencing (WGS) to examine resistance architecture in clinical isolates from eastern India. METHODS: From 1295 culture-positive P. aeruginosa specimens collected at a tertiary care hospital in eastern India. Using predefined criteria, representative MDR and non-MDR isolates were selected, including distinct resistance phenotypes, specimen-source diversity, and hospital and community-acquired settings; multivariate analysis of resistance profiles illustrated phenotypic diversity. Antimicrobial susceptibility assessed using VITEK-2 and Kirby-Bauer disk diffusion, species identity confirmed by 16 S rRNA sequencing, and genomic analysis processed through a reference-guided workflow. Antimicrobial Resistance (AMR) determinants were identified through CARD, and phylogenetic tree constructed from 454 publicly available P. aeruginosa genomes. RESULTS: MDR exhibited greater sequence divergence relative to PA14 (~ 69,000 variants) than the non-MDR isolate (~ 58,700 variants), with > 92% coverage at ≥ 30X depth. Strong genotype-phenotype concordance observed in MDR isolates across five antibiotic classes, associated with β-lactamase variants (PDC-67, OXA-396) and regulatory adaptations (ArmR, cprS). The non-MDR isolate harboured gyrA (T83I) resistance-associated mutations, PDC-1, and OXA-847 without phenotypic expression, indicating silent resistome. Phylogenetically, MDR isolates clustered tightly within the phylogeny, while the non-MDR isolate formed a distinct lineage. CONCLUSION: Observed genomic differences align with adaptation under antimicrobial selection, though confirmation requires larger collections. The non-MDR isolate retained a silent resistome. Findings highlight limitations of phenotype-only diagnostics, support genomic data integration, and emphasize transcriptomics for hidden resistance expression and regulatory dynamics.

Pseudomonas aeruginosa↗

PubMed2026

ReverseGWAS identifies combined phenotypes associated with a genotype in GWA studies.

MOTIVATION: Traditional genome-wide association studies (GWAS) aim to uncover the genetic variants associated with a single phenotype of interest (typically a disease), and to elucidate its genotypic architecture. However, many of today's GWAS simultaneously measure multiple related phenotypes, leading to the possibility of pursuing the reverse aim of elucidating the "phenotypic architecture" of a single genetic variant. In other words, we may ask what combination of measured phenotypes is associated with a given genotypic variant. ReverseGWAS is an algorithmic platform for answering such questions in the context of large-scale multi-phenotype GWAS. RESULTS: We demonstrate the effectiveness of ReverseGWAS on simulated data, showing its ability to identify logical combinations of phenotypes with a reasonable amount of noise. We then apply it to a selection of combined phenotypes from the UK Biobank, obtaining 719 candidate associations using autoimmune diseases and 205 using common ICD10 codes. We find that the majority of these associations (546/719 and 111/205, respectively) successfully replicate in an independent cohort, FinnGen. AVAILABILITY AND IMPLEMENTATION: The source code of ReverseGWAS is freely available to non-commercial users as an installable R package at https://github.com/Leonardini/rgwas.

Phenotype↗

PubMed2026

A sequence-based classifier distinguishes phenotype-associated genes from other gene models in plants.

Only a small fraction of annotated plant genes possess experimentally validated associations with specific phenotypes. Phenotype-associated genes have distinct structural, molecular, and evolutionary characteristics compared with nonvalidated gene models. Here, we develop a simple classifier that uses sequence and evolutionary features, which can be generated for any species with an annotated reference genome assembly, to accurately distinguish phenotype-associated genes from both the overall population of annotated gene models and a specific set of genes identified as being tolerant of premature stop mutations. A model trained solely on genes from maize (Zea mays) identifies and prioritizes rice (Oryza sativa) and Arabidopsis (Arabidopsis thaliana) genes that are highly enriched in genes with experimentally validated links to phenotypes in both of these evolutionarily distant species. Gene models predicted to have a higher probability of being linked to phenotypes display patterns consistent with known biological properties of phenotype-associated genes. Notably, the sets of genes predicted to have a high probability of being linked to phenotype variation do not consist exclusively of well-characterized gene families but included many uncharacterized gene families carrying domains of unknown function. The quantitative scores generated by this model offer a valuable resource for prioritizing and exploring the vast number of uncharacterized gene models in plants, reducing the risk of failure in future reverse genetic efforts and potentially accelerating gene discovery and functional annotation in crops.

Phenotype↗

PubMed1978

Pi phenotypes and the prevalence of chest symptoms and lung function abnormalities in workers employed in dusty industris.

Epidemiologic surveys were carried out on 1,138 white men employed in sawmills and grain elevator terminals in British Columbia. In addition to the administration of an occupational-health questionnaire and spirometry, Pi phenotype and the concentration of serum alpha1-antitrypsin were determined. Most of the workers (88.8 per cent) had the Pi M phenotype, whereas 8.0 per cent had the MS phenotype, and 2.7 per cent had the MZ phenotype. Very few workers (0.4 per cent) had other phenotypes. No differences were found among the 3 major phenotypes in the prevalence of chest symptoms and lung function abnormalities, even among cigarette smokers. These findings did not indicate that workers have the MZ phenotype with intermediate alpha-1-antitrypsin deficiency are particularly susceptible to the development of chronic obstructive lung disease under the conditions prevailing in these industries.

Adult↗

PubMed1977

[Alpha-1-antitrypsin deficiency. Phenotype study of 60 members of the same family].

In two brothers treated for severe pulmonary emphysema, was demonstrated an alpha-1-antitrypsin deficiency associated with a ZZ phenotype (Pi system). The authors carried out a genetic study of the family including 60 members spread over 4 generations. In all, were demonstrated 4 subjects of phenotype ZZ, 29 of phenotype MZ, 3 of phenotype MS ; one subject had a phenotype SZ and 23 members of this family had normal levels of alpha-1-antitrypsin and were of phenotype MM. The disease was transmitted in all cases as an autosomic codominant. The interest of a study of the phenotype in alpha-1-antitrypsin deficiency is emphasized together with the practical steps to be taken on discovery of a subject with the allele responsible for a reduction in serum levels of alpha-1-antitrypsin.

Adult↗

PubMed2026

Genetic interconnections between personality-related phenotypes and psychiatric disorders.

BACKGROUND: Personality-related phenotypes are genetically correlated with psychiatric disorders, but whether these relationships reflect shared genetic loci and differ across individual phenotypes remains unclear. We investigated their shared genetic architecture at the level of specific phenotype-disorder pairs. METHODS: We analyzed genome-wide association study summary statistics for 13 personality-related phenotypes and eight psychiatric disorders in populations of European ancestry. Genetic correlations were evaluated separately for 104 phenotype-disorder pairs using linkage disequilibrium score regression and high-definition likelihood. For pairs supported by both methods, MTAG and CPASSOC were applied separately to identify pleiotropic signals, followed by linkage disequilibrium clumping, Bayesian colocalization, gene prioritization, functional enrichment and bidirectional two-sample Mendelian randomization analyses. No composite personality or psychiatric-disorder phenotype was constructed. RESULTS: Among the 104 evaluated pairs, 77 showed significant positive genetic correlations in both analyses. Joint screening of MTAG and CPASSOC results identified pleiotropic signals in 61 pairs, comprising 1088 independent lead SNV-pair associations and 776 unique SNVs. Bayesian colocalization supported 351 signals across 42 pairs and 284 unique lead SNVs. MAGMA identified 1293 unique genes, of which 379 were prioritized by PoPS and 151 were further supported by SMR. These genes were enriched in brain tissues and biological processes involving nervous system development, synaptic organization and intercellular connectivity. Inverse-variance weighted Mendelian randomization identified 41 forward and 32 reverse associations after false-discovery-rate correction, including 21 pairs with bidirectional evidence. CONCLUSION: These item-resolved analyses identify widespread but heterogeneous genetic sharing between personality-related phenotypes and psychiatric disorders. The findings provide a pair-specific map of shared loci and prioritized genes, while the Mendelian randomization results should be interpreted cautiously because of residual heterogeneity and potential horizontal pleiotropy. Further validation in diverse populations and functional studies is required.

Colocalization↗

PubMed2026

Spectral Transforms as a Tool to Optimize Digital Phenotyping in Biological Images.

Modern livestock breeding has mastered genotyping. Genome-wide association studies, genomic selection, and SNP arrays enable genetic merit prediction at lower cost. However, phenotyping remains the bottleneck, as manual measurement is slow, expensive, subjective, and unable to capture spatial or temporal trait organization. Digital phenotyping via artificial intelligence could resolve this, but deep learning requires thousands of labelled examples, impractical when phenotyping cost itself limits datasets to hundreds of individuals. This creates a paradox: AI could accelerate phenotyping but requires large numbers of samples to train the models. Here, we demonstrate that integrating computer vision with machine learning offers sample-efficient digital phenotyping using eggshell colour as a model system. Rather than learning features from scratch (deep learning), we engineer physically motivated features via Wavelet transforms that decompose images into multi-scale spatial components. Wavelet features captured 14.2 percentage points more variance (R2 = 0.976 vs. 0.834, p < 0.001) than standard colorimetry, with 50% better sample efficiency (achieving at n = 60 what colorimetry required n = 120). Variance decomposition revealed 77% of discriminative capacity derives from spatial patterns (bands, spots, gradients) invisible to scalar averages. Additionally, we identified "cryptic phenotypes" (3.3%) where spatial patterns contradicted average colour, cases where colorimeters failed but Wavelets succeeded. The underlying principle-that spatial decomposition can recover organizational information lost by scalar averaging-may be applicable to other traits with spatial or temporal structure, such as marbling, dermatitis, or pigmentation rhythms, although whether comparable performance gains would be observed remains to be tested empirically. Hence, for breeding programs implementing genomic selection, computer vision-based digital phenotyping captures complex trait variation without massive training datasets, addressing the bottleneck that increasingly limits genetic progress as genotyping becomes trivial.

Wavelet transform↗

PubMed2026

Dental phenotypes associated with novel PHEX variants in X-linked hypophosphatemia.

OBJECTIVES: X-linked hypophosphatemia (XLH) is a genetic disorder related to bone, mainly due to the mutations in PHEX gene. Previous studies have reported that XLH patients had various tooth phenotypes. It is unclear whether there are any rules about these abnormal tooth phenotypes, especially in those XLH cases with PHEX mutations. The objectives of this study were to find the most representative dental characteristics of XLH and the possible phenotype-genotype correlation. DESIGN: Two unrelated patients with XLH underwent clinical, radiographic, biochemical, and genetic evaluation. Whole-exome sequencing and whole-genome sequencing were used to identify pathogenic variants. The ultrastructure of extracted teeth was analyzed using a stereomicroscope, micro-CT, and scanning electron microscopy. In addition, a PubMed search (up to January 2026) identified 22 articles involving 366 patients for descriptive phenotype comparison. RESULTS: Two novel PHEX variants were identified: a novel complex structural variant (NC_000023.11, g.22035649-22041668delins) and a novel heterozygous splice-site variant (NM_000444.6, c.850-1 G>A). Radiographic examination showed enlarged pulp chambers and irregular pulp morphology. Ultrastructural analysis revealed dentin defects, including globular dentin, irregular interglobular dentin, disrupted dentinal tubules, and exposed collagen fibrils. Literature-based analysis indicated prevalent clinical manifestations (pulp necrosis, tooth loss, periodontitis) and radiographic findings (enlarged pulp chamber, and prominent pulp horn). CONCLUSION: In these two patients, novel PHEX variants were associated with a recurrent dentin-pulp phenotype. Integrated clinical, radiographic, ultrastructural, and literature evidence supports dentin defects as a central component of the dental phenotype in XLH and underscores the importance of early dental assessment.

Humans↗

PubMed2026

Causal relationships between oral-gut microbiome and bone neoplasm-related phenotypes: Insights from bidirectional Mendelian randomization.

The human oral and gut microbiota are the 4 largest microbial communities in the body and play crucial roles in maintaining homeostasis and influencing disease. Observational studies have suggested links between these microbiota and bone neoplasm-related phenotypes, but establishing causality has been challenging due to confounding factors and reverse causality. We conducted a bidirectional, 2-sample Mendelian randomization (MR) study to investigate evidence consistent with a potential causal association between the saliva and gut microbiota and various bone neoplasm-related phenotypes. Genetic instruments for saliva and gut microbiota were sourced from large genome-wide association studies. Inverse variance weighted was the primary MR method, supplemented by 4 other MR techniques. Sensitivity analyses, including MR-Egger regression, were performed to assess pleiotropy and heterogeneity. In the forward MR analysis, Veillonella parvula from the saliva microbiota was associated with a decreased risk of bone and connective tissue neoplasms (β: -0.236, 95% CI: [-0.275, -0.197], P = 8.20E-33). MR analyses identified genetically predicted associations between several microbial taxa and bone neoplasm-related phenotypes. Reverse MR analyses showed that genetic liability to bone neoplasm-related phenotypes was associated with variation in the composition of the oral (e.g., Order Bacteroidales, Rothia mucilaginosa) and gut microbiota (e.g., Class Methanobacteria, Genus Eubacterium oxidoreducens group). Sensitivity analyses confirmed the robustness of these findings, as no statistical evidence of substantial heterogeneity or directional horizontal pleiotropy was detected. This study provides genetic evidence supporting a bidirectional causal relationship between specific saliva and gut microbiota and bone neoplasm-related phenotypes. Our findings identify several microbial taxa as potential candidates for future biomarker development and therapeutic investigation in bone neoplasm-related phenotypes. However, these genetically informed associations require further mechanistic, experimental, and prospective clinical validation before clinical application.

Humans↗

PubMed2024

Diverse phenotypes and fertility outcomes of patients with androgen insensitivity syndrome in a Chinese family harboring identical AR gene variant.

BACKGROUND: Androgen insensitivity syndrome (AIS) is a rare genetic disorder characterized by resistance to androgens, mainly due to mutations in the androgen receptor (AR) gene. It can manifest as complete AIS, partial AIS and mild AIS. While there have been studies linking specific AR gene mutations to AIS phenotypes, different clinical AIS phenotypes are also reported in patients with the same AR gene mutation. So far, the precise correlations between phenotypes and genotypes remain incompletely understood. METHODS: We conducted a thorough investigation involving four patients diagnosed with different types of AIS from a single Chinese family. Clinical manifestations, laboratory examinations, and fertility outcomes were well-documented. Furthermore, we performed genetic sequencing to detect possible pathogenetic variants. RESULTS: Whole exome sequencing identified a hemizygous missense variant (c.2263T > C; p.Phe755Leu) of AR gene in all four affected patients with different degrees of undermasculinisation and heterogeneous spermatogenesis. The proband, diagnosed with partial AIS, opted for treatment with donated sperm due to non-obstructive azoospermia, while their older sibling, diagnosed with complete AIS, was raised as a girl. His two maternal uncles were both diagnosed with mild AIS, the older uncle fathered two girls naturally, whereas the younger uncle utilized assisted reproductive technology to conceive a boy because of severe oligoasthenozoospermia. CONCLUSION: Our study first identified the same AR variant (c.2263T > C;p.Phe755Leu) in four affected patients displaying highly diverse phenotypes of AIS and fertility outcomes, thereby significantly expanding the phenotypic spectrum of AIS. Notably, we presented a clear insight into different fertility outcomes of AIS patients with identical AR (c.2263T > C;p.Phe755Leu) variant, which provided reliable evidence that males harboring this variant may obtain biological offspring naturally or in combination with assisted reproductive technology. Furthermore, our study underscored the potential role of androgen concentration in shaping the phenotypic diversity of AIS, warranting further investigation.

Adult↗

PubMed2025

Distinct immune-metabolic phenotypes underlie poor coronary collateral circulation.

BACKGROUND: Coronary collateral circulation (CCC) significantly impacts myocardial perfusion and clinical outcomes in coronary artery disease patients, yet the underlying molecular heterogeneity remains inadequately characterized. OBJECTIVE: To identify distinct molecular phenotypes in patients with poor CCC, validate these phenotypes using clinical parameters, and evaluate their prognostic implications. METHODS: This study enrolled 149 patients (80 with good CCC and 69 with poor CCC) for high-throughput proteomic profiling. Unsupervised consensus clustering identified molecular subtypes within poor CCC patients, followed by differential expression analysis and KEGG pathway enrichment. Boruta feature selection was implemented, and multiple machine learning algorithms were tested on clinical data, with XGBoost optimization (accuracy 80.0%, F1-score 80.31%) and SHAP value interpretation. External validation was performed using the MIMIC database. Kaplan-Meier analysis and Cox regression models assessed major adverse cardiovascular events (MACE). RESULTS: Two distinct phenotypes emerged among poor CCC patients: Cluster 1 (n = 39, Complement-Driven Vascular Remodeling [CDVR]) and Cluster 2 (n = 30, Immuno-Thrombotic Myocardial Dysfunction [ITMD]). An XGBoost model incorporating fasting glucose, eosinophil percentage, and HbA1c achieved excellent discrimination (AUC > 0.91). External validation confirmed the phenotype-specific clinical patterns. Notably, Cluster 2 demonstrated significantly higher MACE incidence compared to Cluster 1 (Log-rank p < 0.05), with KEGG analysis revealing significant upregulation of platelet activation, diabetic cardiomyopathy, and metabolic pathways in the ITMD phenotype. CONCLUSION: Poor CCC encompasses distinct immune-metabolic phenotypes that can be accurately classified using integrated proteomic-clinical modeling. This classification enables more precise risk stratification and may guide personalized therapeutic strategies for coronary artery disease patients with inadequate collateralization.

Humans↗

PubMed1979

Abnormal enzyme phenotype (E1a E1f): normal response to succinylcholine.

The enzyme serum cholinesterase responsible for the hydrolysis of the muscle relaxant succinylcholine exists in the form of several variants. These may be identified in serum by using substances which inhibit their activity to different degrees. The heterozygote for the atypical and fluoride resistant enzymes (E1a E1f) is one of the phenotypes which has been reported to be sinsitive to succinylcholine. A case is described where succinylcholine given on two separate occasions did not induce apnoea in an individual phenotyped as E1a E1f by at least five methods of inhibition. This is the first reported example of such insensitivity to the drug in this phenotype. Temperature activities for the patient's serum over the range of 20 degrees C to 45 degrees C differed from that of an established E1a E1f phenotype used as a control. There was a progressive inactivation of the control serum at temperatures higher than 35 degrees C, as previously reported for this phenotype. Activity in the serum of the subject of this study did not exhibit the peak activity at 35 degrees C but continued to rise and probably reached a peak between 40 degrees C and 45 degrees C. The significance of these results in the context of current methods of phenotyping is discussed.

Adolescent↗

PubMed1979

Multiple new phenotypes induced in 10T1/2 and 3T3 cells treated with 5-azacytidine.

Three new mesenchymal phenotypes were expressed in cultures of Swiss 3T3 and C3H/10T1/2CL8 mouse cells treated with 5-azacytidine or 5-aza-2'-deoxycytidine. These phenotypes were characterized as contractile striated muscle cells, biochemically differentiated adipocytes and chondrocytes capable of the biosynthesis of cartilage-specific proteins. The number of muscle and fat cells which appeared in treated cultures was dependent upon the concentration of 5-azacytidine used, but the chondrocyte phenotype was not expressed frequently enough for quantitation. The differentiated cell types were only observed several days or weeks after treatment with the analog, implying that cell division was obligatory for the expression of the new phenotypes. Oncogenically transformed C3H/10T1/2CL8 cells also developed muscle cells after exposure to 5-azacytidine, but at a reduced rate when compared to the parent line. Five subclones of the 10T1/2 line which were the progeny of single cells all expressed both the muscle and fat phenotypes following 5-azacytidine treatment. The effects of the analog are therefore not due to the selection of preexisting myoblasts or adipocytes in the cell populations. Rather, it is possible that 5-azacytidine, after incorporation into DNA, causes a reversion to a more pluripotential state from which the new phenotypes subsequently differentiate.

Adipose Tissue↗