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At least 19 recordsLinked to original sources
PubMed2025

Quantifying evidence for phenotypic specificity (PP4) for syndromic phenotypes: Large-scale integration of rare germline FH variants from diagnostic laboratory testing for HLRCC and renal cancer.

PURPOSE: Hereditary leiomyomatosis and renal cell cancer (HLRCC) is a rare cancer susceptibility syndrome exclusively attributable to pathogenic variants in FH (HGNC:3700). This article quantitatively weights the phenotypic context (PP4/PS4) of such very rare variants in FH. METHODS: We collated clinical diagnostic testing data on germline FH variants from 387 individuals with HLRCC and 1780 individuals with renal cancer and compared the frequency of "very-rare" variants in each phenotypic cohort with 562,295 population controls. We generated pan-gene very rare variant likelihood ratios (PG-VRV-LRs), domain-specific likelihood ratios for missense variants (DS-VRMV-LR) using spatial clustering analysis, and log2.08 likelihood ratios (LLRs) as applicable within the updated American College of Medical Genetics and Genomics/Association for Molecular Pathology variant classification framework. RESULTS: For HLRCC, the PG-VRV-LR was estimated to be 2669.4 (95% CI 1843.4-3881.2, LLR 10.77) for truncating variants and 214.7 (95% CI 185.0-246.9, LLR 7.33) for missense variants. For renal cancer, the PG-VRV-LR was 95.5 (95% CI 48.9-183.0, LLR 6.23) for truncating variants and 5.8 (95% CI 3.5-9.3, LLR 2.39) for missense variants. Clustering analysis in HLRCC cases revealed 3 "hotspot" regions wherein the DS-VRMV-LR increased to 1226.9. CONCLUSION: These data provide quantitative measures for very rare missense and truncating variants in FH, which reflect the differing phenotypic specificity of HLRCC and renal cancer and may be applicable in clinical variant classification.

Humans↗
PubMed1977

Classification of alpha1-antitrypsin (Pi) phenotypes by isoelectrofocusing. Distinction of six subtypes of the PiM phenotype.

Pi phenotypes have been determined by isoelectrofocusing in a sample of 538 healthy individuals from Southern Germany. Further subdivision of the common PiM phenotype is described. A procedure for the delineation of six common subtypes is presented. It is assumed that the six subtypes are determined by three alleles which are provisionally called PiMa, PiMb, and PiMc. Their frequencies in this sample were 0.75, 0.06, and 0.15, respectively.

Alleles↗
PubMedDate not supplied

Determination of phenotypes of esterases (Set) in fresh saliva and saliva stains by disc electrophoresis and the distribution of Set phenotypes in the Japanese population.

A rapid and simple disc electrophoretic technique for the determination of saliva esterase (Set) types is described. The frequency of Set types was F 16.4%, FS 49.8% and S 33.8%. The estimated gene frequency of Set-1F was 0.413 and of Set-1S was 0.587. An accurate determination of Set types was possible in 5--7 week-old saliva stains. This system may be useful in medicolegal applications.

Electrophoresis, Disc↗
PubMed2025

Optimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants.

Genotype-phenotype (G-P) analyses for complex morphological traits typically utilize simple, predetermined anatomical measures or features derived via unsupervised dimension reduction techniques (e.g. principal component analysis (PCA) or eigen-shapes). Despite the popularity of these approaches, they do not necessarily reveal axes of phenotypic variation that are genetically relevant. Therefore, we introduce a framework to optimize phenotyping for G-P analyses, such as genome-wide association studies (GWAS) of common variants or rare variant association studies (RVAS) of rare variants. Our strategy is two-fold: (i) we construct a multidimensional feature space spanning a wide range of phenotypic variation, and (ii) within this feature space, we use an optimization algorithm to search for directions or feature combinations that are genetically enriched. To test our approach, we examine human facial shape in the context of GWAS and RVAS. In GWAS, we optimize for phenotypes exhibiting high heritability, estimated from either family data or genomic relatedness measured in unrelated individuals. In RVAS, we optimize for the skewness of phenotype distributions, aiming to detect commingled distributions that suggest single or few genomic loci with major effects. We compare our approach with eigen-shapes as baseline in GWAS involving 8246 individuals of European ancestry and in gene-based tests of rare variants with a subset of 1906 individuals. After applying linkage disequilibrium score regression to our GWAS results, heritability-enriched phenotypes yielded the highest SNP heritability, followed by eigen-shapes, while commingling-based traits displayed the lowest SNP heritability. Heritability-enriched phenotypes also exhibited higher discovery rates, identifying the same number of independent genomic loci as eigen-shapes with a smaller effective number of traits. For RVAS, commingling-based traits resulted in more genes passing the exome-wide significance threshold than eigen-shapes, while heritability-enriched phenotypes lead to only a few associations. Overall, our results demonstrate that optimized phenotyping allows for the extraction of genetically relevant traits that can specifically enhance discovery efforts of common and rare variants, as evidenced by their increased power in facial GWAS and RVAS.

Humans↗
PubMed2026

Genetic Correlation Between Brain Imaging Phenotypes and Externalizing Behavior: A Large-Scale LDSC Analysis of UK Biobank IDPs.

Externalizing has been associated with differences in brain structure and function; however, it remains unclear whether these associations reflect shared common-variant genetic influences. Cross-trait linkage disequilibrium score regression was used to estimate genome-wide genetic correlations between externalizing genome-wide association study (GWAS) results and 3,935 brain imaging-derived phenotypes from the UK Biobank BIG40 resource. The imaging phenotypes covered structural magnetic resonance imaging (MRI), diffusion MRI, susceptibility-weighted imaging, resting-state functional MRI, and task-based functional MRI. Results were included in the primary analysis when the imaging phenotype had positive single-nucleotide polymorphism (SNP) heritability, a heritability Z statistic of at least 1.96, a mean GWAS chi-square statistic of at least 1.02, at least 200,000 regression SNPs, and a complete LDSC result without a fatal error. Technical imaging quality-control phenotypes were excluded from biological inference. Individual results were corrected using the Benjamini-Hochberg false discovery rate procedure. Aggregated Cauchy association tests (ACATs) were used to evaluate evidence across all imaging phenotypes and within predefined imaging categories. Statistical power, simultaneous confidence bounds, and alternative quality-control definitions were examined in sensitivity analyses. Of the 3,935 imaging phenotypes, 3,716 produced estimable genetic correlations, 2,980 met the primary LDSC quality-control criteria, and 2,967 were classified as biological imaging phenotypes. No individual phenotype survived false discovery rate correction. The smallest unadjusted P value was 0.0005, and the minimum adjusted q value was 0.486. The distribution of genetic correlations was centered near zero, with a median genetic correlation of 0.0014 and a median absolute genetic correlation of 0.0338. ACAT provided no evidence of an aggregate association across all biological imaging phenotypes (P = 0.302), and no predefined imaging category survived multiple-testing correction. The median minimum detectable genetic correlation at 80% power was 0.216. Bonferroni-adjusted simultaneous confidence intervals were fully contained within the interval [-0.30, 0.30] for 80.0% of phenotypes in the primary analysis and 88.0% under the stringent heritability quality-control definition. Broad and stringent sensitivity analyses produced the same overall conclusions. In this study, no statistically robust evidence of genome-wide genetic correlations between externalizing and individual UK Biobank brain imaging phenotypes was found. Nevertheless, small, localized, mixed-direction, or developmentally specific genetic effects remain possible.

Journal Article↗
PubMed2025

Charting the phenotypic landscape of mitochondrial diseases through a systematic evaluation of pathogenic mitochondrial DNA and nuclear gene variants.

PURPOSE: Primary mitochondrial diseases (PMD) arise from variants in the mitochondrial or nuclear genomes. Phenotype-based recognition of specific PMD genotypes remains difficult, prolonging the diagnostic odyssey. We expanded the MitoPhen database to characterize phenotypic variation across PMD more systematically. METHODS: Individual-level data on mitochondrial DNA disorders, nuclear-encoded mitochondrial diseases, and single large-scale mitochondrial DNA deletions were manually curated with Human Phenotype Ontology (HPO) terms to produce MitoPhen v2. Principal-component analysis summarized system-level abnormalities; HPO-level enrichment and mean phenotype-similarity scores were then used to distinguish common PMD genotypes. RESULTS: MitoPhen v2 adds 3940 individuals to the original release, now encompassing 1597 publications, 10,626 individuals, and 117 genotypes. Among 7586 affected cases, 72,861 HPO terms were recorded. Principal-component analysis revealed 6 phenotype dimensions capturing most system-level variance. At the HPO level, we observed genotype-specific enrichments and identified 111 gene-phenotype links absent from the current HPO database. Using MT-TL1, single large-scale mitochondrial DNA deletions, and POLG as exemplars, phenotype-similarity scores reliably separated individuals with these genotypes from those without. CONCLUSION: MitoPhen v2 enabled systematic, genotype-aware analysis of heterogeneous PMD phenotypes and highlighted the diagnostic value of structured, individual-level data. Phenotype-similarity metrics from such data sets can refine variant interpretation in large rare-disease cohorts and provide a transferable framework for other phenotypically complex genetic disorders.

Humans↗
PubMed1979

Response of variant hereditary angioedema phenotypes to danazol therapy. Genetic implications.

Hereditary angioedema (HAE), an auto-somal dominant disorder characterized by attacks of episodic edema is associated with decreased functional levels of the C1 esterase inhibitor. Approximately 85% of patients have lowered antigen levels of a normal inhibitor protein. 15% of patients have normal or elevated antigenic levels of functionless protein. We have examined the response to danazol therapy of patients with the variant HAE phenotypes possessing the abnormal protein in an effort to determine if these patients possess a normal structural C1 inhibitor allele. Four patients with a variant HAE phenotype were treated successfully with danazol. In two patients, distinguished by the presence of a functionless, albumin-bound, C1 inhibitor (phenotype 2), phenotypic analysis of the danazol response by bidirectional immunoelectrophoresis revealed the appearance of the normal C1 inhibitor gene product during danazol therapy. This relatively cathodal C1 inhibitor peak appears in conjunction with the development of nearly normal functional activity. All of the functional C1 inhibitory activity which appeared in the phenotype 2 treatment serum was associated with the electrophoretically normal inhibitor. This normal protein could be separated from the functionless inhibitor protein by immunoadsorption and molecular sieve chromatography. Danazol therapy of the two patients with an electrophoretically normal, functionless C1 inhibitor (phenotype 3) also resulted in a clinical remission associated with development of a significant increment in functional serum C1 inhibitory activity and C1 inhibitor protein. These findings demonstrate that these two HAE phenotypic variants are heterozygous for the normal serum C1 inhibitor, a finding which was not apparent before phenotypic analysis of this serum during danazol therapy. These data provide strong evidence for a basic similarity between the common form of HAE and its phenotypic variants. They also suggest that a structural gene lesion may result in the abnormalities of serum C1 inhibitor function and disease expression in all three of these HAE phenotypes.

Angioedema↗
PubMed2025

Divergent and stabilizing selection shape the phenotypic space of Arabidopsis thaliana.

Why do we observe some plant phenotypes but not others? The multivariate phenotypic space occupied by individuals or species often reveals both limits and phenotypes strikingly deviating from main syndromes. These observations are usually thought to indicate, respectively, inviable trait combinations and unique phenotypes adapted to specific environments. However, the evolutionary drivers underlying trait covariations often remain unclear. Here, we characterized the phenotypic space of Arabidopsis thaliana by comparing 713 wild accessions collected across the globe with 2,544 artificially-created recombinant individuals. This, combined with the detection of adaptive processes operating within species, allowed us to elucidate the roles of natural selection as a driver of phenotypic (co)variations within A. thaliana. We found that the phenotypic space of this species is constrained and driven by varying levels of divergent and stabilizing selection across different traits. Moreover, at the margins of the European geographic range, strong directional selection favored outlier phenotypes characterized by very late flowering and variation in a WRKY transcription factor gene. Genome analyses revealed that these extreme phenotypes may be explained by hybridization between ancestral and modern lineages of A. thaliana. Our findings demonstrate how interplays between population history and natural selection shape phenotypic diversity in a plant species.

Arabidopsis↗
PubMed2024

Quantitative natural history modeling of HPDL-related disease based on cross-sectional data reveals genotype-phenotype correlations.

PURPOSE: Biallelic HPDL variants have been identified as the cause of a progressive childhood-onset movement disorder, with a broad clinical spectrum from severe neurodevelopmental disorder to juvenile-onset pure hereditary spastic paraplegia type 83. This study aims at delineating the geno- and phenotypic spectra of patients with HPDL-related disease, quantitatively modeling the natural history, and uncovering genotype-phenotype associations. METHODS: A cross-sectional analysis of 90 published and 1 novel case was performed, using a Human-Phenotype-Ontology-based approach. Unsupervised phenotypic clustering was used alongside in silico analyses to identify distinct patient subgroups. RESULTS: The study models the natural history of the HPDL-related disease in a global cohort, clarifying the molecular and phenotypic spectrum and identifying 3 distinct subgroups characterized by differences in onset, clinical trajectories, and survival. It establishes genotype-phenotype associations, showing that the presence of moderately pathogenic missense variants in 1 allele leads to a milder, spastic paraplegic phenotype with later disease onset, whereas biallelic, highly pathogenic missense or truncating variants are associated with a more severe phenotype and reduced life span. CONCLUSION: Quantitative and unbiased natural history modeling in HPDL-related disease reveals significant genotype-phenotype associations, providing a foundation for variant interpretation, anticipatory guidance, and choice of outcome measures in future prospective and functional studies.

Humans↗
PubMed1979

Surface phenotyping, histology and the nature of non-Hodgkin lymphoma in 157 patients.

In a study of 157 patients with lymphoid malignancy, the phenotype of the tumour cells was correlated with the histological classification of the tumour using the Rappaport and the Kiel classifications. The markers used included E, Fc gamma, Fc micron (IgM) and C3d rosetting, estimation of SIg and CyIg, and tests for the expression of HTLA, Ia and ALL. Repeat biopsy specimens were studied in 23 of these patients. The phenotypic features of lymphoblastic malignancy indicated B-cell, T-cell and ALL-positive null-cell tumours in this group. Immunoblastic lymphomas were predominantly of non-capping B-cell type, but T-cell immunoblastic lymphoma occurred in 2 patients. Immunoblastic lymphomas of receptor-silent cells occur, and are ALL- and HTLA-negative. In the category of diffuse, poorly differentiated lymphocytic lymphomas, most cases are of centroblastic and centrocytic tumour of diffuse type, but pure centrocytic tumours and centroblastic tumours occur. The dominant phenotype in this group is of B cells expressing C3d receptors. Nodular poorly differentiated lymphocytic lymphomas (Rappaport) are classified as centroblastic and centrocytic follicular (Kiel) and most express SIg+ C3d+ phenotype. The frequency of this phenotype appeared the same in both diffuse and nodular poorly differentiated lymphocytic neoplasms. The Rappaport group of diffuse well-differentiated lymphocytic lymphoma includes 2 Kiel categories, malignant lymphoma lymphocytic, and malignant lymphoma lymphoplasmacytoid. Cells of the former tumour were considered to be immature B cells resembling those seen in CLL, and characteristically expressing SIg weakly, with a high frequency of single kappa light chain. Cells of the latter tumour are by contrast mature, and are related to the centroblastic and centrocytic follicular tumour by their histogenesis and phenotypic features. Repeat biopsy examinations indicate that T-cell predominance occurs in the prodromal phase of B-cell-predominant tumours of SIg+ C3d+ phenotype. It is concluded that non-Hodgkin lymphoma can be divided into 2 categories: (1) tumours of immature immunologically incompetent cells of lymphoblastic histology and with phenotypic features akin to T, B and Null-cell ALL, and (2) tumours of differentiated lymphocytes expressing the phenotypic features of B lymphocytes, with maturation arrested at one of several stages of an antigen-dependent immune response.

Adult↗
PubMed2024

Longitudinal characterization of impulsivity phenotypes boosts signal for genomic correlates and heritability.

Genomic correlates of impulsivity have been identified in several genome-wide association studies (GWAS) using cross-sectional designs, but no studies have investigated the molecular genetic correlates of impulsivity phenotypes using longitudinally constructed traits. In 3860 unrelated European participants in the Avon Longitudinal Study of Parents and Children (ALSPAC), we constructed longitudinal phenotypes for delay discounting and impulsive personality traits (as measured by the UPPS-P impulsive behavior scales) via assessment at ages 24, 26, and 28. We conducted GWASs of impulsivity using both cross-sectional and longitudinal phenotypes, estimated heritability and their phenotypic and genetic correlations, and evaluated their association with recently-developed polygenic risk scores (PRSs) for the impulsivity indicators themselves and also related psychiatric conditions. Latent growth curve modeling revealed a stable intercept over time for all impulsivity phenotypes. High genetic correlation of cross-sectional measures over time suggested a stable genetic component for delay discounting (rg = 0.53-0.99) and sensation seeking (rg = 0.99). Heritability estimates of the stable longitudinal phenotypes substantively improved as compared to their cross-sectional counterparts, revealing a significant SNP-heritability for delay discounting (0.22; p = 0.03) and sensation seeking (0.35; p = 0.0007). Consistent with previous reports, GWAS and gene-based analyses revealed associations between specific longitudinal impulsivity indicators and CADM2 and NCAM1 genes. The PRSs for the impulsivity indicators and disorders related to self-regulation were also significantly associated with longitudinal impulsivity traits. Finally, we validated the associations between longitudinal impulsivity phenotypes and their PRSs in an independent 13-wave longitudinal study (n = 1019) and the benefit of longitudinal phenotypes in simulation studies. In this first longitudinal genetic study of impulsivity traits, the results revealed stable genomic correlates of delay discounting and sensation seeking over time and further validated the utility of recently-developed PRSs, both in relation to the observed traits and in connecting them to psychiatric disorders. More generally, these findings support using latent intercepts as novel longitudinal phenotypes to boost signal for heritability and genomic correlates of mechanisms contributing to psychiatric disease liability.

Humans↗
PubMed1976

Relation of alpha-1-antitrypsin phenotype to the performance of pulmonary function tests and to the prevalence of respiratory illness in a working population.

Individuals with severe alpha-1-antitrypsin (alpha1AT) deficiency (phenotype Pi ZZ) are abnormally liable to develop emphysema, but it is uncertain whether those with partial alpha1AT deficiency (phenotypes Pi MS and MZ) are similarly susceptible. This study was undertaken to determine the frequency of the various Pi phenotypes in a working population in Northern Ireland and to compare the performance of simple pulmonary function tests and prevalence of respiratory symptoms and chest illness between different phenotypes. The population sample consisted of 1995 working men and women aged between 35 and 70 years. The MRC Questionnaire (1966) was used to assess respiratory symptoms, a forced expiratory spirogram was recorded, and a blood sample was analysed for alpha1AT phenotype by acid starch gel electrophoresis and antigen-antibody crossed electrophoresis in every case. The percentage frequencies of the alpha1AT phenotypes were: Pi MM 86-5; MS 7-97; MZ 3-86; IM 0-6; FM 0-4; SZ 0-25; M 0-15; SS 0-1; Z 0-05; MP 0-05; FS 0-05. Respiratory symptoms and a history of previous chest illness occurred with similar frequency among the Pi M, MS, and MZ phenotypes, and a comparison of the regression coefficients for FEV1, FVC, and MMF on age for each phenotype group showed no significant differences between them overall, or when subdivided according to smoking habits or dust exposure. These findings provide no evidence that individuals of phenotype Pi MS or MZ are more than usually liable to develop chronic airways obstruction.

Adult↗
PubMed2026

Genomic insights into stroke recovery: cross-phenotype associations.

Stroke is a major cause of long-term disability with variable recovery. While clinical factors such as initial severity play a role, genetic factors are increasingly recognized as important contributors to stroke recovery. Genotype studies are generally focused on a single post-stroke behavioural domain, but some genes might relate to broad mechanisms of plasticity. This study therefore aimed to identify cross-phenotypic genetic variants associated across two or more stroke recovery domains. DNA from Stroke, Stress, Rehabilitation, and Genetics study participants was genotyped, resulting in 9 814 610 variants. In order to examine cross-phenotypic results, we first conducted genome-wide association studies on the six recovery domains: motor (grip force), cognition (Telephone Montreal Cognitive Assessment), depression (Patient Health Questionnaire-8), stress (Primary Care Post-Traumatic Stress Disorder Screen), functional status (Stroke Impact Scale-Activities of Daily Living), and disability (modified Rankin Scale 0-2 versus 3-6), some of which were tested longitudinally, yielding nine phenotypes. Models were adjusted for age, sex, initial severity (NIH Stroke Scale score), and ancestry. Cross-phenotype associations were identified by evaluating single nucleotide polymorphisms (SNPs) associated (P < 5e-5) with multiple phenotypes. To determine how these genetic variants may relate to biological mechanisms of recovery, we conducted gene enrichment analyses. Participants (n = 565, 59% male) had mild-moderate initial stroke severity (median acute NIH Stroke Scale score = 4). After accounting for the correlation structure among the nine phenotypes, we observed 319 cross-phenotypic SNPs, 3.45 times the expected number. Five of the cross-phenotypic SNPs were linked to genes relevant to neural development, function and plasticity, e.g. ERICH1 (rs11778883-C), FOX3 (rs55726768-G), LIFR-AS1 (rs76401391-T), RPS6KA2 (rs113518460-C) and TUBGCP2 (rs147150392-C), as were enrichments in RAB5-EEA1, CTNNA1-CTNNB1, CIN85-SH3GL2 and ELMO1-DOCK2 complexes. Multiple gene enrichments were found, e.g. Stroke Impact Scale-Activities of Daily Living and Patient Health Questionnaire 8 at 3 months were enriched for CREB phosphorylation, which is important for long-term potentiation. We identified cross-phenotypic SNPs associated with multiple behavioural domains of stroke recovery. Some of these genes encode, or regulate, druggable proteins. These genetic factors are not well captured by clinical or neuroimaging assessments and so provide a unique window into stroke recovery. These findings, if validated, suggest that some genes may be broadly important to stroke recovery.

GWAS↗
PubMed2026

Osteoarthritis phenotypes: advancing precision medicine through clinical, structural, and molecular stratification.

PURPOSE: Osteoarthritis (OA) is now understood as a heterogeneous syndrome driven by diverse biological, biomechanical, metabolic, genetic, and molecular mechanisms. This variability explains differences in disease progression and treatment response, challenging the traditional "one-size-fits-all" approach. This review highlights OA phenotyping as a key step toward precision medicine, focusing on clinical, structural, and molecular classifications that inform individualized care. METHODS: A narrative review was conducted using a non-systematic search of major databases and Osteoarthritis Research Society International sources (2010-2026). Evidence was thematically synthesized across clinical, imaging, and molecular domains to characterize OA phenotypes and their potential relevance to precision medicine. RESULTS: Multiple OA phenotypes were identified: inflammatory, metabolic, biomechanical, cartilage-subchondral, pain-sensitization, and aging/senescence. These exhibit distinct clinical features, risk factors, and therapeutic responses. Imaging-based phenotypes (e.g., inflammatory, meniscus-cartilage, subchondral bone, atrophic, hypertrophic) and molecular endotypes (low turnover, structural damage, systemic inflammation) further refine stratification. Pain-structure discordance is notable in sensitization phenotypes and may predict poorer surgical outcomes. Joint-specific variations and emerging genomic and epigenetic insights underscore disease complexity. Advances in imaging, biomarkers, and machine learning may enable earlier detection and patient clustering, though clinical application remains limited. CONCLUSION: Phenotype- and endotype-based classification represents a critical advancement toward precision OA management. Tailored interventions based on stratification hold promise for improving outcomes; however, clinical translation remains limited by overlapping phenotypes, lack of validated biomarkers, and inconsistent results from phenotype-driven trials. Wider clinical adoption requires standardized definitions, validation across joints, and integration of multimodal diagnostic tools into routine practice.

Humans↗
PubMed2026

The bidirectional genetic causality between immunocyte phenotypes and dilated cardiomyopathy: A bidirectional Mendelian randomization study.

The association between immunocyte phenotypes and dilated cardiomyopathy (DCM) has been explored, however the exact pathogenesis of the relationship between immune cells and DCM is unclear. This bidirectional two-sample Mendelian randomization (MR) research aims to further validate the causal link between 731 immunocyte phenotypes and DCM. Summary statistics from a genome-wide association study data of individuals with European ancestry were utilized, including 1444 DCM cases and 353,937 controls, as well as 3757 European adults for the 731 immunocyte phenotypes. Causal effects were estimated using inverse variance weighted, MR-Egger regression, weight median estimator, weighted mode, and simple mode. Sensitivity analysis was conducted to confirm data robustness and feasibility. Based on the inverse variance weighted findings, 14 immunocyte phenotypes were risk factors for DCM (P&#x2005;<&#x2005;.05, odds ratio [OR]&#x2005;>&#x2005;1), while 15 immunocyte phenotypes exhibited a protective effect on DCM (P&#x2005;<&#x2005;.05, OR&#x2005;<&#x2005;1). The results of reverse MR analysis suggested evidence that DCM occurrence might elevate the levels of 17 immunocyte phenotypes (P&#x2005;<&#x2005;.05, OR&#x2005;>&#x2005;1) and decrease the levels of 9 immunocyte phenotypes (P&#x2005;<&#x2005;.05, OR&#x2005;<&#x2005;1). Our research indicated that CD28 on secreting regulatory T cell could mitigate the occurrence of DCM, and reciprocally, the progression of DCM could reduce the level of CD28 on secreting regulatory T cell. This study confirmed the bidirectional genetic predictive relationship between immunocyte phenotypes and DCM, underscoring the complex interplay between DCM and the immune system.

Cardiomyopathy, Dilated↗
PubMed2026

Phenotypes of Hereditary Diseases Associated With Rauch-Steindl Syndrome.

PURPOSE: Prenatal phenotypic manifestations of genetic disorders associated with NSD2 variants remain poorly characterized. This study presents our institutional experience with the prenatal diagnosis of NSD2-associated genetic disorders, specifically Rauch-Steindl syndrome (RAUST), aiming to improve understanding of both the molecular and clinical features of RAUST. METHODS: We performed a retrospective analysis of six fetuses and one adult diagnosed with RAUST at our institution and thoroughly reviewed the prenatal ultrasound reports of six fetuses. Prenatal and postnatal phenotypes of RAUST cases were summarized alongside findings from previously published literature. Correlations between NSD2 variant locations, variant types, and phenotypes were analyzed. Additionally, protein modeling was used to visualize structural changes in NSD2 protein before and after C-terminal variants. We integrated single-cell transcriptomic and gene expression data from multiple public databases to investigate spatiotemporal expression patterns of NSD2 during human fetal development. RESULTS: Fetal growth restriction (FGR) was the most prevalent prenatal manifestation in RAUST fetuses, followed by microcephaly. Bilateral renal hypoplasia emerged as a novel prenatal ultrasonographic feature. Postnatally, speech and motor developmental delays were the most commonly reported phenotypes, followed by physical developmental delays and intellectual disability. Genotype-phenotype correlation analysis revealed an association between N-terminal truncating variants in NSD2 and impaired fetal growth parameters. Notably, C-terminal truncating variants-predicted not to directly impact NSD2 functional domains-also exerted disease-causing effects. CONCLUSION: This study provides a comprehensive analysis of prenatal phenotypes in RAUST cases, enriching the prenatal phenotypic spectrum of the disease and facilitating early diagnosis and clinical management of RAUST. Furthermore, our genotype-phenotype correlation findings lay a foundational basis for future research into the complex molecular mechanisms underlying NSD2-associated genetic disorders.

Humans↗
PubMed2026

First-line drug-resistant tuberculosis among children under 15 years in Ethiopia: insights from phenotypic and whole-genome sequencing approaches.

BACKGROUND: Childhood drug-resistant tuberculosis is often underdiagnosed and inadequately characterized due to the paucibacillary nature of the disease. This study aimed to assess resistance to first-line anti-tuberculosis drugs in children using phenotypic drug susceptibility testing and whole-genome sequencing. METHODS: A retrospective-prospective study was conducted on culture-confirmed childhood tuberculosis cases in Ethiopia (2017&#x2013;2023). Phenotypic drug susceptibility testing was performed on 110 Mycobacterium tuberculosis complex isolates. Whole-genome sequencing was completed for 85 of these isolates, which were analyzed using the TB-Profiler and MTBSeq pipelines. We assessed the sensitivity, specificity, predictive values, and kappa agreement of whole-genome sequencing compared with phenotypic drug susceptibility testing. RESULTS: Phenotypic resistance to at least one first-line anti-TB drug was observed in 26/110 (23.6%) of the examined isolates, with isoniazid resistance being the most frequent, 23/110 (20.9%), followed by rifampicin resistance, 18/110 (16.4%). TB-Profiler showed almost perfect agreement with phenotypic drug susceptibility testing for rifampicin (sensitivity 94.4%, kappa&#x2009;=&#x2009;0.96) and isoniazid (sensitivity 91.3%, kappa&#x2009;=&#x2009;0.91), whereas MTBSeq showed slightly lower performance. Both pipelines demonstrated moderate to weak agreement with phenotypic drug susceptibility testing for detecting resistance to ethambutol, pyrazinamide, and streptomycin. The most frequently observed resistance mutations among phenotypically resistant isolates were rpoB (Ser450Leu), katG (S315Thr), embB (Met306Ile), and pncA (C-11&#xa0;A&#x2009;>&#x2009;G) for rifampicin, isoniazid, ethambutol, and pyrazinamide, respectively. Discrepancies between genotypic and phenotypic drug susceptibility testing were observed across all first-line anti-TB drug-resistant isolates, particularly for ethambutol and pyrazinamide. CONCLUSION: We found a high prevalence of isoniazid resistance, along with rifampicin resistance, underscoring the need for early detection in vulnerable groups. Whole-genome sequencing showed good accuracy for these drugs, with TB-Profiler performing best. CLINICAL TRIAL NUMBER: Not applicable.

Humans↗