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PubMed2026

Genomic diversity, inbreeding, and selection signatures in duroc, landrace, and yorkshire pigs from a long-term closed breeding system.

Duroc (DD), Landrace (LL), and Yorkshire (YY) are among the most widely used commercial pig breeds, having undergone intense long-term selection within closed breeding systems. This study presents a comprehensive genomic analysis of genetic diversity, inbreeding patterns, and selection signatures in DD, LL, and YY populations that have been subject to close breeding for over 15 years. Genomic and pedigree data were available for 1,088 animals (DD = 348, LL = 276, YY = 464), genotyped using the GenoBaits® Porcine 100 K SNP panel. Principal component analysis and genetic diversity metrics revealed distinct population structures among the three breeds. Pairwise genetic differentiation supported this pattern, with DD showing the greatest divergence from LL (0.34 ± 0.24) and YY (0.33 ± 0.24), while LL and YY were more closely related (FST = 0.22 ± 0.19). Linkage disequilibrium (LD) analysis further confirmed these differences, as DD exhibited the highest average r² (0.34), followed by LL (0.28) and YY (0.25). Within-breed genetic diversity metrics, including observed heterozygosity (HO: 0.37 in DD, 0.39 in LL, 0.38 in YY), expected heterozygosity (HE: 0.36 in DD, 0.37 in LL, 0.38 in YY), and minor allele frequency (MAF: 0.27 in DD, 0.28 in LL, 0.29 in YY), indicated greater genetic variability in LL and YY compared to DD. Runs of homozygosity (ROH) analyses revealed different patterns of autozygosity, with DD exhibiting more long ROH indicative of recent inbreeding, while YY harbored a higher number of short ROH, suggestive of more ancient demographic events. ROH-based inbreeding coefficients (FROH) consistently exceeded pedigree-based estimates (FPED) across all breeds, highlighting the presence of recent or unrecorded inbreeding that pedigree data may not fully capture. According to Generation Proxy Selection Mapping (GPSM), 17, 1, and 12 significant SNPs were detected in DD, LL, and YY, respectively. Functional annotation of ROH islands and GPSM-significant loci revealed both breed-specific and overlapping QTLs related to traits such as growth, reproduction, and carcass. In general, the findings of this study contribute to a deeper understanding of the genomic consequences of long-term closed breeding and provide reference information to support consideration of breeding strategies that balance continued selection for productivity with the maintenance of genetic diversity in modern commercial pig populations.

Animals↗

PubMed2024

The evolution of cnidarian stinging cells supports a Precambrian radiation of animal predators.

Cnidarians-the phylum including sea anemones, corals, jellyfish, and hydroids-are one of the oldest groups of predatory animals. Nearly all cnidarians are carnivores that use stinging cells called cnidocytes to ensnare and/or envenom their prey. However, there is considerable diversity in cnidocyte form and function. Tracing the evolutionary history of cnidocytes may therefore provide a proxy for early animal feeding strategies. In this study, we generated a time-calibrated molecular clock of cnidarians and performed ancestral state reconstruction on 12 cnidocyte types to test the hypothesis that the original cnidocyte was involved in prey capture. We conclude that the first cnidarians had only the simplest and least specialized cnidocyte type (the isorhiza) which was just as likely to be used for adhesion and/or defense as the capture of prey. A rapid diversification of specialized cnidocytes occurred through the Ediacaran (~654-574 million years ago), with major subgroups developing unique sets of cnidocytes to match their distinct feeding styles. These results are robust to changes in the molecular clock model, and are consistent with growing evidence for an Ediacaran diversification of animals. Our work also provides insight into the evolution of this complex cell type, suggesting that convergence of forms is rare, with the mastigophore being an interesting counterexample.

Animals↗

PubMed2026

Viral tags as keys to advancing invasion genomics.

Invasion genetics and genomics have greatly advanced the study of biological invasions, yet they often fail to resolve population dynamics at the fine spatiotemporal scales characteristic of most invasions. We propose shifting the focus away from the higher-order target species towards their viral symbionts, harnessing these as high-resolution 'genetic tags' to overcome many of these limitations. Owing to their comparably smaller genomes, shorter generation times, and higher mutation rates, most viruses evolve on timescales comparable to the invasion dynamics of their higher-order hosts, potentially better proxying and revealing recent dispersal patterns. We present a conceptual framework outlining how virus evolution may shed light on the contemporary spread of their non-native hosts, opening new avenues for invasion genetics, genomics, and management.

Genomics↗

PubMed2022

Association of Vitamin D Polygenic Risk Scores and Disease Outcome in People With Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: Observational studies suggest low levels of 25-hydroxyvitamin D (25[OH]D) may be associated with increased disease activity in people with multiple sclerosis (PwMS). Large-scale genome-wide association studies (GWAS) suggest 25(OH)D levels are partly genetically determined. The resultant polygenic scores (PGSs) could serve as a proxy for 25(OH)D levels, minimizing potential confounding and reverse causation in analyses with outcomes. Herein, we assess the association of genetically determined 25(OH)D and disease outcomes in MS. METHODS: We generated 25(OH)D PGS for 1,924 PwMS with available genotyping data pooled from 3 studies: the CombiRx trial (n = 575), Johns Hopkins MS Center (n = 1,152), and Immune-Mediated Inflammatory Diseases study (n = 197). 25(OH)D-PGS were derived using summary statistics (p < 5 × 10-8) from a large GWAS including 485,762 individuals with circulating 25(OH)D levels measured. We included clinical and imaging outcomes: Expanded disability status scale (EDSS), timed 25-foot walk (T25FW), nine-hole peg test (9HPT), radiologic activity, and optical coherence tomography-derived ganglion cell inner plexiform layer (GCIPL) thickness. A subset (n = 935) had measured circulating 25(OH)D levels. We fitted multivariable models based on the outcome of interest and pooled results across studies using random effects meta-analysis. Sensitivity analyses included a modified p value threshold for inclusion in the PGS (5 × 10-5) and applying Mendelian randomization (MR) rather than using PGS. RESULTS: Initial analyses demonstrated a positive association between generated 25(OH)D-PGS and circulating 25(OH)D levels (per 1SD increase in 25[OH]D PGS: 3.08%, 95% CI: 1.77%, 4.42%; p = 4.33e-06; R2 = 2.24%). In analyses with outcomes, we did not observe an association between 25(OH)D-PGS and relapse rate (per 1SD increase in 25[OH]D-PGS: 0.98; 95% CI: 0.87-1.10), EDSS worsening (per 1SD: 1.05; 95% CI: 0.87-1.28), change in T25FW (per 1SD: 0.07%; 95% CI: -0.34 to 0.49), or change in 9HPT (per 1SD: 0.09%; 95% CI: -0.15 to 0.33). 25(OH)D-PGS was not associated with new lesion accrual, lesion volume or other imaging-based outcomes (whole brain, gray, white matter volume loss or GCIPL thinning). The results were similarly null in analyses using other p value thresholds or those applying MR. DISCUSSION: Genetically determined lower 25(OH)D levels were not associated with worse disease outcomes in PwMS and raises questions about the plausibility of a treatment effect of vitamin D in established MS.

Humans↗

PubMed2026

Biofilm formation during pneumococcal carriage imprints naturally acquired humoral immunity.

Streptococcus pneumoniae (Spn) colonization of the nasopharynx is a prerequisite for transmission and invasive disease. To investigate how repeated asymptomatic colonization shapes immunity and influences bacterial traits, we developed the Repeated Asymptomatic Murine Pneumococcal Colonization (RAMPC3) model using strains belonging to serotypes: 2 (D39), 3 (WU2), and 4 (TIGR4). Sequential colonization revealed strain- and exposure-order-dependent effects on bacterial burden, with initial colonization yielding robust carriage and subsequent exposures resulting in diminished burden and rapid clearance. Humoral profiling demonstrated antigenic imprinting: the first colonizing strain largely determined IgG and IgA specificity against bacterial proteins, with minimal diversification or expansion after repeated exposures. Reactivity was strongest for biofilm-associated antigens correlating with each strain's biofilm-forming capacity. Notably, experiments using human sera from naturally colonized adults mirrored these findings, with reactivity favoring biofilm antigens independent from capsule. Partial protection as result of colonization was demonstrated as triple-colonized mice had reduced mortality following pneumococcal pneumonia challenge. Likewise, mice colonized with biofilm deficient versions of TIGR4 and then challenged intratracheally with a serotype 6A (6A-10) strain were more likely to develop bacteremia, underscoring the contribution of the biofilm-associated host response to immunity. Finally, IgA responses in nasal-associated lymphoid tissue paralleled serum IgA patterns, validating systemic measurements as a proxy for mucosal immunity. These results reveal that biofilm formation during colonization is a key determinant of humoral immunity and contributes to systemic protection, providing insight into pneumococcal biology and informing strategies to design next-generation interventions.

Animals↗

PubMed2026

Genetically proxied circulating PD-1/PD-L1 levels and broadly defined myocarditis: A bidirectional Mendelian randomization study with exploratory lipidomic analyses.

Myocarditis is an inflammatory myocardial disease with potentially severe outcomes. Programmed cell death protein 1 (PD-1) and programmed death-ligand 1 (PD-L1) regulate immune tolerance, but the association between lifelong genetically proxied circulating PD-1/PD-L1 levels and broadly defined myocarditis remains uncertain. We investigated these associations and explored related plasma lipid species. We conducted bidirectional 2-sample Mendelian randomization using proteomic genome-wide association data from the UK Biobank Pharma Proteomics Project and INTERVAL. FinnGen Release 10 was the primary broadly defined myocarditis outcome, and an independent myocarditis genome-wide association study (GCST90018882) provided outcome-level validation. Complementary estimators, heterogeneity and pleiotropy diagnostics, influence analyses, MR-RAPS, and supportive meta-analyses were performed. Associations with 179 plasma lipid species were examined in exploratory analyses. Higher genetically proxied circulating PD-L1 was inversely associated with broadly defined myocarditis in UKB-PPP (odds ratio [OR] 0.834, 95% confidence interval [CI] 0.698-0.995; P = .0441), and the independent INTERVAL analysis yielded a concordant inverse estimate (OR 0.619, 95% CI: 0.434-0.883; P = .0083); no clear association was observed for PD-1. The MR-RAPS estimate retained the inverse direction; estimates against the independent broadly defined myocarditis dataset were also inverse, and supportive meta-analyses across protein and outcome sources yielded inverse pooled estimates. Reverse MR did not support effects of broadly defined myocarditis liability on circulating PD-1 or PD-L1. Exploratory lipid analyses identified nominal associations requiring confirmation. Higher genetically proxied circulating PD-L1 may be associated with a lower risk of broadly defined myocarditis, supporting further investigation of PD-L1-related immune regulation. These findings do not directly estimate the effects of pharmacologic PD-1/PD-L1 blockade. The lipid findings are hypothesis-generating.

Myocarditis↗

PubMed2026

Sequence optimization targeting mRNA stability enhances monoclonal antibody titers in CHO cells.

This study presents a DNA sequence optimization approach that integrates mRNA stability as a tunable design parameter to enhance monoclonal antibody expression in Chinese hamster ovary (CHO) cells. A comprehensive combinatorial library of synonymous coding-sequence variants of an IgG1 light chain was integrated as single copies at a defined genomic locus in CHO cells with identical regulatory elements. Steady-state mRNA abundance, quantified by deep sequencing of gDNA and mRNA, served as a proxy for mRNA stability. These data were used to train a machine learning model that predicts mRNA abundance from coding sequence using embeddings from a pre-trained nucleotide transformer. This abundance predictor, together with established translational metrics, was incorporated into a genetic algorithm for multi-objective codon optimization. As proof-of-concept, we optimized sequences encoding Trastuzumab to either maximize or minimize the abundance criterion and obtained benchmark sequences from two commercial providers. Using targeted integration, we generated CHO cell lines and measured protein titer and cell-specific productivity. Sequences optimized for high abundance significantly increased intracellular mRNA levels (+41%), protein titer (+59%), and cell-specific productivity (+85%) relative to low-abundance designs, while viable cell densities remained comparable. Compared to commercial benchmarks, high-abundance sequences achieved significantly higher titer (+70%) and cell-specific productivity (+98%). These findings establish mRNA stability as a practical and complementary design parameter for codon optimization in monoclonal antibody production, with potential applicability to other proteins and expression systems.

CHO↗

PubMed2026

Safeguarding biomedical AI: a critical scoping review of privacy-enhancing technologies, hybrid approaches, and deployment models.

BACKGROUND: Biomedical artificial intelligence (AI) requires the integration of privacy-enhancing technologies (PETs) to safeguard sensitive clinical, imaging, and genomic data while preserving analytical utility. OBJECTIVES: This review critically and systematically maps applications of PETs across the biomedical AI lifecycle in accordance with PRISMA-ScR guidelines and evaluates their technical trade-offs, deployment feasibility, and residual risks. METHODS: We systematically searched PubMed, IEEE Xplore, ACM Digital Library, and Scopus for studies published between 2015 and 2025. Eligible studies addressed differential privacy, federated learning, secure multiparty computation, homomorphic encryption, or hybrid approaches in biomedical AI. Data were charted on PET type, modality, lifecycle stage, utility metrics, privacy parameters, and deployment considerations. A critical appraisal rubric assessed threat-model adequacy, methodological clarity, reproducibility, privacy-utility transparency, and deployment realism. Additionally, we hand-searched major venues (USENIX Security, NeurIPS, AAAI) and screened Google Scholar for grey literature, applying de-duplication across sources. RESULTS: We identified 87 studies spanning clinical decision support, genomics, and medical imaging. From 25,761 initial records, 3,754 underwent title/abstract screening and 1,968 underwent full-text assessment. PETs demonstrated distinct strengths and limitations: differential privacy provided provable guarantees but reduced performance on imbalanced data; federated learning improved data access but remained vulnerable to gradient leakage; and cryptographic methods ensured confidentiality at high computational cost. Synthetic data generation supported privacy-conscious data sharing and benchmarking but remained sensitive to disclosure risk, fidelity loss, and subgroup representation. Hybrid and emerging approaches, including trusted execution environments, zero-knowledge proofs, and privacy-preserving transformer architectures, mitigated composability gaps yet lacked full end-to-end assurance. Case studies at hospital and biobank scale illustrated practical feasibility and infrastructure demands. CONCLUSIONS: Situating PETs within technical and operational contexts clarifies their capabilities, limitations, and deployment challenges. Residual risks persist, including fairness concerns, inference-time leakage, and overreliance on PETs as compliance proxies. Sustained technical innovation and institutional governance remain essential for the trustworthy integration of PETs in biomedical AI.

biomedical AI↗

PubMed2026

The Continuity Trap in Data Science Health Research.

Secondary use is now the ordinary condition of data science health research rather than an exception to it. Electronic health records collected for clinical care become prediction tools and inputs for generative AI; imaging archives become foundation-model corpora; genomic datasets become resources for polygenic risk scores; and legacy biospecimens become renewable, indefinitely distributable cell lines. Governance has responded by emphasizing verifiable instruments such as provenance logs, repository approvals, broad-consent forms, data-use agreements, model cards, records of processing, and locality-preserving architectures. These instruments are necessary, and they answer real questions about lineage, privacy, institutional responsibility, and accountability, but they are not sufficient to establish that a present use remains ethically justified. We define ethical continuity as the persistence of normatively relevant relationships between the original conditions of data generation or material collection and subsequent downstream uses, such that current uses remain justifiable in light of the expectations, permissions, meanings, and relational obligations present at entrustment. We then define the Continuity Trap as a review-stage governance error in which a salient signal of continuity in one domain is treated as sufficient evidence of ethical continuity overall, causing inquiry into the remaining domains to close prematurely. The trap is not ordinary noncompliance, ethics creep, or a demand for universal rereview; it is a cross-domain inference error that can arise even in careful, good-faith review. We distinguish it from proxy closure, of which it is a continuity-specific subtype, and from Goodhart's and Campbell's laws, which describe how measures degrade once they become targets. We operationalize ethical continuity across 4 domains: provenance, semantics, authorization, and relational standing, developed in our Representational Veracity framework, and we show that these domains can diverge as data are linked, transformed, modeled, and redeployed. We identify the institutional mechanisms-provenance privilege, descriptor sedimentation, authorization fossilization, and community effacement-that cause auditable signals to be overread, and we examine how the US Health Insurance Portability and Accountability Act (HIPAA) of 1996, the General Data Protection Regulation, the European Health Data Space, US Food and Drug Administration guidance, the US National Institute of Standards and Technology (NIST) AI Risk Management Framework, and federated-learning governance can reduce risk while still inducing continuity traps. We apply the framework to consent and nonconsent settings, including public health, immunization, syndromic, and wastewater surveillance, polygenic risk scores, induced pluripotent stem cells, federated learning, and health-related large language models. The policy implication is trigger-based continuity review: rather than rereviewing every reuse, investigators and reviewers should identify the weakest continuity domain at the present data stage and impose a domain-matched safeguard, recorded in a short continuity statement. This reframing is intended for the committees, repositories, funders, and governance bodies that decide whether reuse may proceed, and it matters most in cross-border and low-resource settings. Provenance should begin ethical review; it should not end it.

Data Science↗

PubMed2026

MET-Aberrant non-small cell lung cancer: from kinase dependence to cell-surface targetability-mechanistic basis and biomarker framework for bispecific antibodies and antibody-drug conjugates.

MET-aberrant non-small cell lung cancer (NSCLC) is not a uniform therapeutic entity. Its biology, diagnostic pathways, and treatment sensitivity differ across MET exon 14 skipping alteration (METex14), MET amplification, and MET overexpression. This heterogeneity cannot be fully explained by conventional event-based classification and is reflected in the distinct clinical activity of MET tyrosine kinase inhibitors (MET-TKIs), bispecific antibodies (BsAbs), and antibody-drug conjugates (ADCs). With the emergence of antibody-based therapies, MET has evolved from a signaling driver to a cell-surface target for receptor modulation and payload delivery. We therefore propose a clinically anchored two-dimensional framework for interpreting therapeutic relevance in MET-aberrant NSCLC: kinase dependence and cell-surface targetability. Neither dimension should be regarded as a directly measurable binary variable. Kinase dependence is inferred from genomic and treatment-contextual proxies, most strongly METex14 and, more conditionally, high-level focal MET amplification. Cell-surface targetability is approximated by drug-specific IHC assessment of assay-defined c-MET protein expression; however, receptor internalization, intracellular trafficking, and payload delivery capacity remain incompletely measurable in routine clinical practice. Within this framework, MET-TKIs have the most evidence-supported established role in tumors with evidence of MET-driven kinase dependence. EGFR × MET BsAbs have demonstrated clinical activity in broad post-osimertinib EGFR-mutant NSCLC, while EGFR/MET co-dependence or MET-mediated bypass activation provides a mechanistic rationale for their use; MET-defined preferential benefit remains to be prospectively established. MET-directed antibody-drug conjugates (MET-ADCs) are supported in drug- and assay-defined populations with high c-MET protein overexpression, although the predictive relevance of delivery-related factors remains hypothesis-generating. Accordingly, MET testing should shift from single-event detection to platform-oriented stratification: next-generation sequencing (NGS) for driver alterations and resistance profiles, fluorescence in situ hybridization (FISH) for high-level focal amplification, and immunohistochemistry (IHC) for surface expression relevant to antibody-based therapies. This framework is intended to organize current biological and clinical evidence rather than to replace drug-specific companion diagnostics, regulatory indications, or prospectively validated treatment-selection algorithms. Precision treatment of MET-aberrant NSCLC is thus moving from event-based drug selection toward mechanism-based therapeutic matching. Future priorities include standardizing biomarkers, defining optimal target populations, and aligning biological subtypes, diagnostic strategies, and therapeutic platforms.

Antibody-drug conjugate↗

PubMed2025

Estimating population structure using epigenome-wide methylation data.

INTRODUCTION: In epigenome-wide association analysis (EWAS), unaddressed population stratification often leads to inflation. We aimed to compute methylation population scores (MPSs) that predict genetic principal components (GPCs) using a feature selection and regression approach. METHODS: We used multi-ethnic methylation data (Illumina 450K/EPIC array) from unrelated MESA (n=929), CARDIA (n=1123), JHS (n=1365), ARIC (n=2338), and HCHS/SOL (n=1475) individuals, randomly assigning 85% of participants from each cohort to a training dataset and the remaining 15% to a test dataset. First, we estimated the associations of GPCs with each available CpG methylation site using linear regression within each cohort, adjusting for age, sex, smoking status, race/ethnic background (as a proxy for background information associated with lifestyle and other environmental exposures that may impact methylation), alcohol use status, body mass index, and cell type proportions. We meta-analyzed the associations across cohorts and selected CpG sites with association FDR-adjusted q-value <0.05. We next aggregated individuallevel data across the cohort-specific training datasets, and applied two-stage weighted least squares Lasso regression, with the GPCs as the outcomes and the selected CpG sites as penalized predictors, adjusting for the aforementioned covariates. The developed MPSs are the weighted sum of selected CpG sites from the Lasso. To evaluate the developed MPSs, we constructed them in the test dataset, and compared them with GPCs, and with MPSs constructed based on a previously-published paper. Comparison was based on correlation analysis and data visualization. We demonstrate the use of the MPSs in EWAS. RESULTS: In the test dataset, the MPSs were highly correlated with GPCs, with correlation decreasing, though not monotonically, for later components. Specifically, MPS1 and GPC1 had R2= 0.99, while MPS7 and GPC7 had R2=0.27 (the lowest observed correlation). In data visualization, MPSs had similar patterns as GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups, while outperforming MPC constructed using alternative published methods. MPSs showed comparable performance to GPCs in reducing some of the inflation in EWAS. CONCLUSIONS: Methylation-based population scores provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent. Unlike previous methods based on unsupervised methylation PCA, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations. The weights for each GPCs derived in our study can be applied to generate MPSs in other studies.

Journal Article↗