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PubMed2025

Patterns of HIV-1 viral load suppression and drug resistance during the dolutegravir transition: a population-based longitudinal study.

BACKGROUND: Data on the population-scale impact of dolutegravir (DTG)-based HIV regimens in sub-Saharan Africa are extremely limited. We used data from a surveillance cohort in southern Uganda to assess viral suppression and antiretroviral (ART) resistance over 10-years alongside DTG scale-up. METHODS: Consenting participants in the population-based Rakai Community Cohort Study between August 2011 and March 2023 aged 15-59 completed questionnaires and provided samples for HIV testing, viral load quantification, and viral deep-sequencing. We collected data on DTG-utilization at HIV care clinics. We estimated the prevalence of HIV suppression (<1,000 copies/mL) and ART resistance using robust Poisson regression. Bayesian logistic regression quantified associations between resistance and individual-level suppression across surveys. FINDINGS: Among 20,383 people living with HIV (PLHIV), suppression increased from 57.1% (95% confidence interval [CI]: 55.4%-58.8%) to 90.3% (95%CI: 89.2%-91.4%) between 2014 and 2022. By 2020 84.4% (95%CI: 83.7%-85.2%) and 64.6% (95%CI: 63.9%-65.3%) of men and women were on DTG regimens. Among treatment-experienced viremic PLHIV, overall resistance decreased from 51.1% (95%CI: 40.7%-64.1%, 2014) to 27.9% (95%CI: 21.3%-36.5%, 2022). Only two participants harbored intermediate/high-level DTG resistance, attributable to inQ148R, inE138K, and inG140A. Low-level INSTI resistance (inS153Y) was observed in 23/207 (7.5%) of viremic individuals, with putative evidence of transmission. By 2022, suppression was unrelated to prior history of NNRTI/NRTI resistance (risk ratios: 1.14, 95%HPD: 0.96-1.32 and 1.12, 95%HPD: 0.88 - 1.35). INTERPRETATION: Viral suppression increased during the DTG-transition with minimal emerging intermediate/high-level resistance. Falling resistance among treatment-experienced PLHIV underscores the role of ART adherence in reducing viremia. The emergence of inS153Y justifies continued genomic surveillance of ART resistance. FUNDING: National Institutes of Health and the Gates Foundation.

Journal Article↗

PubMed2024

Assessing the emergence time of SARS-CoV-2 zoonotic spillover.

Understanding the evolution of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) and its relationship to other coronaviruses in the wild is crucial for preventing future virus outbreaks. While the origin of the SARS-CoV-2 pandemic remains uncertain, mounting evidence suggests the direct involvement of the bat and pangolin coronaviruses in the evolution of the SARS-CoV-2 genome. To unravel the early days of a probable zoonotic spillover event, we analyzed genomic data from various coronavirus strains from both human and wild hosts. Bayesian phylogenetic analysis was performed using multiple datasets, using strict and relaxed clock evolutionary models to estimate the occurrence times of key speciation, gene transfer, and recombination events affecting the evolution of SARS-CoV-2 and its closest relatives. We found strong evidence supporting the presence of temporal structure in datasets containing SARS-CoV-2 variants, enabling us to estimate the time of SARS-CoV-2 zoonotic spillover between August and early October 2019. In contrast, datasets without SARS-CoV-2 variants provided mixed results in terms of temporal structure. However, they allowed us to establish that the presence of a statistically robust clade in the phylogenies of gene S and its receptor-binding (RBD) domain, including two bat (BANAL) and two Guangdong pangolin coronaviruses (CoVs), is due to the horizontal gene transfer of this gene from the bat CoV to the pangolin CoV that occurred in the middle of 2018. Importantly, this clade is closely located to SARS-CoV-2 in both phylogenies. This phylogenetic proximity had been explained by an RBD gene transfer from the Guangdong pangolin CoV to a very recent ancestor of SARS-CoV-2 in some earlier works in the field before the BANAL coronaviruses were discovered. Overall, our study provides valuable insights into the timeline and evolutionary dynamics of the SARS-CoV-2 pandemic.

Animals↗

PubMed2026

Optimal dose and exercise modality to improve HbA1c in older adults with type 2 diabetes mellitus: a systematic review with pairwise, network, and dose-response meta-analyses.

We aimed to compare exercise modalities and evaluate dose-response relationships with glycemic control including continuous aerobic exercise (CAE), resistance training (RT), combined exercise (CE), mind-body exercise (MBE), and high-intensity interval training (HIIT) in older adults with type 2 diabetes mellitus (T2DM). Three databases were searched for randomized controlled trials of exercise interventions in older adults with T2DM reporting glycated hemoglobin (HbA1c). Pairwise, Bayesian network, and dose-response meta-analyses were conducted. Compared with control, HIIT demonstrated the largest estimated reduction (MD = -0.95%; 95% CrI -1.45, -0.49), followed by CE (MD = -0.59%; 95% CrI -0.93, -0.25), CAE (MD = -0.46%; 95% CrI -0.69, -0.24), MBE (MD = -0.42%; 95% CrI -0.76, -0.10), and RT (MD = -0.29%; 95% CrI -0.51, -0.08). Dose-response network meta-analyses suggested a non-linear association between overall exercise dose and HbA1c reduction, with maximal estimated benefits at approximately 704 METs-min/week with the 95% CrI excluding zero between 241 and 920 METs-min/week. HIIT demonstrated the steepest estimated dose-response relationship, but with wider credible intervals. Other exercise modalities showed more gradual dose-response patterns across their estimated effective ranges. Our findings suggest that exercise prescription for older adults with T2DM should be individualized according to exercise modality, dose, and health status.

Humans↗

PubMed2024

Expansion of Oropouche virus in non-endemic Brazilian regions: analysis of genomic characterisation and ecological drivers.

BACKGROUND: Oropouche virus (OROV) is an arbovirus endemic in the Amazon region that closely resembles other arboviruses in terms of human disease, leading to potential misdiagnoses. The virus ecology has mostly restricted its occurrence to the Amazon biome; however, after a large 2023-24 OROV epidemic in the Brazilian Amazon region, outbreaks are being reported across Brazil and in other countries in Latin America. Here, we investigate the OROV spread outside Amazonia. METHODS: In this genomic and epidemiological study, OROV cases from January, 2023, to July, 2024, provided by the General Coordination of Public Health Laboratories of Brazil on Aug 1, 2024, were compared by geographical location (Amazon vs non-Amazon) and municipal population size, and a linear mixed model was employed to assess the relationship between agricultural area size and cases. OROV-positive samples from central laboratories of five non-Amazonian Brazilian states were sequenced using an amplicon-based approach. Bayesian phylogeographical analysis was performed with near full-length viral genomes, incorporating individual travel histories when relevant. The estimated dates of viral introductions in each sampled location were then contextualised with public epidemiological data. FINDINGS: Epidemic data show that outside the Amazon region, OROV cases frequency was 3·9-times higher in small municipalities than in large municipalities. The planted areas of some agricultural products, such as banana plantations, were positively correlated (r=0·39, p<0·0001) with OROV cases. The linear mixed model revealed that, besides banana, cassava also has larger (p<0·05) planted areas in municipalities with OROV cases when compared with those with no cases. The phylogenetic analysis of 32 new OROV genomes reconstructed multiple exportation events of the newly identified reassortant lineage from the Amazon to other Brazilian regions between January and March, 2024. At least three of the previously described OROV phylogenetic clades circulating in the Amazon were the source of viral introductions. Molecular clock analysis estimated that viral introductions happened from 50 days to 100 days before detecting the outbreaks in each state. INTERPRETATION: Our results confirm that the novel OROV reassortant lineage spread from the Amazon to other regions in early 2024, successfully establishing local transmission. The fact that outbreaks were observed in small municipalities, instead of large urban centres, suggests that local ecological conditions that are ideal for OROV vector occurrence, such as the banana plantation environment, might be important factors driving its spread in Brazil. FUNDING: DECIT, CNPq, FAPEAM, and Inova-Fiocruz. TRANSLATION: For the Portuguese translation of the abstract see Supplementary Materials section.

Brazil↗

PubMed2026

Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.

Over 75 Alzheimer's disease (AD) and dementia-associated variants have been identified through genome-wide association studies, but the utility of polygenic risk scores (PRS) for predicting AD and dementia in diverse and admixed populations remains unclear. We compared how PRS approaches differing in p-value thresholds, variant weights, and source ancestry perform in predicting dementia in 6338 African American, Chinese, Hispanic, and White individuals from the Multi-Ethnic Study of Atherosclerosis. We tested clumping and thresholding (C+T) methods with varying parameters against Bayesian approaches (PRS-CS, PRS-CSx). We compared the ability of each method to predict incident dementia in all participants and in groups stratified by self-reported race/ethnicity. We additionally analyzed performance across groups stratified by estimated proportion of non-Finnish European (NFE)-like ancestry. Including more variants does not improve performance. We found comparable associations between dementia and PRS when comparing a C+T method with only 15 SNPs and PRS derived from Bayesian models that include > 800,000 SNPs (HR5e-08 = 1.18, 95% CI: 1.08-1.28; HRCSx = 1.17, 95% CI: 1.07-1.27). The p < 5e-08 C+T method was more strongly associated with incident dementia in populations genetically dissimilar from the source data (HRlowNFE_5e-08 = 1.27, 95% CI: 1.08-1.50; HRlowNFE_CSx = 1.12, 95% CI: 0.94-1.33). More selective PRS models using genome-wide significant SNPs may be preferable for dementia prediction in diverse populations.

Aged↗

PubMed2026

A Bayesian framework for multivariate differential analysis.

Differential analysis is a routine procedure in the statistical analysis toolbox across many applied fields, including quantitative proteomics, the main illustration of the present paper. The state-of-the-art limma approach uses a hierarchical formulation with moderated-variance estimators for each analyte directly injected into the t-statistic. While standard hypothesis testing strategies are recognised for their low computational cost, allowing for quick extraction of the most differential among thousands of elements, they generally overlook key aspects such as handling missing values, inter-element correlations, and uncertainty quantification. The present paper proposes a fully Bayesian framework for differential analysis, leveraging a conjugate hierarchical formulation for both the mean and the variance. Inference is performed by computing the posterior distribution of compared experimental conditions and sampling from the distribution of differences. This approach provides well-calibrated uncertainty quantification at a similar computational cost as hypothesis testing by leveraging closed-form equations. Furthermore, a natural extension enables multivariate differential analysis that accounts for possible inter-element correlations. We also demonstrate that, in this Bayesian treatment, missing at random data should generally be ignored in univariate settings, and further derive a tailored approximation that handles multiple imputation for the multivariate setting. We argue that probabilistic statements in terms of effect size and associated uncertainty are better suited to practical decision-making. Therefore, we finally propose simple and intuitive inference criteria, such as the overlap coefficient, which express group similarity as a probability rather than traditional, and often misleading, p-values. The performance of this approach is evaluated through an extensive empirical study using both synthetic and controlled real-world proteomics datasets. Overall, we believe that this Bayesian framework for (multivariate) differential analysis provides a valuable and intuitive counterpart to standard methods at a comparable computational cost.

Bayes Theorem↗

PubMed2025

Bayesian reconstruction and differential testing of excised introns.

MOTIVATION: Characterizing the differential excision of introns is critical for understanding the functional complexity of a cell or tissue, from normal developmental processes to disease pathogenesis. Most transcript reconstruction methods infer full-length transcripts from high-throughput sequencing data. However, this is a challenging task due to incomplete annotations and the heterogeneous expression of transcripts across cell-types, tissues, and experimental conditions. Several recent methods circumvent these difficulties by considering local splicing events, but these methods lose transcript-level splicing information and may conflate similar, but distinct transcripts. RESULTS: In this work, we formalize a new transcript reconstruction problem that interpolates between the full-length and local splicing perspectives by considering sequences of exon-exon junctions (SEEJs) that co-occur in transcripts. We then present a hierarchical Bayesian admixture model and posterior inference algorithms for computing SEEJs (BSEEJ), and a generalized linear model for characterizing differential SEEJ usage based on model parameter estimates. We show that BSEEJ achieves high F1 score for reconstruction tasks and improved accuracy and sensitivity in differential splicing when compared with six transcript and local splicing methods on simulated data. Lastly, we evaluate BSEEJ on experimental data based on transcript reconstruction, novelty of transcripts produced, model sensitivity to hyperparameters, and a functional analysis of differentially expressed SEEJs. AVAILABILITY AND IMPLEMENTATION: BSEEJ is freely available at https://github.com/bayesomicslab/BSEEJ.

Bayes Theorem↗

PubMed2026

Modelling the effects of biological intervention in a dynamical gene network.

Cellular response to environmental and internal signals can be modeled by dynamical gene regulatory networks (GRN). In the literature, three main classes of gene network models can be distinguished: (1) non-quantitative (or data-based) models which do not describe the probability distribution of gene expressions; (2) quantitative models which fully describe the probability distribution of all genes co-expression; and (3) mechanistic models which allow for a causal interpretation of gene interactions. We propose two rigorous frameworks to model gene alteration in a dynamical GRN, depending on whether the network model is quantitative or mechanistic. We explain how these models can be used for design of experiment, or, if additional alteration data are available, for validation purposes or to improve the parameter estimation of the original model. We apply these methods to the Gaussian graphical model, which is quantitative but non-mechanistic, and to mechanistic models of Bayesian networks and penalized linear regression.

Gene Regulatory Networks↗

PubMed2026

Precision targeting of teacher burnout using network-informed ecological momentary interventions.

Teacher well-being affects classroom functioning and workforce stability, yet generic digital programs rarely use person-specific affect dynamics to select support. This cluster-randomised trial evaluated whether micro-interventions selected from high expected influence (EI) nodes in teachers' contemporaneous affect networks produced larger changes in burnout-related EI and everyday happiness than content-matched random allocation. The objectives were to estimate allocation effects on changes in estimated network summaries and happiness, evaluate network change as a statistical mediator, examine personality moderation, and benchmark simpler allocation rules. A two-arm cluster randomised platform trial was conducted in 84 public schools across four urban districts in H Province. After a 14 day baseline of ecological momentary assessment (EMA), person specific partial correlation networks were estimated for happiness, exhaustion, detachment, efficacy and rumination. An optimisation engine prioritised three brief micro-intervention types per teacher according to baseline EI, while the active control received the same library without network information. EMA continued for 8 weeks; Bayesian multilevel models, permutation-based mediation, and benchmarking analyses were applied. EI-based targeting produced larger reductions in the composite EI-change index than active control (mean difference 0.11, 95% credible interval 0.08 to 0.14) and higher week 7 EMA happiness (4.4 points on a 0 to 100 scale, 95% credible interval 2.7 to 6.0), with a positive arm by week slope difference of 0.62 points per week (95% credible interval 0.39 to 0.85). Model-based mediation estimates were consistent with approximately one half of the happiness difference being statistically associated with change in the composite EI-change index (average conditional mediation estimate 3.5 points, 95% credible interval 2.0 to 5.2). Benchmarking showed smaller gains under severity, threshold, or group-level centrality rules. Effects were stronger among teachers higher in conscientiousness. The findings indicate that integrating EMA, network modelling, and EI-driven optimisation yields measurable gains beyond content-matched exposure, providing a proof of concept for district-scale precision mental health that requires prospective implementation testing. Replication in additional regions, expanded node sets, and longer follow up are warranted to assess durability and generalisability.

Female↗

PubMed2024

Rapid spread of the SARS-CoV-2 Omicron XDR lineage derived from recombination between XBB and BA.2.86 subvariants circulating in Brazil in late 2023.

Recombination plays a crucial role in the evolution of SARS-CoV-2. The Omicron XBB* recombinant lineages are a noteworthy example, as they have been the dominant SARS-CoV-2 variant worldwide in the first half of 2023. Since November 2023, a new recombinant lineage between Omicron subvariants XBB and BA.2.86, designated XDR, has been detected mainly in Brazil. In this study, we reconstructed the spatiotemporal dynamics and estimated the absolute and relative transmissibility of the XDR lineage. The XDR lineage displayed a recombination breakpoint in the ORF1a-coding region, and the most closely related sequences to the 5' and 3' ends of the recombinant correspond to JD.1.1 and JN.1.1 lineages, respectively. The first XDR sequences were detected in November 2023 in the Northeastern Brazilian region, and their prevalence rapidly surged from <1% to 25% by February 2024. The Bayesian phylogeographic analysis supports that the XDR lineage likely emerged in the Northeastern Brazilian region around late October 2023 and rapidly disseminated within and outside Brazilian borders from mid-November onward. The median effective reproductive number of the XDR lineage in Brazil during the initial expansion phase was estimated to be around 1.5, and the average relative instantaneous reproduction numbers of XDR and JN* lineages were estimated to be 1.37 and 1.29 higher than that of co-circulating XBB* lineages. In summary, these findings support that the recombinant lineage XDR arose in the Northeastern Brazilian region in October 2023, shortly after the first detection of JN.1 sequences in the country. In Brazil, the XDR lineage exhibited a higher transmissibility level than its parental XBB.* lineages and is spreading at a rate similar to or slightly faster than the JN.1* lineages.IMPORTANCEThis study highlights the emergence and rapid dissemination of the recombinant SARS-CoV-2 XDR lineage, derived from the Omicron lineages JD.1.1 and JN.1.1. The XDR lineage exhibited equivalent transmissibility to its JN.1* parental lineages and quickly spread across Brazil in late 2023. The findings underscore the critical role of real-time genomic surveillance in detecting novel variants with higher transmission potential. By utilizing phylogenetic and epidemiological methods, this research provides important insights into the molecular dynamics of XDR, which could inform public health responses and vaccine composition updates. The study's significance lies in its ability to document the impact of recombination on viral evolution, offering valuable information to the field of virology and pandemic preparedness.

Brazil↗

PubMed1979

Analysis of life tables with grouping and withdrawals.

A number of individuals is observed at the beginning of a period. At the end of the period the number is surviving, the number who have died and the number who have withdrawn are noted. From these three numbers it is required to estimate the death rate for the period. All relevant quantities are supposed independent and identically distributed for the individuals. The likelihood is calculated and found to depend on two parameters, other than the death rate, and to be unidenttifiable so that no consistent estimators exist. For large numbers, the posterior distribution of the death rate is approximated by a normal distribution whose mean is the root of a quadratic equation and whose variance is the sum of two terms; the first is proportional to the reciprocal of the number of individuals, as usually happens with a consistent estimator; the second does not tend to zero and depends on initial opinions about one of the nuisance parameters. The paper is a simple exercise in the routine use of coherent, Bayesian methodology. Numerical calucations illustrate the results.

Actuarial Analysis↗

PubMed2026

Shared genetic architecture of smoking dependence and Crohn's disease: A cross-trait analysis of GWAS summary statistics.

INTRODUCTION: Smoking dependence (SD) and Crohn's disease (CD) are epidemiologically associated, but whether this relationship reflects shared genetic susceptibility remains unclear. METHODS: We conducted a cross-trait genetic analysis of SD and CD using publicly available genome-wide association study (GWAS) summary statistics from European-ancestry populations. Genome-wide genetic correlation was estimated using linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL). Pleiotropic variants were identified using PLACO and mapped to genomic loci using FUMA. Regional signal sharing was assessed by Bayesian colocalization. Functional analyses included stratified LDSC, Multi-marker Analysis of GenoMic Annotation (MAGMA), GTEx tissue analysis, and Metascape. Expression-linked candidate genes were prioritized using expression quantitative trait locus (eQTL)-based summary-data-based Mendelian randomization (SMR) with heterogeneity in dependent instruments (HEIDI) testing. Genetically informed spatial mapping of cells for complex traits (gsMap) was used for spatial mapping. RESULTS: SD and CD showed positive genetic correlation by LDSC (rg=0.2090, p=0.0008) and HDL (rg=0.3817, p=0.00106). PLACO identified 81 genome-wide significant pleiotropic SNPs, which were mapped by FUMA to three loci at 1p31.3, 5p13.1, and 12q12, represented by rs11209031, rs1395152, and rs17467116, respectively. MAGMA identified 22 FDR-significant genes, four of which remained Bonferroni significant: LRRK2, TNFRSF6B, ZGPAT, and RP4-583P15.15. Cross-trait tissue analysis showed significant enrichment of the shared genetic signal in whole blood and small intestine, while gene-set analysis highlighted inflammatory response (pbon=1.86×10-5) and T-helper 17 cell differentiation (pbon=7.37×10-4). SMR/HEIDI analysis further prioritized RPS6KB1 as a shared expression-linked candidate. Spatial mapping revealed a prominent signal in the embryonic gastrointestinal tract and gene-specific regional patterns involving LRRK2 and SLC2A13 in the adult mouse brain. CONCLUSIONS: SD and CD showed measurable shared genetic susceptibility, with convergent evidence from pleiotropic loci, immune-inflammatory pathway enrichment, tissue-level associations, and spatial transcriptomic mapping.

Crohn's disease↗

PubMed2026

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE = 0.0377 mg/kg, RPD = 5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves↗

PubMed2026

From gut to pancreas: Shared genetic susceptibility and biological convergence in acute pancreatitis and Crohn's disease.

BACKGROUND: Acute pancreatitis (AP) and Crohn's disease (CD) exhibit overlapping clinical presentations and an unexpectedly high rate of comorbidity. Whether this reflects shared genetic susceptibilities remains unclear. METHODS: We performed a cross-trait genome-wide association analysis leveraging European-ancestry summary statistics for AP (Ncases = 8446; Ncontrols = 437,418) and CD (Ncases = 12,194; Ncontrols = 28,072). Firstly, cross-trait genetic correlation was estimated using linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL). Secondly, to pinpoint specific pleiotropic loci and prioritize candidate genes, we employed PLACO under a rigorous composite null hypothesis, integrated with Bayesian colocalization and SMR/HEIDI analyses. Finally, we dissected the underlying biological context by mapping tissue-specific regulatory enrichment and pathway convergence using FUMA, MAGMA, and Stratified LD Score Regression (S-LDSC). RESULTS: AP and CD showed significant positive genetic correlation (LDSC: rg = 0.178, SE = 0.079, P = 0.025; HDL: rg = 0.294, SE = 0.096, P = 0.0021). Pleiotropy analyses revealed 86 SNPs and 6 independent genome-wide significant pleiotropic loci (lead variants at 5q33.1, 6q22.33, 7q34, 10q24.2, 15q22.33 and 19q13.11, PPLACO < 5 × 10-8). Colocalization showed suggestive evidence of a shared causal signal at 6q22.33 (PP4 = 0.666). Gene-based tests of the AP-CD cross-trait statistics prioritized eight pleiotropic genes-RSPO3, ATG16L1, SMAD3, FADS1, ZPBP2, FADS2, PRKAA1 and IRGM. Gene-set analyses highlighted IL-23/Th17-related and broader inflammatory response pathways. CONCLUSIONS: AP and CD share polygenic susceptibility and converge on immune and inflammatory processes, with prioritized genes pointing to autophagy, lipid metabolism and TGF-β/SMAD-related biology.

Humans↗

PubMed2025

Genomic prediction and genome-wide association study for liver abscesses in crossbred beef cattle.

Liver abscesses are a concern in feedlot cattle, and little is known about the role of genetics in their development. This study aimed to estimate genetic parameters and to identify single-nucleotide polymorphisms (SNPs) associated with liver abscesses. Crossbred cattle representing 18 breeds in the U.S. Meat Animal Research Center Germplasm Evaluation Program were phenotyped for liver abscesses at slaughter (n = 9,044). Seventeen percent of cattle had liver abscesses. These cattle had genotypes that were imputed to sequence variant genotypes. After filtering and quality control, 340,723 SNPs were used in the analysis. Liver abscess prevalence was modeled with a single-step genomic best linear unbiased prediction (ssGBLUP) threshold model using a Bayesian framework. The model included contemporary group (sex, treatment group, and slaughter date), additive genomic, and residual effects. Genomic heritability was 0.039 (95% highest posterior density = 0.005, 0.081), which was very small. To assess prediction quality, a 5-fold random cross-validation structure was used. Method Linear Regression was used to assess accuracy, bias, and dispersion by comparing estimated breeding values (EBV) from full and reduced analyses. Cross-validation metrics showed EBV based on genotypes had 0.05 reliability (SD < 0.01) with no bias relative to EBV based on genotypes and phenotypes. For the genome-wide association study, SNP effects were back calculated from the EBV solutions from ssGBLUP. No SNPs were associated with liver abscesses at a Benjamini-Hochberg adjusted 0.05 significance level. Although a large dataset was used, this result was because of the low genomic heritability and imprecise EBV used to calculate SNP effects. Based on these results, environmental factors contribute to most of the variation in liver abscesses. Genetic selection to reduce liver abscesses would be slow because of the low genomic heritability, measurement late in life, and inability to measure breeding animals. A faster approach would be finding additional environmental interventions that maintain animal performance.

Animals↗

PubMed2026

Daily low-dose carboplatin or weekly carboplatin plus nab-paclitaxel for concurrent chemoradiotherapy in older patients with locally advanced non-small cell lung cancer (JCOG1914): A randomized phase 3 trial.

BACKGROUND: Daily low-dose carboplatin with concurrent thoracic radiotherapy is the standard treatment for older patients with unresectable locally advanced non-small cell lung cancer (LA-NSCLC) in Japan. METHODS: This open-label phase 3 trial was conducted at 38 institutions in Japan. Patients aged ≥ 75 years with LA-NSCLC were randomly assigned (1:1) to receive daily carboplatin (30 mg/m2) or weekly carboplatin (area under the curve, 2 mg·min/mL) plus nab-paclitaxel (30 mg/m2) with thoracic radiotherapy. Durvalumab maintenance therapy was recommended after treatment completion. The primary endpoint was overall survival, which was used to assess the non-inferiority of weekly carboplatin plus nab-paclitaxel compared to daily low-dose carboplatin. RESULTS: From December 2020 to March 2024, 124 patients were enrolled (carboplatin arm, 61 and carboplatin plus nab-paclitaxel arm, 63). In the planned interim analysis, the Bayesian predictive probability indicating the non-inferiority of carboplatin plus nab-paclitaxel compared with carboplatin in the final analysis was 8.0%, leading to early study termination for futility. The median overall survival was not estimable in the carboplatin arm; the estimated value in the carboplatin plus nab-paclitaxel arm was 26.1 months (hazard ratio, 1.56; 95% confidence interval, 0.79-3.11; p = 0.200). Two treatment-related and seven non-cancer-related deaths occurred in the carboplatin plus nab-paclitaxel arm. Patients in the carboplatin arm had better quality of life than those in the carboplatin plus nab-paclitaxel arm at 6 weeks (odds ratio, 0.39; 95% confidence interval, 0.18-0.81; p = 0.012). CONCLUSIONS: Daily low-dose carboplatin with concurrent thoracic radiotherapy remains the standard treatment for older patients with unresectable LA-NSCLC in Japan.

Humans↗

PubMed1979

Twin azygotic test for the study of hereditary qualitative traits in twin populations.

Following previous formulations of a model of qualitative analysis of twin population data independent of zygosity, a new Bayesian approach has been developed. The present model can be applied to any qualitative genetic trait in twin population data, provided no specific source of variation be introduced by the twin condition, and allows not only estimation of the frequencies of mono- and dizygosity as well as the gene frequencies, but also verification of the trait's mode of inheritance.

Bayes Theorem↗

PubMed2026

Multi-omics integration and colocalization analyses prioritize candidate molecular loci associated with hypothermia.

BACKGROUND: Hypothermia is a life-threatening condition lacking specific pharmacological treatments. This study aimed to prioritize genetically supported molecular loci associated with hypothermia and to explore their pharmacological tractability using multi-omics data. METHODS: Initially, 2532 druggable genes were curated from the Drug-Gene Interaction Database and established literature. These were cross-referenced with cis-eQTL and cis-pQTL datasets, encompassing 870,655 and 114,281 SNPs for blood, respectively, alongside 2379 shared SNPs across adipose, skeletal muscle, and heart tissues. Matched instrumental variables were integrated with hypothermia GWAS summary statistics for two-sample Mendelian randomization (MR) and Bayesian colocalization. Transcriptomic differential expression analysis (DEA) was subsequently conducted as an exploratory analysis of cold-exposure-associated expression changes. Database-derived compound annotations were systematically re-evaluated according to target specificity, established pharmacological mechanism, and concordance with the direction of the MR estimates. RESULTS: Among 671 gene-level MR tests, 36 genes reached nominal significance, whereas only ABCC8 remained significant after FDR correction. Colocalization was evaluable for 8 of these 36 genes, and 4 loci (COL18A1, SLC1A7, ADIPOQ, and MERTK) met the prespecified PP.H4>0.90 threshold. The remaining 28 loci were not evaluable because sufficient overlapping regional variants were unavailable after harmonization. Transcriptomic analysis identified altered expression of SLC1A3 and SLCO4A1 under cold exposure, although these findings did not directly validate the colocalization-supported loci. Re-evaluation of database-derived compound annotations did not identify any direct, selective, and directionally concordant drug-repurposing candidate for hypothermia. CONCLUSIONS: COL18A1, SLC1A7, ADIPOQ, and MERTK showed colocalization support among the 8 evaluable nominal MR-associated loci. Because colocalization coverage was limited, these genes should be regarded as preliminary candidate loci rather than established therapeutic targets. The pharmacological annotations were indirect, non-selective, unsupported, or directionally inconsistent and should be interpreted solely as hypothesis-generating information.

Bayesian colocalization↗