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PubMed2026

Longitudinal whole-genome analysis of bluetongue virus identifies conserved serotype-specific genomes and distinct genomic constellations within a Colorado sheep flock (2021-2023).

Bluetongue virus (BTV) is a segmented double-stranded RNA virus of ruminants transmitted by Culicoides spp. biting midges. Although the genome consists of ten segments, classification into serotypes is primarily based on genome segment 2. However, reassortment among genomic segments is a major driver of BTV evolution and diversity. This study used longitudinal whole-genome sequencing to characterize BTV genomes collected from 2021 to 2023 within a single sheep flock in Colorado, where multiple serotypes co-circulate. Whole-genome sequences were generated from fourteen blood samples representing four serotypes: BTV-6, -11, -13, and -17. Longitudinal sampling identified multiple BTV serotypes within individual sheep across consecutive years. Tanglegram analysis comparing segment phylogenies to the segment 2 tree demonstrated incongruent topologies across all genomic segments, suggestive of reassortment or the circulation of distinct genomic constellations. Nucleotide-level comparisons revealed high sequence homology among same-serotype samples from the same year, while the greatest genetic divergence was observed among BTV-17 genomes collected in different years. Additionally, all BTV-13 genomes contained a previously undescribed nonsynonymous substitution in segment 10 predicted to extend the encoded protein by three amino acids. Together, these findings demonstrate that highly conserved BTV genomes and distinct genomic constellations can be detected at the flock level across multiple years. This longitudinal whole-genome approach reveals the genetic complexity of endemic BTV populations, including novel variants and genomic patterns consistent with reassortment that are lost with conventional serotyped-based approaches, highlighting the need to integrate whole-genome characterization into endemic BTV monitoring programs.

Animals↗

PubMed2025

PROLONG: penalized regression for outcome guided longitudinal omics analysis with network and group constraints.

MOTIVATION: There is a growing interest in longitudinal omics data paired with some longitudinal clinical outcome. Given a large set of continuous omics variables and some continuous clinical outcome, each measured for a few subjects at only a few time points, we seek to identify those variables that co-vary over time with the outcome. To motivate this problem we study a dataset with hundreds of urinary metabolites along with Tuberculosis mycobacterial load as our clinical outcome, with the objective of identifying potential biomarkers for disease progression. For such data clinicians usually apply simple linear mixed effects models which often lack power given the low number of replicates and time points. We propose a penalized regression approach on the first differences of the data that extends the lasso + Laplacian method [Li and Li (Network-constrained regularization and variable selection for analysis of genomic data. Bioinformatics 2008;24:1175-82.)] to a longitudinal group lasso + Laplacian approach. Our method, PROLONG, leverages the first differences of the data to increase power by pairing the consecutive time points. The Laplacian penalty incorporates the dependence structure of the variables, and the group lasso penalty induces sparsity while grouping together all contemporaneous and lag terms for each omic variable in the model. RESULTS: With an automated selection of model hyper-parameters, PROLONG correctly selects target metabolites with high specificity and sensitivity across a wide range of scenarios. PROLONG selects a set of metabolites from the real data that includes interesting targets identified during EDA. AVAILABILITY AND IMPLEMENTATION: An R package implementing described methods called "prolong" is available at https://github.com/stevebroll/prolong. Code snapshot available at 10.5281/zenodo.14804245.

Humans↗

PubMed2026

Plasma von Willebrand Factor and ADAMTS13 Interact With APOE-ε4 in Predicting Longitudinal Brain Atrophy and Cognitive Decline Over a 9-Year Follow-Up.

BACKGROUND: Von Willebrand factor (VWF) and ADAMTS13 (a disintegrin and metalloproteinase with thrombospondin type 1 motif, 13) are linked to dementia risk, and limited evidence suggests apolipoprotein E (APOE)-ε4 alters VWF release. This study assessed whether baseline VWF and ADAMTS13 levels predict neurodegeneration and cognitive decline and evaluated effect modification by APOE-ε4 carriership. METHODS: Vanderbilt Memory and Aging Project cohort participants (n=332, 73±7 years, 59% male) completed serial blood draw, neuropsychological assessment, and brain magnetic resonance imaging over 6.4 years (range 1.4-9.7 years). Baseline plasma VWF and ADAMTS13 levels were quantified using mass spectrometry and Olink. Fully adjusted linear mixed-effects models related protein×time and protein×APOE-ε4×time interaction terms to longitudinal brain magnetic resonance imaging and neuropsychological outcomes. RESULTS: Lower baseline ADAMTS13 predicted faster declines in language (β=0.11, P=0.01), information processing speed (β=0.27, P=0.001), executive function (β=0.01, P=0.03), episodic memory (β=0.01, P=0.03), and visuospatial ability (β=0.11, P=0.001) and faster increases in global (β=-0.29, P=0.01) and frontal (β=-0.17, P=0.01) white matter hyperintensity volumes. Associations between ADAMTS13 and faster rates of cognitive decline and white matter injury were driven by APOE-ε4 carriers. Models relating VWF to longitudinal outcomes were null. APOE-ε4 interacted with VWF on longitudinal gray matter volumetric outcomes, such that faster rates of global gray matter atrophy were observed with higher baseline VWF levels among APOE-ε4 noncarriers only (β=-1530.5, P<0.001). CONCLUSIONS: ADAMTS13 shows promise as a potential plasma biomarker for brain aging outcomes, but additional research is warranted to understand the performance of VWF in the presence versus absence of an APOE-ε4 allele.

Humans↗

PubMed2026

Longitudinal Clinical, Physiological, and Molecular Profiling of Female Patients With Metastatic Cancer: Protocol and Feasibility of a Multicenter High-Definition Oncology Study.

PURPOSE: A substantial proportion of patients receiving genomically matched therapies do not achieve clinical benefit, underscoring the influence of nongenetic factors on cancer outcomes. High-Definition Oncology (HDO) proposes integrating longitudinal, multimodal patient data-spanning clinical, molecular, physiological, and behavioral domains-to enable truly individualized cancer care. This manuscript describes the HDO study design, framework, and feasibility results in women with metastatic cancer. METHODS: We initiated a prospective, multicenter observational study (HDO study; ClinicalTrials.gov identifier: NCT06590506) enrolling 300 female patients with newly diagnosed metastatic breast, lung, or colorectal cancer. Here, we report the study design, standardized workflows, prespecified feasibility criteria, and early internal pilot results. Eleven data modalities are collected longitudinally, including tumor and germline genomics, germline epigenomics, gut microbiome, blood and stool metabolomics and proteomics, exposome characterization, wearable-derived physiological monitoring, digital footprint assessment, medical imaging, and patient-reported outcomes. Standardized workflows govern clinical procedures, data acquisition, biospecimen processing, and quality control across all participating sites. RESULTS: Feasibility was evaluated in the first 30 participants (10% of planned accrual). Patients completed 100% of scheduled clinical visits, 97.4% of planned plasma collections, 80.7% of stool samples, and all tumor biopsies. Wearable devices captured activity, heart rate, sleep, and blood oxygen saturation data during 95.0%, 84.2%, 90.6%, and 70.7% of total patient-days, respectively. Biospecimens met predefined quality control metrics across all molecular modalities. Engagement with mobile applications for pain and emotion reporting exceeded 80%. CONCLUSION: The HDO study demonstrates the feasibility of comprehensive, longitudinal, multimodal data collection in women with metastatic cancer. This internal pilot establishes an integrated framework for future analyses aimed at characterizing disease trajectories, defining molecular and physiological determinants of outcomes, and developing patient-specific computational models.

Humans↗

PubMed2025

Predicting the First Onset of Suicidal Thoughts and Behaviors in Adolescents Using Multimodal Risk Factors: A 4-Year Longitudinal Study.

OBJECTIVE: Suicide is one of the leading causes of death among youth worldwide, yet existing studies that aimed to predict the first onset of suicidal thoughts and behaviors (STB) included a limited number of data modalities and/or focused on adult populations. This study aimed to prospectively predict first-onset STB across 4-year follow-ups in adolescents using an existing STB history classification model that was previously applied to baseline data and a new machine learning model with 195 biopsychosocial features. METHOD: Participants were 7,503 unrelated adolescents (54.5% female, ages 9-11 years at baseline) from the multisite, longitudinal Adolescent Brain Cognitive Development (ABCD) Study. An existing baseline STB history classification model was applied to predict longitudinal first-onset STB in adolescents compared with healthy controls and clinical controls (individuals with a mental health disorder but no STB). A new elastic net logistic regression model with 195 features was trained on data from 14 sites (n = 5,220), and the resulting top 15 features were validated at 7 independent sites (n = 2,283). RESULTS: The previously developed model to classify STB lifetime history also prospectively predicted first-onset STB in adolescents with an area under the curve (AUC) [95% CI] of 0.73 [0.70, 0.75], p < .001, compared with healthy controls and AUC [95% CI] of 0.63 [0.60, 0.66], p < .001, compared with clinical controls. The newly trained model with top 15 features performed similarly with AUC [95% CI] of 0.73 [0.71, 0.76], p < .001, and AUC [95% CI] of 0.64 [0.60, 0.66], p < .001, for the same comparison groups. The most consistent predictors across models included female sex, sleep disturbances, and maladaptive home and school environments. CONCLUSION: The models predicted first-onset STB in adolescents with moderate accuracy. This study also confirmed the roles of well-established psychological risk factors for STB and identified several novel neurocognitive and brain imaging risk factors. Future studies should validate these models in large-scale diverse samples before clinical translation. PLAIN LANGUAGE SUMMARY: This study followed over 7,500 adolescents for 4 years and tested 2 machine learning models using psychological, social, and brain data to identify those at risk of experiencing suicidal thoughts or behaviors. Both models predicted first-time suicidal thoughts or behaviors with moderate accuracy. Key risk factors that were identified included being female, experiencing sleep problems, and negative home and school environments. DIVERSITY & INCLUSION STATEMENT: We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way. Diverse cell lines and/or genomic datasets were not available. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. We actively worked to promote sex and gender balance in our author group. One or more of the authors of this paper received support from a program designed to increase minority representation in science. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list. While citing references scientifically relevant for this work, we also actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our reference list. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work.

Adolescent↗

PubMed2026

A multi-ancestry polygenic risk score for body mass index predicts longitudinal weight change.

BACKGROUND: Identifying individuals at risk for future weight gain is challenging, partly because associations with traditional clinical risk factors may be biased by confounding and reverse causation. Polygenic risk scores (PRS) provide a stable, lifelong measure of genetic predisposition to obesity. However, existing PRS have not been evaluated for their association with longitudinal weight change in adulthood and often lack generalizability across diverse genetic ancestry groups. METHODS: We conducted ancestry-specific genome-wide association study meta-analyses of body mass index (BMI) in populations of European, African or African American, Admixed American, East Asian, and South Asian ancestries and developed ancestry-specific PRS. A multi-ancestry polygenic risk score (MAPRS) was trained using ancestry-specific PRS in a model selection dataset (N = 39,685) from the All of Us Research Program (AoU). We evaluated the MAPRS in an independent AoU model evaluation dataset (N = 158,743) for BMI prediction and in a separate AoU test dataset (N = 78,219) with repeated measurements over 1.5-2.5 years for weight change prediction. The outcomes included change in BMI and ≥ 10% or ≥ 5% total body weight (TBW) gain. We further examined the relationship between MAPRS and 12 clinical risk factors commonly comorbid with obesity in relation to weight change. RESULTS: The MAPRS captured 7.05% of the variance in measured BMI in the AoU model evaluation dataset and demonstrated improved generalizability across all non-European genetic ancestry groups. In the AoU test dataset, conditioned on baseline BMI at the second-to-last measurement, a one SD increase in MAPRS was associated with a 0.16 kg/m2 increase in future BMI (standard error = 0.012 kg/m2; p-value = 2.2 × 10-39), 1.27-fold increased odds of experiencing ≥ 10% TBW gain (95% CI: 1.24-1.31; p-value = 1.4 × 10-55), and 1.15-fold increased odds of experiencing ≥ 5% TBW gain (95% CI: 1.13-1.18; p-value = 2.8 × 10-39). These associations were observed across all genetic ancestry groups and remained highly consistent after adjustment for any clinical risk factor. In contrast, most clinical risk factors demonstrated inconsistent or weaker associations with weight change outcomes. CONCLUSIONS: We developed an MAPRS for BMI that represents a robust and generalizable risk factor for longitudinal weight gain in adulthood, providing a foundation for genetically informed risk stratification and earlier, more targeted obesity prevention strategies.

Humans↗

PubMed2026

Ossification variants of the distal femoral condyle: longitudinal 3 T MRI evidence of progression to juvenile osteochondritis dissecans in asymptomatic siblings of patients with JOCD.

OBJECTIVE: Ossification variants (OVs) of the femoral condyles are traditionally regarded as benign developmental findings distinct from juvenile osteochondritis dissecans (JOCD). We aimed to characterize the longitudinal MRI behavior of OVs and JOCD lesions in asymptomatic siblings of JOCD patients. MATERIALS AND METHODS: In this HIPAA-compliant longitudinal pilot study, seven asymptomatic siblings of JOCD patients underwent serial 3 T bilateral knee MRI. Two fellowship-trained musculoskeletal radiologists independently assessed 56 studies for bone marrow edema, lesion location, and MRI-defined category (OV or JOCD). RESULTS: OV and MRI-defined JOCD lesions were identified in 21 of 28 condyles (75%, 95% CI: 56.6-87.3%), while 7 condyles (25%, 95% CI: 12.7-43.4%) remained normal throughout follow-up. Six condyles demonstrated MRI-defined JOCD lesions at one or more timepoints. Three OV lesions evolved over time: two progressed to MRI-defined JOCD but remained clinically silent, and one progressed from OV to MRI-defined JOCD and subsequently to clinically manifest JOCD requiring surgery. Using Generalized Linear Mixed model, a statistically significant association was found between bone marrow edema and MRI-defined category (F = 31.73, p < 0.001). OV lesions showed absent or trace edema, whereas JOCD showed definite edema. Inter-reader agreement using Cohen's Kappa was moderate to substantial between the radiologists (κ = 0.479-0.739, 95% CI: 0.314-0.633, 0.644-0.845, p < 0.001). CONCLUSIONS: In siblings of patients with JOCD, OV lesions are common and may represent dynamic MRI phenotypes along a continuum of epiphyseal ossification abnormalities, with occasional progression to MRI-defined JOCD and rare progression to clinically manifest JOCD.

Humans↗

PubMed2026

Gender-specific pathways linking body dissatisfaction, self-disgust, and social anxiety in Chinese adolescents: A three-wave longitudinal study.

Adolescence is a critical period for physical and psychological development. Body dissatisfaction is a significant concern during this stage, contributing to psychological issues such as social anxiety. However, the longitudinal relationships among body dissatisfaction, self-disgust, and social anxiety, as well as the potential role of gender differences in these dynamics, remain unclear. A total of 1109 junior high school students in China completed the baseline survey, with data collected at three time points (Mage = 12.67 years, SD = 0.68; 51.9% girls). Data were collected using the Body Areas Satisfaction Scale (BASS), the Self-Disgust Scale (SDS), and the Social Anxiety Scale for Children (SASC). Structural equation modeling (SEM) was employed to examine the longitudinal mediating effects among body dissatisfaction, self-disgust, and social anxiety, as well as to explore gender differences in these relationships. After controlling for autoregressive effects of self-disgust and social anxiety across waves, body dissatisfaction at T1 was found to indirectly predict social anxiety at T3 through self-disgust at T2, while indirectly predicting self-disgust at T3 through social anxiety at T2. Multi-group analyses revealed significant gender differences: for females, only the mediating pathway with self-disgust as the mediator was significant; for males, only the pathway with social anxiety as the mediator was significant. These findings contribute to a more nuanced understanding of the emotional mechanisms linking body dissatisfaction to social anxiety and highlight the importance of considering gender-specific pathways in prevention and intervention efforts.

Adolescent↗

PubMed2026

Longitudinal associations between family factors and the neurodevelopmental and psychosocial outcomes of children with congenital heart disease: A systematic review.

Family factors have been gaining increased attention in understanding adverse neurodevelopmental and psychosocial outcomes for children with congenital heart disease (CHD). To clarify relevance, we undertook a systematic review of only longitudinal studies which assessed such associations. Comparisons with the contribution of disease/surgical factors were also made where included studies considered such. We included longitudinal studies which assessed dynamic family factors (e.g. parent mental health, attachment, family functioning) and later child outcomes. Searches were conducted across CINAHL, Medline-Pubmed, PsychInfo and SCOPUS Web of Science. The NIH Quality Assessment Tool was used to evaluate study quality and risk of bias. Eighteen studies, utilizing data from 11 study samples and 2109 participants, met inclusion criteria. These studies included samples from infancy, with follow-up periods stretching into young adulthood, and with various degrees of CHD severity. The quality of studies was "good" to "fair", with key limitations of attrition and limited sociocultural diversity in samples. Findings suggested that family factors predicted later child psychosocial outcomes and more consistently than severity of disease indicators. This contrasted with a much smaller number of studies examining family factors and child neurodevelopmental outcomes, where no reliable conclusions could be reached. Findings highlight the importance of screening and family focused interventions for this population.

Child↗

PubMed2026

Longitudinal analysis of circulating tumor DNA and CA19-9 dynamics in predicting disease relapse and monitoring treatment response in stage I-III pancreatic ductal adenocarcinoma: An interim analysis of a prospective observational study.

INTRODUCTION: Postoperative recurrence is the leading cause of mortality in resected pancreatic ductal adenocarcinoma (PDAC), yet reliable tools for early relapse detection and treatment response assessment remain lacking. METHODS: In a prospective cohort of 136 patients with resected stage I-III PDAC receiving adjuvant chemotherapy, we evaluated circulating tumor DNA (ctDNA) and CA19-9 as longitudinal biomarkers across multiple postoperative time windows. RESULTS: ctDNA consistently outperformed CA19-9 as an independent prognostic factor; ctDNA positivity at on-treatment and surveillance assessments achieved a positive predictive value of 91.7%, while persistent negativity identified the lowest-risk patients. Integrating CA19-9 with ctDNA resolved the ctDNA-alone gap in distinguishing treatment clearance from conversion, improving discrimination of responders from non-responders (HR 3.72; P = .008). A time-weighted dynamic ctDNA risk score (MinerVa-dynamic) further stratified ctDNA-negative patients into clinically distinct prognostic subgroups, achieving an area under the curve of 0.87 and 0.82 for one- and two-year disease-free survival prediction, respectively. CONCLUSIONS: These findings support a dual-biomarker longitudinal monitoring framework as a practical, individualized approach to postoperative surveillance and early therapeutic decision-making in PDAC.

CA19-9↗

PubMed2024

Longitudinal effects of elexacaftor/tezacaftor/ivacaftor on the oropharyngeal metagenome in adolescents with cystic fibrosis.

BACKGROUND: Triple modulator therapy elexacaftor/tezacaftor/ivacaftor (ETI) improves lung function and impacts upon the respiratory microbiome in people with Cystic fibrosis (pwCF) with advanced lung disease. However, adolescents with cystic fibrosis (CF) are less colonized with bacterial pathogens than adult pwCF but their microbiota already differs from healthy individuals. The aim of this study was to longitudinally analyze the impact of ETI on the respiratory metagenome in adolescents with predominantly mild CF lung disease. METHODS: In this prospective observational study, we included pwCF aged 12-20 years with at least one F508del mutation, who collected oropharyngeal swabs before and after initiation of ETI therapy twice per week to biweekly over three months. We performed whole metagenome shotgun sequencing, followed by host DNA filtering and taxonomic profiling. We used linear and additive mixed effects models adjusted for known confounders and corrected for multiple testing to study longitudinal development of the microbiome. We analyzed bacterial diversity, abundance, and strain-level phylogeny. RESULTS: We analyzed the metagenomic data of 297 swabs of 20 pwCF. Microbiome composition changed after initiation of ETI therapy. We observed a slight diversification of the microbiome over time (Inv Simpson, Coef 0.085, 95 %CI 0.003, 0.17, p = 0.04). Strain-level analysis and clustering showed that strain retention of the most frequent bacterial species is predominant even during ETI therapy. CONCLUSIONS: During three months of ETI therapy, commensal bacteria increased, which may help to prevent overgrowth of bacterial pathogens.

Humans↗

PubMed2026

Autistic-like traits and longitudinal changes in health-related quality of life among individuals with bipolar disorder: A 12-month study.

OBJECTIVE: Autistic-like traits are common in bipolar disorder (BD) and have been linked to poor functional outcomes, yet their longitudinal impact on quality of life (QOL) remains unclear. This study examined whether autistic-like traits are associated with 12-month changes in health-related QOL in BD. METHODS: Seventy-eight outpatients with BD who completed 12-month follow-up assessments were included (mean age = 34.9 years). Autistic-like traits were assessed using the Social Responsiveness Scale for Adults (SRS-A), with participants classified into elevated- and non-elevated-traits groups. Depressive and manic symptoms were evaluated using the 17-item Hamilton Depression Rating Scale (HAMD-17) and the Young Mania Rating Scale (YMRS). QOL was measured using the 36-Item Short-Form Health Survey (SF-36). Linear mixed models were used to examine longitudinal changes. RESULTS: HAMD-17 scores demonstrated significant main effects of time and group, reflecting overall improvement but persistently higher depressive symptoms in the elevated-traits group. YMRS scores indicated a significant group effect only. Physical QOL remained stable, while mental QOL improved over time without group differences. Role/social QOL showed significant main effects of time and group, with consistently lower scores in the elevated-traits group. No group × time interactions emerged, suggesting similar rates of change between groups. CONCLUSIONS: This prospective study suggests that autistic-like traits in BD are associated with persistently poorer role/social functioning over time rather than differences in recovery trajectories. Assessing autistic-like traits may help identify patients at risk of poorer functioning and guide tailored psychosocial interventions.

Autistic-like traits↗

PubMed2026

Lineage dynamics of invasive Escherichia coli isolates in the Netherlands from 1975 to 2021: a retrospective longitudinal genomic analysis.

BACKGROUND: Escherichia coli is a common cause of invasive infections such as bloodstream and cerebrospinal fluid infections in neonates. Strains positive for the K1 capsule are considered the most common cause of such neonatal invasive infections. This assumption of K1 dominance, and indeed the population genomics of E coli causing invasive infections in general is largely unstudied. We aimed to provide a comprehensive characterisation of this pathogen population using a longitudinal isolate collection. METHODS: In this analysis we report the findings of the SENTINEL study, a longitudinal genomic analysis of 1790 invasive E coli isolates collected mainly from newborns in the Netherlands between 1975 and 2021 by the Netherlands Reference Laboratory for Bacterial Meningitis, Amsterdam University Medical Centre, Amsterdam, Netherlands. The dataset included all bacterial strains cultured from cerebrospinal fluid or blood in cases of (clinical) bacterial meningitis (1976 to 1980). In 1981 the criteria were expanded to include neonates (aged ≤4 weeks) with E coli sepsis, and from July, 2016 all infants younger than 1 year with E coli sepsis were included. All isolates were sequenced using either the HiSeq 2500 or HiSeq 4000 platforms (Illumina, San Diego, CA, USA). We confirmed species and identified sequence types (STs), detected antimicrobial resistance genes, virulence genes, and the presence of K1 capsule, and characterised the dynamics of these factors over time. FINDINGS: Our data show a highly dynamic bacterial population that is entirely unaffected by antimicrobial resistance determinants. Key pathogen population fluctuations include the complete disappearance of the dominant lineage ST567 and the swapping of dominant ST95 clones from a single serotype O18:H7 clone to two distinct serotype O1:H7 clones, with changes in virulence factors including major fimbrial adhesins. These findings, combined with only 58·8% (1053 of 1790) prevalence in K1-expressing isolates in the entire study population, point to host-pathogen interaction and immune selection pressures as key drivers of bacterial population dynamics in this largely antimicrobial-naive population. INTERPRETATION: Our data show the vital need for ongoing genomic surveillance of microbial pathogen populations to guide appropriate intervention strategies. Additionally, genomic insights of a pathogen population from one specific disease syndrome or patient population cannot always be generalised across other cohorts. FUNDING: Wellcome Antimicrobial and Antimicrobial Resistance Doctoral Training Programme and the National Institute for Health and Care Research Birmingham Biomedical Research Centre.

Netherlands↗

PubMed2026

Multidimensional GWAS analyses on longitudinal phenotypes reveal candidate genes regulating multi-stage egg production traits in Wannan yellow chicken.

Egg production performance directly determines the economic viability of indigenous chicken breeding. However, the genetic regulation of multi-stage egg production traits remains difficult to characterize due to their complex and dynamic nature. Here, we integrated a multidimensional GWAS framework, including single-trait GWAS, multi-trait GWAS (MTAG), and longitudinal trajectory-based GWAS (TrajGWAS), to identify stage-specific and shared genetic effects underlying egg production traits in Wannan yellow chickens (WNY). Whole-genome sequencing of 354 WNY hens (10× depth) and quality control yielded 14,253,816 SNPs for analysis. Selective sweep analyses comparing red jungle fowl, commercial layers, and WNY identified a genomic region containing IGF1 under significant selection pressure. Single-trait GWAS identified SNPs 4_57990480 (BMPR1B) and 17_370912 (LOC112531479) associated with egg production across three laying stages (21-30, 31-40, and 21-40 weeks). MTAG further identified loci 8_4336468 (FASLG) and 21_654726 (CHD5) with shared effects across the laying period, whereas TrajGWAS revealed longitudinal associations involving PRKG1 and identified dynamic loci associated with clutch traits, including GRID1. For clutch traits, stage-specific loci were detected for average clutch size (ACS) and maximum clutch size (MCS), including SNP 8_8542036 at 21-30 weeks, PROK1 at 31-40 weeks, and CUL5, ALKBH8 across the entire laying period. These results demonstrate that integrating complementary GWAS strategies improves the resolution of genetic architecture underlying egg production traits by capturing trait-specific, shared, and stage-dependent genetic effects. The identified GWAS loci and selective-sweep candidate regions provide insights into the genetic architecture of egg production traits and breed differentiation.

Egg production↗

PubMed2026

A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma.

Pediatric high-grade glioma (pHGG) is an incurable central nervous system malignancy that is a leading cause of pediatric cancer death. While pHGG shares many similarities with adult glioma, it comprises distinct disease entities. In this study, we longitudinally profile a molecularly diverse cohort of 16 pHGG patients through single-nucleus RNA and ATAC sequencing, whole-genome sequencing, and CODEX spatial proteomics to capture the evolution of neoplastic and microenvironmental features during disease progression and treatment. We define a set of core pHGG neoplastic cell states and observe differential tumor-myeloid interactions between malignant cell phenotypes. We find that essential neuromodulators and the interferon response are upregulated post-therapy, implicating them as malignant cell-intrinsic targets. We observe an increase in oligodendrocytes upon progression and that they coordinate spatial motifs with proneural tumor cells. This multiomic atlas of longitudinal pHGG captures features of therapy response and provides a scalable reference for the study of pediatric brain tumors.

Humans↗

PubMed2026

Longitudinal variability of lipoprotein(a) in youth-onset type 1 diabetes: implications for cardiovascular risk stratification.

BACKGROUND: Lipoprotein(a) [Lp(a)] is a genetically determined and independent cardiovascular risk factor, traditionally considered stable across the lifespan, supporting a single lifetime measurement strategy. However, its longitudinal behaviour during childhood and adolescence remains poorly characterised, particularly in individuals with type 1 diabetes who face a markedly increased lifetime risk of coronary artery disease. We therefore aimed to characterise intra- and inter-individual trajectories of Lp(a) in a paediatric type 1 diabetes cohort and to assess the implications of Lp(a) variability for cardiovascular risk classification. METHODS: We conducted a retrospective single-centre cohort study of children and adolescents with type 1 diabetes attending Geneva University Hospitals between 2012 and 2023. Annual fasting Lp(a) concentrations were analysed longitudinally. Variability was assessed in participants with ≥ 2 measurements. Clinically relevant thresholds were used to evaluate cardiovascular risk reclassification. Paired Wilcoxon tests, Pearson and Kendall correlations, and Holm-adjusted p-values (P < 0.05) were applied. Analyses were conducted in R. RESULTS: A total of 286 participants contributed 1403 Lp(a) measurements, with observation periods varying across individuals (median 6.2 years, IQR 2.9-9.6) and between 1 and 13 measurements per participant. At baseline, 26% had elevated Lp(a) (≥ 300 mg/l). Among participants with serial measurements, 32% showed intraindividual fluctuations exceeding 50% of their individual maximum value. Reclassification across the 300 mg/l cardiovascular risk threshold occurred in 11.9% of participants. Lp(a) concentrations peaked between ages 10 and 13 years and declined thereafter. Modest seasonal variation was observed, with higher concentrations in autumn and winter (P < 0.05). CONCLUSIONS: In youth with type 1 diabetes, Lp(a) is not as stable as previously assumed, exhibiting clinically relevant variability over time. These findings challenge the current paradigm of a single lifetime Lp(a) measurement and suggest that repeated assessment, particularly during adolescence, may improve early cardiovascular risk stratification.

Humans↗

PubMed2025

Comprehensive cross-sectional and longitudinal comparisons of plasma glial fibrillary acidic protein and neurofilament light across FTD spectrum disorders.

BACKGROUND: Therapeutic development for frontotemporal dementia (FTD) is hindered by the lack of biomarkers that inform susceptibility/risk, prognosis, and the underlying causative pathology. Blood glial fibrillary acidic protein (GFAP) has garnered attention as a FTD biomarker. However, investigations of GFAP in FTD have been hampered by symptomatic and histopathologic heterogeneity and small cohort sizes contributing to inconsistent findings. Therefore, we evaluated plasma GFAP as a FTD biomarker and compared its performance to that of neurofilament light (NfL) protein, a leading FTD biomarker. METHODS: We availed ARTFL LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) study resources to conduct a comprehensive cross-sectional and longitudinal examination of the susceptibility/risk, prognostic, and predictive performance of GFAP and NfL in the largest series of well-characterized presymptomatic FTD mutation carriers and participants with sporadic or familial FTD syndromes. Utilizing single molecule array technology, we measured GFAP and NfL in plasma from 161 controls, 127 presymptomatic mutation carriers, 702 participants with a FTD syndrome, and 67 participants with mild behavioral and/or cognitive changes. We used multivariable linear regression and Cox proportional hazard models adjusted for co-variates to examine the biomarker utility of baseline GFAP and NfL concentrations or their rates of change. RESULTS: Compared to controls, GFAP and NfL were elevated in each FTD syndrome but GFAP, unlike NfL, poorly discriminated controls from participants with mild symptoms. Similarly, both baseline GFAP and NfL were higher in presymptomatic mutation carriers who later phenoconverted, but NfL better distinguished non-converters from phenoconverters. We additionally observed that GFAP and NfL were associated with disease severity indicators and survival, but NfL far outperformed GFAP. Nevertheless, we validated findings that the GFAP/NfL ratio may discriminate frontotemporal lobar degeneration with tau versus TDP-43 pathology. CONCLUSIONS: Our head-to-head comparison of plasma GFAP and NfL as biomarkers for FTD indicate that NfL consistently outmatched GFAP as a prognostic and predictive biomarker for participants with a FTD syndrome, and as a susceptibility/risk biomarker for people at genetic risk of FTD. Our findings underscore the need to include leading biomarkers in investigations evaluating new biomarkers if the field is to fully ascertain their performance and clinical value.

Humans↗

PubMed2022

Temporal associations between leukocytes DNA methylation and blood lipids: a longitudinal study.

BACKGROUND: The associations between blood lipids and DNA methylation have been investigated in epigenome-wide association studies mainly among European ancestry populations. Several studies have explored the direction of the association using cross-sectional data, while evidence of longitudinal data is still lacking. RESULTS: We tested the associations between peripheral blood leukocytes DNA methylation and four lipid measures from Illumina 450 K or EPIC arrays in 1084 participants from the Chinese National Twin Registry and replicated the result in 988 participants from the China Kadoorie Biobank. A total of 23 associations of 19 CpG sites were identified, with 4 CpG sites located in or adjacent to 3 genes (TMEM49, SNX5/SNORD17 and CCDC7) being novel. Among the validated associations, we conducted a cross-lagged analysis to explore the temporal sequence and found temporal associations of methylation levels of 2 CpG sites with triglyceride and 2 CpG sites with high-density lipoprotein-cholesterol (HDL-C) in all twins. In addition, methylation levels of cg11024682 located in SREBF1 at baseline were temporally associated with triglyceride at follow-up in only monozygotic twins. We then performed a mediation analysis with the longitudinal data and the result showed that the association between body mass index and HDL-C was partially mediated by the methylation level of cg06500161 (ABCG1), with a mediation proportion of 10.1%. CONCLUSIONS: Our study indicated that the DNA methylation levels of ABCG1, AKAP1 and SREBF1 may be involved in lipid metabolism and provided evidence for elucidating the regulatory mechanism of lipid homeostasis.

Humans↗