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PubMed2024

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

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

Humans↗

PubMed2026

Pilot study identifying distinct circulating proteomic profiles associated with longitudinal CT-defined fibrotic and inflammatory sarcoidosis.

INTRODUCTION: Pulmonary sarcoidosis exhibits heterogeneous clinical trajectories ranging from self-limited disease resolution to chronic progressive fibrosis, yet reliable biomarkers capable of distinguishing these disease patterns remain lacking. Whether longitudinal CT-defined sarcoidosis phenotypes are associated with distinct circulating molecular signatures remains unknown. METHODS: We performed high-throughput plasma proteomics (SomaScan 11K) in participants with pulmonary sarcoidosis classified into longitudinal chest CT-defined progressive fibrosis, progressive nodular inflammatory disease, or resolving disease trajectories, along with healthy controls. CT phenotypes were assigned based on predefined longitudinal changes in reticulation, traction bronchiectasis, nodular involvement, and mediastinal lymphadenopathy across serial CT scans. One plasma sample per participant was selected from the study visit corresponding to the CT time point at which criteria for the assigned longitudinal phenotype were met. Principal component analysis, hierarchical clustering, pathway enrichment, and correlation-based analyses linking protein expression to quantitative CT features were used to evaluate whether distinct longitudinal CT phenotypes were associated with divergent proteomic signatures. RESULTS: Principal component analysis and hierarchical clustering suggested partial segregation by CT-defined phenotype. Longitudinal CT phenotypes were associated with distinct pathway-level proteomic signatures, with progressive fibrosis enriched for epithelial-mesenchymal transition signaling, and progressive nodular inflammatory disease enriched for mTORC1, MYC, oxidative phosphorylation, adipogenesis, and fatty acid metabolism pathways. Correlation analyses showed coordinated protein-expression patterns associated with fibrotic CT features and mediastinal lymph node enlargement. DISCUSSION: These findings suggest that longitudinal CT-defined fibrotic and inflammatory sarcoidosis phenotypes are associated with distinct pathway-level proteomic signatures. This pilot study provides preliminary proof-of-concept evidence that integrating longitudinal CT imaging phenotypes with plasma proteomics may serve as a framework for future mechanistic studies and biomarker discovery in pulmonary sarcoidosis.

Humans↗

PubMed2025

Association Between Ratio of Triglycerides to HDL-C and Cognitive Impairment: A Longitudinal Population-Based Analysis and Mendelian Randomization Study.

OBJECTIVES: This study aimed to explore the longitudinal association between the triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio and cognitive impairment in older adults and further assess potential causality using Mendelian randomization (MR). DESIGN: Longitudinal population-based analysis combined with two-sample MR. Data from Waves 6-8 (2015-2019) of the Survey of Health, Ageing, and Retirement in Europe (SHARE) were analyzed using hierarchical regression models and mixed linear effects models. MR utilized genome-wide association studies (GWAS) summary data. PARTICIPANTS: 11,444 adults aged ≥60 years from SHARE Wave 6, with longitudinal follow-up in Waves 7 (N = 2,775) and 8 (N = 5,469). MEASUREMENTS: TG/HDL-C ratio, cognitive function (orientation, immediate/delayed recall, verbal fluency, numeracy), and cognitive impairment (defined as scores >1.5 SD below age-group mean). Covariates included socio-demographics, health behaviors, comorbidities, and national-level factors. MR employed genetic variants associated with TG/HDL-C as instrumental variables. RESULTS: Higher TG/HDL-C ratios were negatively associated with total cognitive scores (β = -0.115, χ² = 15.44, df = 1, p < 0.001), immediate recall (β = -0.029, χ² = 12.34, df = 1, p < 0.001), delayed recall (β = -0.028, χ² = 7.33, df = 1, p < 0.001), verbal fluency (β = -0.038, χ² = 11.53, df = 1, p < 0.001), and numeracy (β = -0.019, χ² = 4.55, df = 1, p < 0.05) in fully adjusted models. Longitudinal analysis revealed increased cognitive impairment risk in the highest TG/HDL-C quartile (OR=1.43, 95% CI:1.01-2.03, χ² = 9.24, df = 1) over 4 years. MR supported a causal link between elevated TG/HDL-C and cognitive decline. CONCLUSIONS: Elevated TG/HDL-C ratios are longitudinally associated with cognitive decline in older adults. Managing lipid metabolism may mitigate cognitive impairment, highlighting the importance of TG/HDL-C as a modifiable risk factor in aging populations.

Humans↗

PubMed2026

Longitudinal dynamics of gene expression and metabolomics in an aging population cohort.

Multiomic profiling provides a comprehensive physiological overview at the molecular level, but understanding of its spatiotemporal dynamics remains limited in human populations. We profiled longitudinal whole-blood gene expression and metabolite levels in 335 females over 8 years. Levels of 5061 genes and 181 metabolites changed over time, with individual trajectories often diverging from population-level trends. Longitudinally variable genes showed cell type specificity and enrichment for aging-relevant pathways, including cardiometabolic and neurodegenerative disorders. Longitudinal trajectories were further shaped by genetics, circadian rhythm, seasonality, and environmental pollutant exposures. Integrative analyses revealed extensive static and time-variable cross-omic connectivity. Longitudinal profiling offers insight into the temporal evolution of age-related conditions at the molecular level, and understanding individual variation within these longitudinal patterns will be essential for future precision medicine approaches.

Female↗

PubMed2026

Longitudinal functional network connectivity changes across the clinical stages of C9orf72 hexanucleotide repeat expansion carriers.

INTRODUCTION: Intrinsic functional connectivity network abnormalities in C9orf72 hexanucleotide repeat expansion carriers emerge during the asymptomatic phase, yet longitudinal studies remain limited. We examined cross-sectional abnormalities and longitudinal connectivity changes across clinical stages. METHODS: We analyzed task-free functional magnetic resonance imaging (fMRI) and structural MRI data in 36 asymptomatic (aSxC9), 17 prodromal (proC9), and 29 symptomatic (SxC9) carriers, and 107 healthy controls (HCs). Functional networks previously found altered in C9orf72, including salience, sensorimotor, default mode, and medial pulvinar thalamic networks, were examined. Associations between longitudinal connectivity and gray matter decline with baseline neurofilament light chain (NfL) concentrations and symptom severity were assessed. RESULTS: aSxC9 and SxC9 showed longitudinal connectivity changes within specific networks. In aSxC9, connectivity changes correlated with baseline NfL. In proC9 and SxC9, changes in connectivity and gray matter were associated with baseline NfL and symptom severity. DISCUSSION: C9orf72 expansion carriers demonstrate stage-specific network connectivity changes.

Humans↗

PubMed2022

Uric Acid Levels Are Associated with Bone Mineral Density in Mexican Populations: A Longitudinal Study.

Background: Inconsistent epidemiological evidence between uric acid (UA) and bone mineral density (BMD) has been observed. Therefore, we evaluated the association between UA and BMD in Mexican adults. Methods: This analysis was conducted on 1423 participants from the Health Workers Cohort Study. We explored cross-sectional associations using linear regression and longitudinal associations using fixed-effects linear regression by sex and age groups (<45 and ≥45 years). Results: In females <45 years old, the cross-sectional analysis showed that UA levels were positively associated with total hip BMD. However, in the longitudinal analysis, we observed a negative association with the femoral neck and lumbar spine BMD. In contrast, in males <45 years old, we found an increase in total hip and femoral neck BMD in the groups with high levels of UA in the longitudinal association. On the other hand, in females ≥45 years old, we observed a longitudinal association between UA and loss of BMD at different sites. We did not observe an association between UA levels and BMD in males ≥45 years old. Conclusions: Our results suggest higher serum UA levels are associated with low BMD at different skeletal sites in Mexican females. Further studies are needed to delineate the underlying mechanisms behind this observation.

Male↗

PubMed2026

Longitudinal Repeated Protein Measurements in a Multiethnic Cohort Identify Novel Diabetes Biomarkers That Reveal Unique Disease Pathways.

There is up to a fourfold increase in diabetes biomarkers identified with longitudinal repeated versus single time point proteomic measurements. The increase in biomarkers identified with longitudinal repeated measurements is supported by a similar proportion being nominated as causal for type 2 diabetes with Mendelian randomization. Proteins unique to the longitudinal repeated analyses highlighted biological pathways (e.g., posttranslational protein modification and cellular structure and cycle regulation) that were distinct from pathways enriched among the shared proteins (e.g., small-molecule metabolic and catabolic processes). Longitudinal protein measurements identify additional novel disease biomarkers and disparate biological pathways compared with single measurement analyses.

Journal Article↗

PubMed2026

Genetic evidence that advanced COVID-19 accelerates longitudinal brain atrophy: A Mendelian randomization study.

Coronavirus disease 2019 (COVID-19) was reported to persist long-term in the brain and leave several long-term neurologic sequelae. However, the causal relationship between COVID-19 and brain aging is still unknown. The genome-wide association study (GWAS) data on COVID-19 phenotypes (susceptibility, hospitalization, and severity), involving a total of 5,779,391 participants, were collected from the COVID-19 Host Genetics Initiative. In addition, GWAS data on longitudinal changes in 15 brain structures, assessed via magnetic resonance imaging across the lifespan, were sourced from the ENIGMA Consortium and involved 15,640 participants. Two-sample Mendelian randomization was conducted to infer the causal relationship between COVID-19 and longitudinal brain changes. Multi-trait GWAS meta-analysis, colocalization, and fine-mapping analyses were performed to identify shared genetic etiologies. H3K27me3 ChIP-seq was used to evaluate the regulatory effect of colocalized loci. Two-step Mendelian randomization was applied to explore potential mediating mechanisms across multi-omics layers, including proteomics, metabolomics, and immunomics. Our results showed that COVID-19 hospitalization (β = -262.405, P = .041) and severity (β = -177.676, P = .049) were genetically associated with atrophied volume of total brain during longitudinal change. This suggests that individuals with advanced COVID-19 may be more susceptible to accelerated global brain aging. Caudate was genetically affected by all COVID-19 phenotypes. Seven variants were shared between advanced COVID-19 and global brain aging. rs117169628 was colocalized between advanced COVID-19 and global brain aging, and exerted an inhibitory effect on CDH15 expression, further strengthening the causality. Six metabolites, 1 protein, and 1 immune trait were identified as potential mediators. Our study indicates that advanced COVID-19 might be genetically associated with accelerated brain aging. Brain health should be paid more attention in long COVID-19.

Humans↗

PubMed2026

Retention strategies and participant retention rates among prospective longitudinal pregnancy cohorts: a systematic mapping review.

Prospective longitudinal pregnancy cohorts can answer questions about fetal and early life exposures and later health outcomes; however, there are challenges to retaining participants in longitudinal studies, particularly over life transitions like the birth of a child. Optimal methods for retaining participants in longitudinal research are unclear. A systematic mapping review was conducted to identify prospective cohort studies and randomized controlled trials that enrolled pregnant participants and their infants. Data on retention rates and 17 retention strategies was extracted. A random effects meta-analysis generated pooled annual retention rates inversely weighted to the number of baseline participants. Spearman rank coefficients were used to assess correlation between strategy use and retention. A random-effects meta-regression was used to determine if select retention strategies were associated with participant retention. We identified 130 studies, involving 472 022 pregnancies. A downward trend in pooled mean retention rates were observed. Studies utilized an average of 6.8 (SD 3.9) retention strategies. Statistically significant associations were not observed between strategy use and retention rates at follow-up (p > 0.05). Prospective studies of pregnant people and their infants used multiple retention strategies. Participant retention rates declined over time, suggesting that additional factors may influence study participation in the postpartum period.

Humans↗

PubMed2026

Longitudinal progression, metrics, age-dependence, and modifiers of ataxia severity in SCA27B: a multicentre study of 219 patients.

BACKGROUND: Spinocerebellar Ataxia 27B (SCA27B) is a novel, frequent and likely treatable late-onset autosomal-dominant ataxia caused by GAA repeat-expansions in FGF14. For understanding disease evolution and imminent trial planning, metrics of the most widely used clinical outcome assessment (Scale for the Assessment and Rating of Ataxia/SARA), longitudinal progression and modifiers thereof are warranted. METHODS: Multicentre intercontinental observational study (2015-2024) of 661 assessments from 219 patients with SCA27B (age: 68 ± 10 years; SARA: 9 ± 6 points) with item-level distribution-based analyses to characterise SARA metrics relative to ageing-related impairment in 390 healthy controls; and linear mixed-effects modelling to determine longitudinal progression and demographic or genetic modifiers. FINDINGS: Ataxia severity in SCA27B as assessed by SARA was primarily attributable to gait, stance, and lower-limb impairment; other ataxia domains scored ≤1 SARA point in 79-94% of patients. Discrimination of SCA27B motor performance from controls decreased with age due to ageing-related motor variability captured by SARA, thus limiting potential metric response windows for symptomatic treatments. Disease progression was faster in the presence of interfering ageing-related comorbidities in 14 (6%) patients. Overall longitudinal progression of SCA27B was 0.54 SARA points/year [95% CI: 0.37-0.71]. Expansions of (GAA)> 180 repeats were frequent also on the shorter allele (n = 18 (8%), range: 196-348 repeats), and associated with faster progression (+1.6 SARA points/year, [95% CI: 0.9-2.2]), including also otherwise less affected ataxia domains speech and sitting. INTERPRETATION: Disease progression in SCA27B is characterised by mild progression, ageing-related motor variabilities and comorbidities, and associated with repeat size on both alleles. FUNDING: Else-Kröner-Fresenius-Stiftung, EU, DFG, BMBF, CIHR, NAF, Ataxia-UK, CSC.

Humans↗

PubMed2024

Phthalates and sex steroid hormones across the perimenopausal period: A longitudinal analysis of the Midlife Women's Health Study.

BACKGROUND: The menopausal transition involves significant sex hormone changes. Environmental chemicals, such as urinary phthalate metabolites, are associated with sex hormone levels in cross-sectional studies. Few studies have assessed longitudinal associations between urinary phthalate metabolite concentrations and sex hormone levels during menopausal transition. METHODS: Pre- and perimenopausal women from the Midlife Women's Health Study (MWHS) (n = 751) contributed data at up to 4 annual study visits. We quantified 9 individual urinary phthalate metabolites and 5 summary measures (e.g., phthalates in plastics (∑Plastic)), using pooled annual urine samples. We measured serum estradiol, testosterone, and progesterone collected at each study visit, unrelated to menstrual cycling. Linear mixed-effects models and hierarchical Bayesian kernel machine regression analyses evaluated adjusted associations between individual and phthalate mixtures with sex steroid hormones longitudinally. RESULTS: We observed associations between increased concentrations of certain phthalate metabolites and lower testosterone and higher sub-ovulatory progesterone levels, e.g., doubling of monoethyl phthalate (MEP), monobenzyl phthalate (MBzP), di-2-ethylhexyl phthalate (∑DEHP) metabolites, ∑Plastic, and ∑Phthalates concentrations were associated with lower testosterone (e.g., for ∑DEHP: -4.51%; 95% CI: -6.72%, -2.26%). For each doubling of MEP, certain DEHP metabolites, and summary measures, we observed higher mean sub-ovulatory progesterone (e.g., ∑AA (metabolites with anti-androgenic activity): 6.88%; 95% CI: 1.94%, 12.1%). Higher levels of the overall time-varying phthalate mixture were associated with lower estradiol and higher progesterone levels, especially for 2nd year exposures. CONCLUSIONS: Phthalates were longitudinally associated with sex hormone levels during the menopausal transition. Future research should assess such associations and potential health impacts during this understudied period.

Humans↗

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↗