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PubMed2026

Beyond Exons: Linking Noncoding Heritability and Polygenicity across Complex Human Traits and Disorders.

The genetic architecture of complex traits spans a continuum of polygenicity, yet it remains unclear how differences in polygenicity relate to the functional localization of SNP heritability across the genome. We use a MiXeR-based framework to partition heritability across exonic, intronic, and intergenic regions for 34 traits and introduce a likelihood-based annotation contribution score that quantifies annotation-specific impact on heritability. Exons explain a minority of heritability, and their contribution decreases with increasing polygenicity, from an average of 22% in less polygenic somatic diseases and biomarkers to 13% in highly polygenic psychiatric and cognitive phenotypes. Intergenic fractions show the opposite trend, whereas intronic fractions remain relatively stable. Analysis of a broader set of functional annotations reveals systematic differences along the polygenicity axis: highly polygenic traits show stronger contributions from comparative genomics and variant-effect scores, whereas less polygenic traits show stronger contributions in promoter, transcription, and chromatin annotations. Together, these results indicate that the functional partitioning of heritability systematically varies with polygenicity, pointing to a shift from gene-proximal regulatory architectures to architectures shaped by numerous dispersed regulatory effects as a key determinant of differences in polygenicity across traits.

Journal Article↗

PubMed1991

Nonparametric tests of association between survival time and continuously measured covariates: the logit-rank and associated procedures.

O'Brien's logit-rank procedure (1978, Biometrics 34, 243-250) is shown to arise as a score test based on the partial likelihood for a proportional hazards model provided the covariate structure is suitably defined. Within this framework the asymptotic properties claimed by O'Brien can be readily deduced and can be seen to be valid under a more general model of censoring than that considered in his paper. More important, perhaps, it is now possible to make a more natural and interpretable generalization to the multiple regression problem than that suggested by O'Brien as a means of accounting for the effects of nuisance covariates. This can be achieved either by modelling or stratification. The proportional hazards framework is also helpful in that it enables us to recognize the logit-rank procedure as being one member of a class of contending procedures. One consequence of this is that the relative efficiencies of any two procedures can be readily evaluated using the results of Lagakos (1988, Biometrika 75, 156-160). Our own evaluations suggest that, for non-time-dependent covariates, a simplification of the logit-rank procedure, leading to considerable reduction in computational complexity, is to be preferred to the procedure originally outlined by O'Brien.

Biometry↗

PubMed1986

Recognition and frequency judgments in young and elderly adults.

Three experiments examined frequency judgments and recognition memory in young and elderly adults. Subjects were presented a long list of words at either a 5-s rate (Experiments 1 & 3) or a 1-s rate (Experiment 2), after which frequency-judgment and recognition memory tasks were administered. Either an absolute (Experiments 1 & 2) or a relative (Experiment 3) frequency-judgment task was used. The recognition test, which involved repeated tests of some items, involved either one incorrect item paired with each correct item (Experiments 1 & 2), or four incorrect items (Experiment 3). Age-related differences in frequency judgments, for the more frequently presented items, were found in all three experiments. For the recognition scores, the predicted interaction between age and successive tests was found only in Experiment 3. The results were interpreted within the framework of age-related differences in elaborative encoding and in distractibility to irrelevant stimuli.

Adolescent↗

PubMed2026

Evolving Role of Immunotherapy in Advanced Esophageal Squamous Cell Carcinoma: Are Programmed Death-Ligand 1 (PD-L1) Cutoffs Still Relevant?

Immune checkpoint inhibitors have transformed the management of advanced esophageal squamous cell carcinoma (ESCC) across first-line, second-line, and perioperative settings. Programmed death-ligand 1 (PD-L1) expression has served as the principal biomarker guiding patient selection for these agents, yet it is measured inconsistently across trials and antibody platforms, and its predictive value has come under renewed scrutiny as follow-up data have matured. This review synthesizes the pivotal randomized trials that established anti-programmed cell death protein-1 therapy in ESCC, critically appraises the pooled and patient-level meta-analyses that have re-examined outcomes across biomarker subgroups, and situates recent regulatory reassessment of PD-L1 thresholds within this broader evidence base. Assay heterogeneity between scoring systems, discordance across antibody clones, and the biological distinction between PD-L1 as a prognostic versus a predictive marker are examined as sources of continued uncertainty. The review concludes by considering emerging genomic and microenvironmental biomarkers that may eventually complement or refine PD-L1-based patient selection, and offers a framework for interpreting a single expression threshold as an approximate, assay-dependent stratifier rather than a precise biological boundary.

combined positive score↗

PubMed2025

vcfgl: a flexible genotype likelihood simulator for VCF/BCF files.

MOTIVATION: Accurate quantification of genotype uncertainty is pivotal in ensuring the reliability of genetic inferences drawn from NGS data. Genotype uncertainty is typically modeled using Genotype Likelihoods (GLs), which can help propagate measures of statistical uncertainty in base calls to downstream analyses. However, the effects of errors and biases in the estimation of GLs, introduced by biases in the original base call quality scores or the discretization of quality scores, as well as the choice of the GL model, remain under-explored. RESULTS: We present vcfgl, a versatile tool for simulating genotype likelihoods associated with simulated read data. It offers a framework for researchers to simulate and investigate the uncertainties and biases associated with the quantification of uncertainty, thereby facilitating a deeper understanding of their impacts on downstream analytical methods. Through simulations, we demonstrate the utility of vcfgl in benchmarking GL-based methods. The program can calculate GLs using various widely used genotype likelihood models and can simulate the errors in quality scores using a Beta distribution. It is compatible with modern simulators such as msprime and SLiM, and can output data in pileup, Variant Call Format (VCF)/BCF, and genomic VCF file formats, supporting a wide range of applications. The vcfgl program is freely available as an efficient and user-friendly software written in C/C++. AVAILABILITY AND IMPLEMENTATION: vcfgl is freely available at https://github.com/isinaltinkaya/vcfgl.

Software↗

PubMed2026

A machine learning-derived intratumoral heterogeneity-related signature predicts the prognosis for and therapeutic response in patients with skin cutaneous melanoma.

BACKGROUND: Reliable biomarkers for predicting prognosis and therapeutic response in skin cutaneous melanoma (SKCM) remain limited. This study aimed to develop an intratumoral heterogeneity (ITH)-related prognostic signature for SKCM using integrative machine learning. METHODS: RNA sequencing (RNA-seq) data from 472 SKCM patients in The Cancer Genome Atlas (TCGA) and 214 patients in the GSE65904 cohort were analyzed. ITH scores were calculated using the DEPTH2 algorithm. Differentially expressed genes (DEGs) were identified between high- and low-ITH groups [|log2fold change (FC)| ≥1, false discovery rate (FDR) <0.05]. Based on 38 prognostic DEGs identified by univariate Cox regression, we employed an integrative framework of 101 machine learning algorithm combinations to construct prognostic models in the TCGA training cohort. The model with the highest average concordance index (C-index) was validated in the GSE65904 cohort and selected as the prognostic ITH-related signature (PIRS). Associations of the PIRS risk score with tumor mutational burden (TMB), immune cell infiltration, immune checkpoint gene expression, and drug sensitivity were systematically evaluated. Model performance was assessed using receiver operating characteristic (ROC) curves and Cox regression analyses. RESULTS: A 38-gene PIRS was constructed using the plsRcox algorithm. Patients with high PIRS risk scores exhibited significantly poorer overall survival (OS) in both the TCGA and Gene Expression Omnibus (GEO) cohorts. The PIRS was identified as an independent prognostic factor, with area under the curve (AUC) values of 0.779, 0.734, and 0.756 for 1-, 3-, and 5-year survival, respectively. High-risk samples displayed significantly lower TMB (P<0.05), reduced immune and stromal cell infiltration (P<0.001), downregulated immune function, and decreased expression of immune checkpoint genes. Additionally, high- and low-PIRS risk score groups exhibited distinct sensitivity patterns to different classes of targeted agents. CONCLUSIONS: The machine learning-derived PIRS robustly predicts prognosis in SKCM patients. Its clinical application is promising for optimizing patient risk stratification and treatment decisions, though further prospective validation is warranted.

Skin cutaneous melanoma (SKCM)↗

PubMed1984

A scale to measure physician beliefs about psychosocial aspects of patient care.

This report describes the development and initial validation of a self-report instrument designed to measure beliefs about psychosocial aspects of patient care held by primary care physicians. The strategy used was borrowed from psychological measurement: a rational scale was constructed based on an existing theoretical framework concerning the physician's role, what the patient wants and physicians' reactions to their patients as people. The validation step compared scale scores obtained by diverse groups of providers. Psychometric characteristics of the Physician Belief Scale are adequate: scores follow an approximately normal distribution with the mean near the midpoint of possible scores. Lower scores on the Scale represent a more psychosocial approach to patient care. Initial construct validation was successful: physicians from four disciplines obtained scores congruent with expectations about the psychosocial orientations of the disciplines. A reliable and valid measure has been developed to assess physicians' psychosocial beliefs. The instrument may be used to evaluate effectiveness of behavioral science teaching, describing regional or other differences in physician beliefs within and between specialties and estimating changes in provider beliefs.

Attitude of Health Personnel↗

PubMed2026

Comprehensive evaluation of AlphaFold/OpenFold prediction of experimentally unresolved proteins through novel metrics.

Predicting accurate protein structures is essential for understanding molecular mechanisms, interpreting the impact of sequence variation, and supporting translational applications ranging from drug discovery to clinical genomics. Recent advances in deep-learning-based predictors such as AlphaFold2, OpenFold, and AlphaFold3 have transformed structural biology, enabling routine in silico modeling even for challenging or previously uncharacterized proteins. However, systematic benchmarking of these tools-especially for novel targets and single amino acid variants-remains limited. Conventional global metrics often fail to capture biologically meaningful discrepancies. By evaluating multiple implementations of AlphaFold2 and OpenFold, together with ColabFold and the AlphaFold3 server, across 10 different proteins and 222 single amino acid protein variants encompassing a wide range of sizes, structures, and functions, we show that although widely used global indicators-like mean pLDDT, pTM-score, and RMSD-frequently suggest comparable performance, substantial local-level differences remain elusive. To address this gap, we introduce a comparative framework leveraging Bland-Altman agreement analysis, to evaluate per-residue Cα-confidence differences and Per-Residue profiles (PRPs), complemented by Uniform Manifold Approximation and Projection (UMAP). This approach reveals marked localized divergences, particularly within flexible or intrinsically disordered regions, where both predictor choice and single-residue substitutions trigger the largest conformational shifts. We further demonstrate that using reduced homology databases has minimal impact on predicted structural quality, offering computationally efficient alternatives. Collectively, our findings underscore the importance of integrating global and residue-specific evaluations to more accurately assess robustness, agreement, and practical usability across contemporary protein structure prediction methods.

Proteins↗

PubMed2025

A large-scale study across the avian clade identifies ecological drivers of neophobia.

Neophobia, or aversion to novelty, is important for adaptability and survival as it influences the ways in which animals navigate risk and interact with their environments. Across individuals, species and other taxonomic levels, neophobia is known to vary considerably, but our understanding of the wider ecological drivers of neophobia is hampered by a lack of comparative multispecies studies using standardized methods. Here, we utilized the ManyBirds Project, a Big Team Science large-scale collaborative open science framework, to pool efforts and resources of 129 collaborators at 77 institutions from 24 countries worldwide across six continents. We examined both difference scores (between novel object test and control conditions) and raw data of latency to touch familiar food in the presence (test) and absence (control) of a novel object among 1,439 subjects from 136 bird species across 25 taxonomic orders incorporating lab, field, and zoo sites. We first demonstrated that consistent differences in neophobia existed among individuals, among species, and among other taxonomic levels in our dataset, rejecting the null hypothesis that neophobia is highly plastic at all taxonomic levels with no evidence for evolutionary divergence. We then tested for effects of ecological factors on neophobia, including diet, sociality, habitat, and range, while accounting for phylogeny. We found that (i) species with more specialist diets were more neophobic than those with more generalist diets, providing support for the Neophobia Threshold Hypothesis; (ii) migratory species were also more neophobic than nonmigratory species, which supports the Dangerous Niche Hypothesis. Our study shows that the evolution of avian neophobia has been shaped by ecological drivers and demonstrates the potential of Big Team Science to advance our understanding of animal behavior.

Animals↗

PubMed1993

A comparison of ICD-10 and DSM-III-R criteria for substance abuse and dependence.

As part of DSM-IV field trials for substance use disorders, 100 inpatients from two psychiatric substance abuse units were interviewed using a modified version of the Substance Abuse Module (SAM) to ascertain substance use diagnoses according to ICD-10 and DSM-III-R criteria. Both criteria sets developed from the theoretical framework presented by Gross and Edwards (1976) and thus, they should demonstrate close concurrence in diagnoses of dependence and abuse/harmful use. The kappa scores obtained in these analyses demonstrate good to excellent agreement on the diagnoses of dependence across substances. There was poor agreement between DSM-III-R and ICD-10 for abuse/harmful use diagnoses. Although there is generally good agreement between DSM-III-R and ICD-10 for substance dependence diagnoses, important differences exist between the two criteria sets both for the diagnoses of abuse and harmful use, and for the diagnosis of marijuana dependence. These differences are primarily due to the inclusion of social problems and repeated use of substances in hazardous situations as DSM-III-R criteria.

Alcoholism↗

PubMed2026

Development and Validation of a Clinical Polygenic Risk Report in U.S.-Based Health Systems for 8 Cardiovascular Conditions.

BACKGROUND: Polygenic risk scores (PRS) stratify inherited cardiovascular risk, but their path to clinical implementation remains unclear. OBJECTIVES: We aimed to develop and validate integrated PRS for 8 cardiovascular conditions and outline a framework for their clinical reporting. METHODS: We analyzed genotype and clinical data from 245,394 All of Us Research Program participants. Publicly available PRS for 8 traits-coronary artery disease, atrial fibrillation, type 2 diabetes, venous thromboembolism (VTE), thoracic aortic aneurysm (TAA), extreme hypertension, severe hypercholesterolemia, and elevated lipoprotein(a)-were combined using PRSmix, an elastic-net approach. Integrated PRS were externally validated in 53,306 Mass General Brigham Biobank participants using logistic regression, adjusting for age, sex, and ancestry. RESULTS: Of 53,306 genotyped Mass General Brigham Biobank participants (55.6% women, mean age 53 ± 17 years), integrated PRS demonstrated robust discrimination and appropriate calibration across 8 cardiovascular traits. Comparing high genetic risk (top 10% of PRS distribution, or top 20% for rarer TAA and VTE) vs average risk (26th-75th percentiles, or 21st-80th percentiles for TAA and VTE) yielded ORs: coronary artery disease (3.7 [95% CI: 3.4-4.1]), type 2 diabetes (3.1 [95% CI: 2.8-3.3]), atrial fibrillation (3.0 [95% CI: 2.7-3.3]), VTE (1.9 [95% CI: 1.6-2.0]), TAA (1.7 [95% CI: 1.5-1.9]), hypertension (2.1 [95% CI: 1.8-2.3]), hypercholesterolemia (4.1 [95% CI: 3.7-4.5]), and lipoprotein(a) (41.0 [95% CI: 27.0-62.2]). Incorporating integrated PRS into clinical models improved risk classification, while prospective analyses confirmed significant associations with incident cardiovascular outcomes. CONCLUSIONS: Integrated PRS offer an implementable framework for genetic risk reporting, and are now available as a clinically orderable test. Broader prospective validation studies are needed to further establish clinical utility.

Humans↗

PubMed1985

Type A behavior, nonverbal expressive style, and health.

Understanding the precise nature of the links among styles of behavior, emotional expression, and the development of heart disease is a major challenge in psychology and health. In the present research, 60 men at high risk for coronary heart disease were examined in terms of their expressive style, their specific nonverbal cues, their personality, and their health. As assessed by the self-report Jenkins Activity Survey (JAS; Jenkins, Zyzanski, & Rosenman, 1979), half the men were Type A and half were Type B. To provide a more refined grouping, the men were further classified on the basis of scores on the Affective Communication Test (ACT; H. S. Friedman, Prince, Riggio, & DiMatteo, 1980), a self-report measure of nonverbal expressiveness. In the framework of theory and research on nonverbal expressive style, videotapes of the men were extensively rated and coded in terms of their judged appearance, the actual audio and video nonverbal cues emitted, and the words said (transcript). Two groups of Type A individuals were found--one that was repressed, tense, and illness-prone, but another that was healthy, talkative, in control, and charismatic. Furthermore, in addition to the expected healthy Type B men, a subgroup of Type B men was found who were submissive, repressed, tense, have an external locus of control, and may be illness-prone. A refined conception of the Type A behavior pattern is deemed necessary in light of these findings. Implications for improving the validity of the Type A construct and understanding the link between psychosocial factors and disease are discussed.

Adult↗

PubMed1984

Clinical evaluation of language functions (CELF) diagnostic battery: an analysis and critique.

To summarize, the main strengths of the CELF are the clarity with which the manual describes the subtests and the instructions provided for test administration. Major concerns center on the absence of a theoretical framework as a basis for the selection of language skills assessed, the use of only "normal" children in the standardization sample, the lack of scoring criteria for one subtest, the seemingly incorrect weighting system for another, and minimal evidence of test reliability and validity.

Adolescent↗

PubMed1991

Evaluation of likelihood ratios for complex genetic models.

Although methods for computing likelihoods for simple genetic models on large and complex pedigrees have been known for some time, and although methods for evaluating likelihoods for complex genetic models on small pedigrees have likewise been well known, likelihood evaluation for complex models given data on extended pedigrees has remained an intractable problem. The Gibbs sampler provides a method of Monte Carlo evaluation of likelihood ratios for complex models on extended and/or complex pedigrees. With increasing computer speeds, this approach provides a tractable and efficient approach to many such likelihood evaluation problems in linkage and segregation analysis. In this paper, however, the authors restrict attention to two basic building-blocks of the overall process. The first is the sequential computation of Gaussian likelihoods for multiple random-effects models on extended pedigrees. The second is the use of this in the Monte Carlo evaluation of likelihoods for the classical mixed model of segregation analysis. The implementation of the Gibbs sampler on pedigrees that permits this Monte Carlo evaluation is detailed. An example is then presented, and finally, in the context of this same example, it is also shown how linkage analysis for a quantitative trait falls within this same framework.

Female↗

PubMed2026

Predictive evolutionary genomics: principles, validation, and practice.

Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c. 20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world.

Genomics↗

PubMed1994

Sibling adaptation to childhood cancer collaborative study: prevalence of sibling distress and definition of adaptation levels.

A multisite collaborative study assessed the frequency and intensity of emotional/behavioral distress in siblings of children with cancer. A sample of 254 siblings, aged 4 to 18 years, and their parents completed interviews and self-report measures 6 to 42 (average 22.5) months after diagnosis of cancer in a brother or sister. Matched controls were obtained from respondents to the Child Health Supplement of the National Health Interview Survey administered in 1988 (CHS88). Before diagnosis, the prevalence of parent-reported emotional/behavioral problems among siblings was similar to that in the general population (7.7% vs 6.3%; p = not significant). After diagnosis, prevalence rose to 18% among siblings. When siblings were grouped according to the presence or absence of problems exacerbated by and/or arising after diagnosis, four levels of adaptation, consistent with scores on the Behavior Problem Scales from the CHS88, emerged. This differentiation may help explain inconsistencies in sibling response reported previously and provides a framework for investigating factors that enhance adaptation.

Adaptation, Psychological↗

PubMed1991

[Familiarity, favorability, and cognitive complexity: integration of frequency of interaction hypothesis and vigilance hypothesis].

Previous studies using Bieri's 'cognitive complexity' score had supported 'vigilance hypothesis' which assumed that impressions of unfavorable persons were more complex than favorable persons. Thus, Bieri's measure seemed to be invalid because the findings were completely contrary to 'frequency of interaction hypothesis', presented in the theoretical framework of 'cognitive complexity', which assumed that impressions of familiar persons were more complex than unfamiliar persons, since people could be supposed to have more intimate acquaintance with favorable persons. The purpose of present study was to indicate the invalidity was caused by the research design where familiarity was dependent on favorability and to show that even Bieri's score could support 'interaction hypothesis', if one variables could be statistically orthogonized to the other. In each of two surveys reported, about two hundred female undergraduates completed a Rep test where they rated favorable and unfavorable persons on the basis of some dimensions which included favorability and familiarity. The results obtained through various regression analyses supported the above predictions. Moreover, it was revealed that, with favorability controlled, Bieri's score showed almost linear increases as familiarity increased, though the score of extremely unfamiliar persons was rather higher than the score the linear function could predict.

Adult↗

PubMed2025

MO-GCAN: multi-omics integration based on graph convolutional and attention networks.

MOTIVATION: Cancer subtypes play a critical role in disease progression, prognosis, and treatment, making their detection essential for tailoring precision medicine. Studies have shown that multi-omics integration outperforms single-omics approaches in cancer subtyping tasks. However, due to the high-dimensionality of multi-omics data, many existing studies either fail to capture the correlation between true labels and learned features, or lack sufficient capacity to model complex biological representations. These limitations hinder the full potential of leveraging the rich and complementary information embedded in multi-omics datasets. RESULT: We propose a framework that leverages supervised feature learning and classification based on a graph-based learning approach with attention mechanism for cancer subtyping. More specifically, we train graph convolutional network models on each omics dataset to extract latent representations, which are then concatenated to form a comprehensive multi-omics feature embedding. We further develop sample fusion network based on the omics-specific graphs, incorporating the derived features and feeding them into a graph attention model for subtype classification. This two-stage multi-omics framework is applied to eight cancer types, with performance evaluated in terms of test accuracy, training time, macro-averaged precision, recall, and F-score. Experimental results show that the proposed method outperforms state-of-the-art approaches across various cancer types. Additionally, we provide empirical evidence supporting the hypothesis that retaining a limited number of high-confidence edges and utilizing enriched embeddings from intermediate graph neural network layers can improve predictive performance. AVAILABILITY AND IMPLEMENTATION: Data and the code are available at https://github.com/YD-00/MO-GCAN-Updated.git.

Neoplasms↗