Evaluating Performance and Agreement of Coronary Heart Disease Polygenic Risk Scores

JAMA, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 16, 2024

Importance Polygenic risk scores (PRSs) for coronary heart disease (CHD) are a growing clinical and commercial reality. Whether existing provide similar individual-level assessments of susceptibility remains incompletely characterized. Objective To characterize the agreement CHD PRSs that perform similarly at population level. Design, Setting, Participants Cross-sectional study participants from diverse backgrounds enrolled in All Us Research Program (AOU), Penn Medicine BioBank (PMBB), University California, Los Angeles (UCLA) ATLAS Precision Health Biobank with electronic health record genotyping data. Exposures published new developed separately testing samples. Main Outcomes Measures performed population-level prediction were identified by comparing calibration discrimination models prevalent CHD. Individual-level was tested intraclass correlation coefficient (ICC) Light κ. Results A total 48 calculated 171 095 AOU participants. The mean (SD) age 56.4 (16.8) years. 104 947 (61.3%) female. 35 590 (20.8%) most genetically to an African reference population, 29 801 (17.4%) admixed American 100 493 (58.7%) European remaining Central/South Asian, East Middle Eastern populations. There 17 589 (10.3%) 153 506 without (89.7%) When included model CHD, 46 had practically equivalent Brier area under receiver operator curves (region practical equivalence ±0.02). Twenty percent least 1 score both top bottom 5% risk. Continuous individual predictions poor (ICC, 0.373 [95% CI, 0.372-0.375]). κ, used evaluate consistency assignment, did not exceed 0.56. Analysis among 41 193 PMBB 53 092 yielded different sets scores, which also lacked agreement. Conclusions Relevance level demonstrated highly variable estimates Recognizing may generate incongruent estimates, effective implementation will require refined statistical methods quantify uncertainty strategies communicate this patients clinicians.

Язык: Английский

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The impact of common and rare genetic variants on bradyarrhythmia development

Nature Genetics, Год журнала: 2025, Номер unknown

Опубликована: Янв. 2, 2025

Язык: Английский

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Using Family History Data to Improve the Power of Association Studies: Application to Cancer in UK Biobank

Genetic Epidemiology, Год журнала: 2025, Номер 49(1)

Опубликована: Янв. 1, 2025

ABSTRACT In large cohort studies the number of unaffected individuals outnumbers affected individuals, and power can be low to detect associations for outcomes with prevalence. We consider how including recorded family history in regression models increases between genetic variants disease risk. show theoretically using Monte‐Carlo simulations that a disease, weighting 0.5 compared true cases, associations. This is powerful approach detecting moderate effects, but larger effect sizes > more powerful. illustrate this both common exome sequencing data over 400,000 UK Biobank evaluate association burden protein‐truncating genes risk four cancer types.

Язык: Английский

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Subcontinental Genetic Diversity in the All of Us Research Program: Implications for Biomedical Research

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Янв. 10, 2025

ABSTRACT The All of Us Research Program ( ) seeks to accelerate biomedical research and address the underrepresentation minorities by recruiting over one million ethnically diverse participants across United States. A key question is how self-identification with discrete, predefined race ethnicity categories compares genetic diversity at continental subcontinental levels. To contextualize in , we analyzed ∼2 common variants from 230,016 unrelated whole genomes using classical population genetics methods, alongside reference panels such as 1000 Genomes Project, Human Genome Diversity Simons Project. Our analysis reveals that within self-identified groups exhibit a gradient rather than discrete clusters. distributions ancestries show considerable variation ethnicity, both nationally states, reflecting historical impacts U.S. colonization, transatlantic slave trade, recent migrations. samples filled most gaps along top five principal components current global panels. Notably, “Hispanic or Latino” spanned much three-way (African, Native American, European) admixture spectrum. Ancestry was significantly associated body mass index (BMI) height, even after adjusting for socio-environmental covariates. In particular, West-Central East African showed opposite associations BMI. This study emphasizes importance assessing ancestries, approach insufficient control confounding association studies.

Язык: Английский

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A genealogy-based approach for revealing ancestry-specific structures in admixed populations

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Янв. 14, 2025

Elucidating ancestry-specific structures in admixed populations is crucial for comprehending population history and mitigating confounding effects genome-wide association studies. Existing methods elucidating the generally rely on frequency-based estimates of genetic relationship matrix (GRM) among individuals after masking segments from ancestry components not being targeted investigation. However, these approaches disregard linkage information between markers, potentially limiting their resolution revealing structure within an component. We introduce expected GRM (as-eGRM), a novel framework relatedness individuals. The key design as-eGRM consists defining pairwise based genealogical trees encoded Ancestral Recombination Graph (ARG) local calls computing expectation across genome. Comprehensive evaluations using both simulated stepping-stone models empirical datasets three-way Latino cohorts showed that analysis robustly outperforms existing with diverse demographic histories. Taken together, has promise to better reveal fine-scale component individuals, which can help improve robustness interpretation findings studies disease or complex traits understudied populations.

Язык: Английский

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The Social Construction of Categorical Data: Mixed Methods Approach to Assessing Data Features in Publicly Available Datasets

JMIR Medical Informatics, Год журнала: 2025, Номер 13, С. e59452 - e59452

Опубликована: Янв. 28, 2025

Background In data-sparse areas such as health care, computer scientists aim to leverage much available information possible increase the accuracy of their machine learning models’ outputs. As a standard, categorical data, patients’ gender, socioeconomic status, or skin color, are used train models in fusion with other data types, medical images and text-based information. However, effects including features for model training data-scarce underexamined, particularly regarding intended serve individuals equitably diverse population. Objective This study aimed explore data’s on outputs, rooted collection dataset publication processes, proposed mixed methods approach examining datasets’ categories before using them training. Methods Against theoretical background social construction categories, we suggest assess utility an example, applied our Brazilian dermatological (Dermatological Surgical Assistance Program at Federal University Espírito Santo [PAD-UFES] 20). We first present exploratory, quantitative that assesses when excluding each unique PAD-UFES 20 transformer-based algorithm. then pair analysis qualitative examination based interviews authors. Results Our suggests scattered across predictive classes. gives insights into how were collected why they published, explaining some observed. findings highlight constructedness publicly datasets, meaning category heavily depend both these defined by creators sociomedico context which collected. reveals relevant limitations datasets contexts different from those data. Conclusions caution against without reflection dependency features, areas. conclude scientific, context-dependent is helpful judging population intended.

Язык: Английский

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Experience using conventional compared to ancestry-based population descriptors in clinical genomics laboratories

The American Journal of Human Genetics, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

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Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues

Human Genomics, Год журнала: 2025, Номер 19(1)

Опубликована: Янв. 31, 2025

Non-communicable diseases (NCDs) such as cardiovascular diseases, chronic respiratory cancers, diabetes, and mental health disorders pose a significant global challenge, accounting for the majority of fatalities disability-adjusted life years worldwide. These arise from complex interactions between genetic, behavioral, environmental factors, necessitating thorough understanding these dynamics to identify effective diagnostic strategies interventions. Although recent advances in multi-omics technologies have greatly enhanced our ability explore interactions, several challenges remain. include inherent complexity heterogeneity multi-omic datasets, limitations analytical approaches, severe underrepresentation non-European genetic ancestries most omics which restricts generalizability findings exacerbates disparities. This scoping review evaluates landscape data related NCDs 2000 2024, focusing on advancements integration, translational applications, equity considerations. We highlight need standardized protocols, harmonized data-sharing policies, advanced approaches artificial intelligence/machine learning integrate study gene-environment interactions. also opportunities translating insights (GxE) research into precision medicine strategies. underscore potential advancing enhancing patient outcomes across diverse underserved populations, emphasizing fairness-centered strategic investments build local capacities underrepresented populations regions.

Язык: Английский

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CASP8 intronic expansion identified by poly-glycine-arginine pathology increases Alzheimer’s disease risk

Proceedings of the National Academy of Sciences, Год журнала: 2025, Номер 122(7)

Опубликована: Фев. 12, 2025

Alzheimer’s disease (AD) affects more than 10% of the population ≥65 y age, but underlying biological risks most AD cases are unclear. We show anti-poly-glycine-arginine (a-polyGR) positive aggregates frequently accumulate in sporadic autopsy brains (45/80 cases). hypothesize that these caused by one or polyGR-encoding repeat expansion mutations. developed a CRISPR/deactivated-Cas9 enrichment strategy to identify candidate GR-encoding mutations directly from genomic DNA isolated a-polyGR(+) cases. Using this approach, we an interrupted (GGGAGA) n intronic within SINE-VNTR-Alu element CASP8 ( -GGGAGA EXP ). Immunostaining using a-polyGR and locus-specific C-terminal antibodies demonstrate expresses hybrid poly(GR)n(GE)n(RE)n proteins (+) brains. In cells, expression minigenes leads increased p-Tau (Ser202/Thr205) levels. Consistent with other types repeat-associated non-AUG (RAN) proteins, protein levels stress. Additionally, stress-induced reduced metformin. Association studies specific aggregate promoting sequence variants found ~3.6% controls 7.5% increase risk [ -GGGAGA-AD-R1; OR 2.2, 95% CI (1.5185 3.1896), P = 3.1 × 10 −5 ]. Cells transfected high-risk -GGGAGA-AD-R1 variant toxicity aggregates. Taken together, data polyGR(+) as frequent unexpected type brain pathology alleles relatively common factor. support model which combined stress risk.

Язык: Английский

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Leveraging protein structural information to improve variant effect prediction

Current Opinion in Structural Biology, Год журнала: 2025, Номер 92, С. 103023 - 103023

Опубликована: Фев. 22, 2025

Despite massive sequencing efforts, understanding the difference between human pathogenic and benign variants remains a challenge. Computational variant effect predictors (VEPs) have emerged as essential tools for assessing impact of genetic variants, although their performance varies. Initially, sequence-based methods dominated field, but recent advances, particularly in protein structure prediction technologies like AlphaFold, led to an increased utilization structural information by VEPs aimed at scoring missense variants. This review highlights progress integrating into VEPs, showcasing novel models such AlphaMissense, PrimateAI-3D, CPT-1 that demonstrate improved evaluation. Structural data offers more interpretability, especially non-loss-of-function provides insights complex interactions vivo. As field utilizing biomolecular structures will be pivotal future VEP development, with breakthroughs protein-ligand protein-nucleic acid offering new avenues.

Язык: Английский

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