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PubMed2026

Robust replication of associations across patient-mediated and provider-sourced EHR data in the All of Us research program.

The All of Us Research Program is assembling a nationwide cohort with electronic health record (EHR) resources through two complementary pathways: healthcare provider organization (HPO)-sourced EHRs and patient-mediated EHR (PME) contributed through patient portal linkages. The comparative research utility of these two data sources has not been systematically evaluated. Here, we compared PME and HPO EHRs with respect to disease prevalence, phenotype-phenotype associations, and replication of established genotype-phenotype associations using data from 19,703 PME and 373,887 HPO participants. We benchmarked disease prevalence against national estimates, conducted phenome-wide association studies for 10 commonly studied diseases, and tested replication of more than 5000 established genotype-phenotype associations across multiple ancestral groups. Disease prevalence was consistently lower in PME than in HPO, although prevalence of most diseases in both cohorts exceeded national estimates. Both data sources reproduced known phenotype-phenotype associations and showed moderate-to-strong concordance in effect sizes across the phenome. The overall genotype-phenotype replication rate was 49.1% (5399/10,999) in HPO and 5.9% (381/6482) in PME across ancestral groups, with effect sizes strongly correlated among well-powered associations (R = 0.84, P < 0.001). To disentangle the impact of sample size from data quality, we performed 1:1 propensity score matching. After matching, the replication gap in genotype-phenotype associations narrowed from 8.3-fold to 1.3-fold, with equivalent replication rates among adequately powered associations and strongly concordant effect sizes; comorbidity patterns were also consistent across all 10 diseases tested. These findings demonstrate that both data sources are valuable for clinical and genomic research and can inform other cohorts integrating provider-derived and patient-mediated EHRs.

Computational biology and bioinformatics↗

PubMed2024

Algorithms for the identification of prevalent diabetes in the All of Us Research Program validated using polygenic scores.

The All of Us Research Program (AoU) is an initiative designed to gather a comprehensive and diverse dataset from at least one million individuals across the USA. This longitudinal cohort study aims to advance research by providing a rich resource of genetic and phenotypic information, enabling powerful studies on the epidemiology and genetics of human diseases. One critical challenge to maximizing its use is the development of accurate algorithms that can efficiently and accurately identify well-defined disease and disease-free participants for case-control studies. This study aimed to develop and validate type 1 (T1D) and type 2 diabetes (T2D) algorithms in the AoU cohort, using electronic health record (EHR) and survey data. Building on existing algorithms and using diagnosis codes, medications, laboratory results, and survey data, we developed and implemented algorithms for identifying prevalent cases of type 1 and type 2 diabetes. The first set of algorithms used only EHR data (EHR-only), and the second set used a combination of EHR and survey data (EHR+). A universal algorithm was also developed to identify individuals without diabetes. The performance of each algorithm was evaluated by testing its association with polygenic scores (PSs) for type 1 and type 2 diabetes. We demonstrated the feasibility and utility of using AoU EHR and survey data to employ diabetes algorithms. For T1D, the EHR-only algorithm showed a stronger association with T1D-PS compared to the EHR + algorithm (DeLong p-value = 3 × 10-5). For T2D, the EHR + algorithm outperformed both the EHR-only and the existing T2D definition provided in the AoU Phenotyping Library (DeLong p-values = 0.03 and 1 × 10-4, respectively), identifying 25.79% and 22.57% more cases, respectively, and providing an improved association with T2D PS. We provide a new validated type 1 diabetes definition and an improved type 2 diabetes definition in AoU, which are freely available for diabetes research in the AoU. These algorithms ensure consistency of diabetes definitions in the cohort, facilitating high-quality diabetes research.

Humans↗

PubMed2026

Sociodemographic trends in prostate cancer: insights from the All of Us Research Program.

BACKGROUND: Prostate cancer disproportionately affects vulnerable populations. The All of Us Research Program (AoURP) is a database that aims to encapsulate the diversity of the United States. To explore the utility of this dataset in assessing prostate cancer disparities, we investigated whether treatment usage, disease progression, and genomic research participation vary across sociodemographic factors among AoURP participants with prostate cancer. METHODS: We identified AoURP participants with prostate cancer. Genomic research participation in AoURP, treatment usage, time-to-treatment, and time-to-metastasis were assessed by demographics and distance from a National Cancer Institute-designated comprehensive cancer center. Multivariable logistic regression and Cox proportional hazards regression were performed to evaluate treatment usage and time-to-treatment and time-to-metastasis, respectively. RESULTS: We observed lower genomic data availability in Black vs White patients (P < .001). In multivariable analyses, patients residing more than 80 miles from an NCI-designated comprehensive cancer center were less likely to receive androgen receptor pathway inhibitors (odds ratio [OR] = 0.30, 95% CI = 0.14 to 0.66; P = .002) and bone targeting agents (OR = 0.46, 95% CI = 0.30 to 0.70; P < .001) but more likely to undergo prostatectomy (OR = 1.97, 95% CI = 1.43 to 2.71; P < .001) than those residing less than 40 miles away. These patients also initiated treatment faster (hazard ratio [HR] = 1.54, 95% CI = 1.27 to 1.87; P < .001) and developed metastasis slower (HR = 0.58, 95% CI = 0.40 to 0.86; P = .006). Black patients were less likely to receive radiation (OR = 0.45, 95% CI = 0.23 to 0.88; P = .020), prostatectomy (OR = 0.65, 95% CI = 0.44 to 0.96; P = .028), and bone targeting agents (OR = 0.65, 95% CI = 0.45 to 0.93; P = .018) than White patients. CONCLUSIONS: Prostate cancer treatment usage, disease progression, and genomic research participation varied between demographic populations. As AoURP matures, additional studies may leverage future data releases to confirm these findings.

Aged↗

PubMed2025

Genotype-first assessment of presentation and penetrance of neurofibromatosis type 1, autosomal dominant polycystic kidney disease, and Marfan syndrome within the All of Us research program cohort.

PURPOSE: Phenotype-based ascertainment of probands in studies of Mendelian disorders may exclude individuals with mild phenotypes or that lack health care access. We explore this premise in All of Us Research Program participants with pathogenic variation causal for 3 Mendelian conditions: autosomal dominant polycystic kidney disease (ADPKD), Marfan syndrome, and neurofibromatosis type 1 (NF1). METHODS: We identified All of Us Research Program participants with putatively pathogenic variation in NF1, FBN1, PKD1, and PKD2. Concept terms were extracted from electronic health records to assess participant diagnosis and phenotype. Variant annotation and participant surveys were evaluated to identify biological and social factors differentiating diagnosed and undiagnosed individuals. RESULTS: Large proportions of individuals with pathogenic variation in NF1, FBN1, or PKD1/PKD2 lack the associated diagnosis of NF1 (47%), Marfan syndrome (58%), or ADPKD (52%), respectively. Pathogenic variants in diagnosed individuals have greater inferred deleteriousness for NF1 and ADPKD, and undiagnosed individuals had less severe phenotypes compared with diagnosed individuals for all 3 conditions. CONCLUSION: A genotype-first ascertainment of individuals in genomic research allows for a more comprehensive assessment of Mendelian disease and removes biases that confound our understanding of the penetrance and presentation of these conditions.

Humans↗

PubMed2026

No association between alcohol consumption and hip osteoarthritis: a diverse national analysis of 87,585 adults from the "All of Us" research program.

INTRODUCTION: Hip osteoarthritis (OA) is estimated to affect 62.6 million individuals by 2050. A probable link exists between alcohol use and hip OA. However, the results are inconsistent, and the relationship between alcohol and hip OA remains speculative. To address these gaps, this study aimed to utilize the diverse, nationally representative All of Us Research Program dataset to explore the association between alcohol consumption and hip OA. METHODS: This retrospective case-control study utilized data from the All of Us Research Program Controlled Tier Dataset v8. 17,517 hip OA cases and 70,068 controls were identified. A 1:4 case-to-control matching ratio was applied based on age and sex. Alcohol use frequency was categorized into five levels: Never, Monthly or Less, Two to Four Times per Month, Two to Three Times per Week, and Four or More Times per Week. Multivariable logistic regression models evaluated the association between alcohol use frequency and hip OA after adjusting for demographic and clinical variables. RESULTS: Multivariable analysis found that alcohol use frequency was not significantly associated with hip OA. Compared to never users, participants with low (OR 0.98, 95% CI 0.93-1.04, P = 0.583), moderate (OR 0.99-1.01, all P > 0.05), and high (OR 1.02, 95% CI 0.95-1.09, P = 0.599) levels of alcohol consumption had no statistically significant differences in odds of hip OA. Female sex, Asian race, diabetes, hypertension, hyperlipidemia, and nicotine dependence increased the odds of hip OA. CONCLUSION: Any level of alcohol consumption was not significantly associated with the odds of hip OA. This study adds valuable insight to the current body of conflicting evidence. Further prospective studies appear warranted to shed light on the long-term effects of different alcoholic beverages on different joints. Key Points • This study found no significant association between any degree of alcohol consumption and the odds of developing hip osteoarthritis. • Utilizing data from 87,585 adults in the NIH "All of Us" Research Program, this is the first study to analyze this relationship in a large, nationally representative population. • The research provides clarity to previously conflicting literature by demonstrating that alcohol lacks a clear harmful or protective effect on the clinical course of the disease. • The analysis highlights that independent risk factors such as Asian race, nicotine dependence, and components of metabolic syndrome increase the odds of hip osteoarthritis.

Humans↗

PubMed2026

Menopause in the All of Us Research Program: a descriptive summary of electronic health record and survey response across sociodemographic characteristics.

OBJECTIVES: Menopause is a significant physiological transition with implications for health outcomes (eg, cardiometabolic disease), yet gaps remain in understanding this transition, including how menopause timing and type influence health outcomes. Large-scale cohort studies in midlife (age=40-60) females, including the All of Us Research Program (AoURP), provide opportunities to study menopause across diverse populations and data modalities. We characterized menopause-related data in AoURP, focusing on age distributions and concordance between electronic health record (EHR) diagnosis codes and survey responses. METHODS: We analyzed menopause-related surveys, EHR diagnostic codes, and genomic data among ~396,000 AoURP female participants. We summarized menopause-related variables across data sources, evaluated overlap between survey, EHR, and genomic data sets, and described age distributions overall and across sociodemographic characteristics. RESULTS: Among ~396,000 females, survey responses captured ~193,000 menopause observations, nearly seven times more than EHR diagnoses (~28,000), suggesting under-ascertainment in EHR data. Nearly all females (~99%) with an EHR menopause diagnosis reported menopause in the survey. Approximately 22,000 participants had overlapping menopause-related EHR, survey, and genomic data. Survey age patterns matched expectations, with participants predominantly <40 years reporting premenopausal status and those >60 years reporting postmenopausal status. A small subset with age >70 years (N≈1,700; 4%) reported no menopause, suggesting response or recall bias. EHR menopause codes were concentrated after age 45 years, with a notable spike at age 65. Modest differences in survey-based menopause age distributions were observed across sociodemographic characteristics (eg, race and ancestry). CONCLUSIONS: These findings inform sampling strategies, power calculations, phenotype definition, and study design for menopause research using AoURP data.

Age↗

PubMed2025

Large-scale admixture mapping in the All of Us Research Program improves the characterization of cross-population phenotypic differences.

Admixed individuals have largely been understudied in medical research due to their complex genetic ancestries. However, the consideration of admixture can help identify ancestry-enriched genetic associations, delineating some of the genetic underpinnings of cross-population phenotypic variation. To this end, we performed local ancestry inference within the All of Us Research Program to identify individuals with recent admixture between African (AFR) and European (EUR) populations (N=48,921). We identified evidence of local AFR ancestry enrichment at the HLA locus, suggestive of putative selection since admixture. Furthermore, we performed the largest admixture mapping (ADM) efforts in AFR-EUR Admixed individuals for 22 traits, identifying 71 associations between inferred local AFR ancestries and a trait. Variants from published GWAS could only account for 18 (25%) of the ADM associations, highlighting novel loci where ancestral haplotypes explained some phenotypic variation. Previous studies likely have not identified these loci due to the low availability of high-powered GWAS in populations genetically similar to AFR. One such loci was 9q21.33, associated with 1.4-fold risk of end-stage kidney disease (ESKD) for carriers of inferred local AFR ancestries at the region. This locus contains the gene SLC28A3, which has previously been linked to kidney function but has never been associated with cross-population ESKD prevalence differences. Together, our results expand upon the existing literature on phenotypic differences between populations, highlighting loci where genetic ancestries play a critical role in the genetic architecture of disease.

Journal Article↗

PubMed2025

Building a Digital Health Research Platform to Enable Recruitment, Enrollment, Data Collection, and Follow-Up for a Highly Diverse Longitudinal US Cohort of 1 Million People in the All of Us Research Program: Design and Implementation Study.

BACKGROUND: Longitudinal cohort studies have traditionally relied on clinic-based recruitment models, which limit cohort diversity and the generalizability of research outcomes. Digital research platforms can be used to increase participant access, improve study engagement, streamline data collection, and increase data quality; however, the efficacy and sustainability of digitally enabled studies rely heavily on the design, implementation, and management of the digital platform being used. OBJECTIVE: We sought to design and build a secure, privacy-preserving, validated, participant-centric digital health research platform (DHRP) to recruit and enroll participants, collect multimodal data, and engage participants from diverse backgrounds in the National Institutes of Health's (NIH) All of Us Research Program (AOU). AOU is an ongoing national, multiyear study aimed to build a research cohort of 1 million participants that reflects the diversity of the United States, including minority, health-disparate, and other populations underrepresented in biomedical research (UBR). METHODS: We collaborated with community members, health care provider organizations (HPOs), and NIH leadership to design, build, and validate a secure, feature-rich digital platform to facilitate multisite, hybrid, and remote study participation and multimodal data collection in AOU. Participants were recruited by in-person, print, and online digital campaigns. Participants securely accessed the DHRP via web and mobile apps, either independently or with research staff support. The participant-facing tool facilitated electronic informed consent (eConsent), multisource data collection (eg, surveys, genomic results, wearables, and electronic health records [EHRs]), and ongoing participant engagement. We also built tools for research staff to conduct remote participant support, study workflow management, participant tracking, data analytics, data harmonization, and data management. RESULTS: We built a secure, participant-centric DHRP with engaging functionality used to recruit, engage, and collect data from 705,719 diverse participants throughout the United States. As of April 2024, 87% (n=613,976) of the participants enrolled via the platform were from UBR groups, including racial and ethnic minorities (n=282,429, 46%), rural dwelling individuals (n=49,118, 8%), those over the age of 65 years (n=190,333, 31%), and individuals with low socioeconomic status (n=122,795, 20%). CONCLUSIONS: We built a participant-centric digital platform with tools to enable engagement with individuals from different racial, ethnic, and socioeconomic backgrounds and other UBR groups. This DHRP demonstrated successful use among diverse participants. These findings could be used as best practices for the effective use of digital platforms to build and sustain cohorts of various study designs and increase engagement with diverse populations in health research.

Humans↗

PubMed2025

Association of HFE genotypes with hemochromatosis-related phenotypes in the All of Us research program.

PURPOSE: Type 1 hereditary hemochromatosis (HH) can result in iron overload and liver disease if not detected and treated early. Most cases are found among people homozygous for HFE p.Cys282Tyr variants. Compound heterozygosity with the HFE p.His63Asp variant is associated with disease to a lesser degree. We sought to examine the association of HFE variation with HH-related phenotypes and assess the prevalence of testing and diagnosis of HH using All of Us data. METHODS: We used data from 133,978 participants with genetic information linked to medical records. For different HFE genotypes, we examined the prevalence of HH diagnosis codes and related biochemical and clinical phenotypes. RESULTS: Among participants who were p.Cys282Tyr homozygotes, the prevalence of HH diagnosis codes was 22.6% among males and 15.6% among females. Serum transferrin-iron saturation measures were available only for 31.4% of males and 21.1% of females who were p.Cys282Tyr homozygotes. Liver disease, including cirrhosis or hepatocellular carcinoma, was present more among males who were p.Cys282Tyr homozygotes compared with males with no p.Cys282Tyr or p.His63Asp variants (15.5% vs 8.5%, P = .0001). Of the 71 participants who were p.Cys282Tyr homozygotes with indication of liver disease, 32 (45.1%) did not have a serum transferrin-iron saturation measure, and 37 (52.1%) did not have diagnosis codes for HH. CONCLUSION: Limited serum transferrin-iron saturation measures or HH diagnosis codes among p.Cys282Tyr homozygotes, even those with liver disease, suggests potential undertesting and underdiagnosis of type 1 HH in clinical practice and a need for improved awareness, education, and testing around HH.

C282Y homozygosity↗

PubMed2026

Large-scale admixture mapping in the All of Us Research Program improves the characterization of cross-population phenotypic differences.

Admixed individuals have been understudied in medical research largely due to their complex genetic ancestries. However, the consideration of admixture can identify ancestry-enriched genetic associations, delineating genetic underpinnings of cross-population phenotypic variation. Here, we performed admixture mapping in individuals with inferred admixture from African and European populations (N = 48,921). Across 22 traits, we identified 71 ancestry-trait associations, including loci where ancestral haplotypes explained phenotypic variation yet were missed by single-variant association testing due to their stricter multiple testing burden. One such locus where inferred local AFR ancestries are associated with increased hemoglobin A1c (HbA1c) was 12q14.3, highlighting its potential role in explaining differences between populations. Together, our results expand upon the phenotypic differences between populations and characterize loci where genetic ancestries play a critical role in the architecture of disease.

Humans↗

PubMed2026

Genetic architecture of postpartum psychosis: from common to rare genetic variation.

Postpartum psychosis is a severe psychiatric condition marked by the abrupt onset of psychosis, mania, or psychotic depression following childbirth. Despite evidence for a strong genetic basis, the roles of common and rare genetic variation remain poorly understood. Leveraging data from Swedish national registers and genomic data from the All of Us Research Program, we estimated family-based heritability at 55% and whole-genome sequencing-based heritability at 46%. Rare coding variant analysis identified HMGCR as a gene in which rare damaging variants confer risk for postpartum psychosis (FDR < 0.05). Analyses of 240,009 participants from the All of Us Research Program and 58,990 participants from the Mount Sinai BioMe Biobank identified significant associations linking deleterious rare variants in HMGCR to vascular dementia and mental disorder, not otherwise specified, supporting the gene's broader psychiatric relevance. Additionally, among the top 200 genes ranked by association statistics, 17% of bipolar disorder, 21% of schizophrenia, and 16-25% of multiple autoimmune disorders exhibit a possible association with postpartum psychosis. These findings reveal unique genetic contributions and shared pathways, providing a foundation for understanding pathophysiology and advancing therapeutic strategies.

Humans↗

PubMed2026

Multi-Ancestry Genome-Wide Association with Fine-Mapping Identifies Novel Loci for Pigment Dispersion Syndrome and Pigmentary Glaucoma.

PURPOSE: Pigment dispersion syndrome and pigmentary glaucoma are important causes of ocular hypertension and glaucomatous optic neuropathy, yet their genetic determinants remain incompletely defined, particularly across diverse ancestries. This study aimed to use a large multi-ancestry cohort from the All of Us Research Program to investigate the genetic basis of pigment dispersion syndrome and pigmentary glaucoma. DESIGN: Case-control study. PARTICIPANTS: In total, 572 cases and 37 808 controls with array genotyping and 537 cases and 35 493 controls with whole-genome sequencing. METHODS: Using electronic health record phenotyping in the All of Us Research Program, we performed multi-ancestry genome-wide association analyses using both array-based data and whole-genome sequencing-based data, comparing patients with pigment dispersion syndrome or pigmentary glaucoma to those without either condition. We also performed Firth penalized regression and Fisher analyses, and we performed principal component analyses to assess effect sizes across genetic ancestries. We applied statistical fine-mapping, examined for cross-trait overlap, and assessed expression quantitative trait locus associations for lead variants. MAIN OUTCOME MEASURES: P values and odds ratios of lead loci from genome-wide association analyses; size of credible sets determined from fine-mapping; allele frequency of lead variants in cases, controls, and the general population; expression quantitative trait loci effect size and P values linking lead variants to gene expression. RESULTS: We identified 4 loci reaching genome-wide significance across analyses, including signals near EPHA7 (which mediates cell-cell signaling), within TYR (involved in melanin synthesis and replicated from prior studies), within LINC01138, and near OTX2. Statistical fine-mapping refined 3 of these loci to single-variant 95% credible sets and narrowed the TYR locus to small credible sets, prioritizing possible causal variants. Effect estimates were broadly consistent across genetic ancestry clusters. Lead variants showed regulatory evidence in expression quantitative trait locus, including reduced EPHA7 expression. CONCLUSIONS: These findings implicate both melanogenesis and cell-cell adhesion and signaling pathways in pigment dispersion syndrome and pigmentary glaucoma. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Genome-wide association study↗

PubMed2025

Implementing a training resource for large-scale genomic data analysis in the All of Us Researcher Workbench.

A lack of representation in genomic research and limited access to computational training create barriers for many researchers seeking to analyze large-scale genetic datasets. The All of Us Research Program provides an unprecedented opportunity to address these gaps by offering genomic data from a broad range of participants, but its impact depends on equipping researchers with the necessary skills to use it effectively. The All of Us Biomedical Researcher (BR) Scholars Program at Baylor College of Medicine aims to break down these barriers by providing early-career researchers with hands-on training in computational genomics through the All of Us Evenings with Genetics Research Program. The year-long program begins with the faculty summit, an in-person computational boot camp that introduces scholars to foundational skills for using the All of Us dataset via a cloud-based research environment. The genomics tutorials focus on genome-wide association studies (GWASs), utilizing Jupyter Notebooks and the Hail computing framework to provide an accessible and scalable approach to large-scale data analysis. Scholars engage in hands-on exercises covering data preparation, quality control, association testing, and result interpretation. By the end of the summit, participants will have successfully conducted a GWAS, visualized key findings, and gained confidence in computational resource management. This initiative expands access to genomic research by equipping early-career researchers from a variety of backgrounds with the tools and knowledge to analyze All of Us data. By lowering barriers to entry and promoting the study of representative populations, the program fosters innovation in precision medicine and advances equity in genomic research.

Humans↗

PubMed2026

Systematic common and rare variant association testing in 392,030 whole genomes in All of Us.

Large-scale genome-wide association studies (GWAS) and rare variant association studies (RVAS) from population biobanks provide valuable resources for gene discovery in complex human traits. We present an analysis of the All of Us Research Program v8 release, which includes whole genome sequencing data and harmonized phenotypic information of 392,030 participants after quality control, enabling a unified investigation of rare and common variants across a spectrum of human traits and diseases. We build an extensive phenome- and genome-wide ("All by All") computational framework to perform GWAS and RVAS on 3,602 phenotypes and identify 49,863 approximately independent, high-quality single-variant and gene-level associations. Meta-analyses of All of Us and UK Biobank, with sample sizes as large as 786,871 participants, further enhance statistical power and find 193 pLoF gene-phenotype associations that are not significant in either cohort alone, including 22 associations not highlighted by previous studies. We also present a public interactive browser that integrates association results for common and rare variants to facilitate interpretation and rapid querying of summary statistics, along with supporting documentation, and a Featured Workspace in the All of Us Researcher Workbench. Our framework will apply to iterative data releases as All of Us grows, empowering researchers worldwide to uncover insights into the functional effects of genetic components on complex traits and diseases.

Journal Article↗

PubMed2026

Monogenic ALB Variants as Determinants of Severe Hypercholesterolemia: A Population-Based Cohort Study.

BACKGROUND: Hypoalbuminemia is associated with several risk factors for myocardial infarction, including hypercholesterolemia, liver disease, kidney disease, and diabetes. Homozygosity of loss-of-function (LoF) variants in the ALB gene, which encodes albumin, is a known cause of congenital hypoalbuminemia. Studies have also shown that heterozygous ALB LoF variants are associated with increases in low-density lipoprotein cholesterol (LDL-C), comparable to those seen in familial hypercholesterolemia. OBJECTIVES: This study examined the effect of ALB LoF variants and other causes of low albumin on LDL-C levels in 2 population biobanks. METHODS: This study used data from 2 large cohorts with linked electronic health record and genetic information: Geisinger's MyCode Community Health Initiative, a health care population based in Pennsylvania, USA; and the National Institutes of Health All of Us Research Program, a nationwide epidemiologic cohort. LDL-C values were adjusted for lipid-lowering medication use. Myocardial infarction diagnoses were extracted from electronic health records using International Classification of Diseases codes. A polygenic score for serum albumin was calculated for participants of European ancestry. Linear regression models were used to estimate associations, and results were meta-analyzed across cohorts using fixed-effects models. RESULTS: Among 155,530 MyCode and 405,701 All of Us adult participants, 77 individuals (1 of 7,289) carried an ALB LoF variant. Among noncarriers, a 1 g/dL decrease in serum albumin was associated with a 10.9 mg/dL (95% CI:, 10.4-11.4) decrease in LDL-C. In contrast, ALB LoF variants were associated with a 0.69 g/dL (95% CI: 0.60-0.78) reduction in serum albumin and a 38.3 mg/dL (95% CI: 28.2-48.5) increase in LDL-C. Paradoxically, whereas monogenic determinants of hypoalbuminemia were associated with increased LDL-C, polygenic determinants of lower albumin were associated with a 0.22 mg/dL (95% CI: 0.17-0.26) decrease in LDL-C per decile. CONCLUSIONS: ALB LoF variants represent a previously underrecognized monogenic cause of elevated LDL-C, with effect sizes slightly less than canonical familial hypercholesterolemia variants. The divergent effects of ALB-mediated vs polygenic or physiological reductions in albumin on LDL-C suggest distinct underlying mechanisms.

Humans↗

PubMed2026

Metabolic Dysfunction-Associated Steatotic Liver Disease Is Associated With Adverse Social Factors: An Analysis Using All of Us.

BACKGROUND AND AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is progressive, with estimated global prevalence exceeding 30%. Social determinants of health (SDOH) may impact MASLD risk and progression. However, this has not been fully characterized. We harnessed the power of the All of Us Research Program (AoU) dataset to conduct a comprehensive analysis examining the association between various SDOH and MASLD. METHODS: We conducted a retrospective cross-sectional analysis of the AoU database. We identified participants with MASLD using ICD-9 and -10 codes and excluded individuals with other chronic liver diseases or self-reported heavy alcohol use. Healthy control participants were devoid of chronic liver diseases, heavy alcohol use, and comorbidities associated with MASLD if obese. We examined SDOH by combining relevant questions from various AoU surveys and conducted univariate and multivariate logistic regression to examine the association between various SDOH and MASLD. RESULTS: After matching cases to controls by age and race/ethnicity, the sample of 57,895 participants had a 1:3 case to control ratio; 16,666 had complete SDOH survey data (MASLD to controls, 1:3.4). Compared to controls, individuals with MASLD were more likely to have less than a high school education (10.7% vs 9.7%; P < .001) and annual income ≤$35,000 (42.4% vs 34.3%; P < .001). Compared to controls, participants with MASLD had significantly higher levels of social isolation, neighborhood disorder, perceived stress, food insecurity, and transportation insecurity (P < .001 for all). CONCLUSION: The study identified significant associations between MASLD and multiple SDOH. Future studies should investigate how SDOH interact to drive MASLD risk and progression.

All of Us↗

PubMed2026

Genetic Ancestry and Colorectal Cancer in the All of Us Dataset.

IMPORTANCE: Genetic ancestry may complement biological, behavioral, and clinical factors in understanding colorectal cancer (CRC) disparities; yet, ancestry-informed analyses in CRC remain limited. OBJECTIVE: To characterize associations of genetic ancestry with CRC burden, age at diagnosis, and age-specific risk, and to develop a multiethnic CRC risk-prediction model. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used All of Us data from July 1986 to October 2023, with follow-up through last visit or death (median [IQR], 133.1 [57.1-186.5] months); analyses were conducted from February to June 2026. All of Us is a US research cohort with linked electronic health record (EHR) and short-read whole-genome sequencing (srWGS) data. All of Us Research Program participants with srWGS and linked EHR data were included, except those with hereditary polyposis or Lynch syndrome. EXPOSURES: Genetically inferred ancestry categories and principal components. MAIN OUTCOMES AND MEASURES: Any CRC was the primary outcome. Associations were evaluated using Fisher exact tests, cumulative incidence functions with Gray tests, cause-specific and Fine-Gray subdistribution hazard models, and pooled multivariable logistic regression. Prediction models used penalized least absolute shrinkage and selection operator and extreme gradient boosting (XGBoost). RESULTS: Among 316 624 participants (median [IQR] age, 56.3 [40.2-68.2] years; 172 327 [54.4%] of European ancestry; 191 705 female [61.2%]; 121 585 male [38.8%]), 2914 (0.9%) developed CRC. European ancestry was associated with higher odds of CRC vs all other ancestries combined (odds ratio, 1.50; 95% CI, 1.39-1.62). The median age at CRC diagnosis was older in European (63.4 [53.9-71.2] years) than in American admixed-Latino, African, East Asian, and Other ancestry groups. In cause-specific hazard models on the attained-age scale, American admixed-Latino (hazard ratio, 1.30; 95% CI, 1.14-1.47) and East Asian (hazard ratio, 1.43; 95% CI, 1.06-1.94) ancestry had higher age-specific CRC hazard than European ancestry, with consistent findings on the subdistribution scale accounting for competing death. The multiethnic XGBoost model performed best (receiver operating characteristic area under the curve, 0.898; 95% CI, 0.882-0.912; precision-recall area under the curve, 0.338; 95% CI, 0.296-0.379) and was well calibrated. CONCLUSIONS AND RELEVANCE: In this cohort study, genetic ancestry was associated with meaningful differences in CRC burden and age-specific risk. These findings suggest that a multiethnic XGBoost model may complement CRC screening as a risk-enrichment tool.

Aged↗

PubMed2024

Genetic Analysis of Asymptomatic Antinuclear Antibody Production.

OBJECTIVE: Antinuclear antibodies (ANA) are detected in up to 14% of the population, and many individuals with ANA are asymptomatic. The literature on the genetic contribution to asymptomatic ANA positivity is limited. In this study, we aimed to perform a genome-wide association study of asymptomatic ANA positivity in multiple populations. METHODS: Asymptomatic individuals who were either ANA positive or ANA negative from the All of Us Research Program were included in this study, selecting those with an ANA test performed by immunofluorescence and no evidence of autoimmune disease. Imputation was performed, and a multipopulation meta-analysis including approximately 6 million single-nucleotide polymorphisms (SNPs) was conducted. Genome-wide SNP-based heritability was estimated using the Genome-wide Complex Trait Analysis software. A cumulative genetic risk score for lupus was constructed using previously reported genome-wide significant loci. RESULTS: A total of 1,955 asymptomatic ANA positive and 3,634 asymptomatic ANA negative individuals across three populations were included. The multipopulation meta-analysis revealed SNPs with a suggestive association (P <1 × 10-5) across 8 different loci, but no genome-wide significant loci were identified. A gene variant upstream of HLA-DQB1, (rs17211748, P = 1.4 × 10-6, odds ratio 0.82, 95% confidence interval 0.76-0.89), showed the most significant association. The heritability of asymptomatic ANA positivity was estimated to be 24.9%. Individuals who were asymptomatic and ANA positive did not exhibit increased cumulative genetic risk for lupus compared with individuals who were ANA negative. CONCLUSION: ANA production is not associated with significant genetic risk and is primarily determined by environmental factors.

Humans↗