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GCRP: Integrated Global Chicken Reference Panel from 11,951 Chicken Genomes.

Chickens are a crucial source of protein for humans and a popular model animal for bird research. Despite the emergence of imputation as a reliable genotyping strategy for large populations, the lack of a high-quality chicken reference panel has hindered progress in chicken genome research. To address this, here we introduce the first phase of the 100K Global Chicken Reference Panel (100K GCRP). Currently, two panels are available: a comprehensive mix panel (CMP) for domestication diversity research and a commercial breed panel (CBP) for breeding broilers specifically. Evaluation of genotype imputation quality showed that CMP had the highest imputation accuracy compared to imputation using existing chicken panels in Animal-SNPAtlas and Animal Genotype Imputation Database (AGIDB), whereas CBP performed stably in the imputation of commercial populations. Additionally, we found that genome-wide association studies using GCRP-imputed data, whether on simulated or real phenotypes, exhibited greater statistical power. In conclusion, our study indicates that the GCRP effectively fills the gap in high-quality reference panels for chickens, providing an effective imputation platform for future genetic and breeding research. The project includes 11,951 samples and provides services for various applications on its website at http://farmrefpanel.com/GCRP/#/.

Animals

Predicted brain-regional gene expression patterns in individuals living with Alzheimer's disease.

Studying brain gene expression in Alzheimer's Disease (AD) remains difficult as postmortem brain is difficult to access, cannot be used to guide donor treatment, may be confounded by environmental factors before and after death, and is difficult to link to early AD states or disease progression. To circumvent these limitations, several studies have tested blood transcriptome biomarkers for AD. However, gene-expression levels in the blood have limited correlation with those in the brain. To evaluate the potential of monitoring Alzheimer's progression with peripheral data, we used transcriptome-imputation to identify brain-region-specific AD-associated gene-expression differences in cohorts with blood-based transcriptome data. This approach provides a high-resolution image of AD-associated molecular differences in the brains of individuals actively living with disease. We analyzed eight AD studies (777 AD cases, 779 cognitively unimpaired controls), imputing transcriptomes in 10 brain regions via the Brain Gene Expression and Network Imputation Engine (BrainGENIE). Hundreds of differentially expressed genes (DEGs) associated with AD were identified in nine brain regions, with anterior cingulate cortex and amygdala showing the most differential expression. AD-associated genes were enriched in pathways such as proteostasis, mitochondrial dysfunction, and immune activation. We observed significant yet moderate concordance between imputed AD-associated changes and those directly measured in the dorsolateral prefrontal cortex and cerebellum. These transcriptomic changes can guide future in vitro studies focused on pathogenesis or be targets of novel therapeutic development. In conclusion, we demonstrated the scope and utility of brain expression imputation from the peripheral transcriptome, laying the groundwork for biomarker discovery and prospective AD studies.

Alzheimer Disease

A vision of how low-coverage sequence data should contribute to genetic evaluation in the future.

Low-coverage sequencing refers to sequencing DNA of individuals to a low depth of coverage (e.g., 0.5X) and imputing that sequence to a genomic sequence based on reference haplotypes from individuals sequenced to a high depth of coverage (e.g., ≥10X). It has been proposed as an alternative to genotyping by Single-nucleotide polymorphisms (SNP) arrays. At least one commercial product based on it is available for agricultural species. Concerns limiting adoption in its current form are: 1) the cost of storing the huge volume of data it generates and 2) whether that additional data will result in improved accuracy of genetic evaluation. This work envisions future implementation of low-coverage sequencing to reduce storage costs and enhance genetic evaluations by leveraging the additional information in the full sequence of the pangenome to account for more genetic variation. We propose addressing the storage issue by representing genomic sequence of an individual in a pair of haplotype arrays with each element pointing to an enumerated haplotype of the sequence within one of approximately 50,000 defined genome segments. Assuming 60 million genomic variants, the infrastructure required to translate the identifier of any enumerated haplotype into its genomic sequence would require less than 10 gigabytes of binary storage. Each haplotype array element would require 2 bytes, so the marginal binary storage required to represent the genomic sequence of an individual would be about 200 kilobytes (KB), similar to the genotypes from a SNP array with 200,000 markers. This assumes no pedigree and no ambiguity of the imputation, though the latter is unrealistic. Strategies to minimize, and when necessary, to manage and efficiently represent ambiguity are proposed. The genomic sequence of an individual could be stored in about 1 KB (binary) if both parents have unambiguous sequences stored as described above. The proposed system for representing the pangenome includes algorithms for read mapping and imputation intended to leverage all known genetic variation in the target population. It is also designed to use sequencing reads generated for imputing the genomic sequence of new individuals to identify unrecognized mutations, crossovers, and structural variants, thus continuously improving the genome representation, especially if widespread use of low-coverage sequencing in livestock industries is realized. This could make improved genetic merit and management of livestock feasible without computational burden.

Animals

FINEMAP-miss: fine-mapping genome-wide association studies with missing genotype information.

MOTIVATION: The most informative genome-wide association studies (GWAS) are meta-analyses that have combined multiple studies to increase the GWAS sample size. Statistical fine-mapping is a key downstream analysis of GWAS to jointly evaluate the probability of causality of all variants in a genomic region of interest. Current fine-mapping methods are miscalibrated in the meta-analysis setting due to variation in sample size across the variants. RESULTS: We introduce FINEMAP-miss, a new fine-mapping method that extends the FINEMAP model to account for variant-specific missingness. We show that FINEMAP-miss is well-calibrated in meta-analysis simulations where the standard fine-mapping fails. Compared to the summary statistics imputation approach, FINEMAP-miss provides clear improvement when the causal variants have low imputation information or when the sample size or complexity of the meta-analysis setting increase. We successfully apply FINEMAP-miss on a breast cancer GWAS meta-analysis where neither the standard fine-mapping nor the summary statistics imputation are applicable. AVAILABILITY: An open source implementation of FINEMAP-miss as an R package ("finemapmiss") is available at https://github.com/JoonasKartau/finemapmiss. The archived version of FINEMAP-miss used for this publication can be found on Zenodo at https://doi.org/10.5281/zenodo.17492622. SUPPLEMENTARY INFORMATION: is available at the journal's web site.

Genome-Wide Association Study

Global and local ancestry estimation in a captive baboon colony.

The last couple of decades have highlighted the importance of studying hybridization, particularly among primate species, as it allows us to better understand our own evolutionary trajectory. Here, we report on genetic ancestry estimates using dense, full genome data from 881 olive (Papio anubus), yellow (Papio cynocephalus), or olive-yellow crossed captive baboons from the Southwest National Primate Research Center. We calculated global and local ancestry information, imputed low coverage genomes (n = 830) to improve marker quality, and updated the genetic resources of baboons available to assist future studies. We found evidence of historical admixture in some putatively purebred animals and identified errors within the Southwest National Primate Research Center pedigree. We also compared the outputs between two different phasing and imputation pipelines along with two different global ancestry estimation software. There was good agreement between the global ancestry estimation software, with R2 > 0.88, while evidence of phase switch errors increased depending on what phasing and imputation pipeline was used. We also generated updated genetic maps and created a concise set of ancestry informative markers (n = 1,747) to accurately obtain global ancestry estimates.

Animals

Meta-analysis of over 8,000 individuals from Hawai'i and Samoa for genetic associations to cardiometabolic phenotypes.

Although genome-wide association studies (GWAS) now routinely reveal genetic associations and biological insights in millions of individuals, underrepresentation of global populations, such as those from Polynesia, continue to persist. These exclusions, often driven by logistical challenges and lack of data, prevent systematic identification of population-enriched associations, such as the association of the missense variant at the CREBRF locus to BMI and type 2 diabetes discovered commonly occurring in Polynesian populations due to its rarity in global populations. Armed with the recently updated TOPMed imputation panel that could benefit studies in diverse populations that previously had poorer imputation performance, we performed the first GWAS of Native Hawaiians and largest to date of Polynesian-ancestry populations (combined N up to 8,461) to identify population-enriched associations for 13 adiposity and cardiometabolic traits available across both cohorts: BMI, fasting glucose, fasting insulin, HDL, height, hip circumference, HOMA-IR, LDL, T2D, total cholesterol, triglycerides, waist circumference, and waist-hip ratio. We found 25 trait-loci associations that met genome-wide significance: 20 previously reported or known associations and 5 associations newly confirmed via meta-analysis. In particular, with improved statistical power, we were able to confirm the suspected association between the missense CREBRF variant with fasting glucose levels. The remaining 4 potentially novel loci-trait associations for BMI, LDL, and waist-hip ratio, however, were not replicated in multi-ethnic datasets from All-of-Us despite having reasonable power to replicate. The lack of Polynesian-enriched findings outside of the CREBRF locus informs the bounds of the effect sizes or frequency of any enriched variants, and suggests that further expansion of cohort sizes from this region of the world and improved imputation references specific to these populations are needed to identify more population-enriched associations.

Journal Article

Genetic architecture and analysis practices of circulating metabolites in the NHLBI Trans-Omics for Precision Medicine Program.

Circulating metabolite levels partly reflect the state of human health and diseases and can be impacted by genetic determinants. Hundreds of loci associated with circulating metabolites have been identified; however, most findings focus on predominantly European ancestry or single-study analyses. Leveraging the rich metabolomics resources generated by the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) Program, we harmonized and accessibly cataloged 1,729 circulating metabolites among 25,058 ancestrally diverse samples. From our comparison of multiple methods, we provided a set of reasonable strategies for outlier and imputation handling to process metabolite data and show that inverse normalization by study and half-minimum imputation provide mostly similar results for pooled or meta-analysis. Following the practical analysis framework, we further performed a genome-wide association analysis on 1,135 selected metabolites using whole-genome sequencing data from 16,359 individuals passing the quality-control filters and discovered 1,775 independent loci associated with 667 metabolites. Among 160 unreported locus-metabolite pairs, we identified associations with loci locating within previously implicated metabolite-associated genes, as well as associations with loci locating in genes such as GAB3 and VSIG4 (located on the X chromosome) that may play a role in metabolic regulation. In the sex-stratified analysis, we revealed 85 independent locus-metabolite pairs with evidence of sexual dimorphism, which were located in well-known metabolic genes such as FADS2, D2HGDH, SUGP1, and UGT2B17, strongly supporting the importance of exploring sex difference in the human metabolome. Taken together, our study depicted the genetic contribution to circulating metabolite levels, providing additional insight into the understanding of human health.

Humans

Genetic Architecture of Idiopathic Inflammatory Myopathies From Meta-Analyses.

OBJECTIVE: Idiopathic inflammatory myopathies (IIMs, myositis) are rare systemic autoimmune disorders that lead to muscle inflammation, weakness, and extramuscular manifestations, with a strong genetic component influencing disease development and progression. Previous genome-wide association studies identified loci associated with IIMs. In this study, we imputed data from two prior genome-wide myositis studies and analyzed the largest myositis data set to date to identify novel risk loci and susceptibility genes associated with IIMs and its clinical subtypes. METHODS: We performed association analyses on 14,903 individuals (3,206 patients and 11,697 controls) with genotypes and imputed data from the Trans-Omics for Precision Medicine reference panel. Fine-mapping and expression quantitative trait locus colocalization analyses in myositis-relevant tissues indicated potential causal variants. Functional annotation and network analyses using the random walk with restart (RWR) algorithm explored underlying genetic networks and drug repurposing opportunities. RESULTS: Our analyses identified novel risk loci and susceptibility genes, such as FCRLA, NFKB1, IRF4, DCAKD, and ATXN2 in overall IIMs; NEMP2 in polymyositis; ACBC11 in dermatomyositis; and PSD3 in myositis with anti-histidyl-transfer RNA synthetase autoantibodies (anti-Jo-1). We also characterized effects of HLA region variants and the role of C4. Colocalization analyses suggested putative causal variants in DCAKD in skin and muscle, HCP5 in lung, and IRF4 in Epstein-Barr virus (EBV)-transformed lymphocytes, lung, and whole blood. RWR further prioritized additional candidate genes, including APP, CD74, CIITA, NR1H4, and TXNIP, for future investigation. CONCLUSION: Our study uncovers novel genetic regions contributing to IIMs, advancing our understanding of myositis pathogenesis and offering new insights for future research.

Humans

The projection of ocellar neurons within the brain of the locust, Schistocerca gregaria.

Cobalt iontophoresis of the median and lateral ocellar nerves of Schistocerca gregaria, combined with silver impregnated sections of the brain, has demonstrated the projection area of the large and medium-sized ocellar afferent neurons. These neurons terminate within the brain and their cell bodies lie within the protocerebrum. Ocellar neurons project to two discrete areas on each side of the brain, each area receiving input from a different set of fibres. Both postero-dorsal complexes receive an imput from two large ipsilateral and two large median fibres. Their dendritic fields maintain an ordered spatial array relative to one another. The two antero-lateral complexes receive an imput from one large ipsilateral fibre and medium-sized ipsilateral and medium small-field afferent fibres. Each lateral ocellus has two large fibres in common with the median ocellus. These lateromedial fibres receive photoreceptor input from both ocelli but form no major arborisations within the brain. The lateral ocellar tracts appear to form a third ocellar association area since higher-order neurons branch amongst the lateral and latero-medial fibres within the tract. The axons of the higher-order neurons descend to the ventral cord via the circumoesophageal commissures.

Animals

Prognostic modeling of overall survival in metastatic pancreatic cancer: an inflammation-based tool validated in PANTHEIA-SEOM cohort.

PURPOSE: To develop and internally validate the PANTHEIA-SIRI prognostic model, which integrates log-transformed systemic inflammation response index (SIRI) with clinical predictors, to estimate overall survival (OS) in metastatic pancreatic ductal adenocarcinoma (mPDAC) treated with first-line chemotherapy. METHODS: We used data from the multicenter PANTHEIA-SEOM registry. OS was defined from chemotherapy start. The model was fitted as a Weibull accelerated failure time model in the survival-analysis population with multiple imputation. Predictors were log-transformed baseline SIRI, modeled with restricted cubic splines, ECOG, tumor burden, chemotherapy regimen, and anorexia-cachexia syndrome. Internal validation used a separate, non-overlapping cohort from the same registry; the centers contributing to each cohort are listed in a supplementary annex. TRIPOD was followed. Discrimination was assessed with Harrell´s C-index and calibration with IPCW Brier scores and IPA. RESULTS: The derivation cohort comprised 672 patients with SIRI data (593 analyzed for survival) across 22 Spanish hospitals (2015-2025); 80.1% had died after a median OS of 9.9 months. The imputation-pooled derivation C-index was 0.654 (95% CI, 0.627-0.681); optimism-corrected, 0.629. Internal validation used 62 separate patients from the same registry; 96.8% had died after a median OS of 9.2 months. The validation C-index was 0.603 (95% CI, 0.518-0.687). Calibration was adequate at 6 and 12 months. CONCLUSIONS: The PANTHEIA-SIRI model provides individualized OS estimates in mPDAC with routine clinical predictors. Its open-access calculator ( https://pantheia-siri.shinyapps.io/calc/ ) may support prognostic communication, treatment-intensity selection, and supportive-care planning. Routine clinical implementation will require further validation in larger, fully independent cohorts.

Cachexia

Efficacy and safety of deucravacitinib, an oral, selective tyrosine kinase 2 inhibitor, in patients with active psoriatic arthritis: 52-week results from the randomised, double-blind, placebo-controlled phase 3 POETYK PsA-1 trial.

OBJECTIVES: The randomised, double-blind, placebo-controlled, phase 3 Program fOr Evaluation of TYK2 inhibitor Psoriatic Arthritis-1 (POETYK PsA-1) trial evaluated the efficacy, safety, and tolerability of deucravacitinib, an oral, selective tyrosine kinase 2 inhibitor, in patients with PsA na&#xef;ve to biologic disease-modifying antirheumatic drugs. METHODS: Adults with active PsA, high-sensitivity C-reactive protein concentration &#x2265; 3 mg/L, and &#x2265; 1 PsA-related hand and/or foot erosion detectable via radiograph were randomised 1:1 to oral deucravacitinib 6 mg once daily or placebo through week (W) 16. At W16, patients continued receiving deucravacitinib or switched from placebo to deucravacitinib through W52. The primary endpoint was American College of Rheumatology 20% improvement in response (ACR20) at W16. Nonresponder imputation was used for missing data. Efficacy and safety were evaluated through W52. Post hoc rank analysis of covariance was used to evaluate structural damage with no missing data imputation. RESULTS: In 670 patients, a significantly greater proportion of those receiving deucravacitinib vs placebo achieved ACR20 at W16 (54.2% vs 34.1%, P < .001). Responses with deucravacitinib were increased at W52. Patients who switched from placebo to deucravacitinib achieved improvements similar to those in patients who received continuous deucravacitinib. Inhibition of structural damage was observed at W16 and W52. At W16, incidences of serious adverse events (AEs) (deucravacitinib, 1.8%; placebo, 2.4%) and discontinuations due to AEs (2.4%; 1.8%) were low and remained low through W52, without imbalances in cardiovascular events, malignancies, or opportunistic infections. No new safety signals were detected; no deaths occurred. CONCLUSIONS: Deucravacitinib demonstrated superiority vs placebo for clinical responses, patient-reported outcomes, and structural damage inhibition in patients with PsA, with favourable tolerability and safety.

Humans

A novel reusable transcriptome-wide association study workflow used to map key genes linked to important cattle traits.

Transcriptome-wide association studies (TWAS) are a powerful approach for studying the genes underlying complex traits by directly integrating GWAS and gene expression datasets. In cattle, they have been previously applied to identify genes driving fertility, milk production, and health. However, these studies have also highlighted several challenges, from difficulties in reproducing these complex analyses to limitations from poor genotype calls, especially when called directly from RNA sequencing data. To address these and other challenges, for the H2020 BovReg Project, we have developed a streamlined, species-agnostic, and reusable Nextflow TWAS workflow to integrate transcriptomic and GWAS summary statistic datasets. Our workflow first generates accurate genotype calls and gene expression prediction models from transcriptomic datasets and then applies these tools to impute gene expression levels into GWAS cohorts, enabling the association of genes with traits of interest. We explore optimal strategies for calling genetic variants directly from transcriptomic data and illustrate that using imputation approaches specifically designed for low-pass sequencing data can improve variant calling over previously adopted methods. We demonstrate the utility of our TWAS workflow by applying it to both novel and publicly available GWAS cohorts for cattle, detecting novel gene-trait associations for complex traits. Using a new transcriptome annotation of the cattle genome generated for the BovReg project we also illustrate how previously un-assayable associations can be detected. The results and the workflow we present, provide a new resource for the community and contribute to a better understanding of the molecular drivers of complex traits in cattle with the goal of eventually leveraging this information in future breeding decisions.

Animals

Efficacy and safety of once-weekly semaglutide 2&#xb7;4 mg in Chinese adults with overweight or obesity (STEP 12): a randomised, double-blind, placebo-controlled, multicentre, phase 3b trial.

BACKGROUND: Semaglutide 2&#xb7;4 mg is a GLP-1 receptor agonist that reduces bodyweight, and provides other cardiometabolic benefits, among people with a BMI at least 30 kg/m2 or at least 27 kg/m2 and with weight-related comorbidities. This trial aimed to evaluate the efficacy, tolerability, and safety of semaglutide 2&#xb7;4 mg in adults from mainland China and Taiwan with overweight or obesity according to locally defined, BMI thresholds. METHODS: This completed randomised, double-blind, placebo-controlled, multicentre, two-armed, parallel-group, phase 3b trial (STEP 12) was conducted at 19 sites across mainland China and Taiwan. Adults with a BMI of 24-<28 kg/m2 and at least one weight-related comorbidity, or a BMI of 28-<30 kg/m2, with or without type 2 diabetes, were randomly assigned (2:1) to once-weekly subcutaneous semaglutide 2&#xb7;4 mg or placebo, plus lifestyle intervention, for 44 weeks. Randomisation was performed by the study sponsor using the Randomisation Trial Supplies Management System. Coprimary endpoints were percentage change in bodyweight and the proportion of participants achieving at least 5% bodyweight reduction. Safety was analysed descriptively in all participants who received the trial intervention. Missing data at week 44 were imputed with washout multiple imputation. This study is registered with ClinicalTrials.gov, NCT06041217, and is completed. FINDINGS: Between Sept 15, 2023, and May 7, 2025, of 254 screened participants, 161 (66&#xb7;5%) of 242 participants were randomly assigned to semaglutide 2&#xb7;4 mg and 81 (33&#xb7;5%) to placebo; 121 (50&#xb7;0%) participants were female, and 47 (19&#xb7;4%) participants had type 2 diabetes. Bodyweight reduction was greater with semaglutide versus placebo (-12&#xb7;1% [SE 0&#xb7;6] vs -2&#xb7;2% [0&#xb7;8]; estimated treatment difference -9&#xb7;9 percentage points [95% CI -11&#xb7;8 to -8&#xb7;0]; p<0&#xb7;0001), with a greater proportion of participants achieving at least 5% bodyweight reduction (80&#xb7;5% vs 24&#xb7;4%; odds ratio [OR] 14&#xb7;8 [95% CI 7&#xb7;4 to 29&#xb7;6]; p<0&#xb7;0001). Adverse events were reported in 141 (87&#xb7;6%) of 161 participants in the semaglutide 2&#xb7;4 mg group and 61 (75&#xb7;3%) of 81 participants in the placebo group, with gastrointestinal disorders being the most common. INTERPRETATION: Semaglutide 2&#xb7;4 mg provided a superior reduction in bodyweight versus placebo in Chinese adults with overweight or obesity. The safety profile was consistent with the known profile of semaglutide. FUNDING: Novo Nordisk A/S. TRANSLATION: For the Mandarin translation of the abstract see Supplementary Materials section.

Adult

Effect of vestibular deafferentation upon positional nystagmus in the squirrel monkey.

Seventeen of eighteen squirrel monkeys, under a restrained condition, showed positional nystagmus in different body positions. Good repeatability and consistency of the nystagmus were found, especially at the left-lateral, right-lateral, and head-hanging positions. Positional nystagmus was not observed after the subject underwent bilateral labyrinthectomy. However, one subject in which part of the crista ampullaris posterior remained, continuously showed a positional nystagmus. Therefore, the existence of a minimal vestibular imput from the crista ampullaris could provoke the nystagmus. Some changes occurred in positional nystagmus after bilateral macular ablation; however, the nystagmus did not completely disappear. Even though imput from the crista ampullaris is essential to provoke positional nystagmus in squirrel monkeys, the positional nystagmus probably results from a central dyscoordination between vestibulo-oculomotor function, spino-oculomotor function, vestibular and brain circulation, and psychological condition.

Animals

Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes.

Type 2 diabetes (T2D) genome-wide association studies (GWASs) often overlook rare variants as a result of previous imputation panels' limitations and scarce whole-genome sequencing (WGS) data. We used TOPMed imputation and WGS to conduct the largest T2D GWAS meta-analysis involving 51,256 cases of T2D and 370,487 controls, targeting variants with a minor allele frequency as low as 5&#x2009;&#xd7;&#x2009;10-5. We identified 12 new variants, including a rare African/African American-enriched enhancer variant near the LEP gene (rs147287548), associated with fourfold increased T2D risk. We also identified a rare missense variant in HNF4A (p.Arg114Trp), associated with eightfold increased T2D risk, previously reported in maturity-onset diabetes of the young with reduced penetrance, but observed here in a T2D GWAS. We further leveraged these data to analyze 1,634 ClinVar variants in 22 genes related to monogenic diabetes, identifying two additional rare variants in HNF1A and GCK associated with fivefold and eightfold increased T2D risk, respectively, the effects of which were modified by the individual's polygenic risk score. For 21% of the variants with conflicting interpretations or uncertain significance in ClinVar, we provided support of being benign based on their lack of association with T2D. Our work provides a framework for using rare variant GWASs to identify large-effect variants and assess variant pathogenicity in monogenic diabetes genes.

Diabetes Mellitus, Type 2

OmicsPred as a centralised resource for genetic prediction of multi-omic traits.

Genetic prediction of multi-omic data has emerged as a cost-effective alternative to direct omics profiling, particularly useful for identifying molecular features associated with disease susceptibility. However, despite its popularity, multi-omic imputation models are fragmented across studies, hindering findability, accessibility, interoperability and re-use. To address this, we developed OmicsPred (https://www.omicspred.org), a centralised platform for the deposition and dissemination of genetic prediction models of multi-omic traits. OmicsPred unifies the most commonly used molecular imputation models (e.g. from PredictDB) and other published studies totalling 3,339,469 prediction models spanning transcriptomic, proteomic, and metabolomic traits (as of May 2026). Each model is accompanied by metadata describing score development and predictive performance, and distributed in formats compatible with popular analytic tools, such as PGS Catalog Calculator and MetaXcan. To demonstrate the utility of the resource for systematic target discovery, we perform a multi-omic phenome-wide association analysis in Million Veterans Program data.

Journal Article