Building a vertically integrated genomic learning health system: The biobank at the Colorado Center for Personalized Medicine.

Precision medicine initiatives across the globe have led to a revolution of repositories linking large-scale genomic data with electronic health records, enabling genomic analyses across the entire phenome. Many of these initiatives focus solely on research insights, leading to limited direct benefit to patients. We describe the biobank at the Colorado Center for Personalized Medicine (CCPM Biobank) that was jointly developed by the University of Colorado Anschutz Medical Campus and UCHealth to serve as a unique, dual-purpose research and clinical resource accelerating personalized medicine. This living resource currently has more than 200,000 participants with ongoing recruitment. We highlight the clinical, laboratory, regulatory, and HIPAA-compliant informatics infrastructure along with our stakeholder engagement, consent, recontact, and participant engagement strategies. We characterize aspects of genetic and geographic diversity unique to the Rocky Mountain region, the primary catchment area for CCPM Biobank participants. We leverage linked health and demographic information of the CCPM Biobank participant population to demonstrate the utility of the CCPM Biobank to replicate complex trait associations in the first 33,674 genotyped individuals across multiple disease domains. Finally, we describe our current efforts toward return of clinical genetic test results, including high-impact pathogenic variants and pharmacogenetic information, and our broader goals as the CCPM Biobank continues to grow. Bringing clinical and research interests together fosters unique clinical and translational questions that can be addressed from the large EHR-linked CCPM Biobank resource within a HIPAA- and CLIA-certified environment.

Session Introduction: Overcoming health disparities in precision medicine.

The following sections are included:OverviewDealing with the lack of diversity in current research datasetsDevelopment of fair machine learning algorithmsRace, genetic ancestry, and population structureConclusionAcknowledgments.

Xanthine oxidoreductase gene polymorphisms are associated with high risk of sepsis and organ failure.

BACKGROUND: Sepsis and associated organ failures confer substantial morbidity and mortality. Xanthine oxidoreductase (XOR) is implicated in the development of tissue oxidative damage in a wide variety of respiratory and cardiovascular disorders including sepsis and sepsis-associated acute respiratory distress syndrome (ARDS). We examined whether single nucleotide polymorphisms (SNPs) in the XDH gene (encoding XOR) might influence susceptibility to and outcome in patients with sepsis. METHODS: We genotyped 28 tag SNPs in XDH gene in the CELEG cohort, including 621 European American (EA) and 353 African American (AA) sepsis patients. Serum XOR activity was measured in a subset of CELEG subjects. Additionally, we assessed the functional effects of XDH variants utilizing empirical data from different integrated software tools and datasets. RESULTS: Among AA patients, six intronic variants (rs206805, rs513311, rs185925, rs561525, rs2163059, rs13387204), in a region enriched with regulatory elements, were associated with risk of sepsis (P < 0.008-0.049). Two out of six SNPs (rs561525 and rs2163059) were associated with risk of sepsis-associated ARDS in an independent validation cohort (GEN-SEP) of 590 sepsis patients of European descent. Two common SNPs (rs1884725 and rs4952085) in tight linkage disequilibrium (LD) provided strong evidence for association with increased levels of serum creatinine (Padjusted<0.0005 and 0.0006, respectively), suggesting a role in increased risk of renal dysfunction. In contrast, among EA ARDS patients, the missense variant rs17011368 (I703V) was associated with enhanced mortality at 60-days (P < 0.038). We found higher serum XOR activity in 143 sepsis patients (54.5 ± 57.1 mU/mL) compared to 31 controls (20.9 ± 12.4 mU/mL, P = 1.96 × 10- 13). XOR activity was associated with the lead variant rs185925 among AA sepsis patients with ARDS (P < 0.005 and Padjusted<0.01). Multifaceted functions of prioritized XDH variants, as suggested by various functional annotation tools, support their potential causality in sepsis. CONCLUSIONS: Our findings suggest that XOR is a novel combined genetic and biochemical marker for risk and outcome in patients with sepsis and ARDS.

The genetic determinants of recurrent somatic mutations in 43,693 blood genomes.

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.

Phenotypic and Endotypic Determinants of Atopic Dermatitis Severity From the Atopic Dermatitis Research Network (ADRN) Registry.

BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin condition with a highly variable clinical phenotype. OBJECTIVE: This study aimed to identify historical and clinical features and biomarkers associated with AD severity. METHODS: A US registry of extensively phenotyped AD participants (aged 0.73-80 years) were enrolled at 9 academic centers. Information on family and personal medical history, examination, skin swabs (culture), and serum biomarkers was collected to evaluate their association with AD severity. RESULTS: Participants with AD (N = 2862) whose disease was categorized as mild (11.6%), moderate (58.0%), or severe (30.4%) based on Rajka-Langeland scoring were enrolled. The trend test, when adjusting for gender, race, and age, demonstrated that severity was strongly (P ≤ .04) associated with a personal/family history of allergic disorders, history of alopecia, exposure to passive smoke, ocular herpes infection, skin bacterial and viral infections, and history of arrhythmia. Features observed more frequently (P ≤ .002), as a function of severity, included skin infections (impetigo, human papillomavirus, and molluscum contagiosum virus), Staphylococcus aureus colonization, excoriations, hyperlinear palms, ichthyosis, blepharitis, conjunctivitis, ectropion, and wheezing. Serum IgE, allergen and food (≤6 years) Phadiatop, and eosinophilia were strongly linked to severity (P < .001). CONCLUSIONS: In a diverse US AD population, severity was associated with a history of atopic disorders, skin and extracutaneous bacterial and viral infections (by history and physical examination), higher IgE, eosinophilia and allergen sensitization, atopic skin manifestations (ie, excoriation, hyperlinear palms, and ichthyosis), and atopic ocular features (ie, blepharitis, conjunctivitis, and ectropion) as well as asthma findings (ie, wheezing). Data from our prospective registry significantly advance our understanding of AD phenotypes and endotypes, which is critical to achieve optimal management.

Aberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis.

Mutations in a diverse set of driver genes increase the fitness of haematopoietic stem cells (HSCs), leading to clonal haematopoiesis1. These lesions are precursors for blood cancers2-6, but the basis of their fitness advantage remains largely unknown, partly owing to a paucity of large cohorts in which the clonal expansion rate has been assessed by longitudinal sampling. Here, to circumvent this limitation, we developed a method to infer the expansion rate from data from a single time point. We applied this method to 5,071 people with clonal haematopoiesis. A genome-wide association study revealed that a common inherited polymorphism in the TCL1A promoter was associated with a slower expansion rate in clonal haematopoiesis overall, but the effect varied by driver gene. Those carrying this protective allele exhibited markedly reduced growth rates or prevalence of clones with driver mutations in TET2, ASXL1, SF3B1 and SRSF2, but this effect was not seen in clones with driver mutations in DNMT3A. TCL1A was not expressed in normal or DNMT3A-mutated HSCs, but the introduction of mutations in TET2 or ASXL1 led to the expression of TCL1A protein and the expansion of HSCs in vitro. The protective allele restricted TCL1A expression and expansion of mutant HSCs, as did experimental knockdown of TCL1A expression. Forced expression of TCL1A promoted the expansion of human HSCs in vitro and mouse HSCs in vivo. Our results indicate that the fitness advantage of several commonly mutated driver genes in clonal haematopoiesis may be mediated by TCL1A activation.

A functional genomics pipeline to identify high-value asthma and allergy CpGs in the human methylome.

BACKGROUND: DNA methylation of cytosines at cytosine-phosphate-guanine (CpG) dinucleotides (CpGs) is a widespread epigenetic mark, but genome-wide variation has been relatively unexplored due to the limited representation of variable CpGs on commercial high-throughput arrays. OBJECTIVES: To explore this hidden portion of the epigenome, this study combined whole-genome bisulfite sequencing with in silico evidence of gene regulatory regions to design a custom array of high-value CpGs. This study focused on airway epithelial cells from children with and without allergic asthma because these cells mediate the effects of inhaled microbes, pollution, and allergens on asthma and allergic disease risk. METHODS: This study identified differentially methylated regions from whole-genome bisulfite sequencing in nasal epithelial cell DNA from a total of 39 children with and without allergic asthma of both European and African ancestries. This study selected CpGs from differentially methylated regions, previous allergy or asthma epigenome-wide association studies (EWAS), or genome-wide association study loci, and overlapped them with functional annotations for inclusion on a custom Asthma&Allergy array. This study used both the custom and EPIC arrays to perform EWAS of allergic sensitization (AS) in nasal epithelial cell DNA from children in the URECA (Urban Environment and Childhood Asthma) birth cohort and using the custom array in the INSPIRE [Infant Susceptibility to Pulmonary Infections and Asthma Following RSV Exposure] birth cohort. Each CpG on the arrays was assigned to its nearest gene and its promotor capture Hi-C interacting gene and performed expression quantitative trait methylation (eQTM) studies for both sets of genes. RESULTS: Custom array CpGs were enriched for intermediate methylation levels compared to EPIC CpGs. Intermediate methylation CpGs were further enriched among those associated with AS and for eQTMs on both arrays. CONCLUSIONS: This study revealed signature features of high-value CpGs and evidence for epigenetic regulation of genes at AS EWAS loci that are robust to race/ethnicity, ascertainment, age, and geography.

The IL-4Rα Q576R polymorphism is associated with increased severity of atopic dermatitis and exaggerates allergic skin inflammation in mice.

BACKGROUND: Atopic dermatitis (AD) is characterized by TH2-dominated skin inflammation and systemic response to cutaneously encountered antigens. The TH2 cytokines IL-4 and IL-13 play a critical role in the pathogenesis of AD. The Q576->R576 polymorphism in the IL-4 receptor alpha (IL-4Rα) chain common to IL-4 and IL-13 receptors alters IL-4 signaling and is associated with asthma severity. OBJECTIVE: We sought to investigate whether the IL-4Rα R576 polymorphism is associated with AD severity and exaggerates allergic skin inflammation in mice. METHODS: Nighttime itching interfering with sleep, Rajka-Langeland, and Eczema Area and Severity Index scores were used to assess AD severity. Allergic skin inflammation following epicutaneous sensitization of mice 1 or 2 IL-4Rα R576 alleles (QR and RR) and IL-4Rα Q576 (QQ) controls was assessed by flow cytometric analysis of cells and quantitative RT-PCR analysis of cytokines in skin. RESULTS: The frequency of nighttime itching in 190 asthmatic inner-city children with AD, as well as Rajka-Langeland and Eczema Area and Severity Index scores in 1116 White patients with AD enrolled in the Atopic Dermatitis Research Network, was higher in subjects with the IL-4Rα R576 polymorphism compared with those without, with statistical significance for the Rajka-Langeland score. Following epicutaneous sensitization of mice with ovalbumin or house dust mite, skin infiltration by CD4+ cells and eosinophils, cutaneous expression of Il4 and Il13, transepidermal water loss, antigen-specific IgE antibody levels, and IL-13 secretion by antigen-stimulated splenocytes were significantly higher in RR and QR mice compared with QQ controls. Bone marrow radiation chimeras demonstrated that both hematopoietic cells and stromal cells contribute to the mutants' exaggerated allergic skin inflammation. CONCLUSIONS: The IL-4Rα R576 polymorphism predisposes to more severe AD and increases allergic skin inflammation in mice.

Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing.

Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.

Session Introduction: Overcoming health disparities in precision medicine.

The following sections are included: Overview, Equitable risk prediction, Pharmacoequity, Race, genetic ancestry, and population structure, Conclusion, Acknowledgments, References.

Genetic diversity fuels gene discovery for tobacco and alcohol use.

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

African-specific alleles modify risk for asthma at the 17q12-q21 locus in African Americans.

BACKGROUND: Asthma is the most common chronic disease in children, occurring at higher frequencies and with more severe disease in children with African ancestry. METHODS: We tested for association with haplotypes at the most replicated and significant childhood-onset asthma locus at 17q12-q21 and asthma in European American and African American children. Following this, we used whole-genome sequencing data from 1060 African American and 100 European American individuals to identify novel variants on a high-risk African American-specific haplotype. We characterized these variants in silico using gene expression and ATAC-seq data from airway epithelial cells, functional annotations from ENCODE, and promoter capture (pc)Hi-C maps in airway epithelial cells. Candidate causal variants were then assessed for correlation with asthma-associated phenotypes in African American children and adults. RESULTS: Our studies revealed nine novel African-specific common variants, enriched on a high-risk asthma haplotype, which regulated the expression of GSDMA in airway epithelial cells and were associated with features of severe asthma. Using ENCODE annotations, ATAC-seq, and pcHi-C, we narrowed the associations to two candidate causal variants that are associated with features of T2 low severe asthma. CONCLUSIONS: Previously unknown genetic variation at the 17q12-21 childhood-onset asthma locus contributes to asthma severity in individuals with African ancestries. We suggest that many other population-specific variants that have not been discovered in GWAS contribute to the genetic risk for asthma and other common diseases.

Rare genetic variants explain missing heritability in smoking.

Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.

Epigenetics may characterize asymptomatic COVID-19 infection.

RT-PCR is the foremost clinical test for diagnosis of COVID-19. Unfortunately, PCR-based testing has limitations and may not result in a positive test early in the course of infection before symptoms develop. Enveloped RNA viruses, such as coronaviruses, alter peripheral blood methylation and DNA methylation signatures may characterize asymptomatic versus symptomatic infection. We used Illumina's Infinium MethylationEPIC BeadChip array to profile peripheral blood samples from 164 patients who tested positive for SARS-CoV-2 by RT-PCR, of whom 8 had no symptoms. Epigenome-wide association analysis identified 10 methylation sites associated with infection and a quantile-quantile plot showed little inflation. These preliminary results suggest that differences in methylation patterns may distinguish asymptomatic from symptomatic infection.

COVID-19 Surveillance in the Biobank at the Colorado Center for Personalized Medicine: Observational Study.

BACKGROUND: Characterizing the experience and impact of the COVID-19 pandemic among various populations remains challenging due to the limitations inherent in common data sources, such as electronic health records (EHRs) or cross-sectional surveys. OBJECTIVE: This study aims to describe testing behaviors, symptoms, impact, vaccination status, and case ascertainment during the COVID-19 pandemic using integrated data sources. METHODS: In summer 2020 and 2021, we surveyed participants enrolled in the Biobank at the Colorado Center for Personalized Medicine (CCPM; N=180,599) about their experience with COVID-19. The prevalence of testing, symptoms, and impacts of COVID-19 on employment, family life, and physical and mental health were calculated overall and by demographic categories. Survey respondents who reported receiving a positive COVID-19 test result were considered a "confirmed case" of COVID-19. Using EHRs, we compared COVID-19 case ascertainment and characteristics in EHRs versus the survey. Positive cases were identified in EHRs using the International Statistical Classification of Diseases, 10th revision (ICD-10) diagnosis codes, health care encounter types, and encounter primary diagnoses. RESULTS: Of the 25,063 (13.9%) survey respondents, 10,661 (42.5%) had been tested for COVID-19, and of those, 1366 (12.8%) tested positive. Nearly half of those tested had symptoms or had been exposed to someone who was infected. Young adults (18-29 years) and Hispanics were more likely to have positive tests compared to older adults and persons of other racial/ethnic groups. Mental health (n=13,688, 54.6%) and family life (n=12,233, 48.8%) were most negatively affected by the pandemic and more so among younger groups and women; negative impacts on employment were more commonly reported among Black respondents. Of the 10,249 individuals who responded to vaccination questions from version 2 of the survey (summer 2021), 9770 (95.3%) had received the vaccine. After integration with EHR data up to the time of the survey completion, 1006 (4%) of the survey respondents had a discordant COVID-19 case status between EHRs and the survey. Using all longitudinal EHR and survey data, we identified 11,472 (6.4%) COVID-19-positive cases among Biobank participants. In comparison to COVID-19 cases identified through the survey, EHR-identified cases were younger and more likely to be Hispanic. CONCLUSIONS: We found that the COVID-19 pandemic has had far-reaching and varying effects among our Biobank participants. Integrated data assets, such as the Biobank at the CCPM, are key resources for population health monitoring in response to public health emergencies, such as the COVID-19 pandemic.

Lipid mediators are detectable in the nasal epithelium and differ by asthma status in female subjects.

BACKGROUND: Lipid mediators, bioactive products of polyunsaturated fatty acid metabolism, contribute to inflammation initiation and resolution in allergic diseases; however, their presence in lung-related biosamples has not been fully described. OBJECTIVE: We aimed to quantify lipid mediators in the nasal airway epithelium and characterize preliminary associations with asthma. METHODS: Using liquid chromatography-mass spectrometry, we conducted a pilot study to quantify 56 lipid mediators from nasal epithelial samples collected from 11 female participants of an outpatient asthma clinic and community controls (aged 30-55 years). We examined the presence of each compound using descriptive statistics to test whether lipid mediators could distinguish subjects with asthma (n = 8) from control subjects (n = 3) using linear regression and partial least squares discriminant analysis. RESULTS: Fifteen lipid mediators were detectable in all samples, including resolvin (Rv) D5 (RvD5), with the highest median concentrations (in pg/µg protein) of 13-HODE (126.481), 15-HETE (32.869), and 13-OxoODE (13.251). From linear regression adjusted for age, prostaglandin E2 (PGE2) had a trend (P < .1) for higher concentrations in patients with severe asthma compared to controls (mean difference, 0.95; 95% confidence interval, -0.04 to 1.95). Asthma patients had higher scores on principal component 3 compared to controls (mean difference, 2.42; 95% confidence interval, 0.89 to 3.96), which represented lower levels of proresolving 15-HEPE, 19,20-DiHDPA, RvD5, 14-HDHA, 17-HDHA, and 13-HOTrE. Most of these compounds were best at discriminating asthma cases from controls in partial least squares discriminant analysis. CONCLUSION: Lipid mediators are detectable in the nasal epithelium, and their levels distinguish asthma cases from controls.

HLA alleles and sustained peanut consumption promote IgG4 responses in subjects protected from peanut allergy.

We investigated the interplay between genetics and oral peanut protein exposure in the determination of the immunological response to peanut using the targeted intervention in the LEAP clinical trial. We identified an association between peanut-specific IgG4 and HLA-DQA1*01:02 that was only observed in the presence of sustained oral peanut protein exposure. The association between IgG4 and HLA-DQA1*01:02 was driven by IgG4 specific for the Ara h 2 component. Once peanut consumption ceased, the association between IgG4-specific Ara h 2 and HLA-DQA1*01:02 was attenuated. The association was validated by observing expanded IgG4-specific epitopes in people who carried HLA-DQA1*01:02. Notably, we confirmed the previously reported associations with HLA-DQA1*01:02 and peanut allergy risk in the absence of oral peanut protein exposure. Interaction between HLA and presence or absence of exposure to peanut in an allergen- and epitope-specific manner implicates a mechanism of antigen recognition that is fundamental to driving immune responses related to allergy risk or protection.

Discovering metabolite quantitative trait loci in asthma using an isolated population.

BACKGROUND: Integration of metabolomics with genetics may advance understanding of disease pathogenesis but has been underused in asthma genetic studies. OBJECTIVE: We sought to discover new genetic effects in asthma and to characterize the molecular consequences of asthma genetic risk through integration with the metabolome in a homogeneous population. METHODS: From fasting serum samples collected on 348 Tangier Island residents, we quantified 2612 compounds using untargeted metabolomics. Genotyping was performed using Illumina's MEGA array imputed to the TOPMed reference panel. To prioritize metabolites for genome-wide association analysis, we performed a metabolome-wide association study with asthma, selecting asthma-associated metabolites with heritability q value less than 0.01 for genome-wide association analysis. We also tested the association between all metabolites and 8451 candidate asthma single nucleotide polymorphisms previously associated with asthma in the UK Biobank. We followed up significant associations by characterizing shared genetic signal for metabolites and asthma using colocalization analysis. For detailed Methods, please see this article's Online Repository at www.jacionline.org. RESULTS: A total of 60 metabolites were associated with asthma (P < .01), including 40 heritable metabolites tested in genome-wide association analysis. We observed a strong association peak for the endocannabinoid linoleoyl ethanolamide on chromosome 6 in VNN1 (P < 2.7 × 10-9). We found strong evidence (colocalization posterior probability >75%) for a shared causal variant between 3 metabolites and asthma, including the polyamine acisoga and variants in LPP, and derivative leukotriene B4 and intergenic variants in chr10p14. CONCLUSIONS: We identified novel metabolite quantitative trait loci with asthma associations. Identification and characterization of these genetically driven metabolites may provide insight into the functional consequences of genetic risk factors for asthma.

Polygenic prediction of atopic dermatitis improves with atopic training and filaggrin factors.

BACKGROUND: While numerous genetic loci associated with atopic dermatitis (AD) have been discovered, to date, work leveraging the combined burden of AD risk variants across the genome to predict disease risk has been limited. OBJECTIVES: This study aims to determine whether polygenic risk scores (PRSs) relying on genetic determinants for AD provide useful predictions for disease occurrence and severity. It also explicitly tests the value of including genome-wide association studies of related allergic phenotypes and known FLG loss-of-function (LOF) variants. METHODS: AD PRSs were constructed for 1619 European American individuals from the Atopic Dermatitis Research Network using an AD training dataset and an atopic training dataset including AD, childhood onset asthma, and general allergy. Additionally, whole genome sequencing data were used to explore genetic scoring specific to FLG LOF mutations. RESULTS: Genetic scores derived from the AD-only genome-wide association studies were predictive of AD cases (PRSAD: odds ratio [OR], 1.70; 95% CI, 1.49-1.93). Accuracy was first improved when PRSs were built off the larger atopy genome-wide association studies (PRSAD+: OR, 2.16; 95% CI, 1.89-2.47) and further improved when including FLG LOF mutations (PRSAD++: OR, 3.23; 95% CI, 2.57-4.07). Importantly, while all 3 PRSs correlated with AD severity, the best prediction was from PRSAD++, which distinguished individuals with severe AD from control subjects with OR of 3.86 (95% CI, 2.77-5.36). CONCLUSIONS: This study demonstrates how PRSs for AD that include genetic determinants across atopic phenotypes and FLG LOF variants may be a promising tool for identifying individuals at high risk for developing disease and specifically severe disease.

Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program.

Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.