Clinical associations with a polygenic predisposition to benign lower white blood cell counts

Polygenic variation unrelated to disease contributes to interindividual variation in baseline white blood cell (WBC) counts, but its clinical significance is uncharacterized. We investigated the clinical consequences of a genetic predisposition toward lower WBC counts among 89,559 biobank participants from tertiary care centers using a polygenic score for WBC count (PGSWBC) comprising single nucleotide polymorphisms not associated with disease. A predisposition to lower WBC counts was associated with a decreased risk of identifying pathology on a bone marrow biopsy performed for a low WBC count (odds-ratio = 0.55 per standard deviation increase in PGSWBC [95%CI, 0.30-0.94], p = 0.04), an increased risk of leukopenia (a low WBC count) when treated with a chemotherapeutic (n = 1724, hazard ratio [HR] = 0.78 [0.69-0.88], p = 4.0 × 10-5) or immunosuppressant (n = 354, HR = 0.61 [0.38-0.99], p = 0.04). A predisposition to benign lower WBC counts was associated with an increased risk of discontinuing azathioprine treatment (n = 1,466, HR = 0.62 [0.44-0.87], p = 0.006). Collectively, these findings suggest that there are genetically predisposed individuals who are susceptible to escalations or alterations in clinical care that may be harmful or of little benefit.

Risk factors affecting polygenic score performance across diverse cohorts

Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed effects of covariate stratification and interaction on body mass index (BMI) PGS (PGS BMI ) across four cohorts of European (N=491,111) and African (N=21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R 2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R 2 being nearly double between best and worst performing quintiles for certain covariates. 28 covariates had significant PGS BMI -covariate interaction effects, modifying PGS BMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R 2 differences among strata and interaction effects - across all covariates, their main effects on BMI were correlated with their maximum R 2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGS BMI individuals have highest R 2 and increase in PGS effect. Using quantile regression, we show the effect of PGS BMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R 2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGS BMI performance and effects, we investigated ways to increase model performance taking into account non-linear effects. Machine learning models (neural networks) increased relative model R 2 (mean 23%) across datasets. Finally, creating PGS BMI directly from GxAge GWAS effects increased relative R 2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGS BMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.

Comparing ancestry calibration approaches for a trans-ancestry colorectal cancer polygenic risk score

Background

Colorectal cancer (CRC) is a complex disease with monogenic, polygenic and environmental risk factors. Polygenic risk scores (PRS) are being developed to identify high polygenic risk individuals. Due to differences in genetic background, PRS distributions vary by ancestry, necessitating calibration.

Methods

We compared four calibration methods using the All of Us Research Program Whole Genome Sequence data for a CRC PRS previously developed in participants of European and East Asian ancestry. The methods contrasted results from linear models with A) the entire data set or an ancestrally diverse training set AND B) covariates including principal components of ancestry or admixture. Calibration with the training set adjusted the variance in addition to the mean.

Results

All methods performed similarly within ancestry with OR (95% C.I.) per s.d. change in PRS: African 1.5 (1.02, 2.08), Admixed American 2.2 (1.27, 3.85), European 1.6 (1.43, 1.89), and Middle Eastern 1.1 (0.71, 1.63). Using admixture and an ancestrally diverse training set provided distributions closest to standard Normal with accurate upper tail frequencies.

Conclusion

Although the PRS is predictive of CRC risk for most ancestries, its performance varies by ancestry. Post-hoc calibration preserves the risk prediction within ancestries. Training a calibration model on ancestrally diverse participants to adjust both the mean and variance of the PRS, using admixture as covariates, created standard Normal z-scores. These z-scores can be used to identify patients at high polygenic risk, and can be incorporated into comprehensive risk scores including other known risk factors, allowing for more precise risk estimates.

Genetic sex validation for sample tracking in next-generation sequencing clinical testing

OBJECTIVE

Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups.

RESULTS

Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors (49.09%), samples from transgender participants (3.64%) and stem cell or bone marrow transplant patients (7.27%) along with undetermined sample mix-ups (40%) for which sample swaps occurred prior to arrival at genome centers, however the exact cause of the events at the sampling sites resulting in the mix-ups were not able to be determined.

Genomic data in the All of Us Research Program

Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for the field of human genetics1-4. The All of Us Research Program is a longitudinal cohort study aiming to enrol a diverse group of at least one million individuals across the USA to accelerate biomedical research and improve human health5,6. Here we describe the programme's genomics data release of 245,388 clinical-grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities. All of Us identified more than 1 billion genetic variants, including more than 275 million previously unreported genetic variants, more than 3.9 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry. Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all.

Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations

Polygenic risk scores (PRSs) have improved in predictive performance, but several challenges remain to be addressed before PRSs can be implemented in the clinic, including reduced predictive performance of PRSs in diverse populations, and the interpretation and communication of genetic results to both providers and patients. To address these challenges, the National Human Genome Research Institute-funded Electronic Medical Records and Genomics (eMERGE) Network has developed a framework and pipeline for return of a PRS-based genome-informed risk assessment to 25,000 diverse adults and children as part of a clinical study. From an initial list of 23 conditions, ten were selected for implementation based on PRS performance, medical actionability and potential clinical utility, including cardiometabolic diseases and cancer. Standardized metrics were considered in the selection process, with additional consideration given to strength of evidence in African and Hispanic populations. We then developed a pipeline for clinical PRS implementation (score transfer to a clinical laboratory, validation and verification of score performance), and used genetic ancestry to calibrate PRS mean and variance, utilizing genetically diverse data from 13,475 participants of the All of Us Research Program cohort to train and test model parameters. Finally, we created a framework for regulatory compliance and developed a PRS clinical report for return to providers and for inclusion in an additional genome-informed risk assessment. The initial experience from eMERGE can inform the approach needed to implement PRS-based testing in diverse clinical settings.

Prospective, multi-site study of healthcare utilization after actionable monogenic findings from clinical sequencing

As large-scale genomic screening becomes increasingly prevalent, understanding the influence of actionable results on healthcare utilization is key to estimating the potential long-term clinical impact. The eMERGE network sequenced individuals for actionable genes in multiple genetic conditions and returned results to individuals, providers, and the electronic health record. Differences in recommended health services (laboratory, imaging, and procedural testing) delivered within 12 months of return were compared among individuals with pathogenic or likely pathogenic (P/LP) findings to matched individuals with negative findings before and after return of results. Of 16,218 adults, 477 unselected individuals were found to have a monogenic risk for arrhythmia (n = 95), breast cancer (n = 96), cardiomyopathy (n = 95), colorectal cancer (n = 105), or familial hypercholesterolemia (n = 86). Individuals with P/LP results more frequently received services after return (43.8%) compared to before return (25.6%) of results and compared to individuals with negative findings (24.9%; p < 0.0001). The annual cost of qualifying healthcare services increased from an average of $162 before return to $343 after return of results among the P/LP group (p < 0.0001); differences in the negative group were non-significant. The mean difference-in-differences was $149 (p < 0.0001), which describes the increased cost within the P/LP group corrected for cost changes in the negative group. When stratified by individual conditions, significant cost differences were observed for arrhythmia, breast cancer, and cardiomyopathy. In conclusion, less than half of individuals received billed health services after monogenic return, which modestly increased healthcare costs for payors in the year following return.

Genetic variation in the human leukocyte antigen region confers susceptibility to Clostridioides difficile infection

Clostridioides difficile (C. diff.) infection (CDI) is a leading cause of hospital acquired diarrhea in North America and Europe and a major cause of morbidity and mortality. Known risk factors do not fully explain CDI susceptibility, and genetic susceptibility is suggested by the fact that some patients with colons that are colonized with C. diff. do not develop any infection while others develop severe or recurrent infections. To identify common genetic variants associated with CDI, we performed a genome-wide association analysis in 19,861 participants (1349 cases; 18,512 controls) from the Electronic Medical Records and Genomics (eMERGE) Network. Using logistic regression, we found strong evidence for genetic variation in the DRB locus of the MHC (HLA) II region that predisposes individuals to CDI (P > 1.0 × 10-14; OR 1.56). Altered transcriptional regulation in the HLA region may play a role in conferring susceptibility to this opportunistic enteric pathogen.

Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations

Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values < 0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.

Longitudinal adherence to breast cancer surveillance following cancer genetic testing in an integrated health care system

PURPOSE

Screening with mammography and breast magnetic resonance imaging (MRI) is an important risk management strategy for individuals with inherited pathogenic variants (PVs) in genes associated with increased breast cancer risk. We describe longitudinal screening adherence in individuals who underwent cancer genetic testing as part of usual care in a vertically integrated health system.

METHODS

We determined the proportion time covered (PTC) by annual mammography and breast MRI for individuals with PVs in TP53, BRCA1, BRCA2, PALB2, NF1, CHEK2, and ATM. We determined time covered by biennial mammography beginning at age 50 years for individuals who received negative results, uncertain results, or with PVs in genes without specific breast cancer screening recommendations.

RESULTS

One hundred and forty individuals had PVs in TP53, BRCA1, BRCA2, PALB2, NF1, CHEK2, or ATM. Among these individuals, average PTC was 48% (range 0-99%) for annual screening mammography and 34% (range 0-100%) for annual breast MRI. Average PTC was highest for individuals with PVs in CHEK2 (N = 14) and lowest for individuals with PVs in TP53 (N = 3). Average PTC for biennial mammography (N = 1,027) was 49% (0-100%).

CONCLUSION

Longitudinal screening adherence in individuals with PVs in breast cancer associated genes, as measured by the proportion of time covered, is low; adherence to annual breast MRI falls below that of annual mammography. Additional research should examine screening behavior in individuals with PVs in breast cancer associated genes with a goal of developing interventions to improve adherence to recommended risk management.

Full-length Isoform Sequencing for Resolving the Molecular Basis of Charcot-Marie-Tooth 2A

Objectives

Transcript sequencing of patient-derived samples has been shown to improve the diagnostic yield for solving cases of suspected Mendelian conditions, yet the added benefit of full-length long-read transcript sequencing is largely unexplored.

Methods

We applied short-read and full-length transcript sequencing and mitochondrial functional studies to a patient-derived fibroblast cell line from an individual with neuropathy that previously lacked a molecular diagnosis.

Results

We identified an intronic homozygous MFN2 c.600-31T>G variant that disrupts the branch point critical for intron 6 splicing. Full-length long-read isoform complementary DNA (cDNA) sequencing after treatment with a nonsense-mediated mRNA decay (NMD) inhibitor revealed that this variant creates 5 distinct altered splicing transcripts. All 5 altered splicing transcripts have disrupted open reading frames and are subject to NMD. Furthermore, a patient-derived fibroblast line demonstrated abnormal lipid droplet formation, consistent with MFN2 dysfunction. Although correctly spliced full-length MFN2 transcripts are still produced, this branch point variant results in deficient MFN2 levels and autosomal recessive Charcot-Marie-Tooth disease, axonal, type 2A (CMT2A).

Discussion

This case highlights the utility of full-length isoform sequencing for characterizing the molecular mechanism of undiagnosed rare diseases and expands our understanding of the genetic basis for CMT2A.

Synchronized long-read genome, methylome, epigenome, and transcriptome for resolving a Mendelian condition

Resolving the molecular basis of a Mendelian condition (MC) remains challenging owing to the diverse mechanisms by which genetic variants cause disease. To address this, we developed a synchronized long-read genome, methylome, epigenome, and transcriptome sequencing approach, which enables accurate single-nucleotide, insertion-deletion, and structural variant calling and diploid de novo genome assembly, and permits the simultaneous elucidation of haplotype-resolved CpG methylation, chromatin accessibility, and full-length transcript information in a single long-read sequencing run. Application of this approach to an Undiagnosed Diseases Network (UDN) participant with a chromosome X;13 balanced translocation of uncertain significance revealed that this translocation disrupted the functioning of four separate genes (NBEA, PDK3, MAB21L1, and RB1) previously associated with single-gene MCs. Notably, the function of each gene was disrupted via a distinct mechanism that required integration of the four 'omes' to resolve. These included nonsense-mediated decay, fusion transcript formation, enhancer adoption, transcriptional readthrough silencing, and inappropriate X chromosome inactivation of autosomal genes. Overall, this highlights the utility of synchronized long-read multi-omic profiling for mechanistically resolving complex phenotypes.

Genetic Sex Validation for Sample Tracking in Clinical Testing

Objective

Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups.

Results

Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors, samples from transgender participants and stem cell or bone marrow transplant patients along with undetermined sample mix-ups.

Clinical consequences of a polygenic predisposition to benign lower white blood cell counts: Consequences of benign WBC count genetics

Polygenic variation unrelated to disease contributes to interindividual variation in baseline white blood cell (WBC) counts, but its clinical significance is undefined. We investigated the clinical consequences of a genetic predisposition toward lower WBC counts among 89,559 biobank participants from tertiary care centers using a polygenic score for WBC count (PGSWBC) comprising single nucleotide polymorphisms not associated with disease. A predisposition to lower WBC counts was associated with a decreased risk of identifying pathology on a bone marrow biopsy performed for a low WBC count (odds-ratio=0.55 per standard deviation increase in PGSWBC [95%CI, 0.30 - 0.94], p=0.04), an increased risk of leukopenia (a low WBC count) when treated with a chemotherapeutic (n=1,724, hazard ratio [HR]=0.78 [0.69 - 0.88], p=4.0×10-5) or immunosuppressant (n=354, HR=0.61 [0.38 - 0.99], p=0.04). A predisposition to benign lower WBC counts was associated with an increased risk of discontinuing azathioprine treatment (n=1,466, HR=0.62 [0.44 - 0.87], p=0.006). Collectively, these findings suggest that a WBC count polygenic score identifies individuals who are susceptible to escalations or alterations in clinical care that may be harmful or of little benefit.

Evaluating construct validity of computable acute respiratory distress syndrome definitions in adults hospitalized with COVID-19: an electronic health records based approach

BACKGROUND

Evolving ARDS epidemiology and management during COVID-19 have prompted calls to reexamine the construct validity of Berlin criteria, which have been rarely evaluated in real-world data. We developed a Berlin ARDS definition (EHR-Berlin) computable in electronic health records (EHR) to (1) assess its construct validity, and (2) assess how expanding its criteria affected validity.

METHODS

We performed a retrospective cohort study at two tertiary care hospitals with one EHR, among adults hospitalized with COVID-19 February 2020-March 2021. We assessed five candidate definitions for ARDS: the EHR-Berlin definition modeled on Berlin criteria, and four alternatives informed by recent proposals to expand criteria and include patients on high-flow oxygen (EHR-Alternative 1), relax imaging criteria (EHR-Alternatives 2-3), and extend timing windows (EHR-Alternative 4). We evaluated two aspects of construct validity for the EHR-Berlin definition: (1) criterion validity: agreement with manual ARDS classification by experts, available in 175 patients; (2) predictive validity: relationships with hospital mortality, assessed by Pearson r and by area under the receiver operating curve (AUROC). We assessed predictive validity and timing of identification of EHR-Berlin definition compared to alternative definitions.

RESULTS

Among 765 patients, mean (SD) age was 57 (18) years and 471 (62%) were male. The EHR-Berlin definition classified 171 (22%) patients as ARDS, which had high agreement with manual classification (kappa 0.85), and was associated with mortality (Pearson r = 0.39; AUROC 0.72, 95% CI 0.68, 0.77). In comparison, EHR-Alternative 1 classified 219 (29%) patients as ARDS, maintained similar relationships to mortality (r = 0.40; AUROC 0.74, 95% CI 0.70, 0.79, Delong test P = 0.14), and identified patients earlier in their hospitalization (median 13 vs. 15 h from admission, Wilcoxon signed-rank test P < 0.001). EHR-Alternative 3, which removed imaging criteria, had similar correlation (r = 0.41) but better discrimination for mortality (AUROC 0.76, 95% CI 0.72, 0.80; P = 0.036), and identified patients median 2 h (P < 0.001) from admission.

CONCLUSIONS

The EHR-Berlin definition can enable ARDS identification with high criterion validity, supporting large-scale study and surveillance. There are opportunities to expand the Berlin criteria that preserve predictive validity and facilitate earlier identification.

Genetic Architecture of Dilated Cardiomyopathy in Individuals of African and European Ancestry

Importance

Black patients with dilated cardiomyopathy (DCM) have increased familial risk and worse outcomes than White patients, but most DCM genetic data are from White patients.

Objective

To compare the rare variant genetic architecture of DCM by genomic ancestry within a diverse population of patients with DCM.

Design

Cross-sectional study enrolling patients with DCM who self-identified as non-Hispanic Black, Hispanic, or non-Hispanic White from June 7, 2016, to March 15, 2020, at 25 US advanced heart failure programs. Variants in 36 DCM genes were adjudicated as pathogenic, likely pathogenic, or of uncertain significance.

Exposure

Presence of DCM.

Main Outcomes and Measures

Variants in DCM genes classified as pathogenic/likely pathogenic/uncertain significance and clinically actionable (pathogenic/likely pathogenic).

Results

A total of 505, 667, and 26 patients with DCM of predominantly African, European, or Native American genomic ancestry, respectively, were included. Compared with patients of European ancestry, a lower percentage of patients of African ancestry had clinically actionable variants (8.2% [95% CI, 5.2%-11.1%] vs 25.5% [95% CI, 21.3%-29.6%]), reflecting the lower odds of a clinically actionable variant for those with any pathogenic variant/likely pathogenic variant/variant of uncertain significance (odds ratio, 0.25 [95% CI, 0.17-0.37]). On average, patients of African ancestry had fewer clinically actionable variants in TTN (difference, -0.09 [95% CI, -0.14 to -0.05]) and other genes with predicted loss of function as a disease-causing mechanism (difference, -0.06 [95% CI, -0.11 to -0.02]). However, the number of pathogenic variants/likely pathogenic variants/variants of uncertain significance was more comparable between ancestry groups (difference, -0.07 [95% CI, -0.22 to 0.09]) due to a larger number of non-TTN non-predicted loss of function variants of uncertain significance, mostly missense, in patients of African ancestry (difference, 0.15 [95% CI, 0.00-0.30]). Published clinical case-based evidence supporting pathogenicity was less available for variants found only in patients of African ancestry (P < .001).

Conclusion and Relevance

Patients of African ancestry with DCM were less likely to have clinically actionable variants in DCM genes than those of European ancestry due to differences in genetic architecture and a lack of representation of African ancestry in clinical data sets.

Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies LRRC4C, LHX5-AS1 and nominates ancestry-specific loci PTPRK , GRB14 , and KIAA0825 as novel risk loci for Alzheimer's disease: the Alzheimer's Disease Genetics Consortium

Limited ancestral diversity has impaired our ability to detect risk variants more prevalent in non-European ancestry groups in genome-wide association studies (GWAS). We constructed and analyzed a multi-ancestry GWAS dataset in the Alzheimer's Disease (AD) Genetics Consortium (ADGC) to test for novel shared and ancestry-specific AD susceptibility loci and evaluate underlying genetic architecture in 37,382 non-Hispanic White (NHW), 6,728 African American, 8,899 Hispanic (HIS), and 3,232 East Asian individuals, performing within-ancestry fixed-effects meta-analysis followed by a cross-ancestry random-effects meta-analysis. We identified 13 loci with cross-ancestry associations including known loci at/near CR1 , BIN1 , TREM2 , CD2AP , PTK2B , CLU , SHARPIN , MS4A6A , PICALM , ABCA7 , APOE and two novel loci not previously reported at 11p12 ( LRRC4C ) and 12q24.13 ( LHX5-AS1 ). Reflecting the power of diverse ancestry in GWAS, we observed the SHARPIN locus using 7.1% the sample size of the original discovering single-ancestry GWAS (n=788,989). We additionally identified three GWS ancestry-specific loci at/near ( PTPRK ( P =2.4×10 -8 ) and GRB14 ( P =1.7×10 -8 ) in HIS), and KIAA0825 ( P =2.9×10 -8 in NHW). Pathway analysis implicated multiple amyloid regulation pathways (strongest with P adjusted =1.6×10 -4 ) and the classical complement pathway ( P adjusted =1.3×10 -3 ). Genes at/near our novel loci have known roles in neuronal development ( LRRC4C, LHX5-AS1 , and PTPRK ) and insulin receptor activity regulation ( GRB14 ). These findings provide compelling support for using traditionally-underrepresented populations for gene discovery, even with smaller sample sizes.

Genome-wide Association Study for AKI

Key Points

Two genetic variants in the DISP1-TLR5 gene locus were associated with risk of AKI. DISP1 and TLR5 were differentially regulated in kidney biopsy tissue from patients with AKI compared with no AKI.

Background

Although common genetic risks for CKD are well established, genetic factors influencing risk for AKI in hospitalized patients are poorly understood.

Methods

We conducted a genome-wide association study in 1369 participants in the Assessment, Serial Evaluation, and Subsequent Sequelae of AKI Study; a multiethnic population of hospitalized participants with and without AKI matched on demographics, comorbidities, and kidney function before hospitalization. We then completed functional annotation of top-performing variants for AKI using single-cell RNA sequencing data from kidney biopsies in 12 patients with AKI and 18 healthy living donors from the Kidney Precision Medicine Project.

Results

No genome-wide significant associations with AKI risk were found in Assessment, Serial Evaluation, and Subsequent Sequelae of AKI (P < 5×10 −8 ). The top two variants with the strongest association with AKI mapped to the dispatched resistance-nodulation-division (RND) transporter family member 1 (DISP1) gene and toll-like receptor 5 (TLR5) gene locus, rs17538288 (odds ratio, 1.55; 95% confidence interval, 1.32 to 182; P = 9.47×10 −8 ) and rs7546189 (odds ratio, 1.53; 95% confidence interval, 1.30 to 1.81; P = 4.60×10 −7 ). In comparison with kidney tissue from healthy living donors, kidney biopsies in patients with AKI showed differential DISP1 expression in proximal tubular epithelial cells (adjusted P = 3.9× 10−2) and thick ascending limb of the loop of Henle (adjusted P = 8.7× 10−3) and differential TLR5 gene expression in thick ascending limb of the loop of Henle (adjusted P = 4.9× 10−30).

Conclusions

AKI is a heterogeneous clinical syndrome with various underlying risk factors, etiologies, and pathophysiology that may limit the identification of genetic variants. Although no variants reached genome-wide significance, we report two variants in the intergenic region between DISP1 and TLR5 , suggesting this region as a novel risk for AKI susceptibility.

Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations

Polygenic risk scores (PRS) have improved in predictive performance supporting their use in clinical practice. Reduced predictive performance of PRS in diverse populations can exacerbate existing health disparities. The NHGRI-funded eMERGE Network is returning a PRS-based genome-informed risk assessment to 25,000 diverse adults and children. We assessed PRS performance, medical actionability, and potential clinical utility for 23 conditions. Standardized metrics were considered in the selection process with additional consideration given to strength of evidence in African and Hispanic populations. Ten conditions were selected with a range of high-risk thresholds: atrial fibrillation, breast cancer, chronic kidney disease, coronary heart disease, hypercholesterolemia, prostate cancer, asthma, type 1 diabetes, obesity, and type 2 diabetes. We developed a pipeline for clinical PRS implementation, used genetic ancestry to calibrate PRS mean and variance, created a framework for regulatory compliance, and developed a PRS clinical report. eMERGE's experience informs the infrastructure needed to implement PRS-based implementation in diverse clinical settings.

Dominant-negative variant in SLC1A4 causes an autosomal dominant epilepsy syndrome

SLC1A4 is a trimeric neutral amino acid transporter essential for shuttling L-serine from astrocytes into neurons. Individuals with biallelic variants in SLC1A4 are known to have spastic tetraplegia, thin corpus callosum, and progressive microcephaly (SPATCCM) syndrome, but individuals with heterozygous variants are not thought to have disease. We identify an 8-year-old patient with global developmental delay, spasticity, epilepsy, and microcephaly who has a de novo heterozygous three amino acid duplication in SLC1A4 (L86_M88dup). We demonstrate that L86_M88dup causes a dominant-negative N-glycosylation defect of SLC1A4, which in turn reduces the plasma membrane localization of SLC1A4 and the transport rate of SLC1A4 for L-serine.

SPTSSA variants alter sphingolipid synthesis and cause a complex hereditary spastic paraplegia

Sphingolipids are a diverse family of lipids with critical structural and signalling functions in the mammalian nervous system, where they are abundant in myelin membranes. Serine palmitoyltransferase, the enzyme that catalyses the rate-limiting reaction of sphingolipid synthesis, is composed of multiple subunits including an activating subunit, SPTSSA. Sphingolipids are both essential and cytotoxic and their synthesis must therefore be tightly regulated. Key to the homeostatic regulation are the ORMDL proteins that are bound to serine palmitoyltransferase and mediate feedback inhibition of enzymatic activity when sphingolipid levels become excessive. Exome sequencing identified potential disease-causing variants in SPTSSA in three children presenting with a complex form of hereditary spastic paraplegia. The effect of these variants on the catalytic activity and homeostatic regulation of serine palmitoyltransferase was investigated in human embryonic kidney cells, patient fibroblasts and Drosophila. Our results showed that two different pathogenic variants in SPTSSA caused a hereditary spastic paraplegia resulting in progressive motor disturbance with variable sensorineural hearing loss and language/cognitive dysfunction in three individuals. The variants in SPTSSA impaired the negative regulation of serine palmitoyltransferase by ORMDLs leading to excessive sphingolipid synthesis based on biochemical studies and in vivo studies in Drosophila. These findings support the pathogenicity of the SPTSSA variants and point to excessive sphingolipid synthesis due to impaired homeostatic regulation of serine palmitoyltransferase as responsible for defects in early brain development and function.

Returning integrated genomic risk and clinical recommendations: The eMERGE study

PURPOSE

Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk.

METHODS

To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results.

RESULTS

GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022.

CONCLUSION

Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Familial Hypercholesterolemia in the Electronic Medical Records and Genomics Network: Prevalence, Penetrance, Cardiovascular Risk, and Outcomes After Return of Results

BACKGROUND

The implications of secondary findings detected in large-scale sequencing projects remain uncertain. We assessed prevalence and penetrance of pathogenic familial hypercholesterolemia (FH) variants, their association with coronary heart disease (CHD), and 1-year outcomes following return of results in phase III of the electronic medical records and genomics network.

METHODS

Adult participants (n=18 544) at 7 sites were enrolled in a prospective cohort study to assess the clinical impact of returning results from targeted sequencing of 68 actionable genes, including LDLR, APOB, and PCSK9. FH variant prevalence and penetrance (defined as low-density lipoprotein cholesterol >155 mg/dL) were estimated after excluding participants enrolled on the basis of hypercholesterolemia. Multivariable logistic regression was used to estimate the odds of CHD compared to age- and sex-matched controls without FH-associated variants. Process (eg, referral to a specialist or ordering new tests), intermediate (eg, new diagnosis of FH), and clinical (eg, treatment modification) outcomes within 1 year after return of results were ascertained by electronic health record review.

RESULTS

The prevalence of FH-associated pathogenic variants was 1 in 188 (69 of 13,019 unselected participants). Penetrance was 87.5%. The presence of an FH variant was associated with CHD (odds ratio, 3.02 [2.00-4.53]) and premature CHD (odds ratio, 3.68 [2.34-5.78]). At least 1 outcome occurred in 92% of participants; 44% received a new diagnosis of FH and 26% had treatment modified following return of results.

CONCLUSIONS

In a multisite cohort of electronic health record-linked biobanks, monogenic FH was prevalent, penetrant, and associated with presence of CHD. Nearly half of participants with an FH-associated variant received a new diagnosis of FH and a quarter had treatment modified after return of results. These results highlight the potential utility of sequencing electronic health record-linked biobanks to detect FH.

Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female-Specific Health Conditions

Background Cardiometabolic diseases are highly comorbid, but their relationship with female-specific or overwhelmingly female-predominant health conditions (breast cancer, endometriosis, pregnancy complications) is understudied. This study aimed to estimate the cross-trait genetic overlap and influence of genetic burden of cardiometabolic traits on health conditions unique to women. Methods and Results Using electronic health record data from 71 008 ancestrally diverse women, we examined relationships between 23 obstetrical/gynecological conditions and 4 cardiometabolic phenotypes (body mass index, coronary artery disease, type 2 diabetes, and hypertension) by performing 4 analyses: (1) cross-trait genetic correlation analyses to compare genetic architecture, (2) polygenic risk score-based association tests to characterize shared genetic effects on disease risk, (3) Mendelian randomization for significant associations to assess cross-trait causal relationships, and (4) chronology analyses to visualize the timeline of events unique to groups of women with high and low genetic burden for cardiometabolic traits and highlight the disease prevalence in risk groups by age. We observed 27 significant associations between cardiometabolic polygenic scores and obstetrical/gynecological conditions (body mass index and endometrial cancer, body mass index and polycystic ovarian syndrome, type 2 diabetes and gestational diabetes, type 2 diabetes and polycystic ovarian syndrome). Mendelian randomization analysis provided additional evidence of independent causal effects. We also identified an inverse association between coronary artery disease and breast cancer. High cardiometabolic polygenic scores were associated with early development of polycystic ovarian syndrome and gestational hypertension. Conclusions We conclude that polygenic susceptibility to cardiometabolic traits is associated with elevated risk of certain female-specific health conditions.

Genetic Predictors of Blood Pressure Traits are Associated with Preeclampsia

Background

Preeclampsia, a pregnancy complication characterized by hypertension after 20 gestational weeks, is a major cause of maternal and neonatal morbidity and mortality. The mechanisms leading to preeclampsia are unclear; however, there is evidence that preeclampsia is highly heritable. We evaluated the association of polygenic risk scores (PRS) for blood pressure traits and preeclampsia to assess whether there is shared genetic architecture.

Methods

Participants were obtained from Vanderbilt University's BioVU, the Electronic Medical Records and Genomics network, and the Penn Medicine Biobank. Non-Hispanic Black and White females of reproductive age with indications of pregnancy and genotype information were included. Preeclampsia was defined by ICD codes. Summary statistics for diastolic blood pressure (DBP), systolic blood pressure (SBP), and pulse pressure (PP) PRS were obtained from Giri et al 2019. Associations between preeclampsia and each PRS were evaluated separately by race and study population before evidence was meta-analyzed. Prediction models were developed and evaluated using 10-fold cross validation.

Results

In the 3,504 Black and 5,009 White individuals included, the rate of preeclampsia was 15.49%. The DBP and SBP PRSs were associated with preeclampsia in Whites but not Blacks. The PP PRS was significantly associated with preeclampsia in Blacks and Whites. In trans-ancestry meta-analysis, all PRSs were associated with preeclampsia (OR DBP =1.10, 95% CI=1.02-1.17, p =7.68×10 -3 ; OR SBP =1.16, 95% CI=1.09-1.23, p =2.23×10 -6 ; OR PP =1.14, 95% CI=1.07-1.27, p =9.86×10 -5 ). However, addition of PRSs to clinical prediction models did not improve predictive performance.

Conclusions

Genetic factors contributing to blood pressure regulation in the general population also predispose to preeclampsia.

Bi-allelic ATG4D variants are associated with a neurodevelopmental disorder characterized by speech and motor impairment

Autophagy regulates the degradation of damaged organelles and protein aggregates, and is critical for neuronal development, homeostasis, and maintenance, yet few neurodevelopmental disorders have been associated with pathogenic variants in genes encoding autophagy-related proteins. We report three individuals from two unrelated families with a neurodevelopmental disorder characterized by speech and motor impairment, and similar facial characteristics. Rare, conserved, bi-allelic variants were identified in ATG4D, encoding one of four ATG4 cysteine proteases important for autophagosome biogenesis, a hallmark of autophagy. Autophagosome biogenesis and induction of autophagy were intact in cells from affected individuals. However, studies evaluating the predominant substrate of ATG4D, GABARAPL1, demonstrated that three of the four ATG4D patient variants functionally impair ATG4D activity. GABARAPL1 is cleaved or "primed" by ATG4D and an in vitro GABARAPL1 priming assay revealed decreased priming activity for three of the four ATG4D variants. Furthermore, a rescue experiment performed in an ATG4 tetra knockout cell line, in which all four ATG4 isoforms were knocked out by gene editing, showed decreased GABARAPL1 priming activity for the two ATG4D missense variants located in the cysteine protease domain required for priming, suggesting that these variants impair the function of ATG4D. The clinical, bioinformatic, and functional data suggest that bi-allelic loss-of-function variants in ATG4D contribute to the pathogenesis of this syndromic neurodevelopmental disorder.

Full-length isoform sequencing for resolving the molecular basis of Charcot-Marie-Tooth 2A

Objectives

Transcript sequencing of patient derived samples has been shown to improve the diagnostic yield for solving cases of likely Mendelian disorders, yet the added benefit of full-length long-read transcript sequencing is largely unexplored.

Methods

We applied short-read and full-length isoform cDNA sequencing and mitochondrial functional studies to a patient-derived fibroblast cell line from an individual with neuropathy that previously lacked a molecular diagnosis.

Results

We identified an intronic homozygous MFN2 c.600-31T>G variant that disrupts a branch point critical for intron 6 spicing. Full-length long-read isoform cDNA sequencing after treatment with a nonsense-mediated mRNA decay (NMD) inhibitor revealed that this variant creates five distinct altered splicing transcripts. All five altered splicing transcripts have disrupted open reading frames and are subject to NMD. Furthermore, a patient-derived fibroblast line demonstrated abnormal lipid droplet formation, consistent with MFN2 dysfunction. Although correctly spliced full-length MFN2 transcripts are still produced, this branch point variant results in deficient MFN2 protein levels and autosomal recessive Charcot-Marie-Tooth disease, axonal, type 2A (CMT2A).

Discussion

This case highlights the utility of full-length isoform sequencing for characterizing the molecular mechanism of undiagnosed rare diseases and expands our understanding of the genetic basis for CMT2A.

Precision medicine for developmental and epileptic encephalopathies in Africa-strategies for a resource-limited setting

PURPOSE

Sub-Saharan Africa bears the highest burden of epilepsy worldwide. A presumed proportion is genetic, but this etiology is buried under the burden of infections and perinatal insults in a setting of limited awareness and few options for testing. Children with developmental and epileptic encephalopathies (DEEs) are most severely affected by this diagnostic gap in Africa, because the rate of actionable findings is highest in DEE-associated genes.

METHODS

We tested 234 genetically naive South African children diagnosed with/possible DEE using gene panels, exome sequencing, and chromosomal microarray. Statistical comparison of electroclinical features in children with and children without candidate variants was performed to identify characteristics most likely predictive of a positive genetic finding.

RESULTS

Of the 41 (of 234) children with likely/pathogenic variants, 26 had variants supporting precision therapy. Multivariate regression modeling highlighted neonatal or infantile-onset seizures and movement abnormalities as predictive of a positive genetic finding. We used this, coupled with an emphasis on precision medicine outcomes, to propose the pragmatic "Think-Genetics" strategy for early recognition of a possible genetic etiology.

CONCLUSION

Our findings emphasize the importance of an early genetic diagnosis in DEE. We designed the Think-Genetics strategy for early recognition, appropriate interim management, and genetic testing for DEE in resource-constrained settings.

Combining Asian-European Genome-Wide Association Studies of Colorectal Cancer Improves Risk Prediction Across Race and Ethnicity

Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expanded PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS were 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1,681-3,651 cases and 8,696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They were significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values<0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.

Continuing a search for a diagnosis: the impact of adolescence and family dynamics

The "diagnostic odyssey" describes the process those with undiagnosed conditions undergo to identify a diagnosis. Throughout this process, families of children with undiagnosed conditions have multiple opportunities to decide whether to continue or stop their search for a diagnosis and accept the lack of a diagnostic label. Previous studies identified factors motivating a family to begin searching, but there is limited information about the decision-making process in a prolonged search and how the affected child impacts a family's decision. This study aimed to understand how families of children with undiagnosed diseases decide whether to continue to pursue a diagnosis after standard clinical testing has failed. Parents who applied to the Undiagnosed Disease Network (UDN) at the National Institutes of Health (NIH) were recruited to participate in semi-structured interviews. The 2015 Supportive Care Needs model by Pelenstov, which defines critical needs in families with rare/undiagnosed diseases, provided a framework for interview guide development and transcript analysis (Pelentsov et al in Disabil Health J 8(4):475-491, 2015. https://doi.org/10.1016/J.DHJO.2015.03.009 ). A deductive, iterative coding approach was used to identify common unifying themes. Fourteen parents from 13 families were interviewed. The average child's age was 11 years (range 3-18) and an average 63% of their life had been spent searching for a diagnosis. Our analysis found that alignment or misalignment of parent and child needs impact the trajectory of the diagnostic search. When needs and desires align, reevaluation of a decision to pursue a diagnosis is limited. However, when there is conflict between parent and child desires, there is reevaluation, and often a pause, in the search. This tension is exacerbated when children are adolescents and attempting to balance their dependence on parents for medical care with a natural desire for independence. Our results provide novel insights into the roles of adolescents in the diagnostic odyssey. The tension between desired and realistic developmental outcomes for parents and adolescents impacts if, and how, the search for a diagnosis progresses.

Angiopoietin-Like4 Is a Novel Marker of COVID-19 Severity

Vascular dysfunction and capillary leak are common in critically ill COVID-19 patients, but identification of endothelial pathways involved in COVID-19 pathogenesis has been limited. Angiopoietin-like 4 (ANGPTL4) is a protein secreted in response to hypoxic and nutrient-poor conditions that has a variety of biological effects including vascular injury and capillary leak.

OBJECTIVES

To assess the role of ANGPTL4 in COVID-19-related outcomes.

DESIGN SETTING AND PARTICIPANTS

Two hundred twenty-five COVID-19 ICU patients were enrolled from April 2020 to May 2021 in a prospective, multicenter cohort study from three different medical centers, University of Washington, University of Southern California and New York University.

MAIN OUTCOMES AND MEASURES

Plasma ANGPTL4 was measured on days 1, 7, and 14 after ICU admission. We used previously published tissue proteomic data and lung single nucleus RNA (snRNA) sequencing data from specimens collected from COVID-19 patients to determine the tissues and cells that produce ANGPTL4.

RESULTS

Higher plasma ANGPTL4 concentrations were significantly associated with worse hospital mortality (adjusted odds ratio per log2 increase, 1.53; 95% CI, 1.17-2.00; p = 0.002). Higher ANGPTL4 concentrations were also associated with higher proportions of venous thromboembolism and acute respiratory distress syndrome. Longitudinal ANGPTL4 concentrations were significantly different during the first 2 weeks of hospitalization in patients who subsequently died compared with survivors (p for interaction = 8.1 × 10-5). Proteomics analysis demonstrated abundance of ANGPTL4 in lung tissue compared with other organs in COVID-19. ANGPTL4 single-nuclear RNA gene expression was significantly increased in pulmonary alveolar type 2 epithelial cells and fibroblasts in COVID-19 lung tissue compared with controls.

CONCLUSIONS AND RELEVANCE

ANGPTL4 is expressed in pulmonary epithelial cells and fibroblasts and is associated with clinical prognosis in critically ill COVID-19 patients.

Quantifying factors that affect polygenic risk score performance across diverse ancestries and age groups for body mass index

Polygenic risk scores (PRS) have led to enthusiasm for precision medicine. However, it is well documented that PRS do not generalize across groups differing in ancestry or sample characteristics e.g., age. Quantifying performance of PRS across different groups of study participants, using genome-wide association study (GWAS) summary statistics from multiple ancestry groups and sample sizes, and using different linkage disequilibrium (LD) reference panels may clarify which factors are limiting PRS transferability. To evaluate these factors in the PRS generation process, we generated body mass index (BMI) PRS (PRSBMI) in the Electronic Medical Records and Genomics (eMERGE) network (N=75,661). Analyses were conducted in two ancestry groups (European and African) and three age ranges (adult, teenagers, and children). For PRSBMI calculations, we evaluated five LD reference panels and three sets of GWAS summary statistics of varying sample size and ancestry. PRSBMI performance increased for both African and European ancestry individuals using cross-ancestry GWAS summary statistics compared to European-only summary statistics (6.3% and 3.7% relative R2 increase, respectively, pAfrican=0.038, pEuropean=6.26x10-4). The effects of LD reference panels were more pronounced in African ancestry study datasets. PRSBMI performance degraded in children; R2 was less than half of teenagers or adults. The effect of GWAS summary statistics sample size was small when modeled with the other factors. Additionally, the potential of using a PRS generated for one trait to predict risk for comorbid diseases is not well understood especially in the context of cross-ancestry analyses - we explored clinical comorbidities from the electronic health record associated with PRSBMI and identified significant associations with type 2 diabetes and coronary atherosclerosis. In summary, this study quantifies the effects that ancestry, GWAS summary statistic sample size, and LD reference panel have on PRS performance, especially in cross-ancestry and age-specific analyses.

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

BACKGROUND

Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.

RESULTS

To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.

CONCLUSIONS

Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

Quantifying the phenome-wide disease burden of obesity using electronic health records and genomics

OBJECTIVE

High BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome- and phenome-wide approach.

METHODS

This study performed a phenome-wide association study of BMI using a clinical cohort of 736,726 adults. This was followed by genetic association studies using two separate cohorts: one consisting of 65,174 adults in the Electronic Medical Records and Genomics (eMERGE) Network and another with 405,432 participants in the UK Biobank.

RESULTS

Class 3 obesity was associated with 433 phenotypes, representing 59.3% of all billing codes in individuals with severe obesity. A genome-wide polygenic risk score for BMI, accounting for 7.5% of variance in BMI, was associated with 296 clinical diseases, including strong associations with type 2 diabetes, sleep apnea, hypertension, and chronic liver disease. In all three cohorts, 199 phenotypes were associated with class 3 obesity and polygenic risk for obesity, including novel associations such as increased risk of renal failure, venous insufficiency, and gastroesophageal reflux.

CONCLUSIONS

This combined genomic and phenomic systematic approach demonstrated that obesity has a strong genetic predisposition and is associated with a considerable burden of disease across all disease classes.

Childhood exposures to environmental chemicals and neurodevelopmental outcomes in congenital heart disease

BACKGROUND

Children with congenital heart defects have an increased risk of neurodevelopmental disability. The impact of environmental chemical exposures during daily life on neurodevelopmental outcomes in toddlers with congenital heart defects is unknown.

METHODS

This prospective study investigated the impacts of early childhood exposure to mixtures of environmental chemicals on neurodevelopmental outcomes after cardiac surgery. Outcomes were assessed at 18 months of age using The Bayley Scales of Infant and Toddler Development-III. Urinary concentrations of exposure biomarkers of pesticides, phenols, parabens, and phthalates, and blood levels of lead, mercury, and nicotine were measured at the same time point. Bayesian profile regression and weighted quantile sum regression were utilized to assess associations between mixtures of biomarkers and neurodevelopmental scores.

RESULTS

One-hundred and forty infants were enrolled, and 110 (79%) returned at 18 months of age. Six biomarker exposure clusters were identified from the Bayesian profile regression analysis; and the pattern was driven by 15 of the 30 biomarkers, most notably 13 phthalate biomarkers. Children in the highest exposure cluster had significantly lower adjusted language scores by -9.41 points (95%CI: -17.2, -1.7) and adjusted motor scores by -4.9 points (-9.5, -0.4) compared to the lowest exposure. Weighted quantile sum regression modeling for the overall exposure-response relationship showed a significantly lower adjusted motor score (β = -2.8 points [2.5th and 97.5th percentile: -6.0, -0.6]). The weighted quantile sum regression index weights for several phthalates, one paraben, and one phenol suggest their relevance for poorer neurodevelopmental outcomes.

CONCLUSIONS

Like other children, infants with congenital heart defects are exposed to complex mixtures of environmental chemicals in daily life. Higher exposure biomarker concentrations were associated with significantly worse performance for language and motor skills in this population.

Multiancestral polygenic risk score for pediatric asthma

BACKGROUND

Asthma is the most common chronic condition in children and the third leading cause of hospitalization in pediatrics. The genome-wide association study catalog reports 140 studies with genome-wide significance. A polygenic risk score (PRS) with predictive value across ancestries has not been evaluated for this important trait.

OBJECTIVES

This study aimed to train and validate a PRS relying on genetic determinants for asthma to provide predictions for disease occurrence in pediatric cohorts of diverse ancestries.

METHODS

This study applied a Bayesian regression framework method using the Trans-National Asthma Genetic Consortium genome-wide association study summary statistics to derive a multiancestral PRS score, used one Electronic Medical Records and Genomics (eMERGE) cohort as a training set, used a second independent eMERGE cohort to validate the score, and used the UK Biobank data to replicate the findings. A phenome-wide association study was performed using the PRS to identify shared genetic etiology with other phenotypes.

RESULTS

The multiancestral asthma PRS was associated with asthma in the 2 pediatric validation datasets. Overall, the multiancestral asthma PRS has an area under the curve (AUC) of 0.70 (95% CI, 0.69-0.72) in the pediatric validation 1 and AUC of 0.66 (0.65-0.66) in the pediatric validation 2 datasets. We found significant discrimination across pediatric subcohorts of European (AUC, 95% CI, 0.60 and 0.66), African (AUC, 95% CI, 0.61 and 0.66), admixed American (AUC, 0.64 and 0.70), Southeast Asian (AUC, 0.65), and East Asian (AUC, 0.73) ancestry. Pediatric participants with the top 5% PRS had 2.80 to 5.82 increased odds of asthma compared to the bottom 5% across the training, validation 1, and validation 2 cohorts when adjusted for ancestry. Phenome-wide association study analysis confirmed the strong association of the identified PRS with asthma (odds ratio, 2.71, PFDR = 3.71 × 10-65) and related phenotypes.

CONCLUSIONS

A multiancestral PRS for asthma based on Bayesian posterior genomic effect sizes identifies increased odds of pediatric asthma.

Uterine fibroid polygenic risk score (PRS) associates and predicts risk for uterine fibroid

Uterine fibroids (UF) are common pelvic tumors in women, heritable, and genome-wide association studies (GWAS) have identified ~ 30 loci associated with increased risk in UF. Using summary statistics from a previously published UF GWAS performed in a non-Hispanic European Ancestry (NHW) female subset from the Electronic Medical Records and Genomics (eMERGE) Network, we constructed a polygenic risk score (PRS) for UF. UF-PRS was developed using PRSice and optimized in the separate clinical population of BioVU. PRS was validated using parallel methods of 10-fold cross-validation logistic regression and phenome-wide association study (PheWAS) in a seperate subset of eMERGE NHW females (validation set), excluding samples used in GWAS. PRSice determined pt < 0.001 and after linkage disequilibrium pruning (r2 < 0.2), 4458 variants were in the PRS which was significant (pseudo-R2 = 0.0018, p = 0.041). 10-fold cross-validation logistic regression modeling of validation set revealed the model had an area under the curve (AUC) value of 0.60 (95% confidence interval [CI] 0.58-0.62) when plotted in a receiver operator curve (ROC). PheWAS identified six phecodes associated with the PRS with the most significant phenotypes being 218 'benign neoplasm of uterus' and 218.1 'uterine leiomyoma' (p = 1.94 × 10-23, OR 1.31 [95% CI 1.26-1.37] and p = 3.50 × 10-23, OR 1.32 [95% CI 1.26-1.37]). We have developed and validated the first PRS for UF. We find our PRS has predictive ability for UF and captures genetic architecture of increased risk for UF that can be used in further studies.

Pathogenic variants in arteriopathy genes detected in a targeted sequencing study: Penetrance and 1-year outcomes after return of results

PURPOSE

We estimated the penetrance of pathogenic/likely pathogenic (P/LP) variants in arteriopathy-related genes and assessed near-term outcomes following return of results.

METHODS

Participants (N = 24,520) in phase III of the Electronic Medical Records and Genomics network underwent targeted sequencing of 68 actionable genes, including 9 genes associated with arterial aneurysmal diseases. Penetrance was estimated on the basis of the presence of relevant clinical traits. Outcomes occurring within 1 year of return of results included new diagnoses, referral to a specialist, new tests ordered, surveillance initiated, and new medications started.

RESULTS

P/LP variants were present in 34 participants. The average penetrance across genes was 59%, ranging from 86% for FBN1 variants to 25% for SMAD3. Of 16 participants in whom results were returned, 1-year outcomes occurred in 63%. A new diagnosis was made in 44% of the participants, 56% were referred to a specialist, a new test was ordered in 44%, surveillance was initiated in 31%, and a new medication was started in 31%.

CONCLUSION

Penetrance of P/LP variants in arteriopathy-related genes, identified in a large, targeted sequencing study, was variable and overall lower than that reported in clinical cohorts. Meaningful outcomes within the first year were noted in 63% of participants who received results.

Risk-reducing surgery in unaffected individuals receiving cancer genetic testing in an integrated health care system

BACKGROUND

Germline genetic testing enables primary cancer prevention, including through prophylactic surgery. We examined risk-reducing surgeries in unaffected individuals tested for hereditary cancer susceptibly between 2010 and 2018 in the Kaiser Permanente Northwest health system.

METHODS

We used an internal genetic testing database to create a cohort of individuals who received tests including one or more high-penetrance hereditary cancer susceptibility gene. We then identified, after testing, bilateral mastectomy, bilateral salpingo-oophorectomy (BSO), and total hysterectomy procedures in electronic health record and claims data through 2019. We describe surgery utilization by genetic test results and National Comprehensive Cancer Network (NCCN) guidelines.

RESULTS

The cohort included 1020 individuals, 16% with pathogenic/likely pathogenic (P/LP) variants in one or more of the following genes: BRCA1, BRCA2, CHEK2, APC, MUTYH, ATM, MSH2, PALB2, BRIP1, MLH1, MSH6, EPCAM, FLCN, RAD51C, RAD51D, or TP53. Among individuals with P/LP variants making them candidates for mastectomy, BSO, or hysterectomy per NCCN guidelines, 34% (33/97), 24% (23/94), and 8% (1/12), respectively, underwent surgery during follow-up. Fifty-three percent (18/37) of hysterectomies were among APC, BRCA1, and BRCA2 P/LP variant heterozygotes, typically concurrent with BSO. Three individuals with variants of uncertain significance (only) and 22 with negative results had prophylactic surgery after genetic testing.

CONCLUSIONS

Uptake of risk-reducing surgery following usual care genetic testing appears to be lower than in studies that actively recruit high-risk patients and provide testing and follow-up care in specialized settings. Factors in addition to genetic test results and NCCN guidelines motivate prophylactic surgery use and deserve further study.

A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

Large-scale genome-wide association study of coronary artery disease in genetically diverse populations

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.

ORCA, a values-based decision aid for selecting additional findings from genomic sequencing in adults: Efficacy results from a randomized trial

PURPOSE

Individuals having genomic sequencing can choose to be notified about pathogenic variants in genes unrelated to the testing indication. A decision aid can facilitate weighing one's values before making a choice about these additional results.

METHODS

We conducted a randomized trial (N = 231) comparing informed values-choice congruence among adults at risk for a hereditary cancer syndrome who viewed either the Optional Results Choice Aid (ORCA) or web-based additional findings information alone. ORCA is values-focused with a low-literacy design.

RESULTS

Individuals in both arms had informed values-choice congruence (75% and 73% in the decision aid and web-based groups, respectively; odds ratio [OR] = 1.10, 95% CI = 0.58-2.08). Most participants had adequate knowledge (79% and 76% in the decision aid and web-based groups, respectively; OR = 1.20, 95% CI = 0.61-2.34), with no significant difference between groups. Most had information-seeking values (97% and 98% in the decision aid and web-based groups, respectively; OR = 0.59, 95% CI = 0.10-3.61) and chose to receive additional findings.

CONCLUSION

The ORCA decision aid did not significantly improve informed values-choice congruence over web-based information in this cohort of adults deciding about genomic results. Both web-based approaches may be effective for adults to decide about receiving medically actionable additional results.

Genome-wide polygenic score to predict chronic kidney disease across ancestries

Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.

Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations

BACKGROUND

Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations.

METHODS

We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts.

RESULTS

The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance.

CONCLUSIONS

By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Association of Pathogenic Variants in Hereditary Cancer Genes With Multiple Diseases

Importance

Knowledge about the spectrum of diseases associated with hereditary cancer syndromes may improve disease diagnosis and management for patients and help to identify high-risk individuals.

Objective

To identify phenotypes associated with hereditary cancer genes through a phenome-wide association study.

Design, Setting, and Participants

This phenome-wide association study used health data from participants in 3 cohorts. The Electronic Medical Records and Genomics Sequencing (eMERGEseq) data set recruited predominantly healthy individuals from 10 US medical centers from July 16, 2016, through February 18, 2018, with a mean follow-up through electronic health records (EHRs) of 12.7 (7.4) years. The UK Biobank (UKB) cohort recruited participants from March 15, 2006, through August 1, 2010, with a mean (SD) follow-up of 12.4 (1.0) years. The Hereditary Cancer Registry (HCR) recruited patients undergoing clinical genetic testing at Vanderbilt University Medical Center from May 1, 2012, through December 31, 2019, with a mean (SD) follow-up through EHRs of 8.8 (6.5) years.

Exposures

Germline variants in 23 hereditary cancer genes. Pathogenic and likely pathogenic variants for each gene were aggregated for association analyses.

Main Outcomes and Measures

Phenotypes in the eMERGEseq and HCR cohorts were derived from the linked EHRs. Phenotypes in UKB were from multiple sources of health-related data.

Results

A total of 214 020 participants were identified, including 23 544 in eMERGEseq cohort (mean [SD] age, 47.8 [23.7] years; 12 611 women [53.6%]), 187 234 in the UKB cohort (mean [SD] age, 56.7 [8.1] years; 104 055 [55.6%] women), and 3242 in the HCR cohort (mean [SD] age, 52.5 [15.5] years; 2851 [87.9%] women). All 38 established gene-cancer associations were replicated, and 19 new associations were identified. These included the following 7 associations with neoplasms: CHEK2 with leukemia (odds ratio [OR], 3.81 [95% CI, 2.64-5.48]) and plasma cell neoplasms (OR, 3.12 [95% CI, 1.84-5.28]), ATM with gastric cancer (OR, 4.27 [95% CI, 2.35-7.44]) and pancreatic cancer (OR, 4.44 [95% CI, 2.66-7.40]), MUTYH (biallelic) with kidney cancer (OR, 32.28 [95% CI, 6.40-162.73]), MSH6 with bladder cancer (OR, 5.63 [95% CI, 2.75-11.49]), and APC with benign liver/intrahepatic bile duct tumors (OR, 52.01 [95% CI, 14.29-189.29]). The remaining 12 associations with nonneoplastic diseases included BRCA1/2 with ovarian cysts (OR, 3.15 [95% CI, 2.22-4.46] and 3.12 [95% CI, 2.36-4.12], respectively), MEN1 with acute pancreatitis (OR, 33.45 [95% CI, 9.25-121.02]), APC with gastritis and duodenitis (OR, 4.66 [95% CI, 2.61-8.33]), and PTEN with chronic gastritis (OR, 15.68 [95% CI, 6.01-40.92]).

Conclusions and Relevance

The findings of this genetic association study analyzing the EHRs of 3 large cohorts suggest that these new phenotypes associated with hereditary cancer genes may facilitate early detection and better management of cancers. This study highlights the potential benefits of using EHR data in genomic medicine.