Subtyping Severe Hypercholesterolemia by Genetic Determinant to Stratify Risk of Coronary Artery Disease.

BACKGROUND: Severe hypercholesterolemia, defined as LDL (low-density lipoprotein) cholesterol (LDL-C) measurement ≥190 mg/dL, is associated with increased risk for coronary artery disease (CAD). Causes of severe hypercholesterolemia include monogenic familial hypercholesterolemia, polygenic hypercholesterolemia, elevated lipoprotein(a) [Lp(a)] hypercholesteremia, polygenic hypercholesterolemia with elevated Lp(a) (two-hit), or nongenetic hypercholesterolemia. The added value of using a genetics approach to stratifying risk of incident CAD among those with severe hypercholesterolemia versus using LDL-C levels alone for risk stratification is not known. METHODS: To determine whether risk stratification by genetic cause provided better 10-year incident CAD risk stratification than LDL-C level, a retrospective cohort study comparing incident CAD risk among severe hypercholesterolemia subtypes (genetic and nongenetic causes) was performed among 130 091 UK Biobank participants. Analyses were limited to unrelated, White British or Irish participants with available exome sequencing data. Participants with cardiovascular disease at baseline were excluded from analyses of incident CAD. RESULTS: Of 130 091 individuals, 68 416 (52.6%) were women, and the mean (SD) age was 56.7 (8.0) years. Of the cohort, 9.0% met severe hypercholesterolemia criteria. Participants with LDL-C between 210 and 229 mg/dL and LDL-C ≥230 mg/dL showed modest increases in incident CAD risk relative to those with LDL-C between 190 and 209 mg/dL (210-229 mg/dL: hazard ratio [HR], 1.3 [95% CI, 1.1-1.7]; ≥230 mg/dL: HR, 1.3 [95% CI, 1.0-1.7]). In contrast, when risk was stratified by genetic subtype, monogenic familial hypercholesterolemia, elevated Lp(a), and two-hit hypercholesterolemia subtypes had increased rates of incident CAD relative to the nongenetic hypercholesterolemia subtype (monogenic familial hypercholesterolemia: HR, 2.3 [95% CI, 1.4-4.0]; elevated Lp(a): HR, 1.5 [95% CI, 1.2-2.0]; two-hit: HR, 1.9 [95% CI, 1.4-2.6]), while polygenic hypercholesterolemia did not. CONCLUSIONS: Genetics-based subtyping for monogenic familial hypercholesterolemia and Lp(a) in those with severe hypercholesterolemia provided better stratification of 10-year incident CAD risk than LDL-C-based stratification.

Yield of Familial Hypercholesterolemia Genetic and Phenotypic Diagnoses After Electronic Health Record and Genomic Data Screening.

Background Data mining of electronic health records to identify patients suspected of familial hypercholesterolemia (FH) has been limited by absence of both phenotypic and genomic data in the same cohort. Methods and Results Using the Geisinger MyCode Community Health Initiative cohort (n=130 257), we ran 2 screening algorithms (Mayo Clinic [Mayo] and flag, identify, network, deliver [FIND] FH) to determine FH genetic and phenotypic diagnostic yields. With 29 243 excluded by Mayo (for secondary causes of hypercholesterolemia, no lipid value in electronic health records), 52 034 excluded by FIND FH (insufficient data to run the model), and 187 excluded for prior FH diagnosis, a final cohort of 59 729 participants was created. Genetic diagnosis was based on presence of a pathogenic or likely pathogenic variant in FH genes. Charts from 180 variant-negative participants (60 controls, 120 identified by FIND FH and Mayo) were reviewed to calculate Dutch Lipid Clinic Network scores; a score ≥5 defined probable phenotypic FH. Mayo flagged 10 415 subjects; 194 (1.9%) had a pathogenic or likely pathogenic FH variant. FIND FH flagged 573; 34 (5.9%) had a pathogenic or likely pathogenic variant, giving a net yield from both of 197 out of 280 (70%). Confirmation of a phenotypic diagnosis was constrained by lack of electronic health record data on physical findings or family history. Phenotypic FH by chart review was present by Mayo and/or FIND FH in 13 out of 120 versus 2 out of 60 not flagged by either (P<0.09). Conclusions Applying 2 recognized FH screening algorithms to the Geisinger MyCode Community Health Initiative identified 70% of those with a pathogenic or likely pathogenic FH variant. Phenotypic diagnosis was rarely achievable due to missing data.

Association of Supernumerary Sex Chromosome Aneuploidies With Venous Thromboembolism.

Importance: An increased risk of venous thromboembolism (VTE) has been reported in men with an additional sex chromosome. The association between other sex chromosome aneuploidies and VTE is not well characterized. Objective: To determine if sex chromosome aneuploidy is associated with VTE. Design, Setting, and Participants: Retrospective cohort study of sex chromosome aneuploidy and VTE, performed by analyzing X- and Y-chromosome dosage and VTE incidence in 642 544 individuals from 2 population-scale biobanks: the US Geisinger MyCode Community Health Initiative (N = 154 519) and the UK Biobank (N = 488 025); analysis was limited to participants self-identified as White because of inadequate sample sizes for other race and ethnicity groups. A total of 108 461 unrelated MyCode participants with electronic health record follow-up ranging from September 1996 to December 2020 and 418 725 unrelated British and Irish UK Biobank participants who attended the baseline assessment between March 2006 and October 2010, with follow-up extending to November 2020, were included in analyses of VTE. Exposures: Sex chromosome aneuploidies. Main Outcomes and Measures: Individuals with 1 primary inpatient VTE diagnosis, 2 primary outpatient VTE diagnoses, or a self-reported VTE diagnosis were defined as VTE cases. P values were adjusted for multiple comparisons. Results: Identification of sex chromosome aneuploidy was undertaken among 642 544 individuals aged 18 to 90 years. Identification of a diagnosis of VTE was undertaken among 108 461 unrelated MyCode participants (65 565 [60.5%] female; mean age at last visit, 58.0 [SD, 17.6] years; median follow-up, 15.3 [IQR, 9.7] years) and among 418 725 unrelated UK Biobank participants (224 695 [53.7%] female; mean age at baseline interview, 56.9 [SD, 8.0] years; median follow-up, 12.0 [IQR, 1.6] years). Among MyCode participants, during 10 years of follow-up, 17 incident VTE events per 1353 person-years were detected among those with supernumerary sex chromosome aneuploidy (1.3% per person-year) compared with 2060 per 816 682 person-years among those with 46,XX or 46,XY (0.25% per person-year) (hazard ratio, 5.4 [95% CI, 3.4-8.7]; 10-year risk difference, 8.8% [95% CI, 4.2%-14.0%]; P < .001). Among UK Biobank participants, during 10 years of follow-up, 16 incident VTE events per 3803 person-years were detected among those with supernumerary sex chromosome aneuploidy (0.42% per person-year) compared with 4491 per 3 970 467 person-years among those with 46,XX or 46,XY (0.11% per person-year) (hazard ratio, 4.1 [95% CI, 2.5-6.7]; 10-year risk difference, 3.7% [95% CI, 1.4%-5.9%]; P < .001). Conclusions and Relevance: Adults with supernumerary sex chromosome aneuploidies compared with 2 sex chromosomes had a small but statistically significant increased risk of VTE. Further research is needed to understand the clinical implications of this association.

Prevalence and Penetrance of Rare Pathogenic Variants in Neurodevelopmental Psychiatric Genes in a Health Care System Population.

OBJECTIVE: Autism, schizophrenia, and other clinically distinct neurodevelopmental psychiatric disorders (NPDs) have shared genetic etiologies, including single-gene and multigenic copy number variants (CNVs). Because rare variants are primarily investigated in clinical cohorts, population-based estimates of their prevalence and penetrance are lacking. The authors determined the prevalence, penetrance, and NPD risk of pathogenic single-gene variants in a large health care system population. METHODS: The authors analyzed linked genomic and electronic health record (EHR) data in a subset of 90,595 participants from Geisinger's MyCode Community Health Initiative, known as the DiscovEHR cohort. Loss-of-function pathogenic variants in 94 high-confidence NPD genes were identified through exome sequencing, and NPD penetrance was calculated using preselected EHR diagnosis codes. NPD risk was estimated using a case-control comparison of DiscovEHR participants with and without NPD diagnoses. Results from single-gene variant analyses were also compared with those from 31 previously reported pathogenic NPD CNVs. RESULTS: Pathogenic variants were identified in 0.34% of the DiscovEHR cohort and demonstrated a 34.3% penetrance for NPDs. Similar to CNVs, sequence variants collectively conferred a substantial risk for several NPD diagnoses, including autism, schizophrenia, and bipolar disorder. Significant NPD risk remained after participants with intellectual disability were excluded from the analysis, confirming the association with major psychiatric disorders in individuals without severe cognitive deficits. CONCLUSIONS: Collectively, rare single-gene variants and CNVs were found in >1% of individuals in a large health care system population and play an important contributory role in mental health disorders. Diagnostic genetic testing for pathogenic variants among symptomatic individuals with NPDs could improve clinical outcomes through early intervention and anticipatory therapeutic support.

Frequency of truncating FLCN variants and Birt-Hogg-Dubé-associated phenotypes in a health care system population.

PURPOSE: Penetrance estimates of Birt-Hogg-Dubé syndrome (BHD)-associated cutaneous, pulmonary, and kidney manifestations are based on clinically ascertained families. In a health care system population, we used a genetics-first approach to estimate the prevalence of pathogenic/likely pathogenic (P/LP) truncating variants in FLCN, which cause BHD, and the penetrance of BHD-related phenotypes. METHODS: Exomes from 135,990 patient-participants in Geisinger's MyCode cohort were assessed for P/LP truncating FLCN variants. BHD-related phenotypes were evaluated from electronic health records. Association between P/LP FLCN variants and BHD-related phenotypes was assessed using Firth's logistic regression. RESULTS: P/LP truncating FLCN variants were identified in 35 individuals (1 in 3234 unrelated individuals), 68.6% of whom had BHD-related phenotype(s), including cystic lung disease (65.7%), pneumothoraces (17.1%), cutaneous manifestations (8.6%), and kidney cancer (2.9%). A total of 4 (11.4%) individuals had prior clinical BHD diagnoses. CONCLUSION: In this health care population, the frequency of P/LP truncating FLCN variants is 60 times higher than the previously reported prevalence. Although most variant-positive individuals had BHD-related phenotypes, a minority were previously clinically diagnosed, likely because cutaneous manifestations, pneumothoraces, and kidney cancer were observed at lower frequencies than in clinical cohorts. Improved clinical recognition of cystic lung disease and education concerning its association with FLCN variants could prompt evaluation for BHD.

Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank.

Cardiometabolic diseases are the leading cause of death worldwide. Despite a known genetic component, our understanding of these diseases remains incomplete. Here, we analyzed the contribution of rare variants to 57 diseases and 26 cardiometabolic traits, using data from 200,337 UK Biobank participants with whole-exome sequencing. We identified 57 gene-based associations, with broad replication of novel signals in Geisinger MyCode. There was a striking risk associated with mutations in known Mendelian disease genes, including MYBPC3, LDLR, GCK, PKD1 and TTN. Many genes showed independent convergence of rare and common variant evidence, including an association between GIGYF1 and type 2 diabetes. We identified several large effect associations for height and 18 unique genes associated with blood lipid or glucose levels. Finally, we found that between 1.0% and 2.4% of participants carried rare potentially pathogenic variants for cardiometabolic disorders. These findings may facilitate studies aimed at therapeutics and screening of these common disorders.

Medical manifestations and health care utilization among adult MyCode participants with neurodevelopmental psychiatric copy number variants.

PURPOSE: Recurrent pathogenic copy number variants (pCNVs) have large-effect impacts on brain function and represent important etiologies of neurodevelopmental psychiatric disorders (NPDs), including autism and schizophrenia. Patterns of health care utilization in adults with pCNVs have gone largely unstudied and are likely to differ in significant ways from those of children. METHODS: We compared the prevalence of NPDs and electronic health record-based medical conditions in 928 adults with 26 pCNVs to a demographically-matched cohort of pCNV-negative controls from >135,000 patient-participants in Geisinger's MyCode Community Health Initiative. We also evaluated 3 quantitative health care utilization measures (outpatient, inpatient, and emergency department visits) in both groups. RESULTS: Adults with pCNVs (24.9%) were more likely than controls (16.0%) to have a documented NPD. They had significantly higher rates of several chronic diseases, including diabetes (29.3% in participants with pCNVs vs 20.4% in participants without pCNVs) and dementia (2.2% in participants with pCNVs vs 1.0% participants without pCNVs), and twice as many annual emergency department visits. CONCLUSION: These findings highlight the potential for genetic information-specifically, pCNVs-to inform the study of health care outcomes and utilization in adults. If, as our findings suggest, adults with pCNVs have poorer health and require disproportionate health care resources, early genetic diagnosis paired with patient-centered interventions may help to anticipate problems, improve outcomes, and reduce the associated economic burden.

Population Genomic Screening for Genetic Etiologies of Neurodevelopmental/Psychiatric Disorders Demonstrates Personal Utility and Positive Participant Responses.

Genomic variants that cause neurodevelopmental/psychiatric disorders (NPD) are relatively prevalent and highly penetrant. This study aimed to understand adults' immediate responses to receiving NPD-related results to inform inclusion in population-based genomic screening programs. Nine recurrent, pathogenic copy number variants (CNVs) were identified from research exome data, clinically confirmed, and disclosed to adult participants of the Geisinger MyCode Community Health Initiative DiscovEHR cohort by experienced genetic counselors. A subset of in-person genetic counseling sessions (n = 27) were audio-recorded, transcribed, and coded using a grounded theory approach. Participant reactions were overwhelmingly positive and indicated that an NPD genetic etiology was highly valuable and personally useful. Participants frequently reported learning disabilities or other NPD that were not documented in their electronic health records and noted difficulties obtaining support for NPD needs. Most intended to share their genetic result with family members and health care providers and were interested in how their result could improve their healthcare. This study indicates that results from population-based NPD genomic screening can provide personal value for adults with NPD, were viewed positively by participants, and could improve clinical outcomes by informing symptom monitoring for NPD and co-morbidities, promoting improved health behaviors, and enhancing psychotherapeutic approaches.

Comprehensive identification of somatic nucleotide variants in human brain tissue.

BACKGROUND: Post-zygotic mutations incurred during DNA replication, DNA repair, and other cellular processes lead to somatic mosaicism. Somatic mosaicism is an established cause of various diseases, including cancers. However, detecting mosaic variants in DNA from non-cancerous somatic tissues poses significant challenges, particularly if the variants only are present in a small fraction of cells. RESULTS: Here, the Brain Somatic Mosaicism Network conducts a coordinated, multi-institutional study to examine the ability of existing methods to detect simulated somatic single-nucleotide variants (SNVs) in DNA mixing experiments, generate multiple replicates of whole-genome sequencing data from the dorsolateral prefrontal cortex, other brain regions, dura mater, and dural fibroblasts of a single neurotypical individual, devise strategies to discover somatic SNVs, and apply various approaches to validate somatic SNVs. These efforts lead to the identification of 43 bona fide somatic SNVs that range in variant allele fractions from ~ 0.005 to ~ 0.28. Guided by these results, we devise best practices for calling mosaic SNVs from 250× whole-genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrate that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees. CONCLUSIONS: This study provides a unified set of best practices to detect somatic SNVs in non-cancerous tissues. The data and methods are freely available to the scientific community and should serve as a guide to assess the contributions of somatic SNVs to neuropsychiatric diseases.

Leveraging population-based exome screening to impact clinical care: The evolution of variant assessment in the Geisinger MyCode research project.

Exome and genome sequencing are increasingly utilized in research studies and clinical care and can provide clinically relevant information beyond the initial intent for sequencing, including medically actionable secondary findings. Despite ongoing debate about sharing this information with patients and participants, a growing number of clinical laboratories and research programs routinely report secondary findings that increase the risk for selected diseases. Recently, there has been a push to maximize the potential benefit of this practice by implementing proactive genomic screening at the population level irrespective of medical history, but the feasibility of deploying population-scale proactive genomic screening requires scaling key elements of the genomic data evaluation process. Herein, we describe the motivation, development, and implementation of a population-scale variant-first screening pipeline combining bioinformatics-based filtering with a manual review process to screen for clinically relevant findings in research exomes generated through the DiscovEHR collaboration within Geisinger's MyCode® research project. Consistent with other studies, this pipeline yields a screen-positive detection rate between 2.1 and 2.6% (depending on inclusion of those with prior indication-based testing) in 130,048 adult MyCode patient-participants screened for clinically relevant findings in 60 genes. Our variant-first pipeline affords cost and time savings by filtering out negative cases, thereby avoiding analysis of each exome one-by-one, as typically employed in the diagnostic setting. While research is still needed to fully appreciate the benefits of population genomic screening, MyCode provides the first demonstration of a program at scale to help shape how population genomic screening is integrated into routine clinical care.

Molecular Diagnostic Yield of Exome Sequencing in Patients With Cerebral Palsy.

Importance: Cerebral palsy is a common neurodevelopmental disorder affecting movement and posture that often co-occurs with other neurodevelopmental disorders. Individual cases of cerebral palsy are often attributed to birth asphyxia; however, recent studies indicate that asphyxia accounts for less than 10% of cerebral palsy cases. Objective: To determine the molecular diagnostic yield of exome sequencing (prevalence of pathogenic and likely pathogenic variants) in individuals with cerebral palsy. Design, Setting, and Participants: A retrospective cohort study of patients with cerebral palsy that included a clinical laboratory referral cohort with data accrued between 2012 and 2018 and a health care-based cohort with data accrued between 2007 and 2017. Exposures: Exome sequencing with copy number variant detection. Main Outcomes and Measures: The primary outcome was the molecular diagnostic yield of exome sequencing. Results: Among 1345 patients from the clinical laboratory referral cohort, the median age was 8.8 years (interquartile range, 4.4-14.7 years; range, 0.1-66 years) and 601 (45%) were female. Among 181 patients in the health care-based cohort, the median age was 41.9 years (interquartile range, 28.0-59.6 years; range, 4.8-89 years) and 96 (53%) were female. The molecular diagnostic yield of exome sequencing was 32.7% (95% CI, 30.2%-35.2%) in the clinical laboratory referral cohort and 10.5% (95% CI, 6.0%-15.0%) in the health care-based cohort. The molecular diagnostic yield ranged from 11.2% (95% CI, 6.4%-16.2%) for patients without intellectual disability, epilepsy, or autism spectrum disorder to 32.9% (95% CI, 25.7%-40.1%) for patients with all 3 comorbidities. Pathogenic and likely pathogenic variants were identified in 229 genes (29.5% of 1526 patients); 86 genes were mutated in 2 or more patients (20.1% of 1526 patients) and 10 genes with mutations were independently identified in both cohorts (2.9% of 1526 patients). Conclusions and Relevance: Among 2 cohorts of patients with cerebral palsy who underwent exome sequencing, the prevalence of pathogenic and likely pathogenic variants was 32.7% in a cohort that predominantly consisted of pediatric patients and 10.5% in a cohort that predominantly consisted of adult patients. Further research is needed to understand the clinical implications of these findings.

Developing and Optimizing Innovative Tools to Address Familial Hypercholesterolemia Underdiagnosis: Identification Methods, Patient Activation, and Cascade Testing for Familial Hypercholesterolemia.

BACKGROUND: Familial hypercholesterolemia (FH) is the most common cardiovascular genetic disorder and, if left untreated, is associated with increased risk of premature atherosclerotic cardiovascular disease, the leading cause of preventable death in the United States. Although FH is common, fatal, and treatable, it is underdiagnosed and undertreated due to a lack of systematic methods to identify individuals with FH and limited uptake of cascade testing. METHODS AND RESULTS: This mixed-method, multi-stage study will optimize, test, and implement innovative approaches for both FH identification and cascade testing in 3 aims. To improve identification of individuals with FH, in Aim 1, we will compare and refine automated phenotype-based and genomic approaches to identify individuals likely to have FH. To improve cascade testing uptake for at-risk individuals, in Aim 2, we will use a patient-centered design thinking process to optimize and develop novel, active family communication methods. Using a prospective, observational pragmatic trial, we will assess uptake and effectiveness of each family communication method on cascade testing. Guided by an implementation science framework, in Aim 3, we will develop a comprehensive guide to identify individuals with FH. Using the Conceptual Model for Implementation Research, we will evaluate implementation outcomes including feasibility, acceptability, and perceived sustainability as well as health outcomes related to the optimized methods and tools developed in Aims 1 and 2. CONCLUSIONS: Data generated from this study will address barriers and gaps in care related to underdiagnosis of FH by developing and optimizing tools to improve FH identification and cascade testing.

Electronic health record analysis identifies kidney disease as the leading risk factor for hospitalization in confirmed COVID-19 patients.

BACKGROUND: Empirical data on conditions that increase risk of coronavirus disease 2019 (COVID-19) progression are needed to identify high risk individuals. We performed a comprehensive quantitative assessment of pre-existing clinical phenotypes associated with COVID-19-related hospitalization. METHODS: Phenome-wide association study (PheWAS) of SARS-CoV-2-positive patients from an integrated health system (Geisinger) with system-level outpatient/inpatient COVID-19 testing capacity and retrospective electronic health record (EHR) data to assess pre-COVID-19 pandemic clinical phenotypes associated with hospital admission (hospitalization). RESULTS: Of 12,971 individuals tested for SARS-CoV-2 with sufficient pre-COVID-19 pandemic EHR data at Geisinger, 1604 were SARS-CoV-2 positive and 354 required hospitalization. We identified 21 clinical phenotypes in 5 disease categories meeting phenome-wide significance (P<1.60x10-4), including: six kidney phenotypes, e.g. end stage renal disease or stage 5 CKD (OR = 11.07, p = 1.96x10-8), six cardiovascular phenotypes, e.g. congestive heart failure (OR = 3.8, p = 3.24x10-5), five respiratory phenotypes, e.g. chronic airway obstruction (OR = 2.54, p = 3.71x10-5), and three metabolic phenotypes, e.g. type 2 diabetes (OR = 1.80, p = 7.51x10-5). Additional analyses defining CKD based on estimated glomerular filtration rate, confirmed high risk of hospitalization associated with pre-existing stage 4 CKD (OR 2.90, 95% CI: 1.47, 5.74), stage 5 CKD/dialysis (OR 8.83, 95% CI: 2.76, 28.27), and kidney transplant (OR 14.98, 95% CI: 2.77, 80.8) but not stage 3 CKD (OR 1.03, 95% CI: 0.71, 1.48). CONCLUSIONS: This study provides quantitative estimates of the contribution of pre-existing clinical phenotypes to COVID-19 hospitalization and highlights kidney disorders as the strongest factors associated with hospitalization in an integrated US healthcare system.

Identification of Neuropsychiatric Copy Number Variants in a Health Care System Population.

Importance: Population screening for medically relevant genomic variants that cause diseases such as hereditary cancer and cardiovascular disorders is increasing to facilitate early disease detection or prevention. Neuropsychiatric disorders (NPDs) are common, complex disorders with clear genetic causes; yet, access to genetic diagnosis is limited. We explored whether inclusion of NPD in population-based genomic screening programs is warranted by assessing 3 key factors: prevalence, penetrance, and personal utility. Objective: To evaluate the suitability of including pathogenic copy number variants (CNVs) associated with NPD in population screening by determining their prevalence and penetrance and exploring the personal utility of disclosing results. Design, Setting, and Participants: In this cohort study, the frequency of 31 NPD CNVs was determined in patient-participants via exome data. Associated clinical phenotypes were assessed using linked electronic health records. Nine CNVs were selected for disclosure by licensed genetic counselors, and participants' psychosocial reactions were evaluated using a mixed-methods approach. A primarily adult population receiving medical care at Geisinger, a large integrated health care system in the United States with the only population-based genomic screening program approved for medically relevant results disclosure, was included. The cohort was identified from the Geisinger MyCode Community Health Initiative. Exome and linked electronic health record data were available for this cohort, which was recruited from February 2007 to April 2017. Data were collected for the qualitative analysis April 2017 through February 2018. Analysis began February 2018 and ended December 2019. Main Outcomes and Measures: The planned outcomes of this study include (1) prevalence estimate of NPD-associated CNVs in an unselected health care system population; (2) penetrance estimate of NPD diagnoses in CNV-positive individuals; and (3) qualitative themes that describe participants' responses to receiving NPD-associated genomic results. Results: Of 90 595 participants with CNV data, a pathogenic CNV was identified in 708 (0.8%; 436 women [61.6%]; mean [SD] age, 50.04 [18.74] years). Seventy percent (n = 494) had at least 1 associated clinical symptom. Of these, 28.8% (204) of CNV-positive individuals had an NPD code in their electronic health record, compared with 13.3% (11 835 of 89 887) of CNV-negative individuals (odds ratio, 2.21; 95% CI, 1.86-2.61; P < .001); 66.4% (470) of CNV-positive individuals had a history of depression and anxiety compared with 54.6% (49 118 of 89 887) of CNV-negative individuals (odds ratio, 1.53; 95% CI, 1.31-1.80; P < .001). 16p13.11 (71 [0.078%]) and 22q11.2 (108 [0.119%]) were the most prevalent deletions and duplications, respectively. Only 5.8% of individuals (41 of 708) had a previously known genetic diagnosis. Results disclosure was completed for 141 individuals. Positive participant responses included poignant reactions to learning a medical reason for lifelong cognitive and psychiatric disabilities. Conclusions and Relevance: This study informs critical factors central to the development of population-based genomic screening programs and supports the inclusion of NPD in future designs to promote equitable access to clinically useful genomic information.

Analysis of the canid Y-chromosome phylogeny using short-read sequencing data reveals the presence of distinct haplogroups among Neolithic European dogs.

BACKGROUND: Most genetic analyses of ancient and modern dogs have focused on variation in the autosomes or on the mitochondria. Mitochondrial DNA is more easily obtained from ancient samples than nuclear DNA and mitochondrial analyses have revealed important insights into the evolutionary history of canids. Utilizing a recently published dog Y-chromosome reference, we analyzed Y-chromosome sequence across a diverse collection of canids and determined the Y haplogroup of three ancient European dogs. RESULTS: We identified 1121 biallelic Y-chromosome SNVs using whole-genome sequences from 118 canids and defined variants diagnostic to distinct dog Y haplogroups. Similar to that of the mitochondria and previous more limited studies of Y diversity, we observe several deep splits in the Y-chromosome tree which may be the result of retained Y-chromosome diversity which predates dog domestication or post-domestication admixture with wolves. We find that Y-chromosomes from three ancient European dogs (4700-7000 years old) belong to distinct clades. CONCLUSIONS: We estimate that the time to the most recent comment ancestor of dog Y haplogroups is 68-151 thousand years ago. Analysis of three Y-chromosomes from the Neolithic confirms long stranding population structure among European dogs.

Genetic Effects on the Correlation Structure of CVD Risk Factors: Exome-Wide Data From a Ghanaian Population.

Plasma concentration of plasminogen activator inhibitor-1 (PAI-1) is highly correlated with several cardiovascular disease (CVD) risk factors. It also plays a direct role in CVD, including myocardial infarction and stroke, by impeding the dissolution of thrombi in the blood. Insofar as PAI-1 links CVD's risk factors to its endpoints, genetic variants modulating the relationship between PAI-1 and risk factors may be of particular clinical and biological interest. The high heritability of PAI-1, which has not been explained by genetic association studies, may also, in large part, be due to this relationship with CVD risk factors. Using exome-wide data from 1,032 Ghanaian study participants, we tested for heterogeneity of correlation by genotype between PAI-1 and 4 CVD risk factors (body mass index, triglycerides, mean arterial pressure, and fasting glucose) under the hypothesis that loci involved in the relationship between PAI-1 and other risk factors will also modify their correlational structure. We found more significant heterogeneities of correlation by genotype than we found marginal effects, with no evidence of type I inflation. The most significant result among all univariate and multivariate tests performed in this study was the heterogeneity of correlation between PAI-1 and mean arterial pressure at rs10738554, near SLC24A2, a gene previously associated with high blood pressure in African Americans.

Y-Chromosome Structural Diversity in the Bonobo and Chimpanzee Lineages.

The male-specific regions of primate Y-chromosomes (MSY) are enriched for multi-copy genes highly expressed in the testis. These genes are located in large repetitive sequences arranged as palindromes, inverted-, and tandem repeats termed amplicons. In humans, these genes have critical roles in male fertility and are essential for the production of sperm. The structure of human and chimpanzee amplicon sequences show remarkable difference relative to the remainder of the genome, a difference that may be the result of intense selective pressure on male fertility. Four subspecies of common chimpanzees have undergone extended periods of isolation and appear to be in the early process of subspeciation. A recent study found amplicons enriched for testis-expressed genes on the primate X-chromosome the target of hard selective sweeps, and male-fertility genes on the Y-chromosome may also be the targets of selection. However, little is understood about Y-chromosome amplicon diversity within and across chimpanzee populations. Here, we analyze nine common chimpanzee (representing three subspecies: Pan troglodytes schweinfurthii, Pan troglodytes ellioti, and Pan troglodytes verus) and two bonobo (Pan paniscus) male whole-genome sequences to assess Y ampliconic copy-number diversity across the Pan genus. We observe that the copy number of Y chromosome amplicons is variable among chimpanzees and bonobos, and identify several lineage-specific patterns, including variable copy number of azoospermia candidates RBMY and DAZ We detect recurrent switchpoints of copy-number change along the ampliconic tracts across chimpanzee populations, which may be the result of localized genome instability or selective forces.

Evidence for extensive pleiotropy among pharmacogenes.

AIM: We sought to identify potential pleiotropy involving pharmacogenes. METHODS: We tested 184 functional variants in 34 pharmacogenes for associations using a custom grouping of International Classification and Disease, Ninth Revision billing codes extracted from deidentified electronic health records of 6892 patients. RESULTS: We replicated several associations including ABCG2 (rs2231142) and gout (p = 1.73 × 10(-7); odds ratio [OR]: 1.73; 95% CI: 1.40-2.12); and SLCO1B1 (rs4149056) and jaundice (p = 2.50 × 10(-4); OR: 1.67; 95% CI: 1.27-2.20). CONCLUSION: In this systematic screen for phenotypic associations with functional variants, several novel genotype-phenotype combinations also achieved phenome-wide significance, including SLC15A2 rs1143672 and renal osteodystrophy (p = 2.67 × 10(-) (6); OR: 0.61; 95% CI: 0.49-0.75).

Population Stratification in the Context of Diverse Epidemiologic Surveys Sans Genome-Wide Data.

Population stratification or confounding by genetic ancestry is a potential cause of false associations in genetic association studies. Estimation of and adjustment for genetic ancestry has become common practice thanks in part to the availability of ancestry informative markers on genome-wide association study (GWAS) arrays. While array data is now widespread, these data are not ubiquitous as several large epidemiologic and clinic-based studies lack genome-wide data. One such large epidemiologic-based study lacking genome-wide data accessible to investigators is the National Health and Nutrition Examination Surveys (NHANES), population-based cross-sectional surveys of Americans linked to demographic, health, and lifestyle data conducted by the Centers for Disease Control and Prevention. DNA samples (n = 14,998) were extracted from biospecimens from consented NHANES participants between 1991-1994 (NHANES III, phase 2) and 1999-2002 and represent three major self-identified racial/ethnic groups: non-Hispanic whites (n = 6,634), non-Hispanic blacks (n = 3,458), and Mexican Americans (n = 3,950). We as the Epidemiologic Architecture for Genes Linked to Environment study genotyped candidate gene and GWAS-identified index variants in NHANES as part of the larger Population Architecture using Genomics and Epidemiology I study for collaborative genetic association studies. To enable basic quality control such as estimation of genetic ancestry to control for population stratification in NHANES san genome-wide data, we outline here strategies that use limited genetic data to identify the markers optimal for characterizing genetic ancestry. From among 411 and 295 autosomal SNPs available in NHANES III and NHANES 1999-2002, we demonstrate that markers with ancestry information can be identified to estimate global ancestry. Despite limited resolution, global genetic ancestry is highly correlated with self-identified race for the majority of participants, although less so for ethnicity. Overall, the strategies outlined here for a large epidemiologic study can be applied to other datasets accessible for genotype-phenotype studies but are sans genome-wide data.