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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 (ED) 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% in 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.

IntroductionAdolescent idiopathic scoliosis (AIS) is a common musculoskeletal disorder with strong evidence for a genetic contribution. CNVs play an important role in congenital scoliosis, but their role in idiopathic scoliosis has been largely unexplored.MethodsExome sequence data from 1197 AIS cases and 1664 in-house controls was analysed using coverage data to identify rare CNVs. CNV calls were filtered to include only highly confident CNVs with >10 average reads per region and mean log-ratio of coverage consistent with single-copy duplication or deletion. The frequency of 55 common recurrent CNVs was determined and correlated with clinical characteristics.ResultsDistal chromosome 16p11.2 microduplications containing the gene SH2B1 were found in 0.7% of AIS cases (8/1197). We replicated this finding in two additional AIS cohorts (8/1097 and 2/433), resulting in 0.7% (18/2727) of all AIS cases harbouring a chromosome 16p11.2 microduplication, compared with 0.06% of local controls (1/1664) and 0.04% of published controls (8/19584) (p=2.28×10−11, OR=16.15). Furthermore, examination of electronic health records of 92 455 patients from the Geisinger health system showed scoliosis in 30% (20/66) patients with chromosome 16p11.2 microduplications containing SH2B1 compared with 7.6% (10/132) of controls (p=5.6×10−4, OR=3.9).ConclusionsRecurrent distal chromosome 16p11.2 duplications explain nearly 1% of AIS. Distal chromosome 16p11.2 duplications may contribute to scoliosis pathogenesis by directly impairing growth or by altering expression of nearby genes, such as TBX6. Individuals with distal chromosome 16p11.2 microduplications should be screened for scoliosis to facilitate early treatment.

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.

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.

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.

Advances in genotyping technology have, over the past decade, enabled the focused search for common genetic variation associated with human diseases and traits. With the recently increased availability of detailed phenotypic data from electronic health records and epidemiological studies, the impact of one or more genetic variants on the phenome is starting to be characterized both in clinical and population-based settings using phenome-wide association studies (PheWAS). These studies reveal a number of challenges that will need to be overcome to unlock the full potential of PheWAS for the characterization of the complex human genome-phenome relationship.

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 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.

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-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.

The prevalence of obesity has been increasing globally, resulting in increased rates of type 2 diabetes, cardiovascular disease, and certain cancers (1). Risk factors for obesity include a sedentary lifestyle, overconsumption of energy, and genetic susceptibility (2, 3). Recent genome-wide association studies have identified several common genetic variants associated with body mass index (BMI; weight (kg)/height (m)2), a measure of adiposity (4, 5). However, the mechanisms underlying these associations have yet to be characterized. Given that macronutrient consumption plays a key role in obesity (6), understanding the biological links between inherited genetic variation and components of energy intake may suggest strategies for reducing the increasing prevalence of obesity (7). To date, at least 32 independent loci have been found to be associated with BMI (8). Many of the genes involved, such as the brain-derived neurotrophic factor gene (BDNF), the melanocortin 4 receptor gene (MC4R), and the fat mass and obesity-associated gene (FTO), are expressed in the central nervous system (9–11), suggesting that they may act through the neurological control of various aspects of energy balance. Indeed, studies have found that obesity risk variants in intron 1 of the FTO gene are associated with greater energy consumption (12–17) or frequency of energy consumption (18) and a reduction in satiety (19–21) and intake control (12, 22, 23). In a recent study of approximately 2,100 adults of mostly European descent (77%), McCaffery et al. (18) found that FTO rs1421085 was associated with percentage of calories derived from fat. Additionally, this and another study found that obesity risk variants in the potassium channel tetramerization domain-containing 15 gene (KCTD15) and BDNF were associated with macronutrient intake (24) or increased meat and dairy intake (18). However, many of these previous studies were conducted in populations of primarily European descent. To further understand the relationship between obesity single-nucleotide polymorphisms (SNPs) and energy consumption, we investigated, as part of the Population Architecture using Genomics and Epidemiology (PAGE) Study (25), the relationship between 6 obesity risk variants and intake of macronutrients (carbohydrate, protein, ethanol, and fat and its subtypes) among type 2 diabetes-free adults from 5 racial/ethnic groups.

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).

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.

Calcineurin-inhibitors CI are immunosuppressive agents prescribed to patients after solid organ transplant to prevent rejection. Although these drugs have been transformative for allograft survival, long-term use is complicated by side effects including nephrotoxicity. Given the narrow therapeutic index of CI, therapeutic drug monitoring is used to prevent acute rejection from underdosing and acute toxicity from overdosing, but drug monitoring does not alleviate long-term side effects. Patients on calcineurin-inhibitors for long periods almost universally experience declines in renal function, and a subpopulation of transplant recipients ultimately develop chronic kidney disease that may progress to end stage renal disease attributable to calcineurin inhibitor toxicity (CNIT). Pharmacogenomics has the potential to identify patients who are at high risk for developing advanced chronic kidney disease caused by CNIT and providing them with existing alternate immunosuppressive therapy. In this study we utilized BioVU, Vanderbilt University Medical Center’s DNA biorepository linked to de-identified electronic medical records to identify a cohort of 115 heart transplant recipients prescribed calcineurin-inhibitors to identify genetic risk factors for CNIT We identified 37 cases of nephrotoxicity in our cohort, defining nephrotoxicity as a monthly median estimated glomerular filtration rate (eGFR) < 30 mL/min/1.73m2 at least six months post-transplant for at least three consecutive months. All heart transplant patients were genotyped on the Illumina ADME Core Panel, a pharmacogenomic genotyping platform that assays 184 variants across 34 genes. In Cox regression analysis adjusting for age at transplant, pre-transplant chronic kidney disease, pre-transplant diabetes, and the three most significant principal components (PCAs), we did not identify any markers that met our multiple-testing threshold. As a secondary analysis we also modeled post-transplant eGFR directly with linear mixed models adjusted for age at transplant, cyclosporine use, median BMI, and the three most significant principal components. While no SNPs met our threshold for significance, a SNP previously identified in genetic studies of the dosing of tacrolimus CYP3A5 rs776746, replicated in an adjusted analysis at an uncorrected p-value of 0.02 (coeff(S.E.) = 14.60(6.41)). While larger independent studies will be required to further validate this finding, this study underscores the EMRs usefulness as a resource for longitudinal pharmacogenetic study designs.

Summary BackgroundVKORC1 and CYP2C9 are important contributors to warfarin dose variability, but explain less variability for individuals of African descent than for those of European or Asian descent. We aimed to identify additional variants contributing to warfarin dose requirements in African Americans. MethodsWe did a genome-wide association study of discovery and replication cohorts. Samples from African-American adults (aged ≥18 years) who were taking a stable maintenance dose of warfarin were obtained at International Warfarin Pharmacogenetics Consortium (IWPC) sites and the University of Alabama at Birmingham (Birmingham, AL, USA). Patients enrolled at IWPC sites but who were not used for discovery made up the independent replication cohort. All participants were genotyped. We did a stepwise conditional analysis, conditioning first for VKORC1 −1639G→A, followed by the composite genotype of CYP2C9*2 and CYP2C9*3. We prespecified a genome-wide significance threshold of p

Aim: Warfarin pharmacogenomic algorithms reduce dosing error, but perform poorly in non-European–Americans. Electronic health record (EHR) systems linked to biobanks may allow for pharmacogenomic analysis, but they have not yet been used for this purpose. Patients & methods: We used BioVU, the Vanderbilt EHR-linked DNA repository, to identify European–Americans (n = 1022) and African–Americans (n = 145) on stable warfarin therapy and evaluated the effect of 15 pharmacogenetic variants on stable warfarin dose. Results: Associations between variants in VKORC1, CYP2C9 and CYP4F2 with weekly dose were observed in European–Americans as well as additional variants in CYP2C9 and CALU in African–Americans. Compared with traditional 5 mg/day dosing, implementing the US FDA recommendations or the International Warfarin Pharmacogenomics Consortium (IWPC) algorithm reduced error in weekly dose in European–Americans (13.5–12.4 and 9.5 mg/week, respectively) but less so in African–Americans (15.2–15.0 and 13.8 mg/week, respectively). By further incorporating associated variants specific for European–Americans and African–Americans in an expanded algorithm, dose-prediction error reduced to 9.1 mg/week (95% CI: 8.4–9.6) in European–Americans and 12.4 mg/week (95% CI: 10.0–13.2) in African–Americans. The expanded algorithm explained 41 and 53% of dose variation in African–Americans and European–Americans, respectively, compared with 29 and 50%, respectively, for the IWPC algorithm. Implementing these predictions via dispensable pill regimens similarly reduced dosing error. Conclusion: These results validate EHR-linked DNA biorepositories as real-world resources for pharmacogenomic validation and discovery. Original submitted 24 August 2011; Revision submitted 9 November 2011