Publications by authors named "David R Crosslin"

93 Publications

Penetrance of Breast Cancer Susceptibility Genes From the eMERGE III Network.

JNCI Cancer Spectr 2021 Aug 8;5(4):pkab044. Epub 2021 May 8.

Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA.

Background: Unbiased estimates of penetrance are challenging but critically important to make informed choices about strategies for risk management through increased surveillance and risk-reducing interventions.

Methods: We studied the penetrance and clinical outcomes of 7 breast cancer susceptibility genes (, , , , , , and ) in almost 13 458 participants unselected for personal or family history of breast cancer. We identified 242 female participants with pathogenic or likely pathogenic variants in 1 of the 7 genes for penetrance analyses, and 147 women did not previously know their genetic results.

Results: Out of the 147 women, 32 women were diagnosed with breast cancer at an average age of 52.8 years. Estimated penetrance by age 60 years ranged from 17.8% to 43.8%, depending on the gene. In clinical-impact analysis, 42.3% (95% confidence interval = 31.3% to 53.3%) of women had taken actions related to their genetic results, and 2 new breast cancer cases were identified within the first 12 months after genetic results disclosure.

Conclusions: Our study provides population-based penetrance estimates for the understudied genes , , and and highlights the importance of using unselected populations for penetrance studies. It also demonstrates the potential clinical impact of genetic testing to improve health care through early diagnosis and preventative screening.
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http://dx.doi.org/10.1093/jncics/pkab044DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346699PMC
August 2021

Genomic considerations for FHIR®; eMERGE implementation lessons.

J Biomed Inform 2021 06 28;118:103795. Epub 2021 Apr 28.

Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.

Structured representation of clinical genetic results is necessary for advancing precision medicine. The Electronic Medical Records and Genomics (eMERGE) Network's Phase III program initially used a commercially developed XML message format for standardized and structured representation of genetic results for electronic health record (EHR) integration. In a desire to move towards a standard representation, the network created a new standardized format based upon Health Level Seven Fast Healthcare Interoperability Resources (HL7® FHIR®), to represent clinical genomics results. These new standards improve the utility of HL7® FHIR® as an international healthcare interoperability standard for management of genetic data from patients. This work advances the establishment of standards that are being designed for broad adoption in the current health information technology landscape.
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http://dx.doi.org/10.1016/j.jbi.2021.103795DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8583906PMC
June 2021

Medical records-based chronic kidney disease phenotype for clinical care and "big data" observational and genetic studies.

NPJ Digit Med 2021 Apr 13;4(1):70. Epub 2021 Apr 13.

Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA.

Chronic Kidney Disease (CKD) represents a slowly progressive disorder that is typically silent until late stages, but early intervention can significantly delay its progression. We designed a portable and scalable electronic CKD phenotype to facilitate early disease recognition and empower large-scale observational and genetic studies of kidney traits. The algorithm uses a combination of rule-based and machine-learning methods to automatically place patients on the staging grid of albuminuria by glomerular filtration rate ("A-by-G" grid). We manually validated the algorithm by 451 chart reviews across three medical systems, demonstrating overall positive predictive value of 95% for CKD cases and 97% for healthy controls. Independent case-control validation using 2350 patient records demonstrated diagnostic specificity of 97% and sensitivity of 87%. Application of the phenotype to 1.3 million patients demonstrated that over 80% of CKD cases are undetected using ICD codes alone. We also demonstrated several large-scale applications of the phenotype, including identifying stage-specific kidney disease comorbidities, in silico estimation of kidney trait heritability in thousands of pedigrees reconstructed from medical records, and biobank-based multicenter genome-wide and phenome-wide association studies.
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http://dx.doi.org/10.1038/s41746-021-00428-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044136PMC
April 2021

Genome-wide association studies of low back pain and lumbar spinal disorders using electronic health record data identify a locus associated with lumbar spinal stenosis.

Pain 2021 08;162(8):2263-2272

Genomic Medicine Institute, Geisinger, Danville, PA, United States.

Abstract: Identifying genetic risk factors for lumbar spine disorders may lead to knowledge regarding underlying mechanisms and the development of new treatments. We conducted a genome-wide association study involving 100,811 participants with genotypes and longitudinal electronic health record data from the Electronic Medical Records and Genomics Network and Geisinger Health. Cases and controls were defined using validated algorithms and clinical diagnostic codes. Electronic health record-defined phenotypes included low back pain requiring healthcare utilization (LBP-HC), lumbosacral radicular syndrome (LSRS), and lumbar spinal stenosis (LSS). Genome-wide association study used logistic regression with additive genetic effects adjusting for age, sex, site-specific factors, and ancestry (principal components). A fixed-effect inverse-variance weighted meta-analysis was conducted. Genetic variants of genome-wide significance (P < 5 × 10-8) were carried forward for replication in an independent sample from UK Biobank. Phenotype prevalence was 48.8% for LBP-HC, 19.8% for LSRS, and 7.9% for LSS. No variants were significantly associated with LBP-HC. One locus was associated with LSRS (lead variant rs146153280:C>G, odds ratio [OR] = 1.17 for G, P = 2.1 × 10-9), but was not replicated. Another locus on chromosome 2 spanning GFPT1, NFU1, and AAK1 was associated with LSS (lead variant rs13427243:G>A, OR = 1.10 for A, P = 4.3 × 10-8) and replicated in UK Biobank (OR = 1.11, P = 5.4 × 10-5). This was the first genome-wide association study meta-analysis of lumbar spinal disorders using electronic health record data. We identified 2 novel associations with LSRS and LSS; the latter was replicated in an independent sample.
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http://dx.doi.org/10.1097/j.pain.0000000000002221DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8277660PMC
August 2021

Copy Number Variant Analysis and Genome-wide Association Study Identify Loci with Large Effect for Vesicoureteral Reflux.

J Am Soc Nephrol 2021 Feb 17. Epub 2021 Feb 17.

Department of Clinical Genetics, Our Lady's Children's Hospital Crumlin, Dublin, Ireland.

Background: Vesicoureteral reflux (VUR) is a common, familial genitourinary disorder, and a major cause of pediatric urinary tract infection (UTI) and kidney failure. The genetic basis of VUR is not well understood.

Methods: A diagnostic analysis sought rare, pathogenic copy number variant (CNV) disorders among 1737 patients with VUR. A GWAS was performed in 1395 patients and 5366 controls, of European ancestry.

Results: Altogether, 3% of VUR patients harbored an undiagnosed rare CNV disorder, such as the 1q21.1, 16p11.2, 22q11.21, and triple X syndromes ((OR, 3.12; 95% CI, 2.10 to 4.54; =6.35×10) The GWAS identified three study-wide significant and five suggestive loci with large effects (ORs, 1.41-6.9), containing canonical developmental genes expressed in the developing urinary tract ( and ). In particular, 3.3% of VUR patients were homozygous for an intronic variant in (rs13013890; OR, 3.65; 95% CI, 2.39 to 5.56; =1.86×10). This locus was associated with multiple genitourinary phenotypes in the UK Biobank and eMERGE studies. Analysis of mutant mice confirmed the role of Wnt5a signaling in bladder and ureteric morphogenesis.

Conclusions: These data demonstrate the genetic heterogeneity of VUR. Altogether, 6% of patients with VUR harbored a rare CNV or a common variant genotype conferring an OR >3. Identification of these genetic risk factors has multiple implications for clinical care and for analysis of outcomes in VUR.
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http://dx.doi.org/10.1681/ASN.2020050681DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8017540PMC
February 2021

The FamilyTalk randomized controlled trial: patient-reported outcomes in clinical genetic sequencing for colorectal cancer.

Cancer Causes Control 2021 May 16;32(5):483-492. Epub 2021 Feb 16.

Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington Medical Center, Seattle, WA, USA.

As genetics gains favor in clinical oncology, it is important to address patient concerns around confidentiality, privacy, and security of genetic information that might otherwise limit its utilization. We designed a randomized controlled trial to assess the social impact of an online educational tool (FamilyTalk) to increase family communication about colorectal cancer (CRC) risk and screening. Of 208 randomized participants, 149 (71.6%) returned six-month surveys. Overall, there was no difference in CRC screening between the study arms. Privacy and confidentiality concerns about medical and genetic information, reactions to genetic test results, and lifestyle changes did not differ between arms. Participants with pathogenic or likely pathogenic (P/LP) and variant of uncertain significance (VUS) results were more likely than those with negative results to report that the results accurately predicted their disease risks (OR 5.37, p = 0.02 and OR 3.13, p = 0.02, respectively). This trial demonstrated no evidence that FamilyTalk impacted patient-reported outcomes. Low power, due to the limited number of participants with P/LP results in the overall sample, as well as the short follow-up period, could have contributed to the null findings.
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http://dx.doi.org/10.1007/s10552-021-01398-1DOI Listing
May 2021

What improves the likelihood of people receiving genetic test results communicating to their families about genetic risk?

Patient Educ Couns 2021 04 7;104(4):726-731. Epub 2021 Jan 7.

Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington Medical Center, Seattle, USA.

Objective: We currently rely on probands to communicate genetic testing results and health risks within a family to stimulate preventive behaviors, such as cascade testing. Rates of guidelines-based cascade testing are low, possibly due to low frequency or non-urgent communication of risk among family members. Understanding what is being communicated and why may help improve interventions that increase communication and rates of cascade testing.

Methods: Participants (n = 189) who were to receive both positive and negative colorectal cancer (CRC) sequencing results completed surveys on family communication, family functioning, impact of cancer in the family, and future communication of risk and were participants in eMERGE3. Questions were taken from existing surveys and administered electronically using email and a web driven tool.

Results: Common family member targets of CRC risk communication, before results were received, were mothers and fathers, then sisters and grandchildren and finally, children and brothers. A communication impact score of 0.66 (sd = 0.83) indicated low-to-moderate communication impact. Age and education were significantly associated with frequency of familial communication, but not on the cancer-related impact of familial communication.

Conclusions: There is infrequent communication about cancer risk from probands to family members.

Practice Implications: These results demonstrate an opportunity to help families improve communication.
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http://dx.doi.org/10.1016/j.pec.2021.01.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8005444PMC
April 2021

Association between triglycerides, known risk SNVs and conserved rare variation in SLC25A40 in a multi-ancestry cohort.

BMC Med Genomics 2021 01 6;14(1):11. Epub 2021 Jan 6.

Division of Medical Genetics, School of Medicine, University of Washington Medical Center, 1705 NE Pacific St, Box 357720, Seattle, WA, 98195, USA.

Background: Elevated triglycerides (TG) are associated with, and may be causal for, cardiovascular disease (CVD), and co-morbidities such as type II diabetes and metabolic syndrome. Pathogenic variants in APOA5 and APOC3 as well as risk SNVs in other genes [APOE (rs429358, rs7412), APOA1/C3/A4/A5 gene cluster (rs964184), INSR (rs7248104), CETP (rs7205804), GCKR (rs1260326)] have been shown to affect TG levels. Knowledge of genetic causes for elevated TG may lead to early intervention and targeted treatment for CVD. We previously identified linkage and association of a rare, highly conserved missense variant in SLC25A40, rs762174003, with hypertriglyceridemia (HTG) in a single large family, and replicated this association with rare, highly conserved missense variants in a European American and African American sample.

Methods: Here, we analyzed a longitudinal mixed-ancestry cohort (European, African and Asian ancestry, N = 8966) from the Electronic Medical Record and Genomics (eMERGE) Network. We tested associations between median TG and the genes of interest, using linear regression, adjusting for sex, median age, median BMI, and the first two principal components of ancestry.

Results: We replicated the association between TG and APOC3, APOA5, and risk variation at APOE, APOA1/C3/A4/A5 gene cluster, and GCKR. We failed to replicate the association between rare, highly conserved variation at SLC25A40 and TG, as well as for risk variation at INSR and CETP.

Conclusions: Analysis using data from electronic health records presents challenges that need to be overcome. Although large amounts of genotype data is becoming increasingly accessible, usable phenotype data can be challenging to obtain. We were able to replicate known, strong associations, but were unable to replicate moderate associations due to the limited sample size and missing drug information.
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http://dx.doi.org/10.1186/s12920-020-00854-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789246PMC
January 2021

Loci identified by a genome-wide association study of carotid artery stenosis in the eMERGE network.

Genet Epidemiol 2021 02 22;45(1):4-15. Epub 2020 Sep 22.

Division of Medical Genetics, School of Medicine, University of Washington, Seattle, Washington, USA.

Carotid artery atherosclerotic disease (CAAD) is a risk factor for stroke. We used a genome-wide association (GWAS) approach to discover genetic variants associated with CAAD in participants in the electronic Medical Records and Genomics (eMERGE) Network. We identified adult CAAD cases with unilateral or bilateral carotid artery stenosis and controls without evidence of stenosis from electronic health records at eight eMERGE sites. We performed GWAS with a model adjusting for age, sex, study site, and genetic principal components of ancestry. In eMERGE we found 1793 CAAD cases and 17,958 controls. Two loci reached genome-wide significance, on chr6 in LPA (rs10455872, odds ratio [OR] (95% confidence interval [CI]) = 1.50 (1.30-1.73), p = 2.1 × 10 ) and on chr7, an intergenic single nucleotide variant (SNV; rs6952610, OR (95% CI) = 1.25 (1.16-1.36), p = 4.3 × 10 ). The chr7 association remained significant in the presence of the LPA SNV as a covariate. The LPA SNV was also associated with coronary heart disease (CHD; 4199 cases and 11,679 controls) in this study (OR (95% CI) = 1.27 (1.13-1.43), p = 5 × 10 ) but the chr7 SNV was not (OR (95% CI) = 1.03 (0.97-1.09), p = .37). Both variants replicated in UK Biobank. Elevated lipoprotein(a) concentrations ([Lp(a)]) and LPA variants associated with elevated [Lp(a)] have previously been associated with CAAD and CHD, including rs10455872. With electronic health record phenotypes in eMERGE and UKB, we replicated a previously known association and identified a novel locus associated with CAAD.
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http://dx.doi.org/10.1002/gepi.22360DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7891640PMC
February 2021

Evaluation of the MC4R gene across eMERGE network identifies many unreported obesity-associated variants.

Int J Obes (Lond) 2021 01 20;45(1):155-169. Epub 2020 Sep 20.

Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA.

Background/objectives: Melanocortin-4 receptor (MC4R) plays an essential role in food intake and energy homeostasis. More than 170 MC4R variants have been described over the past two decades, with conflicting reports regarding the prevalence and phenotypic effects of these variants in diverse cohorts. To determine the frequency of MC4R variants in large cohort of different ancestries, we evaluated the MC4R coding region for 20,537 eMERGE participants with sequencing data plus additional 77,454 independent individuals with genome-wide genotyping data at this locus.

Subjects/methods: The sequencing data were obtained from the eMERGE phase III study, in which multisample variant call format calls have been generated, curated, and annotated. In addition to penetrance estimation using body mass index (BMI) as a binary outcome, GWAS and PheWAS were performed using median BMI in linear regression analyses. All results were adjusted for principal components, age, sex, and sites of genotyping.

Results: Targeted sequencing data of MC4R revealed 125 coding variants in 1839 eMERGE participants including 30 unreported coding variants that were predicted to be functionally damaging. Highly penetrant unreported variants included (L325I, E308K, D298N, S270F, F261L, T248A, D111V, and Y80F) in which seven participants had obesity class III defined as BMI ≥ 40 kg/m. In GWAS analysis, in addition to known risk haplotype upstream of MC4R (best variant rs6567160 (P = 5.36 × 10, Beta = 0.37), a novel rare haplotype was detected which was protective against obesity and encompassed the V103I variant with known gain-of-function properties (P = 6.23 × 10, Beta = -0.62). PheWAS analyses extended this protective effect of V103I to type 2 diabetes, diabetic nephropathy, and chronic renal failure independent of BMI.

Conclusions: MC4R screening in a large eMERGE cohort confirmed many previous findings, extend the MC4R pleotropic effects, and discovered additional MC4R rare alleles that probably contribute to obesity.
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http://dx.doi.org/10.1038/s41366-020-00675-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7752751PMC
January 2021

Genome-wide Modeling of Polygenic Risk Score in Colorectal Cancer Risk.

Am J Hum Genet 2020 09 5;107(3):432-444. Epub 2020 Aug 5.

School of Public Health, Imperial College London, London SW7 2AZ, UK.

Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these genetic variants can be used jointly for CRC risk prediction. In this paper, we derived and compared different approaches to generating predictive polygenic risk scores (PRS) from genome-wide association studies (GWASs) including 55,105 CRC-affected case subjects and 65,079 control subjects of European ancestry. We built the PRS in three ways, using (1) 140 previously identified and validated CRC loci; (2) SNP selection based on linkage disequilibrium (LD) clumping followed by machine-learning approaches; and (3) LDpred, a Bayesian approach for genome-wide risk prediction. We tested the PRS in an independent cohort of 101,987 individuals with 1,699 CRC-affected case subjects. The discriminatory accuracy, calculated by the age- and sex-adjusted area under the receiver operating characteristics curve (AUC), was highest for the LDpred-derived PRS (AUC = 0.654) including nearly 1.2 M genetic variants (the proportion of causal genetic variants for CRC assumed to be 0.003), whereas the PRS of the 140 known variants identified from GWASs had the lowest AUC (AUC = 0.629). Based on the LDpred-derived PRS, we are able to identify 30% of individuals without a family history as having risk for CRC similar to those with a family history of CRC, whereas the PRS based on known GWAS variants identified only top 10% as having a similar relative risk. About 90% of these individuals have no family history and would have been considered average risk under current screening guidelines, but might benefit from earlier screening. The developed PRS offers a way for risk-stratified CRC screening and other targeted interventions.
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http://dx.doi.org/10.1016/j.ajhg.2020.07.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7477007PMC
September 2020

Relationship between genetic knowledge and familial communication of CRC risk and intent to communicate CRCP genetic information: insights from FamilyTalk eMERGE III.

Transl Behav Med 2021 03;11(2):563-572

Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington Medical Center, Seattle, WA, USA.

Successful translation of genetic information into patient-centered care and improved outcomes depends, at least in part, on patients' genetic knowledge. Although genetic knowledge is believed to be an important facilitator of familial communication of genetic risk information, empirical evidence of this association is lacking. We examined whether genetic knowledge was related to frequency of current familial communication about colorectal cancer and polyp (CRCP) risk, and future intention to share CRCP-related genomic test results with family members in a clinical sample of patients. We recruited 189 patients eligible for clinical CRCP sequencing to the eMERGE III FamilyTalk randomized controlled trial and surveyed them about genetic knowledge and familial communication at baseline. Participants were primarily Caucasian, 47% male, average age of 68 years, mostly well educated, and with high-income levels. Genetic knowledge was positively associated with future-intended familial communication of genetic information (odds ratio = 1.11, 95% confidence interval: 1.02-1.23), but not associated with current communication of CRC risk (β = 0.01, p = .58). Greater current communication of CRC risk was associated with better family functioning (β = 0.04, p = 8.2e-5). Participants' genetic knowledge in this study was minimally associated with their intended familial communication of genetic information. Although participants have good intentions of communication, family-level factors may hinder actual follow through of these intentions. Continued focus on improving proband's genetic knowledge coupled with interventions to overcome family-level barriers to communication may be needed to improve familial communication rates.
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http://dx.doi.org/10.1093/tbm/ibaa054DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7963296PMC
March 2021

The polygenic architecture of left ventricular mass mirrors the clinical epidemiology.

Sci Rep 2020 05 5;10(1):7561. Epub 2020 May 5.

Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.

Left ventricular (LV) mass is a prognostic biomarker for incident heart disease and all-cause mortality. Large-scale genome-wide association studies have identified few SNPs associated with LV mass. We hypothesized that a polygenic discovery approach using LV mass measurements made in a clinical population would identify risk factors and diseases associated with adverse LV remodeling. We developed a polygenic single nucleotide polymorphism-based predictor of LV mass in 7,601 individuals with LV mass measurements made during routine clinical care. We tested for associations between this predictor and 894 clinical diagnoses measured in 58,838 unrelated genotyped individuals. There were 29 clinical phenotypes associated with the LV mass genetic predictor at FDR q < 0.05. Genetically predicted higher LV mass was associated with modifiable cardiac risk factors, diagnoses related to organ dysfunction and conditions associated with abnormal cardiac structure including heart failure and atrial fibrillation. Secondary analyses using polygenic predictors confirmed a significant association between higher LV mass and body mass index and, in men, associations with coronary atherosclerosis and systolic blood pressure. In summary, these analyses show that LV mass-associated genetic variability associates with diagnoses of cardiac diseases and with modifiable risk factors which contribute to these diseases.
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http://dx.doi.org/10.1038/s41598-020-64525-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7200691PMC
May 2020

A genome-wide association study of polycystic ovary syndrome identified from electronic health records.

Am J Obstet Gynecol 2020 10 11;223(4):559.e1-559.e21. Epub 2020 Apr 11.

Genomic Medicine Institute, Geisinger, Danville, PA. Electronic address:

Background: Polycystic ovary syndrome is the most common endocrine disorder affecting women of reproductive age. A number of criteria have been developed for clinical diagnosis of polycystic ovary syndrome, with the Rotterdam criteria being the most inclusive. Evidence suggests that polycystic ovary syndrome is significantly heritable, and previous studies have identified genetic variants associated with polycystic ovary syndrome diagnosed using different criteria. The widely adopted electronic health record system provides an opportunity to identify patients with polycystic ovary syndrome using the Rotterdam criteria for genetic studies.

Objective: To identify novel associated genetic variants under the same phenotype definition, we extracted polycystic ovary syndrome cases and unaffected controls based on the Rotterdam criteria from the electronic health records and performed a discovery-validation genome-wide association study.

Study Design: We developed a polycystic ovary syndrome phenotyping algorithm on the basis of the Rotterdam criteria and applied it to 3 electronic health record-linked biobanks to identify cases and controls for genetic study. In the discovery phase, we performed an individual genome-wide association study using the Geisinger MyCode and the Electronic Medical Records and Genomics cohorts, which were then meta-analyzed. We attempted validation of the significant association loci (P<1×10) in the BioVU cohort. All association analyses used logistic regression, assuming an additive genetic model, and adjusted for principal components to control for population stratification. An inverse-variance fixed-effect model was adopted for meta-analysis. In addition, we examined the top variants to evaluate their associations with each criterion in the phenotyping algorithm. We used the STRING database to characterize protein-protein interaction network.

Results: Using the same algorithm based on the Rotterdam criteria, we identified 2995 patients with polycystic ovary syndrome and 53,599 population controls in total (2742 cases and 51,438 controls from the discovery phase; 253 cases and 2161 controls in the validation phase). We identified 1 novel genome-wide significant variant rs17186366 (odds ratio [OR]=1.37 [1.23, 1.54], P=2.8×10) located near SOD2. In addition, 2 loci with suggestive association were also identified: rs113168128 (OR=1.72 [1.42, 2.10], P=5.2×10), an intronic variant of ERBB4 that is independent from the previously published variants, and rs144248326 (OR=2.13 [1.52, 2.86], P=8.45×10), a novel intronic variant in WWTR1. In the further association tests of the top 3 single-nucleotide polymorphisms with each criterion in the polycystic ovary syndrome algorithm, we found that rs17186366 (SOD2) was associated with polycystic ovaries and hyperandrogenism, whereas rs11316812 (ERBB4) and rs144248326 (WWTR1) were mainly associated with oligomenorrhea or infertility. We also validated the previously reported association with DENND1A1. Using the STRING database to characterize protein-protein interactions, we found both ERBB4 and WWTR1 can interact with YAP1, which has been previously associated with polycystic ovary syndrome.

Conclusion: Through a discovery-validation genome-wide association study on polycystic ovary syndrome identified from electronic health records using an algorithm based on Rotterdam criteria, we identified and validated a novel genome-wide significant association with a variant near SOD2. We also identified a novel independent variant within ERBB4 and a suggestive association with WWTR1. With previously identified polycystic ovary syndrome gene YAP1, the ERBB4-YAP1-WWTR1 network suggests involvement of the epidermal growth factor receptor and the Hippo pathway in the multifactorial etiology of polycystic ovary syndrome.
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http://dx.doi.org/10.1016/j.ajog.2020.04.004DOI Listing
October 2020

A Polygenic and Phenotypic Risk Prediction for Polycystic Ovary Syndrome Evaluated by Phenome-Wide Association Studies.

J Clin Endocrinol Metab 2020 06;105(6)

Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.

Context: As many as 75% of patients with polycystic ovary syndrome (PCOS) are estimated to be unidentified in clinical practice.

Objective: Utilizing polygenic risk prediction, we aim to identify the phenome-wide comorbidity patterns characteristic of PCOS to improve accurate diagnosis and preventive treatment.

Design, Patients, And Methods: Leveraging the electronic health records (EHRs) of 124 852 individuals, we developed a PCOS risk prediction algorithm by combining polygenic risk scores (PRS) with PCOS component phenotypes into a polygenic and phenotypic risk score (PPRS). We evaluated its predictive capability across different ancestries and perform a PRS-based phenome-wide association study (PheWAS) to assess the phenomic expression of the heightened risk of PCOS.

Results: The integrated polygenic prediction improved the average performance (pseudo-R2) for PCOS detection by 0.228 (61.5-fold), 0.224 (58.8-fold), 0.211 (57.0-fold) over the null model across European, African, and multi-ancestry participants respectively. The subsequent PRS-powered PheWAS identified a high level of shared biology between PCOS and a range of metabolic and endocrine outcomes, especially with obesity and diabetes: "morbid obesity", "type 2 diabetes", "hypercholesterolemia", "disorders of lipid metabolism", "hypertension", and "sleep apnea" reaching phenome-wide significance.

Conclusions: Our study has expanded the methodological utility of PRS in patient stratification and risk prediction, especially in a multifactorial condition like PCOS, across different genetic origins. By utilizing the individual genome-phenome data available from the EHR, our approach also demonstrates that polygenic prediction by PRS can provide valuable opportunities to discover the pleiotropic phenomic network associated with PCOS pathogenesis.
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http://dx.doi.org/10.1210/clinem/dgz326DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7453038PMC
June 2020

Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9.

BMC Cardiovasc Disord 2019 10 29;19(1):240. Epub 2019 Oct 29.

Department Primary Care & Population Health, University College London, London, UK.

Background: We characterised the phenotypic consequence of genetic variation at the PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9.

Methods: Published and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Seventeen randomized placebo controlled PCSK9 inhibitor trials were included, providing data on 79,578 participants. Results were scaled to a one mmol/L lower LDL-C concentration.

Results: The PCSK9 GS (comprising 4 SNPs) associations with plasma lipid and apolipoprotein levels were consistent in direction with treatment effects. The GS odds ratio (OR) for myocardial infarction (MI) was 0.53 (95% CI 0.42; 0.68), compared to a PCSK9 inhibitor effect of 0.90 (95% CI 0.86; 0.93). For ischemic stroke ORs were 0.84 (95% CI 0.57; 1.22) for the GS, compared to 0.85 (95% CI 0.78; 0.93) in the drug trials. ORs with type 2 diabetes mellitus (T2DM) were 1.29 (95% CI 1.11; 1.50) for the GS, as compared to 1.00 (95% CI 0.96; 1.04) for incident T2DM in PCSK9 inhibitor trials. No genetic associations were observed for cancer, heart failure, atrial fibrillation, chronic obstructive pulmonary disease, or Alzheimer's disease - outcomes for which large-scale trial data were unavailable.

Conclusions: Genetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. While indicating an increased risk of T2DM, no other possible safety concerns were shown; although precision was moderate.
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http://dx.doi.org/10.1186/s12872-019-1187-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6820948PMC
October 2019

Association of Genetic Risk of Obesity with Postoperative Complications Using Mendelian Randomization.

World J Surg 2020 01;44(1):84-94

The Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.

Background: The extent to which obesity and genetics determine postoperative complications is incompletely understood.

Methods: We performed a retrospective study using two population cohorts with electronic health record (EHR) data. The first included 736,726 adults with body mass index (BMI) recorded between 1990 and 2017 at Vanderbilt University Medical Center. The second cohort consisted of 65,174 individuals from 12 institutions contributing EHR and genome-wide genotyping data to the Electronic Medical Records and Genomics (eMERGE) Network. Pairwise logistic regression analyses were used to measure the association of BMI categories with postoperative complications derived from International Classification of Disease-9 codes, including postoperative infection, incisional hernia, and intestinal obstruction. A genetic risk score was constructed from 97 obesity-risk single-nucleotide polymorphisms for a Mendelian randomization study to determine the association of genetic risk of obesity on postoperative complications. Logistic regression analyses were adjusted for sex, age, site, and race/principal components.

Results: Individuals with overweight or obese BMI (≥25 kg/m) had increased risk of incisional hernia (odds ratio [OR] 1.7-5.5, p < 3.1 × 10), and people with obesity (BMI ≥ 30 kg/m) had increased risk of postoperative infection (OR 1.2-2.3, p < 2.5 × 10). In the eMERGE cohort, genetically predicted BMI was associated with incisional hernia (OR 2.1 [95% CI 1.8-2.5], p = 1.4 × 10) and postoperative infection (OR 1.6 [95% CI 1.4-1.9], p = 3.1 × 10). Association findings were similar after limitation of the cohorts to those who underwent abdominal procedures.

Conclusions: Clinical and Mendelian randomization studies suggest that obesity, as measured by BMI, is associated with the development of postoperative incisional hernia and infection.
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http://dx.doi.org/10.1007/s00268-019-05202-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6925615PMC
January 2020

Rates of Actionable Genetic Findings in Individuals with Colorectal Cancer or Polyps Ascertained from a Community Medical Setting.

Am J Hum Genet 2019 09 15;105(3):526-533. Epub 2019 Aug 15.

Department of Medicine (Medical Genetics), University of Washington School of Medicine, Seattle, WA 98195, USA; Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA. Electronic address:

As clinical testing for Mendelian causes of colorectal cancer (CRC) is largely driven by recognition of family history and early age of onset, the rates of such findings among individuals with prevalent CRC not recognized to have these features is largely unknown. We evaluated actionable genomic findings in community-based participants ascertained by three phenotypes: (1) CRC, (2) one or more adenomatous colon polyps, and (3) control participants over age 59 years without CRC or colon polyps. These participants underwent sequencing for a panel of genes that included colorectal cancer/polyp (CRC/P)-associated and actionable incidental findings genes. Those with CRC had a 3.8% rate of positive results (pathogenic or likely pathogenic) for a CRC-associated gene variant, despite generally being older at CRC onset (mean 72 years). Those ascertained for polyps had a 0.8% positive rate and those with no CRC/P had a positive rate of 0.2%. Though incidental finding rates unrelated to colon cancer were similar for all groups, our positive rate for cardiovascular findings exceeds disease prevalence, suggesting that variant interpretation challenges or low penetrance in these genes. The rate of HFE c.845G>A (p.Cys282Tyr) homozygotes in the CRC group reinforces a previously reported, but relatively unexplored, association between hemochromatosis and CRC. These results in a general clinical population suggest that current testing strategies could be improved in order to better detect Mendelian CRC-associated conditions. These data also underscore the need for additional functional and familial evidence to clarify the pathogenicity and penetrance of variants deemed pathogenic or likely pathogenic, particularly among the actionable genes associated with cardiovascular disease.
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http://dx.doi.org/10.1016/j.ajhg.2019.07.012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6731361PMC
September 2019

GWAS and enrichment analyses of non-alcoholic fatty liver disease identify new trait-associated genes and pathways across eMERGE Network.

BMC Med 2019 07 17;17(1):135. Epub 2019 Jul 17.

Division of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati School of Medicine, Cincinnati, OH, USA.

Background: Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver illness with a genetically heterogeneous background that can be accompanied by considerable morbidity and attendant health care costs. The pathogenesis and progression of NAFLD is complex with many unanswered questions. We conducted genome-wide association studies (GWASs) using both adult and pediatric participants from the Electronic Medical Records and Genomics (eMERGE) Network to identify novel genetic contributors to this condition.

Methods: First, a natural language processing (NLP) algorithm was developed, tested, and deployed at each site to identify 1106 NAFLD cases and 8571 controls and histological data from liver tissue in 235 available participants. These include 1242 pediatric participants (396 cases, 846 controls). The algorithm included billing codes, text queries, laboratory values, and medication records. Next, GWASs were performed on NAFLD cases and controls and case-only analyses using histologic scores and liver function tests adjusting for age, sex, site, ancestry, PC, and body mass index (BMI).

Results: Consistent with previous results, a robust association was detected for the PNPLA3 gene cluster in participants with European ancestry. At the PNPLA3-SAMM50 region, three SNPs, rs738409, rs738408, and rs3747207, showed strongest association (best SNP rs738409 p = 1.70 × 10). This effect was consistent in both pediatric (p = 9.92 × 10) and adult (p = 9.73 × 10) cohorts. Additionally, this variant was also associated with disease severity and NAFLD Activity Score (NAS) (p = 3.94 × 10, beta = 0.85). PheWAS analysis link this locus to a spectrum of liver diseases beyond NAFLD with a novel negative correlation with gout (p = 1.09 × 10). We also identified novel loci for NAFLD disease severity, including one novel locus for NAS score near IL17RA (rs5748926, p = 3.80 × 10), and another near ZFP90-CDH1 for fibrosis (rs698718, p = 2.74 × 10). Post-GWAS and gene-based analyses identified more than 300 genes that were used for functional and pathway enrichment analyses.

Conclusions: In summary, this study demonstrates clear confirmation of a previously described NAFLD risk locus and several novel associations. Further collaborative studies including an ethnically diverse population with well-characterized liver histologic features of NAFLD are needed to further validate the novel findings.
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http://dx.doi.org/10.1186/s12916-019-1364-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636057PMC
July 2019

A phenome-wide association study to discover pleiotropic effects of , , and .

NPJ Genom Med 2019 11;4. Epub 2019 Feb 11.

20Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI 54449 USA.

We conducted an electronic health record (EHR)-based phenome-wide association study (PheWAS) to discover pleiotropic effects of variants in three lipoprotein metabolism genes , , and . Using high-density genotype data, we tested the associations of variants in the three genes with 1232 EHR-derived binary phecodes in 51,700 European-ancestry (EA) individuals and 585 phecodes in 10,276 African-ancestry (AA) individuals; 457 , 730 , and 720 variants were filtered by imputation quality (  > 0.4), minor allele frequency (>1%), linkage disequilibrium (  < 0.3), and association with LDL-C levels, yielding a set of two , three , and five variants in EA but no variants in AA. Cases and controls were defined for each phecode using the PheWAS package in R. Logistic regression assuming an additive genetic model was used with adjustment for age, sex, and the first two principal components. Significant associations were tested in additional cohorts from Vanderbilt University ( = 29,713), the Marshfield Clinic Personalized Medicine Research Project ( = 9562), and UK Biobank ( = 408,455). We identified one , two , and two variants significantly associated with an examined phecode. Only one of the variants was associated with a non-lipid disease phecode, ("myopia") but this association was not significant in the replication cohorts. In this large-scale PheWAS we did not find LDL-C-related variants in , , and to be associated with non-lipid-related phenotypes including diabetes, neurocognitive disorders, or cataracts.
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http://dx.doi.org/10.1038/s41525-019-0078-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370860PMC
February 2019

Probing the Virtual Proteome to Identify Novel Disease Biomarkers.

Circulation 2018 11;138(22):2469-2481

Department of Medicine, Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (E.W.K.).

Background: Proteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a "virtual proteomic" approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals.

Methods: We used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651).

Results: In the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate q<0.1. Among these, 13 associations involved lipid (n=7) or atherosclerosis (n=6) phenotypes. We tested each association for validation in MDCS using directly measured protein levels. At Bonferroni-adjusted significance thresholds, levels of apolipoprotein E isoforms were associated with hyperlipidemia, and circulating C-type lectin domain family 1 member B and platelet-derived growth factor receptor-β predicted subclinical atherosclerosis. Odds ratios for carotid atherosclerosis were 1.31 (95% CI, 1.08-1.58; P=0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66-0.94; P=0.008) per 1-SD increment in platelet-derived growth factor receptor-β.

Conclusions: We demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.
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http://dx.doi.org/10.1161/CIRCULATIONAHA.118.036063DOI Listing
November 2018

Unfolding of hidden white blood cell count phenotypes for gene discovery using latent class mixed modeling.

Genes Immun 2019 09 21;20(7):555-565. Epub 2018 Nov 21.

Department of Biomedical Informatics Medical Education, School of Medicine, University of Washington, Seattle, WA, 98109, USA.

Resting-state white blood cell (WBC) count is a marker of inflammation and immune system health. There is evidence that WBC count is not fixed over time and there is heterogeneity in WBC trajectory that is associated with morbidity and mortality. Latent class mixed modeling (LCMM) is a method that can identify unobserved heterogeneity in longitudinal data and attempts to classify individuals into groups based on a linear model of repeated measurements. We applied LCMM to repeated WBC count measures derived from electronic medical records of participants of the National Human Genetics Research Institute (NHRGI) electronic MEdical Record and GEnomics (eMERGE) network study, revealing two WBC count trajectory phenotypes. Advancing these phenotypes to GWAS, we found genetic associations between trajectory class membership and regions on chromosome 1p34.3 and chromosome 11q13.4. The chromosome 1 region contains CSF3R, which encodes the granulocyte colony-stimulating factor receptor. This protein is a major factor in neutrophil stimulation and proliferation. The association on chromosome 11 contain genes RNF169 and XRRA1; both involved in the regulation of double-strand break DNA repair.
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http://dx.doi.org/10.1038/s41435-018-0051-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6541537PMC
September 2019

The eMERGE genotype set of 83,717 subjects imputed to ~40 million variants genome wide and association with the herpes zoster medical record phenotype.

Genet Epidemiol 2019 02 8;43(1):63-81. Epub 2018 Oct 8.

Feinberg School of Medicine, Northwestern University, Chicago, Illinois.

The Electronic Medical Records and Genomics (eMERGE) network is a network of medical centers with electronic medical records linked to existing biorepository samples for genomic discovery and genomic medicine research. The network sought to unify the genetic results from 78 Illumina and Affymetrix genotype array batches from 12 contributing medical centers for joint association analysis of 83,717 human participants. In this report, we describe the imputation of eMERGE results and methods to create the unified imputed merged set of genome-wide variant genotype data. We imputed the data using the Michigan Imputation Server, which provides a missing single-nucleotide variant genotype imputation service using the minimac3 imputation algorithm with the Haplotype Reference Consortium genotype reference set. We describe the quality control and filtering steps used in the generation of this data set and suggest generalizable quality thresholds for imputation and phenotype association studies. To test the merged imputed genotype set, we replicated a previously reported chromosome 6 HLA-B herpes zoster (shingles) association and discovered a novel zoster-associated loci in an epigenetic binding site near the terminus of chromosome 3 (3p29).
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http://dx.doi.org/10.1002/gepi.22167DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375696PMC
February 2019

A study paradigm integrating prospective epidemiologic cohorts and electronic health records to identify disease biomarkers.

Nat Commun 2018 08 30;9(1):3522. Epub 2018 Aug 30.

Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.

Defining the full spectrum of human disease associated with a biomarker is necessary to advance the biomarker into clinical practice. We hypothesize that associating biomarker measurements with electronic health record (EHR) populations based on shared genetic architectures would establish the clinical epidemiology of the biomarker. We use Bayesian sparse linear mixed modeling to calculate SNP weightings for 53 biomarkers from the Atherosclerosis Risk in Communities study. We use the SNP weightings to computed predicted biomarker values in an EHR population and test associations with 1139 diagnoses. Here we report 116 associations meeting a Bonferroni level of significance. A false discovery rate (FDR)-based significance threshold reveals more known and undescribed associations across a broad range of biomarkers, including biometric measures, plasma proteins and metabolites, functional assays, and behaviors. We confirm an inverse association between LDL-cholesterol level and septicemia risk in an independent epidemiological cohort. This approach efficiently discovers biomarker-disease associations.
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http://dx.doi.org/10.1038/s41467-018-05624-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6117367PMC
August 2018

An Atlas of Genetic Variation Linking Pathogen-Induced Cellular Traits to Human Disease.

Cell Host Microbe 2018 08;24(2):308-323.e6

Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC 27710, USA; Division of Infectious Diseases, Department of Medicine, School of Medicine, Duke University, Durham, NC 27710, USA. Electronic address:

Pathogens have been a strong driving force for natural selection. Therefore, understanding how human genetic differences impact infection-related cellular traits can mechanistically link genetic variation to disease susceptibility. Here we report the Hi-HOST Phenome Project (H2P2): a catalog of cellular genome-wide association studies (GWAS) comprising 79 infection-related phenotypes in response to 8 pathogens in 528 lymphoblastoid cell lines. Seventeen loci surpass genome-wide significance for infection-associated phenotypes ranging from pathogen replication to cytokine production. We combined H2P2 with clinical association data from patients to identify a SNP near CXCL10 as a risk factor for inflammatory bowel disease. A SNP in the transcriptional repressor ZBTB20 demonstrated pleiotropy, likely through suppression of multiple target genes, and was associated with viral hepatitis. These data are available on a web portal to facilitate interpreting human genome variation through the lens of cell biology and should serve as a rich resource for the research community.
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http://dx.doi.org/10.1016/j.chom.2018.07.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6093297PMC
August 2018

LPA Variants Are Associated With Residual Cardiovascular Risk in Patients Receiving Statins.

Circulation 2018 10;138(17):1839-1849

RIKEN Center for Integrative Medical Sciences, Yokohama, Japan (M.K., S.M., M.H., Y.M.).

Background: Coronary heart disease (CHD) is a leading cause of death globally. Although therapy with statins decreases circulating levels of low-density lipoprotein cholesterol and the incidence of CHD, additional events occur despite statin therapy in some individuals. The genetic determinants of this residual cardiovascular risk remain unknown.

Methods: We performed a 2-stage genome-wide association study of CHD events during statin therapy. We first identified 3099 cases who experienced CHD events (defined as acute myocardial infarction or the need for coronary revascularization) during statin therapy and 7681 controls without CHD events during comparable intensity and duration of statin therapy from 4 sites in the Electronic Medical Records and Genomics Network. We then sought replication of candidate variants in another 160 cases and 1112 controls from a fifth Electronic Medical Records and Genomics site, which joined the network after the initial genome-wide association study. Finally, we performed a phenome-wide association study for other traits linked to the most significant locus.

Results: The meta-analysis identified 7 single nucleotide polymorphisms at a genome-wide level of significance within the LPA/PLG locus associated with CHD events on statin treatment. The most significant association was for an intronic single nucleotide polymorphism within LPA/PLG (rs10455872; minor allele frequency, 0.069; odds ratio, 1.58; 95% confidence interval, 1.35-1.86; P=2.6×10). In the replication cohort, rs10455872 was also associated with CHD events (odds ratio, 1.71; 95% confidence interval, 1.14-2.57; P=0.009). The association of this single nucleotide polymorphism with CHD events was independent of statin-induced change in low-density lipoprotein cholesterol (odds ratio, 1.62; 95% confidence interval, 1.17-2.24; P=0.004) and persisted in individuals with low-density lipoprotein cholesterol ≤70 mg/dL (odds ratio, 2.43; 95% confidence interval, 1.18-4.75; P=0.015). A phenome-wide association study supported the effect of this region on coronary heart disease and did not identify noncardiovascular phenotypes.

Conclusions: Genetic variations at the LPA locus are associated with CHD events during statin therapy independently of the extent of low-density lipoprotein cholesterol lowering. This finding provides support for exploring strategies targeting circulating concentrations of lipoprotein(a) to reduce CHD events in patients receiving statins.
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http://dx.doi.org/10.1161/CIRCULATIONAHA.117.031356DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6202211PMC
October 2018

A vascular endothelial growth factor A genetic variant is associated with improved ventricular function and transplant-free survival after surgery for non-syndromic CHD.

Cardiol Young 2018 Jan 20;28(1):39-45. Epub 2017 Sep 20.

1Department of Cardiothoracic Surgery,The Children's Hospital of Philadelphia,Philadelphia,Pennsylvania,United States of America.

Background: We have previously shown that the minor alleles of vascular endothelial growth factor A (VEGFA) single-nucleotide polymorphism rs833069 and superoxide dismutase 2 (SOD2) single-nucleotide polymorphism rs2758331 are both associated with improved transplant-free survival after surgery for CHD in infants, but the underlying mechanisms are unknown. We hypothesised that one or both of these minor alleles are associated with better systemic ventricular function, resulting in improved survival.

Methods: This study is a follow-up analysis of 422 non-syndromic CHD patients who underwent neonatal cardiac surgery with cardiopulmonary bypass. Echocardiographic reports were reviewed. Systemic ventricular function was subjectively categorised as normal, or as mildly, moderately, or severely depressed. The change in function was calculated as the change from the preoperative study to the last available study. Stepwise linear regression, adjusting for covariates, was performed for the outcome of change in ventricular function. Model comparison was performed using Akaike's information criterion. Only variables that improved the model prediction of change in systemic ventricular function were retained in the final model.

Results: Genetic and echocardiographic data were available for 335/422 subjects (79%). Of them, 33 (9.9%) developed worse systemic ventricular function during a mean follow-up period of 13.5 years. After covariate adjustment, the presence of the VEGFA minor allele was associated with preserved ventricular function (p=0.011).

Conclusions: These data support the hypothesis that the mechanism by which the VEGFA single-nucleotide polymorphism rs833069 minor allele improves survival may be the preservation of ventricular function. Further studies are needed to validate this genotype-phenotype association and to determine whether this mechanism is related to increased vascular endothelial growth factor production.
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http://dx.doi.org/10.1017/S1047951117001391DOI Listing
January 2018

Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals.

BioData Min 2017 24;10:25. Epub 2017 Jul 24.

Department of Population Health Sciences, Department of Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, WI USA.

Background: The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglycerides (TG).

Results: Our analysis consisted of a discovery phase using a merged dataset of five different cohorts ( = 12,853 to  = 16,849 depending on lipid phenotype) and a replication phase with ten independent cohorts totaling up to 36,938 additional samples. Filters are often applied before interaction testing to correct for the burden of testing all pairwise interactions. We used two different filters: 1. A filter that tested only single nucleotide polymorphisms (SNPs) with a main effect of  < 0.001 in a previous association study. 2. A filter that only tested interactions identified by Biofilter 2.0. Pairwise models that reached an interaction significance level of  < 0.001 in the discovery dataset were tested for replication. We identified thirteen SNP-SNP models that were significant in more than one replication cohort after accounting for multiple testing.

Conclusions: These results may reveal novel insights into the genetic etiology of lipid levels. Furthermore, we developed a pipeline to perform a computationally efficient interaction analysis with multi-cohort replication.
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http://dx.doi.org/10.1186/s13040-017-0145-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5525436PMC
July 2017
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