Copy number variation analysis in the context of electronic medical records and large-scale genomics consortium efforts

The goal of this paper is to review recent research on copy number variations (CNVs) and their association with complex and rare diseases. In the latter part of this paper, we focus on how large biorepositories such as the electronic medical record and genomics (eMERGE) consortium may be best leveraged to systematically mine for potentially pathogenic CNVs, and we end with a discussion of how such variants might be reported back for inclusion in electronic medical records as part of medical history

Population Dynamics of the Beet Leafhopper in Northeastern Oregon and Incidence of the Beet Leafhopper-Transmitted Virescence Agent Phytoplasma

Beet leafhoppers were collected weekly on yellow sticky traps placed at 36 locations in Morrow and Umatilla Counties in northeastern Oregon in April through November 2007, 2008, and 2009. Insects were counted, collected, and a subset of the insects was tested for the presence of the beet leafhopper-transmitted virescence agent phytoplasma, the causal agent of potato purple top disease in this region. Beet leafhoppers were present throughout the sampling period and the number of insects collected peaked in June of each year with smaller peaks in July and October. Of the 804 insects tested for phytoplasma in 2007, 2008, and 2009, 21, 18, and 22% tested positive for phytoplasma, respectively. Most of the phytoplasma-positive insects were collected from mid-June through July. Positive insects, however, were collected as late as 13 November in 2007 and 2008. These data indicate that a relatively high proportion of the beet leafhoppers in this area are harboring the phytoplasma. Therefore, the potential for development of purple top disease of potatoes from migrating beet leafhoppers in this important potato producing region is quite high and measures to control this pest throughout the growing season are probably necessary in order to reduce disease pressure.Keywords: Plant diseases, BLTVA, Phytoplasm

Genetic variation in the HLA region is associated with susceptibility to herpes zoster.

Herpes zoster, commonly referred to as shingles, is caused by the varicella zoster virus (VZV). VZV initially manifests as chicken pox, most commonly in childhood, can remain asymptomatically latent in nerve tissues for many years and often re-emerges as shingles. Although reactivation may be related to immune suppression, aging and female sex, most inter-individual variability in re-emergence risk has not been explained to date. We performed a genome-wide association analyses in 22,981 participants (2280 shingles cases) from the electronic Medical Records and Genomics Network. Using Cox survival and logistic regression, we identified a genomic region in the combined and European ancestry groups that has an age of onset effect reaching genome-wide significance (P>1.0 × 10(-8)). This region tags the non-coding gene HCP5 (HLA Complex P5) in the major histocompatibility complex. This gene is an endogenous retrovirus and likely influences viral activity through regulatory functions. Variants in this genetic region are known to be associated with delay in development of AIDS in people infected by HIV. Our study provides further suggestion that this region may have a critical role in viral suppression and could potentially harbor a clinically actionable variant for the shingles vaccine

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

IMPORTANCE: Vascular dysfunction and capillary leak are common in critically ill COVID-19 patients, but identification of endothelial pathways involved in COVID-19 pathogenesis has been limited. Angiopoietin-like 4 (ANGPTL4) is a protein secreted in response to hypoxic and nutrient-poor conditions that has a variety of biological effects including vascular injury and capillary leak. OBJECTIVES: To assess the role of ANGPTL4 in COVID-19-related outcomes. DESIGN SETTING AND PARTICIPANTS: Two hundred twenty-five COVID-19 ICU patients were enrolled from April 2020 to May 2021 in a prospective, multicenter cohort study from three different medical centers, University of Washington, University of Southern California and New York University. MAIN OUTCOMES AND MEASURES: Plasma ANGPTL4 was measured on days 1, 7, and 14 after ICU admission. We used previously published tissue proteomic data and lung single nucleus RNA (snRNA) sequencing data from specimens collected from COVID-19 patients to determine the tissues and cells that produce ANGPTL4. RESULTS: Higher plasma ANGPTL4 concentrations were significantly associated with worse hospital mortality (adjusted odds ratio per log CONCLUSIONS AND RELEVANCE: ANGPTL4 is expressed in pulmonary epithelial cells and fibroblasts and is associated with clinical prognosis in critically ill COVID-19 patients

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants

A polygenic and phenotypic risk prediction for polycystic ovary syndrome evaluated by phenomewide association studies

Context: As many as 75% of patients with polycystic ovary syndrome (PCOS) are estimated tobe unidentified in clinical practice. Objective: Utilizing polygenic risk prediction, we aim to identify the phenome-widecomorbidity patterns characteristic of PCOS to improve accurate diagnosis and preventivetreatment.Design, Patients, and Methods: Leveraging the electronic health records (EHRs) of 124 852individuals, 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). Weevaluated its predictive capability across different ancestries and perform a PRS-based phenomewide association study (PheWAS) to assess the phenomic expression of the heightened risk ofPCOS.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 modelacross European, African, and multi-ancestry participants respectively. The subsequent PRSpowered PheWAS identified a high level of shared biology between PCOS and a range ofmetabolic 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 stratificationand risk prediction, especially in a multifactorial condition like PCOS, across different geneticorigins. By utilizing the individual genome-phenome data available from the EHR, our approachalso demonstrates that polygenic prediction by PRS can provide valuable opportunities todiscover the pleiotropic phenomic network associated with PCOS pathogenesis.Abbreviations: AA, African ancestry; ANOVA, analysis of variance; BMI, body mass index; EA,European ancestry; EHR, electronic health records; eMERGE, electronic Medical Records andGenomics Network; GWAS, genome-wide association study; IBD, identity-by-descent; ICDCM, International Classification of Diseases, Clinical Modification; LD, linkage disequilibrium;MA, multi-ancestry; MAF, minor allele frequency; NIH, National Institutes of Health; PCA,principal component analysis; PheWAS, phenome-wide association study; PCOS, polycysticovary syndrome; PPRS, polygenic and phenotypic risk score; PRS, polygenic risk sc

Assessing Potato Psyllid Haplotypes in Potato Crops in the Pacific Northwestern United States

The potato psyllid, Bactericera cockerelli (Šulc), is a vector of the bacterium ‘Candidatus Liberibacter solanacearum’ (Lso) that has been linked to the economically devastating zebra chip disease of potato. To date, four haplotypes of the potato psyllid have been identified and include Central, Western, Northwestern, and Southwestern haplotypes. Zebra chip was reported in potato crops in the Pacific Northwestern United States for the first time in 2011, and the Lso-infected psyllids collected from zebra chip-affected fields were identified as the Western haplotype. Additional studies have reported a mix of the Western and Northwestern psyllid haplotypes in the Pacific Northwest. The present study further examined psyllid population dynamics over the duration of the 2012 potato season in the Pacific Northwest by haplotype analysis of 864 potato psyllids collected from potato fields in Washington, Oregon, and Idaho. In the Yakima Valley of Washington and the lower Columbia Basin of Washington and Oregon, the Northwestern haplotype was predominant (78%), and was detected earlier in the season than the Western haplotype. Interestingly, in south-central Idaho, all four psyllid haplotypes were identified, but the predominant haplotype was the Western haplotype (77%). Here, Northwestern psyllids were detected early in the season from June to mid-August, whereas Central psyllidswere detected in late July and thereafter. These results suggest that haplotype composition of psyllid populations in potato fields throughout the 2012 growing season in south-central Idaho differed greatly from those in Washington and Oregon. Additionally, all psyllids were analyzed for the presence of Lso, and no Lso-positive psyllids were found in Washington and Oregon, whereas Lso-positive psyllids were found in south-central Idaho. These Lso-positive psyllids consisted of the Western, Northwestern, and Central haplotypes

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

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 (n = 12,853 to n = 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 p < 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 p < 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

Genome-Wide Association Studies in Atherosclerosis

Cardiovascular disease remains the major cause of worldwide morbidity and mortality. Its pathophysiology is complex and multifactorial. Because the phenotype of cardiovascular disease often shows a marked heritable pattern, it is likely that genetic factors play an important role. In recent years, large genome-wide association studies have been conducted to decipher the molecular mechanisms underlying this heritable and prevalent phenotype. The emphasis of this review is on the recently identified 17 susceptibility loci for coronary artery disease. Implications of their discovery for biology and clinical medicine are discussed. A description of the landscape of human genetics in the near future in the context of next-generation sequence technologies is provided at the conclusion of this review