Genetic examination of hematological parameters in SARS-CoV-2 infection and COVID-19.

People hospitalized with COVID-19 often exhibit altered hematological traits associated with disease prognosis (e.g., lower lymphocyte and platelet counts). We investigated whether inter-individual variability in baseline hematological traits influences risk of acute SARS-CoV-2 infection or progression to severe COVID-19. We report inconsistent associations between blood cell traits with incident SARS-CoV-2 infection and severe COVID-19 in UK Biobank and the Vanderbilt University Medical Center Synthetic Derivative (VUMC SD). Since genetically determined blood cell measures better represent cell abundance across the lifecourse, we also assessed the shared genetic architecture of baseline blood cell traits on COVID-19 related outcomes by Mendelian randomization (MR) analyses. We found significant relationships between COVID-19 severity and mean sphered cell volume after adjusting for multiple testing. However, MR results differed significantly across different freezes of COVID-19 summary statistics and genetic correlation between these traits was modest (0.1), decreasing our confidence in these results. We observed overlapping genetic association signals between other hematological and COVID-19 traits at specific loci such as MAPT and TYK2. In conclusion, we did not find convincing evidence of relationships between the genetic architecture of blood cell traits and either SARS-CoV-2 infection or COVID-19 hospitalization, though we do see evidence of shared signals at specific loci.

Life is pain: Fibromyalgia as a nexus of multiple liability distributions.

Fibromyalgia is a complex disease of unclear etiology that is complicated by difficulties in diagnosis, treatment, and clinical heterogeneity. To clarify this etiology, healthcare-based data are leveraged to assess the influences on fibromyalgia in several domains. Prevalence is less than 1% of females in our population register data, and about 1/10th that in males. Fibromyalgia often presents with co-occurring conditions including back pain, rheumatoid arthritis, and anxiety. More comorbidities are identified with hospital-associated biobank data, falling into three broad categories of pain-related, autoimmune, and psychiatric disorders. Selecting representative phenotypes with published genome-wide association results for polygenic scoring, we confirm genetic predispositions to psychiatric, pain sensitivity, and autoimmune conditions show associations with fibromyalgia, although these may differ by ancestry group. We conduct a genome-wide association analysis of fibromyalgia in biobank samples, which did not result in any genome-wide significant loci; further studies with increased sample size are necessary to identify specific genetic effects on fibromyalgia. Overall, fibromyalgia appears to have strong clinical and likely genetic links to several disease categories, and could usefully be understood as a composite manifestation of these etiological sources.

Electronic health record phenotypes associated with genetically regulated expression of CFTR and application to cystic fibrosis.

PURPOSE: The increasing use of electronic health records (EHRs) and biobanks offers unique opportunities to study Mendelian diseases. We described a novel approach to summarize clinical manifestations from patient EHRs into phenotypic evidence for cystic fibrosis (CF) with potential to alert unrecognized patients of the disease. METHODS: We estimated genetically predicted expression (GReX) of cystic fibrosis transmembrane conductance regulator (CFTR) and tested for association with clinical diagnoses in the Vanderbilt University biobank (N = 9142 persons of European descent with 71 cases of CF). The top associated EHR phenotypes were assessed in combination as a phenotype risk score (PheRS) for discriminating CF case status in an additional 2.8 million patients from Vanderbilt University Medical Center (VUMC) and 125,305 adult patients including 25,314 CF cases from MarketScan, an independent external cohort. RESULTS: GReX of CFTR was associated with EHR phenotypes consistent with CF. PheRS constructed using the EHR phenotypes and weights discovered by the genetic associations improved discriminative power for CF over the initially proposed PheRS in both VUMC and MarketScan. CONCLUSION: Our study demonstrates the power of EHRs for clinical description of CF and the benefits of using a genetics-informed weighing scheme in construction of a phenotype risk score. This research may find broad applications for phenomic studies of Mendelian disease genes.

Genome-wide association study of major anxiety disorders in 122,341 European-ancestry cases identifies 58 loci and highlights GABAergic signaling.

The major anxiety disorders (ANX; including generalized anxiety disorder, panic disorder, and phobias) are highly prevalent, often onset early, persist throughout life, and cause substantial global disability. Although distinct in their clinical presentations, they likely represent differential expressions of a dysregulated threat-response system. Here we present a genome-wide association meta-analysis comprising 122,341 European ancestry ANX cases and 729,881 controls. We identified 58 independent genome-wide significant ANX risk variants and 66 genes with robust biological support. In an independent sample of 1,175,012 self-report ANX cases and 1,956,379 controls, 51 of the 58 associated variants were replicated. As predicted by twin studies, we found substantial genetic correlation between ANX and depression, neuroticism, and other internalizing phenotypes. Follow-up analyses demonstrated enrichment in all major brain regions and highlighted GABAergic signaling as one potential mechanism underlying ANX genetic risk. These results advance our understanding of the genetic architecture of ANX and prioritize genes for functional follow-up studies.

Polygenic Contributions to Chronic Overlapping Pain Conditions in a Large Electronic Health Record Sample.

Chronic overlapping pain conditions (COPCs) are believed to share common etiological mechanisms involving central sensitization. Genetic and environmental factors putatively combine to influence susceptibility to central sensitization and COPCs. This study employed a genome-wide polygenic risk score approach to evaluate genetic influences on 8 common COPCs. COPCs were identified by International Classification of Disease codes in Vanderbilt's deidentified clinical biorepository (BioVU), with each COPC condition empirically weighted for the level of central sensitization based on prior work. A centralized pain score (CPS) was calculated for 55,340 individuals by summing the weighted number of COPCs. Overall, 12,502 individuals (22.6%) were diagnosed with at least 1 COPC, with females exhibiting nearly twice the mean CPS as males. To assess the genetic influence on centralized pain in COPCs, 6 pain polygenic risk scores (PRSs) were developed using UK Biobank data to predict 6 pain criteria (no pain, neck/shoulder, abdomen, hip, knee, low back pain). These PRSs were then deployed in the BioVU cohort to test for association with CPS. In regression models adjusted for age, sex, and BMI, all pain PRSs except hip pain were significantly associated with CPS. Our findings support a shared polygenic influence across COPCs potentially involving central sensitization mechanisms. PERSPECTIVE: This study used a polygenic risk score approach to investigate genetic influences on chronic overlapping pain conditions. Significant findings in this study provide evidence supporting previous hypotheses that a shared polygenic influence involving central sensitization may underly chronic overlapping pain conditions and can guide future biomarker and risk assessment research.

Improving the computation efficiency of polygenic risk score modeling: faster in Julia.

To enable large-scale application of polygenic risk scores (PRSs) in a computationally efficient manner, we translate a widely used PRS construction method, PRS-continuous shrinkage, to the Julia programming language, PRS.jl. On nine different traits with varying genetic architectures, we demonstrate that PRS.jl maintains accuracy of prediction while decreasing the average runtime by 5.5×. Additional programmatic modifications improve usability and robustness. This freely available software substantially improves work flow and democratizes usage of PRSs by lowering the computational burden of the PRS-continuous shrinkage method.

Genetic Examination of Hematological Parameters in SARS-CoV-2 Infection and COVID-19.

Background: People hospitalized with COVID-19 often exhibit hematological alterations, such as lower lymphocyte and platelet counts, which have been reported to associate with disease prognosis. It is unclear whether inter-individual variability in baseline hematological parameters prior to acute infection influences risk of SARS-CoV-2 infection and progression to severe COVID-19. Methods: We assessed the association of blood cell counts and indices with incident SARS-CoV-2 infection and severe COVID-19 in UK Biobank and the Vanderbilt University Medical Center Synthetic Derivative (VUMC SD). Since genetically determined blood cell measures better represent cell abundance across the lifecourse, we used summary statistics from genome-wide association studies to assess the shared genetic architecture of baseline blood cell counts and indices on COVID-19 outcomes. Results: We observed inconsistent associations between measured blood cell indices and both SARS-CoV-2 infection and COVID-19 hospitalization in UK Biobank and VUMC SD. In Mendelian randomization analyses using genetic summary statistics, no putative causal relationships were identified between COVID-19 related outcomes and hematological indices after adjusting for multiple testing. We observed overlapping genetic association signals between hematological parameters and COVID-19 traits. For example, we observed overlap between infection susceptibility-associated variants at PPP1R15A and red blood cell parameters, and between disease severity-associated variants at TYK2 and lymphocyte and platelet phenotypes. Conclusions: We did not find convincing evidence of a relationship between baseline hematological parameters and susceptibility to SARS-CoV-2 infection or COVID-19 severity, though this relationship should be re-examined as larger and better-powered genetic analyses of SARS-CoV-2 infection and severe COVID-19 become available.

Vascular alterations impede fragile tolerance to pregnancy in type 1 diabetes.

OBJECTIVE: To determine the impact of autoimmunity in the absence of glycemic alterations on pregnancy in type 1 diabetes (T1D). DESIGN: Because nonobese diabetic (NOD) mice experience autoimmunity before the onset of hyperglycemia, we studied pregnancy outcomes in prediabetic NOD mice using flow cytometry and enzyme-linked immunosorbent assays. Once we determined that adverse events in pregnancy occurred in euglycemic mice, we performed an exploratory study using electronic health records to better understand pregnancy complications in humans with T1D and normal hemoglobin A1c levels. SETTING: University Medical Center. PATIENT(S)/ANIMAL(S): Nonobese diabetic mice and electronic health records from Vanderbilt University Medical Center. INTERVENTION(S): Nonobese diabetic mice were administered 200 µg of an anti-interleukin 6 (IL-6) antibody every other day starting on day 5 of gestation. MAIN OUTCOME MEASURE(S): Changes in the number of abnormal and reabsorbed pups in NOD mice and odds of vascular complications in pregnancy in T1D in relation to A1c. RESULT(S): Prediabetic NOD mice had increased adverse pregnancy outcomes compared with nonautoimmune mice; blockade of IL-6, which was secreted by endothelial cells, decreased the number of reabsorbed and abnormal fetuses. Similarly, vascular complications were increased in pregnant patients with T1D across all A1c values. CONCLUSION(S): The vascular secretion of IL-6 drives adverse pregnancy outcomes in prediabetic NOD mice. Pregnant patients with T1D have increased vascular complications even with normal hemoglobin A1cs, indicating a potential effect of autoimmunity on the placental vasculature.

Identifying High-Risk Comorbidities Associated with Opioid Use Patterns Using Electronic Health Record Prescription Data.

Introduction: Opioid use disorders (OUDs) constitute a major public health issue, and we urgently need alternative methods for characterizing risk for OUD. Electronic health records (EHRs) are useful tools for understanding complex medical phenotypes but have been underutilized for OUD because of challenges related to underdiagnosis, binary diagnostic frameworks, and minimally characterized reference groups. As a first step in addressing these challenges, a new paradigm is warranted that characterizes risk for opioid prescription misuse on a continuous scale of severity, i.e., as a continuum. Methods: Across sites within the PsycheMERGE network, we extracted prescription opioid data and diagnoses that co-occur with OUD (including psychiatric and substance use disorders, pain-related diagnoses, HIV, and hepatitis C) for over 2.6 million patients across three health registries (Vanderbilt University Medical Center, Mass General Brigham, Geisinger) between 2005 and 2018. We defined three groups based on levels of opioid exposure: no prescriptions, minimal exposure, and chronic exposure and then compared the comorbidity profiles of these groups to the full registries and to those with OUD diagnostic codes. Results: Our results confirm that EHR data reflects known higher prevalence of substance use disorders, psychiatric disorders, medical, and pain diagnoses in patients with OUD diagnoses and chronic opioid use. Comorbidity profiles that distinguish opioid exposure are strikingly consistent across large health systems, indicating the phenotypes described in this new quantitative framework are robust to health systems differences. Conclusion: This work indicates that EHR prescription opioid data can serve as a platform to characterize complex risk markers for OUD using existing data.

Calcium-Sensing Receptor Polymorphisms at rs1801725 Are Associated with Increased Risk of Secondary Malignancies.

Dysregulation of systemic calcium homeostasis during malignancy is common in most patients with high-grade tumors. However, it remains unclear whether single nucleotide polymorphisms (SNPs) that alter the sensitivity of the calcium-sensing receptor (CaSR) to circulating calcium are associated with primary and/or secondary neoplasms at specific pathological sites in patients of European and African ancestry. Multivariable logistic regression models were used to analyze the association of CASR SNPs with circulating calcium, parathyroid hormone, vitamin D, and primary and secondary neoplasms. Circulating calcium is associated with an increased risk for breast, prostate, and skin cancers. In patients of European descent, the rs1801725 CASR SNP is associated with bone-related cancer phenotypes, deficiency of humoral immunity, and a higher risk of secondary neoplasms in the lungs and bone. Interestingly, circulating calcium levels are higher in homozygous patients for the inactivating CASR variant at rs1801725 (TT genotype), and this is associated with a higher risk of secondary malignancies. Our data suggest that expression of CaSR variants at rs1801725 is associated with a higher risk of developing secondary neoplastic lesions in the lungs and bone, due in part to cancer-induced hypercalcemia and/or tumor immune suppression. Screening of patients for CASR variants at this locus may lead to improved management of high calcium associated tumor progression.

Clinical laboratory test-wide association scan of polygenic scores identifies biomarkers of complex disease.

BACKGROUND: Clinical laboratory (lab) tests are used in clinical practice to diagnose, treat, and monitor disease conditions. Test results are stored in electronic health records (EHRs), and a growing number of EHRs are linked to patient DNA, offering unprecedented opportunities to query relationships between genetic risk for complex disease and quantitative physiological measurements collected on large populations. METHODS: A total of 3075 quantitative lab tests were extracted from Vanderbilt University Medical Center's (VUMC) EHR system and cleaned for population-level analysis according to our QualityLab protocol. Lab values extracted from BioVU were compared with previous population studies using heritability and genetic correlation analyses. We then tested the hypothesis that polygenic risk scores for biomarkers and complex disease are associated with biomarkers of disease extracted from the EHR. In a proof of concept analyses, we focused on lipids and coronary artery disease (CAD). We cleaned lab traits extracted from the EHR performed lab-wide association scans (LabWAS) of the lipids and CAD polygenic risk scores across 315 heritable lab tests then replicated the pipeline and analyses in the Massachusetts General Brigham Biobank. RESULTS: Heritability estimates of lipid values (after cleaning with QualityLab) were comparable to previous reports and polygenic scores for lipids were strongly associated with their referent lipid in a LabWAS. LabWAS of the polygenic score for CAD recapitulated canonical heart disease biomarker profiles including decreased HDL, increased pre-medication LDL, triglycerides, blood glucose, and glycated hemoglobin (HgbA1C) in European and African descent populations. Notably, many of these associations remained even after adjusting for the presence of cardiovascular disease and were replicated in the MGBB. CONCLUSIONS: Polygenic risk scores can be used to identify biomarkers of complex disease in large-scale EHR-based genomic analyses, providing new avenues for discovery of novel biomarkers and deeper understanding of disease trajectories in pre-symptomatic individuals. We present two methods and associated software, QualityLab and LabWAS, to clean and analyze EHR labs at scale and perform a Lab-Wide Association Scan.