Maternal Bacterial Infection During Pregnancy and Offspring Risk of Psychotic Disorders: Variation by Severity of Infection and Offspring Sex

ObjectivePrevious studies suggest that prenatal immune challenges may elevate the risk of schizophrenia and related psychoses in offspring, yet there has been limited research focused on maternal bacterial infection. The authors hypothesized that maternal bacterial infection during pregnancy increases offspring risk of psychotic disorders in adulthood, and that the magnitude of this association varies as a function of severity of infectious exposure and offspring sex.MethodsThe authors analyzed prospectively collected data from 15,421 pregnancies among women enrolled between 1959 and 1966 at two study sites through the Collaborative Perinatal Project. The sample included 116 offspring with confirmed psychotic disorders. The authors estimated associations between maternal bacterial infection during pregnancy and psychosis risk over the subsequent 40 years, stratified by offspring sex and presence of reported parental mental illness, with adjustment for covariates.ResultsMaternal bacterial infection during pregnancy was strongly associated with psychosis in offspring (adjusted odds ratio=1.8, 95% CI=1.2-2.7) and varied by severity of infection and offspring sex. The effect of multisystemic bacterial infection (adjusted odds ratio=2.9, 95% CI=1.3-5.9) was nearly twice that of less severe localized bacterial infection (adjusted odds ratio=1.6, 95% CI=1.1-2.3). Males were significantly more likely than females to develop psychosis after maternal exposure to any bacterial infection during pregnancy.ConclusionsThe study findings suggest that maternal bacterial infection during pregnancy is associated with an elevated risk for psychotic disorders in offspring and that the association varies by infection severity and offspring sex. These findings call for additional investigation and, if the findings are replicated, public health and clinical efforts that focus on preventing and managing bacterial infection in pregnant women

Feasibility of Using a Nationally Representative Telephone Survey to Monitor Multiple Sclerosis Prevalence in the United States

Background: Multiple sclerosis (MS) is the most common chronic neurologic disease of young adults, placing a heavy burden on patients, families, and the healthcare system. Ongoing surveillance of the incidence and prevalence of MS is critical for health policy and research, but feasible options are limited in the United States and many other countries. We investigated the feasibility of monitoring the prevalence of MS using a large national telephone survey of the adult US population. Methods: We developed questions to estimate the lifetime prevalence and age of onset of MS using the US-based Behavioral Risk Factor Surveillance System (BRFSS) and piloted these questions in 4 states (MN, RI, MD, and TX). There was a total of 45,198 respondents aged 18 years and above. Analyses investigated individual state and combined prevalence estimates along with health-related comorbidities and limitations. MS prevalence estimates from the BRFSS were compared to estimates from multi-source administrative claims and traditional population-based methods. Results: The estimated lifetime prevalence of self-reported MS (per 100,000 adults) was 682 (95% CI 528-836); 384 (95% CI 239-529) among males and 957 (95% CI 694-1,220) among females. Estimates were consistent across the 4 states but much higher than recently published estimates using population-based administrative claims data. This was observed for both national results and for MS prevalence estimates from other studies within specific states (MN, RI, and TX). Prevalence estimates for Caucasian, African American, and Hispanic respondents were 824, 741, and 349 per 100,000 respectively. Age and sex distributions were consistent with prior epidemiologic reports. Comorbidity and functional limitations were more pronounced among female than male respondents. Conclusions: While yielding higher overall MS prevalence estimates compared to recent studies, this large-scale self-report telephone method yielded relative prevalence estimates (e.g., prevalence patterns of MS by sex, age, and race-ethnicity) that were generally comparable to other surveillance approaches. With certain caveats, population-based telephone surveys may eventually offer the ability to investigate novel disease correlates and are relatively feasible, and affordable. Further work is needed to create a valid question set and methodology for case ascertainment before this approach could be adopted to accurately estimate MS prevalence

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.Medicine, Faculty ofNon UBCMedical Genetics, Department ofReviewedFacult