Showing papers by "Christopher J. O'Donnell published in 2020"

Prescription Fill Patterns for Commonly Used Drugs During the COVID-19 Pandemic in the United States.

Abstract: This pharmacoepidemiology study uses US pharmacy data to compare prescriptions for hydroxychloroquine/chloroquine and azithromycin in February to April 2020 vs 2019, and vs the top 10 most commonly prescribed drugs in the same year, including angiotensin-converting enzyme inhibitors and angiotensin receptor blockers.

Genotyping Array Design and Data Quality Control in the Million Veteran Program.

Abstract: The Million Veteran Program (MVP), initiated by the Department of Veterans Affairs (VA), aims to collect biosamples with consent from at least one million veterans. Presently, blood samples have been collected from over 800,000 enrolled participants. The size and diversity of the MVP cohort, as well as the availability of extensive VA electronic health records, make it a promising resource for precision medicine. MVP is conducting array-based genotyping to provide a genome-wide scan of the entire cohort, in parallel with whole-genome sequencing, methylation, and other 'omics assays. Here, we present the design and performance of the MVP 1.0 custom Axiom array, which was designed and developed as a single assay to be used across the multi-ethnic MVP cohort. A unified genetic quality-control analysis was developed and conducted on an initial tranche of 485,856 individuals, leading to a high-quality dataset of 459,777 unique individuals. 668,418 genetic markers passed quality control and showed high-quality genotypes not only on common variants but also on rare variants. We confirmed that, with non-European individuals making up nearly 30%, MVP's substantial ancestral diversity surpasses that of other large biobanks. We also demonstrated the quality of the MVP dataset by replicating established genetic associations with height in European Americans and African Americans ancestries. This current dataset has been made available to approved MVP researchers for genome-wide association studies and other downstream analyses. Further data releases will be available for analysis as recruitment at the VA continues and the cohort expands both in size and diversity.

Inherited myeloproliferative neoplasm risk affects haematopoietic stem cells

Abstract: Myeloproliferative neoplasms (MPNs) are blood cancers that are characterized by the excessive production of mature myeloid cells and arise from the acquisition of somatic driver mutations in haematopoietic stem cells (HSCs). Epidemiological studies indicate a substantial heritable component of MPNs that is among the highest known for cancers1. However, only a limited number of genetic risk loci have been identified, and the underlying biological mechanisms that lead to the acquisition of MPNs remain unclear. Here, by conducting a large-scale genome-wide association study (3,797 cases and 1,152,977 controls), we identify 17 MPN risk loci (P < 5.0 × 10−8), 7 of which have not been previously reported. We find that there is a shared genetic architecture between MPN risk and several haematopoietic traits from distinct lineages; that there is an enrichment for MPN risk variants within accessible chromatin of HSCs; and that increased MPN risk is associated with longer telomere length in leukocytes and other clonal haematopoietic states—collectively suggesting that MPN risk is associated with the function and self-renewal of HSCs. We use gene mapping to identify modulators of HSC biology linked to MPN risk, and show through targeted variant-to-function assays that CHEK2 and GFI1B have roles in altering the function of HSCs to confer disease risk. Overall, our results reveal a previously unappreciated mechanism for inherited MPN risk through the modulation of HSC function. A genome-wide association study identifies 17 genetic loci that are associated with the risk of myeloproliferative neoplasms (MPNs), and shows that the modulation of haematopoietic stem cell function drives MPN risk.

Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19

Abstract: Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization (MR) analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2: P=1.6×10−6, IFNAR2: P=9.8×10−11, and IL-10RB: P=1.9×10−14) using cis-eQTL genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared eQTL signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.

Genetic Architecture of Abdominal Aortic Aneurysm in the Million Veteran Program.

Abstract: Background: Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality; however, its genetic determinants remain incompletely defined. In total, 10 previously identified risk...

Rural-Urban Differences in Cardiovascular Mortality in the US, 1999-2017.

Abstract: This study used data from the US Centers for Disease Control and Prevention WONDER database to examined temporal trends in cardiovascular disease age-adjusted mortality rates overall and across subgroups stratified by rural-urban area designation in the US.

Chromosome 1q21.2 and additional loci influence risk of spontaneous coronary artery dissection and myocardial infarction

Abstract: Spontaneous coronary artery dissection (SCAD) is a non-atherosclerotic cause of myocardial infarction (MI), typically in young women. We undertook a genome-wide association study of SCAD (Ncases = 270/Ncontrols = 5,263) and identified and replicated an association of rs12740679 at chromosome 1q21.2 (Pdiscovery+replication = 2.19 × 10−12, OR = 1.8) influencing ADAMTSL4 expression. Meta-analysis of discovery and replication samples identified associations with P < 5 × 10−8 at chromosome 6p24.1 in PHACTR1, chromosome 12q13.3 in LRP1, and in females-only, at chromosome 21q22.11 near LINC00310. A polygenic risk score for SCAD was associated with (1) higher risk of SCAD in individuals with fibromuscular dysplasia (P = 0.021, OR = 1.82 [95% CI: 1.09–3.02]) and (2) lower risk of atherosclerotic coronary artery disease and MI in the UK Biobank (P = 1.28 × 10−17, HR = 0.91 [95% CI :0.89–0.93], for MI) and Million Veteran Program (P = 9.33 × 10−36, OR = 0.95 [95% CI: 0.94–0.96], for CAD; P = 3.35 × 10−6, OR = 0.96 [95% CI: 0.95–0.98] for MI). Here we report that SCAD-related MI and atherosclerotic MI exist at opposite ends of a genetic risk spectrum, inciting MI with disparate underlying vascular biology. Spontaneous coronary artery dissection (SCAD) is a cause of myocardial infarction Here, the authors present a genome-wide association study of SCAD, finding an association at 1q21.2 which potentially affects expression of ADAMTSL4.

The All of Us Research Program: data quality, utility, and diversity

Abstract: Importance: The All of Us Research Program hypothesizes that accruing one million or more diverse participants engaged in a longitudinal research cohort will advance precision medicine and ultimately improve human health. Launched nationally in 2018, to date All of Us has recruited more than 345,000 participants. All of Us plans to open beta access to researchers in May 2020. Objective: To demonstrate the quality, utility, and diversity of the All of Us Research Programs initial data release and beta launch of the cloud-based analysis platform, the cloud-based Researcher Workbench. Evidence: We analyzed the initial All of Us data release, comprising surveys, physical measurements (PM), and electronic health record (EHR) data, to characterize All of Us participants including self-reported descriptors of diversity. Data depth, density, and quality were evaluated using medication sequencing analyses for depression and type 2 diabetes. Replication of known oncologic associations with smoking exposure ascertained by EHR and survey data and calculation of population-based atherosclerotic cardiovascular disease risk scores demonstrated the utility of data and platform capability. Findings: The beta launch of the All of Us Researcher Workbench contains data on 224,143 participants. Seventy-seven percent of this cohort were identified as Underrepresented in Biomedical Research (UBR) including over forty-eight percent self-reporting non-White race. Medication usage patterns in common diseases depression and type 2 diabetes replicated prior findings previously reported in the literature and showed differences based on race. Oncologic associations with smoking were replicated and effect sizes compared for EHR and survey exposures finding general agreement. A cardiovascular disease score was calculated utilizing multiple data elements curated across sources. The cloud-based architecture built in the Researcher Workbench provided secure access and powerful computational resources at a low cost. All analyses have been made available for replication and reuse by registered researchers. Conclusions and Relevance: The All of Us Research Programs initial release of cohort data contains longitudinal and multidimensional data on diverse participants that replicate known associations. This dataset and the cloud-based Researcher Workbench advance the mission of All of Us to make data widely and securely available to researchers to improve human health and advance precision medicine.

Association of FADS1/2 Locus Variants and Polyunsaturated Fatty Acids With Aortic Stenosis

Abstract: Importance: Aortic stenosis (AS) has no approved medical treatment. Identifying etiological pathways for AS could identify pharmacological targets.Objective: To identify novel genetic loci and path ...

DNA methylation age calculators reveal association with diabetic neuropathy in type 1 diabetes.

Abstract: Many CpGs become hyper or hypo-methylated with age. Multiple methods have been developed by Horvath et al. to estimate DNA methylation (DNAm) age including Pan-tissue, Skin & Blood, PhenoAge, and GrimAge. Pan-tissue and Skin & Blood try to estimate chronological age in the normal population whereas PhenoAge and GrimAge use surrogate markers associated with mortality to estimate biological age and its departure from chronological age. Here, we applied Horvath’s four methods to calculate and compare DNAm age in 499 subjects with type 1 diabetes (T1D) from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study using DNAm data measured by Illumina EPIC array in the whole blood. Association of the four DNAm ages with development of diabetic complications including cardiovascular diseases (CVD), nephropathy, retinopathy, and neuropathy, and their risk factors were investigated. Pan-tissue and GrimAge were higher whereas Skin & Blood and PhenoAge were lower than chronological age (p < 0.0001). DNAm age was not associated with the risk of CVD or retinopathy over 18–20 years after DNAm measurement. However, higher PhenoAge (β = 0.023, p = 0.007) and GrimAge (β = 0.029, p = 0.002) were associated with higher albumin excretion rate (AER), an indicator of diabetic renal disease, measured over time. GrimAge was also associated with development of both diabetic peripheral neuropathy (OR = 1.07, p = 9.24E−3) and cardiovascular autonomic neuropathy (OR = 1.06, p = 0.011). Both HbA1c (β = 0.38, p = 0.026) and T1D duration (β = 0.01, p = 0.043) were associated with higher PhenoAge. Employment (β = − 1.99, p = 0.045) and leisure time (β = − 0.81, p = 0.022) physical activity were associated with lower Pan-tissue and Skin & Blood, respectively. BMI (β = 0.09, p = 0.048) and current smoking (β = 7.13, p = 9.03E−50) were positively associated with Skin & Blood and GrimAge, respectively. Blood pressure, lipid levels, pulse rate, and alcohol consumption were not associated with DNAm age regardless of the method used. Various methods of measuring DNAm age are sub-optimal in detecting people at higher risk of developing diabetic complications although some work better than the others.

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes

Abstract: Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier will develop the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we applied clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias displayed effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers averaged below 60% in both studies for all conditions except monogenic diabetes. We assessed additional epidemiologic and genetic factors contributing to risk prediction, demonstrating that inclusion of common polygenic variation significantly improved biomarker estimation for two monogenic dyslipidemias.

Radiomics of Coronary Artery Calcium in the Framingham Heart Study.

Abstract: A radiomics-based score that incorporates complex properties of coronary artery calcium may constitute an imaging biomarker to identify individuals at risk for composite endpoint of major adverse c...

Genetics of Smoking and Risk of Atherosclerotic Cardiovascular Diseases: A Mendelian Randomization Study

Abstract: Importance Smoking is associated with atherosclerotic cardiovascular disease, but the relative contribution to each subtype (coronary artery disease [CAD], peripheral artery disease [PAD], and large-artery stroke) remains less well understood. Objective To determine the effect of smoking on risk of coronary artery disease, peripheral artery disease, and large-artery stroke. Design Mendelian randomization study using summary statistics from genome-wide associations of smoking (up to 462,690 individuals), coronary artery disease (up to 60,801 cases, 123,504 controls), peripheral artery disease (up to 24,009 cases, 150,983 controls), and large-artery stroke (up to 4,373 cases, 406,111 controls) Setting Population-based study of primarily European-ancestry individuals Participants Participants in genome-wide association studies of smoking, coronary artery disease, peripheral artery disease, and stroke. Exposures Genetic liability to smoking defined by lifetime smoking index: an integrated measure of smoking status, age at initiation, age at cessation, number of cigarettes smoked per day, and declining effect of smoking on health outcomes). Main Outcome Measure Risk of coronary artery disease, peripheral artery disease, and large-artery stroke. Results Genetic liability to smoking was associated with increased risk of PAD (OR 2.13; 95% CI 1.78-2.56; P = 3.6 × 10−16), CAD (OR 1.48; 95% CI 1.25-1.75; P = 4.4 × 10−6), and stroke (OR 1.4; 95% CI 1.02-1.92; P = 0.036). Risk of PAD in smokers was greater than risk of large-artery stroke (pdifference = 0.025) or CAD (pdifference = 0.0041). The effect of smoking on ASCVD remained independent from the effects of smoking on traditional cardiovascular risk factors. Conclusions and Relevance Genetic liability to smoking is a strong, causal risk factor for CAD, PAD, and stroke, although the effect of smoking is strongest for PAD. The effect of smoking is independent of traditional cardiovascular risk factors.

Validating a non-invasive, ALT-based non-alcoholic fatty liver phenotype in the million veteran program

Abstract: Background & aims Given ongoing challenges in non-invasive non-alcoholic liver disease (NAFLD) diagnosis, we sought to validate an ALT-based NAFLD phenotype using measures readily available in electronic health records (EHRs) and population-based studies by leveraging the clinical and genetic data in the Million Veteran Program (MVP), a multi-ethnic mega-biobank of US Veterans. Methods MVP participants with alanine aminotransferases (ALT) >40 units/L for men and >30 units/L for women without other causes of liver disease were compared to controls with normal ALT. Genetic variants spanning eight NAFLD risk or ALT-associated loci (LYPLAL1, GCKR, HSD17B13, TRIB1, PPP1R3B, ERLIN1, TM6SF2, PNPLA3) were tested for NAFLD associations with sensitivity analyses adjusting for metabolic risk factors and alcohol consumption. A manual EHR review assessed performance characteristics of the NAFLD phenotype with imaging and biopsy data as gold standards. Genetic associations with advanced fibrosis were explored using FIB4, NAFLD Fibrosis Score and platelet counts. Results Among 322,259 MVP participants, 19% met non-invasive criteria for NAFLD. Trans-ethnic meta-analysis replicated associations with previously reported genetic variants in all but LYPLAL1 and GCKR loci (P<6x10-3), without attenuation when adjusted for metabolic risk factors and alcohol consumption. At the previously reported LYPLAL1 locus, the established genetic variant did not appear to be associated with NAFLD, however the regional association plot showed a significant association with NAFLD 279kb downstream. In the EHR validation, the ALT-based NAFLD phenotype yielded a positive predictive value 0.89 and 0.84 for liver biopsy and abdominal imaging, respectively (inter-rater reliability (Cohen’s kappa = 0.98)). HSD17B13 and PNPLA3 loci were associated with advanced fibrosis. Conclusions We validate a simple, non-invasive ALT-based NAFLD phenotype using EHR data by leveraging previously established NAFLD risk-associated genetic polymorphisms.

Measuring genetic variation in the multi-ethnic Million Veteran Program (MVP)

Abstract: The Million Veteran Program (MVP), initiated by the Department of Veterans Affairs (VA), aims to collect consented biosamples from at least one million Veterans. Presently, blood samples have been collected from over 800,000 enrolled participants. The size and diversity of the MVP cohort, as well as the availability of extensive VA electronic health records make it a promising resource for precision medicine. MVP is conducting array-based genotyping to provide genome-wide scan of the entire cohort, in parallel with whole genome sequencing, methylation, and other omics assays. Here, we present the design and performance of MVP 1.0 custom Axiom array, which was designed and developed as a single assay to be used across the multi-ethnic MVP cohort. A unified genetic quality control analysis was developed and conducted on an initial tranche of 485,856 individuals leading to a high-quality dataset of 459,777 unique individuals. 668,418 genetic markers passed quality control and showed high quality genotypes not only on common variants but also on rare variants. We confirmed the substantial ancestral diversity of MVP with nearly 30% non-European individuals, surpassing other large biobanks. We also demonstrated the quality of the MVP dataset by replicating established genetic associations with height in European Americans and African Americans ancestries. This current data set has been made available to approved MVP researchers for genome-wide association studies and other downstream analyses. Further data releases will be available for analysis as recruitment at the VA continues and the cohort expands both in size and diversity.

Mendelian Randomization Analysis of Hemostatic Factors and Their Contribution to Peripheral Artery Disease-Brief Report.

Abstract: Background and Objective: Peripheral artery disease (PAD) is the third most common form of atherosclerotic vascular disease and is characterized by significant functional disability and increased c...

Minority-centric meta-analyses of blood lipid levels identify novel loci in the Population Architecture using Genomics and Epidemiology (PAGE) study.

Abstract: Lipid levels are important markers for the development of cardio-metabolic diseases. Although hundreds of associated loci have been identified through genetic association studies, the contribution of genetic factors to variation in lipids is not fully understood, particularly in U.S. minority groups. We performed genome-wide association analyses for four lipid traits in over 45,000 ancestrally diverse participants from the Population Architecture using Genomics and Epidemiology (PAGE) Study, followed by a meta-analysis with several European ancestry studies. We identified nine novel lipid loci, five of which showed evidence of replication in independent studies. Furthermore, we discovered one novel gene in a PrediXcan analysis, minority-specific independent signals at eight previously reported loci, and potential functional variants at two known loci through fine-mapping. Systematic examination of known lipid loci revealed smaller effect estimates in African American and Hispanic ancestry populations than those in Europeans, and better performance of polygenic risk scores based on minority-specific effect estimates. Our findings provide new insight into the genetic architecture of lipid traits and highlight the importance of conducting genetic studies in diverse populations in the era of precision medicine.

Opportunities, challenges and expectations management for translating biobank research to precision medicine.

Abstract: With the ascendance of large genomic biobanks that leverage healthcare systems and provide access to DNA, biospecimens and electronic health record (EHR) data, epidemiologists can now conduct population science research at scale in individual cohorts with sample sizes far exceeding 100,000 participants. Largescale biobanks like UK Biobank, that are nested within a national or regional health system, are creating platforms for research that holds the promise to translate genomic medicine findings into “precision” approaches for both individual patient care and population prevention. The current wave of genomic biobanks represents the most recent in a series of eras of individual smaller prospective cohort studies that began in the mid 1900s and provided initial evidence that led to targeted prediction, prevention and treatment approaches (Table 1). The iconic Framingham Heart Study (FHS) provides a useful illustration: the first FHS publication describing “factors of risk” for prediction of coronary heart disease was published well over a decade after initiation of the first FHS examination [1]. Prospective associations of individual risk factors were subsequently validated in independent cohorts and large meta-analyses, and the totality of randomized clinical trials have demonstrated clear benefits from therapies to reduce the level and burden of risk factors and have led to clear guidelines for prevention and/or treatment based on strata of risk, for example for elevated blood pressure [2] and elevated LDL-cholesterol [3]. Framingham multivariable risk strata [4] represent a precursor to “stratified” or “personalized’ prediction, and multivariable risk factor algorithms calibrated to race/ethnicity are now incorporated into treatment guidelines [2, 3]. Importantly, the time interval from discovery to clinical/population implementation has typically been measured in decades not years. In the early days of prospective cohort studies, collaboration among cohorts was rare; however, with the advent of genome-wide association studies (GWAS) at the turn of the century, large international genomics consortia, such as CHARGE [5], GIANT [6], and PGC [7], have thrived based upon collaboration among scores of individual cohorts. The UK Biobank consists of more than 500,000 men and women who were enrolled during 2006–2010 (age range 40–69 years) and for whom health data is being collected over the long term. Since 2012, UK Biobank data has been available to researchers, without exclusive or preferential access, for health-related research inquiry [8]. This democratic and streamlined access to UK Biobank data by researchers across the world is supported by the informed consent of UK Biobank participants and has provided breathtaking opportunities for rapid conduct of big data research using genotype and phenotype at a scale not previously seen in biomedical research. Given the rapidly increasing rate of research publications using UK Biobank data, it is not unreasonable to evaluate the quality and content of research emanating from initial studies derived from this influential biobank and to assess these research findings in the context of potential impact on population health. In the current issue of European Journal of Epidemiology, Glynn and Greenland [9] conducted a comprehensive review of the highest impact published findings from the UK Biobank defined by citations, alternative metric data, or publication in a high impact journal. Of the nearly 700 studies published in the first 7 years of the UK Biobank and first 4 years of access to genotyping data, many published manuscripts have provided novel associations or replication of known associations. However, there have been few studies demonstrating “a method of patient selection or prediction model that enabled significant improvement in * Christopher J. O’Donnell christopher.odonnell@va.gov

Analysis of the Influence of Different Parameters on Droplet Characteristics and Droplet Size Classification Categories for Air Induction Nozzle

Abstract: Droplet characteristics are identified as essential factors in agricultural spray application. The aims of this study were to analyse the influence of spray parameters on droplet characteristics and to determine possible candidate sprays that would produce the same droplet size categorizations as the American Society of Agricultural and Biological Engineers (ASABE) standard S-572.1 for air induction nozzles (AINs). Six different orifice sizes of the Billericay Farm Services (BFS) air induction (AI) flat fan hydraulic nozzles (the air bubblejet) were examined at different spray pressures (200 kPa, 300 kPa, 400 kPa, 500 kPa, 600 kPa and 700 kPa) and concurrent air velocities (2 m/s, 3 m/s, 4 m/s and 5 m/s). The influences of spray parameters on the droplet characteristics were analysed using analysis of covariance (ANCOVA) and analysis of variance (ANOVA). Results showed that: (1) The values of droplet characteristics and the results of ANOVA were significantly different before and after eliminate the influence of dynamic surface tension (DST) on droplet characteristics by ANCOVA; (2) (a) the reduction rates of the droplet diameter sizes decreased with increasing spray pressure; (b) air velocities of 2 m/s and 5 m/s resulted in smaller droplets reports, and air velocities of 3 m/s and 4 m/s are more suitable for agricultural spray applications; (c) a larger nozzle orifice size not always result in a larger droplet size and (3) Fine, Medium, Coarse, Very Coarse and Extremely Coarse droplet classification categories as the ASABE S-572.1 standard categorizations were determined to classify AINs.

Injury Detection in Traumatic Death: Postmortem Computed Tomography vs. Open Autopsy

Abstract: Objective To compare postmortem computed tomography (PMCT) vs. autopsy in detecting and analyzing injuries due to traumatic deaths. Materials and methods In this retrospective study, a cohort of 52 subjects were purposively sampled to reflect a broad range of injuries. Injuries from autopsy and PMCT reports were coded using the Abbreviated Injury Scale (AIS) and the level of agreement of AIS 2+ and 3+ injuries were compared. Results A combined total of 353 AIS-coded injuries were detected - PMCT detected 63% and autopsy detected 74% of injuries. PMCT identified 92 (26%) additional injuries missed by autopsy. PMCT missed 131 (37%) injuries. The kappa value for agreement between the two modalities for presence of injuries was moderate for the majority of anatomic regions [head (κ = 0.53), thoracic organs (κ = 0.58), upper extremity (κ = 0.53), pelvis (κ = 0.45), skeletal chest injuries (κ = 0.57)]. Kappa value was least among abdominal (κ = 0.07) and vascular injuries (κ = 0.10). Substantial agreement (κ = 0.69) was present in lower extremity injuries. PMCT outperformed autopsy for bony injuries, in particular, pelvic injuries, base of skull fractures and upper extremity injuries. PMCT better detected pneumothoraces. Soft tissue injuries, particularly abdominal organ injuries, lung contusions and vascular injuries were better detected by autopsy. When injuries missed by PMCT were re-assessed, subtle but inconclusive imaging findings were identified. Conclusion A combination of PMCT and autopsy can detect more injuries than either modality in isolation. PMCT detected a considerable number of injuries missed by autopsy and vice versa.

Genetic determinants of increased body mass index mediate the effect of smoking on increased risk for type 2 diabetes but not coronary artery disease.

Abstract: Clinical observations have linked tobacco smoking with increased type 2 diabetes risk. Mendelian randomization analysis has recently suggested smoking may be a causal risk factor for type 2 diabetes. However, this association could be mediated by additional risk factors correlated with smoking behavior, which have not been investigated. We hypothesized that body mass index (BMI) could help to explain the association between smoking and diabetes risk. First, we confirmed that genetic determinants of smoking initiation increased risk for type 2 diabetes (OR = 1.21, 95% CI: 1.15-1.27, P = 1 × 10-12) and coronary artery disease (CAD; OR = 1.21, 95% CI: 1.16-1.26, P = 2 × 10-20). Additionally, 2-fold increased smoking risk was positively associated with increased BMI (~0.8 kg/m2, 95% CI: 0.54-0.98 kg/m2, P = 1.8 × 10-11). Multivariable Mendelian randomization analyses showed that BMI accounted for nearly all the risk smoking exerted on type 2 diabetes (OR 1.06, 95% CI: 1.01-1.11, P = 0.03). In contrast, the independent effect of smoking on increased CAD risk persisted (OR 1.12, 95% CI: 1.08-1.17, P = 3 × 10-8). Causal mediation analyses agreed with these estimates. Furthermore, analysis using individual-level data from the Million Veteran Program (MVP) independently replicated the association of smoking behavior with CAD (OR 1.24, 95% CI: 1.12-1.37, P = 2 × 10-5), but not type 2 diabetes (OR 0.98, 95% CI: 0.89-1.08, P = 0.69), after controlling for BMI. Our findings support a model whereby genetic determinants of smoking increase type 2 diabetes risk indirectly through their relationship with obesity. Smokers should be advised to stop smoking to limit type 2 diabetes and CAD risk. Therapeutic efforts should consider pathophysiology relating smoking and obesity.

PCSK9 loss of function is protective against extra-coronary atherosclerotic cardiovascular disease in a large multi-ethnic cohort.

Abstract: Background Therapeutic inhibition of PCSK9 protects against coronary artery disease (CAD) and ischemic stroke (IS). The impact on other diseases remains less well characterized. Methods We created a genetic risk score (GRS) for PCSK9 using four single nucleotide polymorphisms (SNPs) at or near the PCSK9 locus known to impact lower LDL-Cholesterol (LDL-C): rs11583680, rs11591147, rs2479409, and rs11206510. We then used our GRS to calculate weighted odds ratios reflecting the impact of a genetically determined 10 mg/dL decrease in LDL-C on several pre-specified phenotypes including CAD, IS, peripheral artery disease (PAD), abdominal aortic aneurysm (AAA), type 2 diabetes, dementia, chronic obstructive pulmonary disease, and cancer. Finally, we used our weighted GRS to perform a phenome-wide association study. Results Genetic and electronic health record data that passed quality control was available in 312,097 individuals, (227,490 White participants, 58,907 Black participants, and 25,700 Hispanic participants). PCSK9 mediated reduction in LDL-C was associated with a reduced risk of CAD and AAA in trans-ethnic meta-analysis (CAD OR 0.83 [95% CI 0.80-0.87], p = 6.0 x 10-21; AAA OR 0.76 [95% CI 0.68-0.86], p = 2.9 x 10-06). Significant protective effects were noted for PAD in White individuals (OR 0.83 [95% CI 0.71-0.97], p = 2.3 x 10-04) but not in other genetic ancestries. Genetically reduced PCSK9 function associated with a reduced risk of dementia in trans-ethnic meta-analysis (OR 0.86 [95% CI 0.78-0.93], p = 5.0 x 10-04). Conclusions Genetically reduced PCSK9 function results in a reduction in risk of several important extra-coronary atherosclerotic phenotypes in addition to known effects on CAD and IS, including PAD and AAA. We also highlight a novel reduction in risk of dementia, supporting a well-recognized vascular component to cognitive impairment and an opportunity for therapeutic repositioning.

Comparison of water-sensitive paper, Kromekote and Mylar collectors for droplet deposition with a visible fluorescent dye solution

Abstract: The study was conducted at the University of Nebraska Pesticide Application and Technology Laboratory in North Platte, Nebraska in July 2015. Two application volume rates (100 and 200 l · ha−) and three nozzle types (XR, AIXR, TTI) were selected at two flow rates (0.8 and 1.6 l · min−) and at a single application speed of 7.7 km · h−. Each collector type [Mylar washed (MW), Mylar image analysis (MIA), water-sensitive paper (WSP), and Kromekote (KK)] was arranged in a randomized complete block design. Each nozzle treatment was replicated twice, providing six cards of each collector type for each nozzle treatment. A water + 0.4% v/v Rhodamine WT spray solution was applied, given the fluorescent and visible qualities of Rhodamine, which allows it to be applied over all the collector types. MW had the highest coverage at 18.3% across nozzle type, followed by WSP at 18%, KK at 12% and lastly by MIA at 4%. MW resulted in a 58% increase in coverage, WSP in a 56% increase, and KK only an increase of 39% when the volume rate was doubled from 100 l · ha− to 200 l · ha− across nozzle type. MW coverage was similar to KK for half of the nozzles (XR 11002, XR 11004, AIXR 11002). Droplet number density fixed effects were all significant for nozzle type and collector type (p < 0.001) as was the interaction of nozzle type and collector type (p < 0.001). Results from this study suggest a strong correlation to data produced with WSP and MW collectors, as there was full agreement between both types except for the TTI 11004. Using both collector types in the same study would allow for a visual understanding of the distribution of the spray, while also giving an idea of the concentration of that distribution.

Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

Abstract: Background Genome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome. Methods and results Using samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both crosssectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and allcause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 × 10−7 ). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) � 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent

Integration of rare large-effect expression variants improves polygenic risk prediction

Abstract: Summary Polygenic risk scores (PRS) aim to quantify the contribution of multiple genetic loci to an individual’s likelihood of a complex trait or disease. However, existing PRS estimate genetic liability using common genetic variants, excluding the impact of rare variants. We identified rare, large-effect variants in individuals with outlier gene expression from the GTEx project and then assessed their impact on PRS predictions in the UK Biobank (UKB). We observed large deviations from the PRS-predicted phenotypes for carriers of multiple outlier rare variants; for example, individuals classified as “low-risk” but in the top 1% of outlier rare variant burden had a 6-fold higher rate of severe obesity. We replicated these findings using data from the NHLBI Trans-Omics for Precision Medicine (TOPMed) biobank and the Million Veteran Program, and demonstrated that PRS across multiple traits will significantly benefit from the inclusion of rare genetic variants.

The cutting depth required to control calotrope (Calotropis procera) plants using mechanical techniques

Abstract: Calotrope (Calotropis procera (Aiton) W.T. Aiton) is an exotic woody weed that has invaded northern Australia’s rangelands since being introduced in the early 1900s. To expand the range of control options beyond herbicide-based methods, we undertook a stem/root cutting experiment that helped quantify the potential for using mechanical control techniques. Individual, medium-sized (1.72 ± 0.03 m high) calotrope plants were cut off at ground level (0 cm) or below ground (10 or 20 cm) using either a pruning saw or mattock respectively. All calotrope plants cut at ground level reshot vigorously. After four months they had more than twice the number of stems (7.4 ± 0.54) of the uncut control plants and by 12 months they were only 26 cm shorter than the control plants. In contrast, all plants cut at 10 or 20 cm below ground were killed. Some mortality also started occurring in the control and ground level (0 cm) treatments after eight months, but appeared to be associated with a dieback phenomenon. Nevertheless, the results demonstrate the potential to use equipment that severs the root system below ground, such as blade ploughs and cutter bars. A subsequent stick raking demonstration achieved moderate plant mortality (72%) after 13 months, yet produced a six-fold increase in original plant density as a result of new seedling emergence. This finding supports the view that mechanical disturbance will often promote seedling recruitment, and land managers need to have the capacity to undertake follow-up control practices to avoid exacerbating the problem.