Vascular Contributions to Brain Health: Cross-Cutting Themes

As life expectancy grows, brain health is increasingly seen as central to what we mean by successful aging—and vascular brain health as central to overall brain health. Cerebrovascular pathologies are highly prevalent independent contributors to age-related cognitive impairment and at least partly modifiable with available treatments. The current Focused Update addresses vascular brain health from multiple angles, ranging from pathophysiologic mechanisms and neuroimaging features to epidemiologic risk factors, social determinants, and candidate treatments. Here we highlight some of the shared themes that cut across these distinct perspectives: 1) the lifetime course of vascular brain injury pathogenesis and progression; 2) the scientific and ethical imperative to extend vascular brain health research in non-White and non-affluent populations; 3) the need for improved tools to study the cerebral small vessels themselves; 4) the potential role for brain recovery mechanisms in determining vascular brain health and resilience; and 5) the cross-pathway mechanisms by which vascular and neurodegenerative processes may interact. The diverse perspectives featured in this Focused Update offer a sense of the multidisciplinary approaches and collaborations that will be required to launch our populations towards improved brain health and successful aging.

Acute Pediatric Chagas Disease in Antioquia, Colombia: A Geographic Location of Suspected Oral Transmission

Chagas disease, Trypanosoma cruzi infection, is an insidious cause of heart failure in Latin America. Early diagnosis and treatment are critical to prevent irreversible myocardial damage that progressively accumulates over decades. Several structural barriers account for the less than 1% of cases in Colombia being treated, including poor physician knowledge, especially considering that some regions are considered non-endemic. The two cases reported here represent an emerging epidemiologic scenario associated with pediatric Chagas disease. Both cases are suspected oral transmitted parasitic infection in a geographic region of Colombia (Andean region of Antioquia) where no previous oral transmission of Chagas disease had been reported. Their clinical histories and course of disease are presented here to increase physician awareness of the epidemiologic risk factors and clinical manifestations associated with pediatric oral Chagas disease in Antioquia department, Colombia.

Epidemiologic and Clinical Analysis of Tumor Mutational Burden (TMB) in Acute Myeloid Leukemia (AML): Exome Sequencing Study of the Mayo Clinic AML Epidemiology Cohort (MCAEC)

TMB is used to guide PD-1-directed immunotherapy in solid tumor Oncology. However, it has not been systematically studied in AML, where the focus has been on cytogenetic risk and individual driver gene mutations (GM's). TMB contribution to AML epidemiology is also uncertain. We therefore studied its association with epidemiologic risk factors; driver GM's and somatic mutations (SM's) in AML risk genes which we recently demonstrated (ABCB1; CYP1A1; CYP2B6; EPHX1; ERCC1,2,& 5; MEFV; MTRR; and TERT); clinical and cytogenetic features; and outcome after therapy in the MCAEC, a highly annotated clinical epidemiology cohort of consecutive AML pts [Finn, Cancer Epidemiol 39:1084, 2015]. Methods: We obtained somatic leukemia DNA from remnant diagnostic cytogenetic pellets in 98 MCAEC patients (pts), as previously described [Foran, Blood (2017) 130:570a]. Whole exome sequencing (WES) was performed at depth of ~100 million paired end 100bp reads using Agilent SureSelectXT Human All Exon V5 + UTRs target enrichment kit. Reads were mapped to human genome build hg19 using BWA-MEM. Single nucleotide variants (SNVs) and small INDELs were identified using Mayo Clinic (MC) analytic pipeline GenomeGPS 4.0.1 following Broad GATK variant discovery best practices of alignment, realignment and recalibration, and multi-sample joint genotyping; and filtered using both germline whole exome and genome sequencing of ~1200 MC Biobank samples and public germline variant databases of 1000 genome project, 6500 individuals in exome sequencing project, and HapMap phase 3. Remaining variants were annotated using ANNOVAR, and functional variants of non-synonymous, truncating, frame-shift, and splice-sites were used in the statistical association analyses. TMB was defined as the number of functional mutations per Mb of coding region, heterozygous or homozygous. TMB associations with epidemiologic risk, clinical characteristics, and SM's in AML risk genes (listed above) or driver GM's (occurring in 5 or more pts: ASXL1, BCOR, CEBPA, DNMT3A, FLT3, IDH2, KRAS, MLL2-5, NF1, NPM1, NRAS, PHF6, RUNX1, SF3B1, STAG2, TET2, TP53, U2AF1) were evaluated using linear regression models; a rank transformation of TMB was utilized due to its skewed distribution. Multivariable analysis (MVA) models were adjusted for variables with p-value <0.05 in unadjusted analysis. Regression coefficients ("β") were estimated, interpreted as change in mean TMB rank for specified variables or characteristic. Associations with outcomes were examined using logistic regression or Cox proportional hazards regression models. All statistical tests were two-sided (version 3.6.2; R Foundation for Statistical Computing, Vienna, Austria). Results Median age at AML diagnosis was 70 yrs (Range: 19-94 yrs), and 67 pts were male. Cytogenetic risk group was favorable (7%), intermediate-normal (46%) or abnormal (20%), and poor risk (27%). 40/61 pts (66%) achieved complete remission (CR). With a median follow-up of 8.0 months (Range: 0.1 - 186), 80 pts (82%) died and 20 (20%) underwent allogeneic transplantation (AlloBMT). Median TMB was 18.2 (Range: 15.0-70.1). In MVA, significant associations with increased TMB were observed in pts with history of prior immunosuppressive therapy or solid organ transplantation (β=19.48, P=0.015), and with FLT3 (β=21.12, P=0.015), MLL2 (β=20.91, P=0.001), and MLL3 (β=11.31, P=0.031) GM's. A borderline association was observed for U2AF1 (β=16.14, P=0.057). TMB was also associated with SM's in TERT (β=25.13, P=0.028); a borderline association with SM's in ABCB1 was not confirmed in MVA (β=-17.98, P=0.069). Additionally, cytogenetic risk group was associated with TMB in MVA (P=0.005), being highest in intermediate-normal and lowest in poor risk groups. Body Mass Index was inversely associated with TMB (unadjusted β=-16.99, P=0.005), but unconfirmed in MVA (β=-8.29, P=0.12). There was no association with CR (OR=0.93, P=0.46), use of (HR=0.96, P=0.64) or relapse risk (HR=1.00, P=0.98) following AlloBMT, or survival (HR=0.97, P=0.56) (Figure). Conclusions Measurement of TMB is feasible in this AML epidemiologic cohort, and we observed important associations with AML risk factors, risk gene SM's, cytogenetic risk group, and driver GM's. We acknowledge the relatively small sample size and possibility of type II error, and therefore these observations require validation in a large prospective cohort which is planned. Figure 1 Figure 1. Disclosures Foran: OncLive: Honoraria; certara: Honoraria; actinium: Research Funding; boehringer ingelheim: Research Funding; novartis: Honoraria; abbvie: Research Funding; servier: Honoraria; taiho: Honoraria; pfizer: Honoraria; revolution medicine: Honoraria; gamida: Honoraria; takeda: Research Funding; sanofi aventis: Honoraria; trillium: Research Funding; syros: Honoraria; aptose: Research Funding; bms: Honoraria; kura: Research Funding; h3bioscience: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding. Murthy: CRISPR Therapeutics: Research Funding. Finn: Jazz: Consultancy, Speakers Bureau; BMS: Consultancy, Speakers Bureau; BeiGene: Consultancy, Speakers Bureau; ADC Therapeutics: Consultancy, Speakers Bureau. Badar: Pfizer Hematology-Oncology: Membership on an entity's Board of Directors or advisory committees. Cerhan: Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; Genentech: Research Funding; NanoString: Research Funding; Regeneron Genetics Center: Other: Research Collaboration.

603. Misdiagnosis of Lyme Disease in Patients Referred to an Academic Lyme Center

Background Confusion and controversy surround various aspects of Lyme Disease (LD) including diagnosis. Typically, the diagnosis of LD is based on tick exposure, clinical history, exam, and laboratory testing. Laboratory testing and interpretation can be confusing, difficult, and a source of misdiagnosis. Methods One hundred and fifteen records of patients referred to the Integrated Lyme Program at University of Maryland for evaluation of LD were analyzed. All patients underwent initial evaluation by Infectious Disease (ID) physician who made a determination regarding Lyme diagnosis based on history, exam, epidemiologic risk factors and laboratory test results. Pt were determined to have one of the following diagnoses: 1) Acute LD 2) Past LD 3) Post Treatment Lyme Disease Syndrome (PTLDS) 4) Misdiagnosed LD. Data was also collected on reasons for misdiagnosis based on record review, referral information and patient reported information. Results We evaluated 115 patient records from our Lyme Program Registry. There were 78 female (68%) and 37 males (32%). The mean age was 46 years (range 19 to 83). Of the 115 records analyzed, there were 8 (7%) patients with acute Lyme disease; 38 (33%) patients with past Lyme disease , 3 (2.6%) patients with PTLDS and 93 (81%) of patients who were misdiagnosed with LD. Patients were misdiagnosed for multiple reasons and by different people. Twenty three percent (21/93) were misdiagnosed based on false positive IGM Western Blot; 16% (15/93) were misdiagnosed based on misread IGG Western Blot and 14% (13/93) were misdiagnosed based on unconventional Lyme test. The remainder were misdiagnosed based on symptoms. Forty two percent (39/93) were misdiagnosed by PCP; 4.3%(3/93) were misdiagnosed by Urgent/Emergent care physician and 31% (29/93) were misdiagnosed by physicians’ self-referred as Lyme Literate Medical Doctor. The remainder were incorrectly self-diagnosed by patients based on symptoms. Conclusion Misdiagnosis of patients referred to Lyme Center is common and due to various reasons including misinterpretation of laboratory Lyme testing by healthcare providers and misinterpretation of symptoms by patients. Disclosures All Authors: No reported disclosures

Different approaches to quantify years of life lost from COVID-19

The burden of an epidemic is often characterized by death counts, but this can be misleading as it fails to acknowledge the age of the deceased patients. Years of life lost is therefore widely used as a more relevant metric, however, such calculations in the context of COVID-19 are all biased upwards: patients dying from COVID-19 are typically multimorbid, having far worse life expectation than the general population. These questions are quantitatively investigated using a unique Hungarian dataset that contains individual patient level data on comorbidities for all COVID-19 deaths in the country. To account for the comorbidities of the patients, a parametric survival model using 11 important long-term conditions was used to estimate a more realistic years of life lost. As of 12 May, 2021, Hungary reported a total of 27,837 deaths from COVID-19 in patients above 50 years of age. The usual calculation indicates 10.5 years of life lost for each death, which decreases to 9.2 years per death after adjusting for 11 comorbidities. The expected number of years lost implied by the life table, reflecting the mortality of a developed country just before the pandemic is 11.1 years. The years of life lost due to COVID-19 in Hungary is therefore 12% or 1.3 years per death lower when accounting for the comorbidities and is below its expected value, but how this should be interpreted is still a matter of debate. Further research is warranted on how to optimally integrate this information into epidemiologic risk assessments during a pandemic.

Recent SARS-CoV-2 seroconversion in a national, community-based prospective cohort of U.S. adults

SHORT ABSTRACTEpidemiologic risk factors for incident SARS-CoV-2 infection are best characterized via prospective cohort studies, complementing case-based surveillance and cross-sectional seroprevalence studies. In March 2020, we launched the CHASING COVID Cohort Study, a national, community-based prospective cohort study of 6,745 U.S. adults who underwent at-home specimen collection for repeat serologic testing for SARS-CoV-2 antibodies. We identify and quantify several policy-sensitive risk factors for recent SARS-CoV-2 seroconversion, highlight persistent racial/ethnic disparities in incidence, document continued elevated risk among essential workers, and call attention to major gaps in the coverage of public health interventions aimed at testing, isolation, and contact tracing. We conclude that modifiable risk factors and poor reach of public health strategies drive SARS-CoV-2 transmission and inequities across the U.S.

Perinatal granulopoiesis and risk of pediatric asthma

There are perinatal characteristics, such as gestational age, reproducibly associated with the risk for pediatric asthma. Identification of biologic processes influenced by these characteristics could facilitate risk stratification or new therapeutic targets. We hypothesized that transcriptional changes associated with multiple epidemiologic risk factors would be mediators of pediatric asthma risk. Using publicly available transcriptomic data from cord blood mononuclear cells, transcription of genes involved in myeloid differentiation was observed to be inversely associated with a pediatric asthma risk stratification based on multiple perinatal risk factors. This gene signature was validated in an independent prospective cohort and was specifically associated with genes localizing to neutrophil-specific granules. Further validation demonstrated that umbilical cord blood serum concentration of PGLYRP-1, a specific granule protein, was inversely associated with mid-childhood current asthma and early-teen FEV1/FVCx100. Thus, neutrophil-specific granule abundance at birth predicts risk for pediatric asthma and pulmonary function in adolescence.

Legionnaires’ disease in the time of COVID-19

Due to similarities in initial disease presentation, clinicians may be inclined to repeatedly test community-acquired pneumonia cases for COVID-19 before recognizing the need to test for Legionnaires’ disease. Legionnaires’ disease is an illness characterized by pneumonia that has a summer/early fall seasonality due to favorable conditions for Legionella growth and exposure. Legionella proliferate in warm water environments and stagnant sections of indoor plumbing and cooling systems. During the ongoing pandemic crisis, exposures to aerosolized water from recently reopened office or retail buildings should be considered as an epidemiologic risk factor for Legionella exposure and an indication to test. The majority of Legionnaires’ disease cases occurring each year are not diagnosed, and some experts recommend that all patients hospitalized with community-acquired pneumonia without a known etiology be tested for Legionella infection. Proper diagnosis can increase the likelihood of appropriate and timely antibiotic treatment, identify potential clusters of disease, and facilitate source attribution.

Analysis of SARS-CoV-2 antibodies in COVID-19 convalescent blood using a coronavirus antigen microarray

The current practice for diagnosis of COVID-19, based on SARS-CoV-2 PCR testing of pharyngeal or respiratory specimens in a symptomatic patient at high epidemiologic risk, likely underestimates the true prevalence of infection. Serologic methods can more accurately estimate the disease burden by detecting infections missed by the limited testing performed to date. Here, we describe the validation of a coronavirus antigen microarray containing immunologically significant antigens from SARS-CoV-2, in addition to SARS-CoV, MERS-CoV, common human coronavirus strains, and other common respiratory viruses. A comparison of antibody profiles detected on the array from control sera collected prior to the SARS-CoV-2 pandemic versus convalescent blood specimens from virologically confirmed COVID-19 cases demonstrates near complete discrimination of these two groups, with improved performance from use of antigen combinations that include both spike protein and nucleoprotein. This array can be used as a diagnostic tool, as an epidemiologic tool to more accurately estimate the disease burden of COVID-19, and as a research tool to correlate antibody responses with clinical outcomes.