Jenkins, Gregory

This economic evaluation estimates the implementation costs and cost per additional patient receiving the vaccine associated with each of the intervention strategies for increasing rates of human papillomavirus (HPV) vaccination in primary care practices.

ABSTRACT Aims Common genetic variants have been linked to an increased risk of non-ischaemic cardiomyopathy (NICM). The primary objective of this study was to evaluate the significance of these variants in a general population. Methods and results Thirteen NICM risk alleles, previously validated by meta-analyses of case-control genetic association studies, were used to determine genetic risk (GR) in a large, unselected cohort (n = 1897) of Olmsted County residents aged >45 years. Clinical and echocardiographic data, with biomarkers, were correlated with this NICM-GR over a median of 16 years of follow-up (interquartile range [IQR] 15–17). There were no significant differences between the study population quartiles, based on NICM-GR, in terms of age (median 61.6 [IQR 53.6–70.4]), sex (48% male), and cardiovascular risk factors. A significant correlation was detected by specific linear-regression models between NICM-GR and left ventricular (LV) ejection-fraction (beta [standard error]: −2.68 [0.68], p < 0.001), LV end-systolic-diameter (0.22 [0.06], p < 0.001), and LV end-diastolic-diameter (0.14 [0.06], p = 0.01). During follow-up, 46 subjects developed NICM. Using a 3:1 matched-cohort of non-NICM versus NICM patients, linear-regression analysis found a significant correlation between NICM-GR and NICM development (odds ratio 2.27, 95% confidence interval 1.06–4.85, p = 0.03). There was no significant association between these variants and heart failure biomarkers (aldosterone, natriuretic peptides, ST2, galectin-3). Conclusions The NICM-GR correlates with LV function and dimension, and subsequent development of NICM in the general population. The lack of correlation of these variants with cardiovascular risk factors and the renin–angiotensin–aldosterone axis or natriuretic peptides suggest different biological mechanisms involved. These findings support the need to explore newer pathophysiologic pathways in the development of NICM.

ABSTRACTBackgroundInsomnia and substance use disorders (SUD) are common comorbidities of bipolar disorder (BD). Genome‐wide association studies (GWAS) have uncovered shared genetic contributions to insomnia and BD as well as SUDs and BD. Electronic health record (EHR) derived phenotypes (phecodes) and questionnaire data were used to examine the relationship between insomnia genetic liability and SUDs in BD.Methods40,839 participants from the Mayo Clinic Bipolar Disorder Biobank (BD Biobank; n = 774) and Mayo Clinic Biobank (n = 485 BD cases, n = 39,580 controls) were included in the analyses of diagnosis (phecode) outcomes (insomnia, SUD, alcohol use disorder [AUD] and tobacco use disorder [TUD]). Analyses of specific SUD outcomes obtained through the BD Biobank questionnaire included 1789 cases and considered BD subtype. Logistic regression was used to test for associations between insomnia polygenic risk scores (PRS) and insomnia and SUD outcomes in BD cases and controls.ResultsInsomnia PRS was associated with having an insomnia diagnosis (phecode) in the EHR in controls (OR = 1.19, p = 9.64e‐33) but not in BD cases (OR = 1, p = 0.95). Associations between insomnia PRS and SUD diagnoses were significant in BD cases and controls, with the association being stronger in BD cases (interaction p = 0.024). In the BD Biobank data, the insomnia PRS was associated with increased odds of AUD (OR = 1.19, p = 4.26e‐04), TUD (OR = 1.21, p = 1.25e‐05) and cannabis use disorder (OR = 1.16, p = 4.19e‐03).ConclusionThe effect of genetic predisposition to insomnia on SUD risk may be stronger in BD cases than in controls, which could have clinical care implications for individuals with BD and comorbid SUD.

Trial RegistrationClinicalTrials.gov Identifier: NCT03501992

AbstractBackgroundSomali immigrants and refugees constitute one of the largest African ethnic groups immigrating to the United States over the past three decades with the majority resettling in the state of Minnesota. Previous studies have documented significant cancer screening disparities between the Somali population and the general population. However, little is known about cancer incidence among Somali groups living in the United States.MethodsWe determined the incidence of 18 types or sites of malignancy using ICD‐9 and ICD‐10 codes and compared them between Somali and non‐Somali populations in Olmsted County, Minnesota utilizing the Rochester Epidemiology Project medical records‐linkage infrastructure for the years 2000–2020. Poisson regression models were used to model the rates for each malignancy.ResultsThere was a higher incidence and relative risk of liver malignancies among the Somali population versus non‐Somali population, but lower relative risk and incidence of the following malignancies: breast, cervical, and melanoma. After direct age‐sex adjustment to the United States 2000 Census population, liver was the most common cancer in Somali men, while breast cancer was the most common malignancy in women.ConclusionMalignancies related to infectious agents such as viral hepatitis have a higher incidence in the Somali immigrant population of Olmsted County. There is a lower incidence of malignancies related to lifestyle factors in this Somali population. Findings of this study may help inform cancer prevention and screening strategies among Somali communities in the United States.

Abstract BACKGROUND: The diagnosis of monoclonal B-cell lymphocytosis (MBL) is used to characterize patients who have a circulating population of clonal B-cells, a total B-cell count of <5 x 109/L, and no other features of another B-cell lymphoproliferative disorder. In most patients the immunophenotype is similar to that of chronic lymphocytic leukemia with co-expression of CD19 and CD5. The natural history of CLL-phenotype MBL is unclear. We used the Mayo Clinic hematopathology database to identify patients with CLL-phenotype MBL and abstracted clinical information on natural history and prognostic parameters from clinical and research records. METHODS: Using hematopathology records, we identified a cohort of 1820 patients seen at Mayo Clinic between August 1998 and May 2006 who underwent investigation using peripheral blood flow cytometry and who were found to have a clonal B-cell population of CLL phenotype. After elimination of patients with advanced stage (Rai I-IV), previously treated CLL, and individuals with an established diagnosis of CLL/MBL >1 year prior to flow, 636 unique patients with isolated lymphocytosis were identified. Based on our prior analysis (Leukemia Research 32:1458) demonstrating that nearly all patients with an ALC >10x109/L have a B-cell count >5x109/L, we focused the remaining analysis on the 405/636 patients who had an ALC <10x109/L and the necessary raw data from flow cytometry analysis to determine the B-cell count. RESULTS: Among the 405 individuals with an ALC <10x109/L, 306 (76%) had a B-cell count <5x109/L at the time of flow and met the current criteria for the diagnosis of MBL (BJH 130:325). Median age at the time of MBL diagnosis was 70 years (range 34 – 93). A slight male preponderance was observed (59% male). B-cell counts ranged from 0.02 to 4.99x109/L and ALC ranged from 0.3–9.6 x109/L. CD38 status was available for 268 (88%) MBL patients of whom 20% were CD38 positive using the 30% threshold. Cytogenetic analysis by fluorescent in situ hybridization (FISH) was available in 130 (42%) MBL patients. Using the hierarchical classification system of Dohner and colleagues, 57 (44%) were 13q-, 23 (18%) were trisomy 12, 5 (4%) were 11q-, 4 (3%) were 17p-, and 39 (30%) had no defect detected. ZAP-70 status was available for 77 (25%) patients of whom 13% were ZAP-70+ positive. Patients underwent sequential monitoring with a median follow-up of 1.7 yrs (range 0–8.1 yrs). Time from diagnosis to treatment for patients meeting criteria for MBL (n=306) as compared to Rai stage 0 CLL patients with B-cell counts between 5.0 and 10.0 x109/L (n=99) was not significantly different and is shown in Figure 1 (p=0.87). For individuals with MBL, survival free of treatment was 98% (95%CI: 96–100%) at 1 year, 93% (95%CI: 89–98%) at 2 years, and 77% (95%CI: 67–89%) at 5 years. While gender (p=0.10), and B-cell count as a continuous variable (p=0.15) were not found to be associated with time to treatment (TTT) among MBL patients, age (p=0.02, HR=0.94, 95% CI: 0.89–0.99) and CD38 status (p<0.02, HR: 3.3, 95% CI: 1.2–9.2) did show a relationship with TTT. CONCLUSIONS: Although we observed a low rate of progression among individuals meeting criteria for MBL, TFS was similar to individuals meeting current criteria for Rai stage 0 CLL who had B-cell counts between 5.0 – 10.0 x109/L . Among individuals meeting criteria for MBL, younger patients and those who were CD38 positive had a shorter time to treatment. Additional studies are needed to determine what B-cell count or other characteristics should be used to distinguish between MBL and Rai stage 0 CLL. FIGURE: FIGURE:.

Abstract BACKGROUND: The diagnosis of CLL among asymptomatic patients without lymphadenopathy or cytopenias has historically been based on documenting a characteristic lymphocyte clone and the presence of lymphocytosis. Currently, there are no data regarding what lymphocyte type (absolute lymphocyte count [ALC] or B-cell count) or threshold should be used for this diagnosis. We analyzed the relationship of these lymphocyte counts to clinical outcome in a cohort of 459 patients to determine whether the CLL diagnosis: should be based on ALC or B-cell count what lymphocyte threshold should be used for diagnosis whether any lymphocyte counts has independent prognostic value after accounting for molecular prognostic markers. METHODS: We used the Mayo Clinic CLL database to identify all Rai stage 0 patients diagnosed with CLL between 1/1/00 and 12/31/07 who were evaluated and had flow cytometry at Mayo within 12 months of diagnosis. All patients had lymphocytosis (ALC ≥5 x 109/L) and fulfilled the 1996 criteria for CLL. Raw data from the peripheral blood flow analysis was used in conjunction with blood counts to determine ALC and absolute B-cell count at diagnosis. Estimates of survival were calculated using the Kaplan-Meier method. RESULTS: To assess whether B-cell count or ALC more strongly related to clinical outcome, we evaluated the relationship of these variables with treatment free survival (TFS) and overall survival (OS; n=459). When treated as continuous variables (i.e. measuring risk of each 1.0 x 109/L increase in cell count), both ALC and B-cell count were related to TFS (hazard ratio [HR] ALC=1.02; p<0.0001; HR B-cell count=1.02; p<0.0001) and OS (HR ALC=1.02; p=0.04; HR B-cell count=1.02; p=0.02). Because B-cell count and ALC related to TFS and OS as a continuous variables, we next evaluated what threshold (nearest 1.0 x109/L) at diagnosis best related to an individual’s risk of requiring chemotherapeutic treatment and/or dying of CLL using the HR (log rank statistic) and c-statistic [c=1 indicates perfect discrimination between poor survivors and good survivors; c=0.5 equivalent to chance]. The B-cell threshold that best predicted OS was 11 x 109/L (HR=2.36, p=0.01; c=0.60). This threshold also predicted TFS (HR=3.02; p<0.0001; c=0.64). With respect to ALC, a threshold of 12 x 109/L was able to predict TFS (HR=2.28, p=0.003; c=0.62) but not OS (HR=1.62, p=0.12; c=0.56). The B-cell threshold used in the current diagnostic criteria (5 x 109/L) was able to predict TFS (HR=3.24, p<0.0001; c=0.63), but not OS (HR=1.64, p=0.13; c=0.55) Finally, we evaluated the ability of B-cell count to predict TFS independent of IGHV mutation status, ZAP-70 status, CD38 status, and FISH. Since not all patients had all prognostic tests performed, the predictive value of B-cell count (< or ≥11 x 109) independent of the other prognostic variable was assessed for each variable independently. B-cell count retained prognostic value independent of IGHV mutation status, ZAP-70 status, CD38 status, and FISH (all p≤0.001) [Table]. CONCLUSIONS: Although B-cell count and ALC have similar ability to predict TFS and OS as continuous variables, B-cell count may be a better predictor of TFS and OS when a defined lymphocyte threshold is used. These findings provide evidence to justify the recent proposal by Hallek et al (Blood 111:5446) to base the diagnosis of CLL on B-cell count rather than ALC. The results also provide justification for retaining the size of the B-cell count as part of the diagnostic criteria even in the era of molecular/biologic prognostic markers, but imply a threshold of 11 x 109 is the B-cell count that best predicts patient’s TFS and risk of death. Differentiating between CLL and MBL based on a patient’s likelihood of developing clinical symptoms and dying of disease could minimize unnecessary psychologic distress caused by labeling asymptomatic individuals at low risk for adverse clinical consequences as having leukemia. TABLE: TREATMENT FREE SURVIVAL HR p-value CD38 + 3.20 0.0002 B-cell ≥11 3.10 0.0001 ZAP + 8.33 < 0.0001 B-cell ≥11 6.86 < 0.0001 Unmutated 5.26 < 0.0001 B-cell ≥11 3.06 0.001 FISH (17p- or 11q-) 3.97 0.01 B-cell ≥11 3.67 < 0.0001

Background Neprilysin is a metalloprotease involved in proteolysis of numerous peptides, including natriuretic peptides, and is of prognostic and therapeutic importance in heart failure with reduced ejection fraction. No studies have investigated circulating neprilysin in the community, its clinical correlates, or its relationship to cardiovascular disease in the general population. Methods and Results Plasma neprilysin was measured in 1536 participants from Olmsted County, Minnesota, using a commercially available sandwich ELISA assay. Clinical and echocardiographic correlates and subsequent outcomes were determined. Soluble neprilysin is non‐normally distributed in the community (median: 3.9 ng/mL; interquartile range: 1.0–43.0 ng/mL). There was no relationship between plasma neprilysin and age (Spearman correlation: −0.04, P =0.16); body mass index (Spearman correlation: −0.04, P =0.16); glomerular filtration rate (Spearman correlation: −0.007, P =0.8); or A‐, B‐, or C‐type natriuretic peptides (Spearman correlation: 0.03, P =0.22; −0.001, P =0.96; 0.01, P =0.67, respectively). Among tertiles of neprilysin, the lowest tertile group had the highest prevalence of smokers ( P <0.001), hypertension ( P =0.04), dyslipidemia ( P =0.03), and diastolic dysfunction ( P =0.02). Soluble neprilysin was not prospectively associated with death or heart failure over a median of 10.7 years. Conclusions In a large community‐based cohort, for the first time, we described the distribution of circulating neprilysin in the general community. We observed that neprilysin does not correlate with natriuretic peptide levels and is not independently associated with adverse outcomes. The novel associations observed between low soluble neprilysin levels and an adverse cardiometabolic and smoking profile requires further investigation.

Objectives: Persistent cognitive impairment after critical illness is an important healthcare problem forecasted to worsen in the near future. However, the epidemiology is insufficiently explored. We aimed to determine potentially modifiable risk factors during ICU hospitalization that play a significant role in developing persistent cognitive impairment. Design: An observational case-control study. Settings: Mayo Clinic ICUs between July 1, 2004, and November 20, 2015. Patients: We conducted a study nested in a large cohort of 98,227 adult critically ill patients. Using previously validated computable phenotypes for dementia and cognitive impairment, we determined the onset of cognitive impairment relative to ICU hospitalization and associated risk factors. The primary endpoint of the study was new and persistent cognitive impairment documented between 3 and 24 months after ICU discharge. Interventions: Unadjusted and adjusted analyses were performed to identify potentially modifiable risk factors during ICU hospitalization. Measurements and Main Results: Among 21,923 unique patients identified as cognitively impaired (22% of the entire ICU cohort), 2,428 (2.5%) developed incident new and persistent cognitive dysfunction after the index ICU admission. Compared with age- and sex-matched ICU controls (2,401 pairs), cases had higher chronic illness burden (Charlson Comorbidity Index, 6.2 vs 5.1; p < 0.01), and were more likely to have multiple ICU stays (22% vs 14%; p < 0.01). After adjustment for baseline differences, new and persistent cognitive dysfunction was associated with higher frequency of acute brain failure in the ICU, a higher exposure to severe hypotension, hypoxemia, hyperthermia, fluctuations in serum glucose, and treatment with quinolones or vancomycin. Association with sepsis observed in univariate analysis did not persist after adjustment. Conclusions: Cognitive dysfunction is highly prevalent in ICU patients. Incident new and persistent cognitive impairment is less common but important, potentially preventable problem after critical illness. Chronic comorbidities and number of ICU stays increase the risk of post-ICU cognitive dysfunction irrespective of age. Modifiable ICU exposures were identified as potential targets for future prevention trials.

AbstractBackgroundRenal dysfunction occurs commonly after heart transplantation (HTx) with wide inter‐individual variability but whether a genetic predisposition exists in these patients is unknown. Genomewide association studies (GWAS) have not been performed to assess the association of genetic variation with change in renal function after HTx.MethodsClinical and demographic data of patients who underwent HTx and provided blood samples and consent for genetic analysis were included. Genotyping was performed using Illumina Infinium Human CoreExome v1.0 analysis kit. A GWAS utilizing linear regression models was performed with estimated glomerular filtration rate (eGFR) at 1 year as the phenotype after adjusting for baseline eGFR prior to HTx and conversion from calcineurin inhibitor to sirolimus as primary immunosuppression therapy.ResultsA total of 251 HTx recipients were genotyped for 314,903 single nucleotide polymorphisms (SNPs). The mean (SD) age was 50 (12.5) years; most patients were of European origin (n = 243, 96.8%) and males (n = 179, 71.3%). After adjustment for potential confounders, two variants, rs17033285 (P = 4.3 × 10−7) and rs4917601 (P = 6.46 × 10−7), in a long non‐coding RNA (lncRNA) gene LINC01121 and a pseudogene BTBD7P2, were identified to have a significant association with change in GFR at 1 year after HTx.ConclusionsOur first of its kind GWAS demonstrates that genetic variation affects renal function after HTx independent of other risk factors. Agnostic genetic approaches such as these may lead to identification of novel biological pathways such as the role of lncRNAs in the development of renal dysfunction post‐HTx.