Citations

AbstractObjectiveThis study sought to determine if single‐chamber operation and/or loss of rate response (RR) during elective replacement indicator (ERI) in patients with dual‐chamber pacemakers lead to increased symptom burden, healthcare utilization, and atrial fibrillation (AF).BackgroundDual‐chamber pacemakers often change from dual‐ to single‐chamber pacing mode and/or lose RR functionality at ERI to preserve battery. Single‐chamber pacing increases the incidence of heart failure, AF, and pacemaker syndrome suggesting these changes may be deleterious.MethodsA retrospective analysis of 700 patients was completed. Three comparisons were analyzed: Comparison 1: mode change and RR loss versus no change; Comparison 2: RR loss only versus no change; Comparison 3: mode change only versus no change (in patients with no RR programmed at baseline).ResultsIn Comparison 1, 121 (46%) patients with setting changes experienced symptoms (most often dyspnea and fatigue/exercise intolerance) versus 3 (4%) without setting changes (p < .0001). Similar results were noted in Comparisons 2 and 3 (p = .0016 and p = .0001, respectively). In Comparison 1, patients with setting change sought provider contact more than patients without setting changes (p = .0001). A significant difference was not noted in Comparison 2 or 3. Overall 14 (2%) patients were hospitalized, all of whom had setting changes.ConclusionsSetting changes at ERI including a change from dual‐ to single‐chamber pacing and/or loss of RR results in a significantly increased symptom burden and increased healthcare utilization.

Abstract Registry-based epidemiologic studies suggest associations between chronic inflammatory intestinal diseases and pancreatic ductal adenocarcinoma (PDAC). As genetic susceptibility contributes to a large proportion of chronic inflammatory intestinal diseases, we hypothesize that the genomic regions surrounding established genome-wide associated variants for these chronic inflammatory diseases are associated with PDAC. We examined the association between PDAC and genomic regions (±500 kb) surrounding established common susceptibility variants for ulcerative colitis, Crohn's disease, inflammatory bowel disease, celiac disease, chronic pancreatitis, and primary sclerosing cholangitis. We analyzed summary statistics from genome-wide association studies data for 8,384 cases and 11,955 controls of European descent from two large consortium studies using the summary data-based adaptive rank truncated product method to examine the overall association of combined genomic regions for each inflammatory disease group. Combined genomic susceptibility regions for ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis were associated with PDAC at P values &lt; 0.05 (0.0040, 0.0057, 0.011, and 3.4 × 10−6, respectively). After excluding the 20 PDAC susceptibility regions (±500 kb) previously identified by GWAS, the genomic regions for ulcerative colitis, Crohn disease, and inflammatory bowel disease remained associated with PDAC (P = 0.0029, 0.0057, and 0.0098, respectively). Genomic regions for celiac disease (P = 0.22) and primary sclerosing cholangitis (P = 0.078) were not associated with PDAC. Our results support the hypothesis that genomic regions surrounding variants associated with inflammatory intestinal diseases, particularly, ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis are associated with PDAC. Significance: The joint effects of common variants in genomic regions containing susceptibility loci for inflammatory bowel disease and chronic pancreatitis are associated with PDAC and may provide insights to understanding pancreatic cancer etiology.

AbstractSchwann cells are the nerve ensheathing cells of the peripheral nervous system. Absence, loss and malfunction of Schwann cells or their myelin sheaths lead to peripheral neuropathies such as Charcot-Marie-Tooth disease in humans. During Schwann cell development and myelination chromatin is dramatically modified. However, impact and functional relevance of these modifications are poorly understood. Here, we analyzed histone H2B monoubiquitination as one such chromatin modification by conditionally deleting the Rnf40 subunit of the responsible E3 ligase in mice. Rnf40-deficient Schwann cells were arrested immediately before myelination or generated abnormally thin, unstable myelin, resulting in a peripheral neuropathy characterized by hypomyelination and progressive axonal degeneration. By combining sequencing techniques with functional studies we show that H2B monoubiquitination does not influence global gene expression patterns, but instead ensures selective high expression of myelin and lipid biosynthesis genes and proper repression of immaturity genes. This requires the specific recruitment of the Rnf40-containing E3 ligase by Egr2, the central transcriptional regulator of peripheral myelination, to its target genes. Our study identifies histone ubiquitination as essential for Schwann cell myelination and unravels new disease-relevant links between chromatin modifications and transcription factors in the underlying regulatory network.

Abstract Background: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level. Methods: We conducted a gene–environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I–III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case–control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics. Results: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P &lt; 1.25 × 10−6) was observed in the meta-analysis (PGxE = 1.2 ×10−6, PJoint = 4.2 ×10−7). Conclusions: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans. Impact: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.

Background: Long-QT syndrome (LQTS) is characterized by a prolonged heart rate–corrected QT interval (QTc). Genome-wide association studies identified common genetic variants that collectively explain ≈8% to 10% of QTc variation in the general population. Methods: Overall, 423 patients with LQT1, LQT2, or LQT3 were genotyped for 61 QTc-associated genetic variants used in a prototype QTc–polygenic risk score (QTc-PRS). A weighted QTc-PRS (range, 0–154.8 ms) was calculated for each patient, and the FHS (Framingham Heart Study) population-based reference cohort (n=853). Results: The average QTc-PRS in LQTS was 88.0±7.2 and explained only ≈2.0% of the QTc variability. The QTc-PRS in LQTS probands (n=137; 89.3±6.8) was significantly greater than both FHS controls (87.2±7.4, difference-in-means±SE: 2.1±0.7, P <0.002) and LQTS genotype-positive family members (87.5±7.4, difference-in-mean, 1.8±.7, P <0.009). There was no difference in QTc-PRS between symptomatic (n=156, 88.6±7.3) and asymptomatic patients (n=267; 87.7±7.2, difference-in-mean, 0.9±0.7, P=0.15). LQTS patients with a QTc≥480 ms (n=120) had a significantly higher QTc-PRS (89.3±6.7) than patients with a QTc<480 ms (n=303, 87.6±7.4, difference-in-mean, 1.7±0.8, P <0.05). There was no difference in QTc-PRS or QTc between genotypes. Conclusions: The QTc-PRS explained <2% of the QTc variability in our LQT1, LQT2, and LQT3 cohort, contributing 5× less to their QTc value than in the general population. This prototype QTc-PRS does not distinguish/predict the clinical outcomes of individuals with LQTS.

8026 Background: CLL progression and CLL-related complications (infections and second malignancies) were the leading cause of death (COD) in a prospective cohort of CLL patients (Strati, BJH 2017). The CLL-IPI integrates major clinical and molecular prognostic factors and stratifies patients into 4 risk groups with distinct prognosis. It is unknown if COD differs according to CLL-IPI risk group in patients with newly diagnosed CLL. Methods: Patients diagnosed with CLL between 1/2000-12/2019 and seen within 1 year of diagnosis were identified from the Mayo Clinic CLL database. Cumulative incidences of cause-specific death were analyzed using Gray’s test, with deaths from different causes treated as competing events and deaths from unknown causes excluded. Results: 1276 patients were included in this study. The median age at diagnosis was 63 years (range 24-92), and 880 (69%) were male. Based on CLL-IPI score, 449 (35%) had low risk disease, 443 (35%) had intermediate risk disease, and 384 (30%) had high/very high risk disease. Median follow-up time for the study was 6 years; 286 deaths occurred. The COD was CLL progression in 99 (35%), infection in 16 (6%), second malignancy in 47 (16%), CLL-unrelated in 59 (21%), and unknown in 65 (23%) patients. The rates of death due to CLL progression were higher (17.3% at 5 years; 30.3% at 10 years) than the rates due to CLL-related complications (5.7% at 5 years; 12.9% at 10 years) or due to CLL-unrelated causes (8.6% at 5 years; 16.9% at 10 years) in the CLL-IPI high/very high risk group, but not the CLL-IPI low or intermediate risk group (Table). A higher CLL-IPI risk group was associated with a higher rate of death due to CLL progression ( P < 0.001), as well as a higher rate of death due to CLL-related complications ( P = 0.013), and CLL-unrelated causes ( P < 0.001). Conclusions: Causes of death in newly diagnosed CLL patients differ according to their CLL-IPI risk group. In patients with high/very high risk CLL, improving CLL disease control with novel agents seems justified. In patients with low/intermediate risk CLL, there should be increased efforts to reverse immune dysfunction to reduce infections and second malignancies. [Table: see text]

PURPOSE To provide evidence-based guidance on the clinical management of cancer cachexia in adult patients with advanced cancer. METHODS A systematic review of the literature collected evidence regarding nutritional, pharmacologic, and other interventions, such as exercise, for cancer cachexia. PubMed and the Cochrane Library were searched for randomized controlled trials (RCTs) and systematic reviews of RCTs published from 1966 through October 17, 2019. ASCO convened an Expert Panel to review the evidence and formulate recommendations. RESULTS The review included 20 systematic reviews and 13 additional RCTs. Dietary counseling, with or without oral nutritional supplements, was reported to increase body weight in some trials, but evidence remains limited. Pharmacologic interventions associated with improvements in appetite and/or body weight include progesterone analogs and corticosteroids. The other evaluated interventions either had no benefit or insufficient evidence of benefit to draw conclusions on efficacy. Limitations of the evidence include high drop-out rates, consistent with advanced cancer, as well as variability across studies in outcomes of interest and methods for outcome assessment. RECOMMENDATIONS Dietary counseling may be offered with the goals of providing patients and caregivers with advice for the management of cachexia. Enteral feeding tubes and parenteral nutrition should not be used routinely. In the absence of more robust evidence, no specific pharmacological intervention can be recommended as the standard of care; therefore, clinicians may choose not to prescribe medications specifically for the treatment of cancer cachexia. Nonetheless, when it is decided to trial a drug to improve appetite and/or improve weight gain, currently available pharmacologic interventions that may be used include progesterone analogs and short-term (weeks) corticosteroids.

Background: Long QT syndrome (LQTS) is a rare genetic disorder and a major preventable cause of sudden cardiac death in the young. A causal rare genetic variant with large effect size is identified in up to 80% of probands (genotype positive) and cascade family screening shows incomplete penetrance of genetic variants. Furthermore, a proportion of cases meeting diagnostic criteria for LQTS remain genetically elusive despite genetic testing of established genes (genotype negative). These observations raise the possibility that common genetic variants with small effect size contribute to the clinical picture of LQTS. This study aimed to characterize and quantify the contribution of common genetic variation to LQTS disease susceptibility. Methods: We conducted genome-wide association studies followed by transethnic meta-analysis in 1656 unrelated patients with LQTS of European or Japanese ancestry and 9890 controls to identify susceptibility single nucleotide polymorphisms. We estimated the common variant heritability of LQTS and tested the genetic correlation between LQTS susceptibility and other cardiac traits. Furthermore, we tested the aggregate effect of the 68 single nucleotide polymorphisms previously associated with the QT-interval in the general population using a polygenic risk score. Results: Genome-wide association analysis identified 3 loci associated with LQTS at genome-wide statistical significance ( P <5×10 −8 ) near NOS1AP , KCNQ1 , and KLF12 , and 1 missense variant in KCNE1 (p.Asp85Asn) at the suggestive threshold ( P <10 −6 ). Heritability analyses showed that ≈15% of variance in overall LQTS susceptibility was attributable to common genetic variation ( h2SNP 0.148; standard error 0.019). LQTS susceptibility showed a strong genome-wide genetic correlation with the QT-interval in the general population (r g =0.40; P =3.2×10 −3 ). The polygenic risk score comprising common variants previously associated with the QT-interval in the general population was greater in LQTS cases compared with controls ( P <10−13), and it is notable that, among patients with LQTS, this polygenic risk score was greater in patients who were genotype negative compared with those who were genotype positive ( P <0.005). Conclusions: This work establishes an important role for common genetic variation in susceptibility to LQTS. We demonstrate overlap between genetic control of the QT-interval in the general population and genetic factors contributing to LQTS susceptibility. Using polygenic risk score analyses aggregating common genetic variants that modulate the QT-interval in the general population, we provide evidence for a polygenic architecture in genotype negative LQTS.