Combined Scintigraphy and Tumor Marker Analysis Predicts Unfavorable Histopathology of Neuroblastic Tumors with High Accuracy

Objectives Our aim was to improve the prediction of unfavorable histopathology (UH) in neuroblastic tumors through combined imaging and biochemical parameters. Methods I-123-MIBG SPECT and MRI was performed before surgical resection or biopsy in 47 consecutive pediatric patients with neuroblastic tumor. Semi-quantitative tumor-to-liver count-rate ratio (TLCRR),MRI tumor size and margins, urine catecholamine and NSE blood levels of neuron specific enolase (NSE) were recorded. Accuracy of single and combined variables for prediction of UH was tested by ROC analysis with Bonferroni correction. Results 34 of 47 patients had UH based on the International Neuroblastoma Pathology Classification (INPC). TLCRR and serum NSE both predicted UH with moderate accuracy. Optimal cut-off for TLCRR was 2.0, resulting in 68% sensitivity and 100% specificity (AUC-ROC 0.86, p < 0.001). Optimal cut-off for NSE was 25.8 ng/ml, resulting in 74% sensitivity and 85% specificity (AUC-ROC 0.81, p = 0.001). Combination of TLCRR/NSE criteria reduced false negative findings from 11/9 to only five, with improved sensitivity and specificity of 85% (AUC-ROC 0.85, p < 0.001). Conclusion Strong I-123-MIBG uptake and high serum level of NSE were each predictive of UH. Combined analysis of both parameters improved the prediction of UH in patients with neuroblastic tumor. MRI parameters and urine catecholamine levels did not predict UH

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Combined Scintigraphy and Tumor Marker Analysis Predicts Unfavorable Histopathology of Neuroblastic Tumors with High Accuracy.

Our aim was to improve the prediction of unfavorable histopathology (UH) in neuroblastic tumors through combined imaging and biochemical parameters.123I-MIBG SPECT and MRI was performed before surgical resection or biopsy in 47 consecutive pediatric patients with neuroblastic tumor. Semi-quantitative tumor-to-liver count-rate ratio (TLCRR), MRI tumor size and margins, urine catecholamine and NSE blood levels of neuron specific enolase (NSE) were recorded. Accuracy of single and combined variables for prediction of UH was tested by ROC analysis with Bonferroni correction.34 of 47 patients had UH based on the International Neuroblastoma Pathology Classification (INPC). TLCRR and serum NSE both predicted UH with moderate accuracy. Optimal cut-off for TLCRR was 2.0, resulting in 68% sensitivity and 100% specificity (AUC-ROC 0.86, p < 0.001). Optimal cut-off for NSE was 25.8 ng/ml, resulting in 74% sensitivity and 85% specificity (AUC-ROC 0.81, p = 0.001). Combination of TLCRR/NSE criteria reduced false negative findings from 11/9 to only five, with improved sensitivity and specificity of 85% (AUC-ROC 0.85, p < 0.001).Strong 123I-MIBG uptake and high serum level of NSE were each predictive of UH. Combined analysis of both parameters improved the prediction of UH in patients with neuroblastic tumor. MRI parameters and urine catecholamine levels did not predict UH

Results of the ROC analysis.

<p>**AUC-ROC > 0,80.</p><p>*p < 0.005 in accordance with Bonferroni correction.</p><p>ROC = receiver-operating-characteristic, AUC = area under the curve, CI = confidence interval, MRI = magnetic resonance imaging, TLCRR = tumor-to-liver count-rate ratio, MN = metanephrine, VMA = vanillylmandelic acid, A = adrenaline, NA = noradrenaline, HVA = homovanillic acid, DP = dopamine, NSE = neuron-specific enolase.</p><p>Accuracy of several imaging parameters and tumor markers for prediction of unfavorable histopathology was tested by ROC analysis using Bonferroni correction for multiple comparisons. Corresponding AUC-ROC, p value and 95% CI are given.</p

Patient characteristics. INSS = International Neuroblastoma Staging System.

<p>Patient characteristics. INSS = International Neuroblastoma Staging System.</p

Urine catecholamine metabolite levels and serum NSE in patients with favorable histopathology (FH) and unfavorable histopathology (UH) according to the International Neuroblastoma Pathology Classification (INPC).

<p>Concentrations are given as mean ± standard deviation (SD). Difference was tested by unpaired Mann-Whitney test including Bonferroni correction for multiple comparisons (p < 0.005*). MN = metanephrine, VMA = vanillylmandelic acid, A = adrenaline, NA = noradrenaline, HVA = homovanillic acid, DP = dopamine, NSE = neuron-specific enolase.</p

Performance of TLCRR, NSE and combined analysis for prediction of unfavorable histopathology.

<p>Sensitivity (SE), specificity (SP), positive predictive value (PPV), negative predictive value (NPV), and accuracy (AC) are each given in percent using optimal cut-off as determined by ROC analysis. Relative risk (RR) was calculated. TLCRR = tumor-to-liver count-rate ratio, NSE = neuron-specific enolase, ROC = receiver-operating-characteristic.</p

ROC of TLCRR and serum NSE for prediction of unfavorable histopathology.

<p>Receiver-operating-characteristic (ROC) is given for TLCRR (dashed line) and serum NSE (continuous line). AUC-ROC was 0.86 for TLCRR. Optimal cut-off determined by the Youden index was 2.0 (*), resulting in a sensitivity of 68% and a specificity of 100%. AUC-ROC was 0.81 for serum NSE. Optimal cut-off was 25.8 ng/ml (**) with a sensitivity of 74% and a specificity of 85%. AUC-ROC = area under the receiver-operating-characteristic, TLCRR = tumor-to-liver count-rate ratio, NSE = neuron-specific enolase.</p

Genetic loci associated with heart rate variability and their effects on cardiac disease risk

Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.74<r g <-0.55) and blood pressure (-0.35<r g <-0.20). These findings provide clinically relevant biological insight into heritable variation in vagal heart rhythm regulation, with a key role for genetic variants (GNG11, RGS6) that influence G-protein heterotrimer action in GIRK-channel induced pacemaker membrane hyperpolarization

Genetic loci associated with heart rate variability and their effects on cardiac disease risk (vol 8, pg 15805, 2017)

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