Association study between polymorphisms in DNA methylation-related genes and testicular germ cell tumor risk.

BACKGROUND: Testicular germ cell tumors (TGCTs), histologically classified as seminomas and non-seminomas, are believed to arise from primordial gonocytes, with the maturation process blocked when are subjected to DNA methylation reprogramming. Single-nucleotide polymorphisms (SNPs) in DNA methylation machinery and folate-dependent one-carbon metabolism genes have been postulated to influence the proper establishment of DNA methylation. METHODS: In this pathway-focused investigation we evaluated the association between 273 selected tag SNPs from 28 DNA methylation-related genes and TGCT risk. We carried out association analysis at individual SNP and gene-based level using summary statistics from the Genome Wide Association Study meta-analysis recently conducted by the international Testicular Cancer Consortium on 10,156 TGCT cases and 179,683 controls. RESULTS: In individual SNP analyses, seven SNPs, four mapping within MTHFR, were associated with TGCT risk after correction for multiple testing (q-value ≤.05). Queries of public databases showed that three of these SNPs were associated with MTHFR changes in enzymatic activity (rs1801133) or expression level in testis tissue (rs12121543, rs1476413). Gene-based analyses revealed MTHFR (q-value=8.4x10-4), MECP2 (q-value=2x10-3) and ZBTB4 (q-value=0.03) as the top TGCT-associated genes. Stratifying by tumor histology, four MTHFR SNPs were associated with seminoma. In gene-based analysis MTHFR was associated with risk of seminoma (q-value=2.8x10-4), but not with non-seminomatous tumors (q-value=0.22). CONCLUSIONS: Genetic variants within MTHFR, potentially having an impact on the DNA methylation pattern, are associated with TGCT risk. IMPACT: This finding suggests that TGCT pathogenesis could be associated to the folate cycle status, and this relation could be partly due to hereditary factors

Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function tests

The interpretation of pulmonary function tests (PFTs) to diagnose respiratory diseases is built on expert opinion that relies on the recognition of patterns and the clinical context for detection of specific diseases. In this study, we aimed to explore the accuracy and interrater variability of pulmonologists when interpreting PFTs compared with artificial intelligence (AI)-based software that was developed and validated in more than 1500 historical patient cases.120 pulmonologists from 16 European hospitals evaluated 50 cases with PFT and clinical information, resulting in 6000 independent interpretations. The AI software examined the same data. American Thoracic Society/European Respiratory Society guidelines were used as the gold standard for PFT pattern interpretation. The gold standard for diagnosis was derived from clinical history, PFT and all additional tests.The pattern recognition of PFTs by pulmonologists (senior 73%, junior 27%) matched the guidelines in 74.4±5.9% of the cases (range 56-88%). The interrater variability of κ=0.67 pointed to a common agreement. Pulmonologists made correct diagnoses in 44.6±8.7% of the cases (range 24-62%) with a large interrater variability (κ=0.35). The AI-based software perfectly matched the PFT pattern interpretations (100%) and assigned a correct diagnosis in 82% of all cases (p<0.0001 for both measures).The interpretation of PFTs by pulmonologists leads to marked variations and errors. AI-based software provides more accurate interpretations and may serve as a powerful decision support tool to improve clinical practice.status: publishe

Molecular imaging of depressive disorders

This chapter summarizes findings of a large number of molecular imaging studies in the field of unipolar and bipolar depression (BD). Brain metabolism in depressed unipolar and bipolar patients is generally hypoactive in the middle frontal gyri, the pregenual and posterior anterior cingulate, the superior temporal gyrus, the insula, and the cerebellum, while hyperactivity exists in subcortical (caudate nucleus, thalamus), limbic (amygdala, anterior hippocampus), and medial and inferior frontal regions. Interestingly, after depletion of serotonin or noradrenalin/dopamine in vulnerable (recovered) major depressive disorder (MDD) patients, a similar response pattern in metabolism occurs. Findings on the pre-and postsynaptic dopaminergic system show indications that, at least in subgroups of retarded MDD patients, presynaptic dopaminergic markers may be decreased, while postsynaptic markers may be increased. The findings regarding serotonin synthesis, pre-and postsynaptic imaging can be integrated to a presumable loss of serotonin in MDD, while this remains unclear in BD. This reduction of serotonin and dopamine in MDD was recently summarized in a revised version of the monoamine hypothesis, which focuses more on a dysfunction at the level of the MAO enzyme. This should be addressed further in future studies. Nevertheless, it should be acknowledged that the serotonergic and dopaminergic systems appear adaptive; therefore, it remains difficult to distinguish state and trait abnormalities. Therefore, future longitudinal molecular imaging studies in the same subjects at different clinical mood states (preferably with different tracers and imaging modalities) are needed to clarify whether the observed changes in transporters and receptors are compensatory reactions or reflect different, potentially causal mechanisms. Several suggestions for future developments are also provided at the end of this chapter