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Commentary on: Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research. The diagnostic pitfalls of surveys: If you score positive on a test of addiction, you still have a good chance not to be addicted.

ABSTRACT: Survey-based studies often fail to take into account the predictive value of a test, in other words, the probability of a person having (or not having) the disease when scoring positive (or negative) on the given screening test.We re-visited the theory and basic calculations of diagnostic accuracy.In general, the lower the prevalence the worse the predictive value is. When the disorder is relatively rare, a positive test finding is typically not useful in confirming its presence given the high proportion of false positive cases. For example, using the Compulsive Buying Scale (Faber & O'Guinn, 1992) three in four people classified as having compulsive buying disorder will in fact not have the disorder.Screening tests are limited to serve as an early detection "gate" and only clinical (interview-based) studies are suitable to claim that a certain behaviour is truly "pathological".

SUBMITTER: Maraz A

PROVIDER: S-EPMC4627675 | biostudies-other | 2015 Sep

REPOSITORIES: biostudies-other

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Project description:BackgroundOver the past few years, the use of molecular techniques to detect cultivation-independent, eukaryotic diversity has proven to be a powerful approach. Based on small-subunit ribosomal RNA (SSU rRNA) gene analyses, these studies have revealed the existence of an unexpected variety of new phylotypes. Some of them represent novel diversity in known eukaryotic groups, mainly stramenopiles and alveolates. Others do not seem to be related to any molecularly described lineage, and have been proposed to represent novel eukaryotic kingdoms. In order to review the evolutionary importance of this novel high-level eukaryotic diversity critically, and to test the potential technical and analytical pitfalls and limitations of eukaryotic environmental DNA surveys (EES), we analysed 484 environmental SSU rRNA gene sequences, including 81 new sequences from sediments of the small river, the Seymaz (Geneva, Switzerland).ResultsBased on a detailed screening of an exhaustive alignment of eukaryotic SSU rRNA gene sequences and the phylogenetic re-analysis of previously published environmental sequences using Bayesian methods, our results suggest that the number of novel higher-level taxa revealed by previously published EES was overestimated. Three main sources of errors are responsible for this situation: (1) the presence of undetected chimeric sequences; (2) the misplacement of several fast-evolving sequences; and (3) the incomplete sampling of described, but yet unsequenced eukaryotes. Additionally, EES give a biased view of the diversity present in a given biotope because of the difficult amplification of SSU rRNA genes in some taxonomic groups.ConclusionsEnvironmental DNA surveys undoubtedly contribute to reveal many novel eukaryotic lineages, but there is no clear evidence for a spectacular increase of the diversity at the kingdom level. After re-analysis of previously published data, we found only five candidate lineages of possible novel high-level eukaryotic taxa, two of which comprise several phylotypes that were found independently in different studies. To ascertain their taxonomic status, however, the organisms themselves have now to be identified.

Project description:High throughput sequencing technologies are revolutionizing genetic research. With this "rise of the machines", genomic sequences can be obtained even for unknown genomes within a short time and for reasonable costs. This has enabled evolutionary biologists studying genetically unexplored species to identify molecular markers or genomic regions of interest (e.g. micro- and minisatellites, mitochondrial and nuclear genes) by sequencing only a fraction of the genome. However, when using such datasets from non-model species, it is possible that DNA from non-target contaminant species such as bacteria, viruses, fungi, or other eukaryotic organisms may complicate the interpretation of the results. In this study we analysed 14 genomic pyrosequencing libraries of aquatic non-model taxa from four major evolutionary lineages. We quantified the amount of suitable micro- and minisatellites, mitochondrial genomes, known nuclear genes and transposable elements and searched for contamination from various sources using bioinformatic approaches. Our results show that in all sequence libraries with estimated coverage of about 0.02-25%, many appropriate micro- and minisatellites, mitochondrial gene sequences and nuclear genes from different KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways could be identified and characterized. These can serve as markers for phylogenetic and population genetic analyses. A central finding of our study is that several genomic libraries suffered from different biases owing to non-target DNA or mobile elements. In particular, viruses, bacteria or eukaryote endosymbionts contributed significantly (up to 10%) to some of the libraries analysed. If not identified as such, genetic markers developed from high-throughput sequencing data for non-model organisms may bias evolutionary studies or fail completely in experimental tests. In conclusion, our study demonstrates the enormous potential of low-coverage genome survey sequences and suggests bioinformatic analysis workflows. The results also advise a more sophisticated filtering for problematic sequences and non-target genome sequences prior to developing markers.

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Commentary on: Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research. The diagnostic pitfalls of surveys: If you score positive on a test of addiction, you still have a good chance not to be addicted.

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