Short hypervariable microhaplotypes: A novel set of very short high discriminating power loci without stutter artefacts

Molecular Technology and Informatics for Personalised Medicine and Healt

FDSTools: A software package for analysis of massively parallel sequencing data with the ability to recognise and correct STR stutter and other PCR or sequencing noise

Molecular Technology and Informatics for Personalised Medicine and Healt

Comprehensive diagnostics of acute myeloid leukemia by whole transcriptome RNA sequencing

Acute myeloid leukemia (AML) is caused by genetic aberrations that also govern the prognosis of patients and guide risk-adapted and targeted therapy. Genetic aberrations in AML are structurally diverse and currently detected by different diagnostic assays. This study sought to establish whole transcriptome RNA sequencing as single, comprehensive, and flexible platform for AML diagnostics. We developed HAMLET (Human AML Expedited Transcriptomics) as bioinformatics pipeline for simultaneous detection of fusion genes, small variants, tandem duplications, and gene expression with all information assembled in an annotated, user-friendly output file. Whole transcriptome RNA sequencing was performed on 100 AML cases and HAMLET results were validated by reference assays and targeted resequencing. The data showed that HAMLET accurately detected all fusion genes and overexpression of EVI1 irrespective of 3q26 aberrations. In addition, small variants in 13 genes that are often mutated in AML were called with 99.2% sensitivity and 100% specificity, and tandem duplications in FLT3 and KMT2A were detected by a novel algorithm based on soft-clipped reads with 100% sensitivity and 97.1% specificity. In conclusion, HAMLET has the potential to provide accurate comprehensive diagnostic information relevant for AML classification, risk assessment and targeted therapy on a single technology platform

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder

This paper is dedicated to the memory of Psychiatric Genomics Consortium (PGC) founding member and Bipolar disorder working group co-chair Pamela Sklar. We thank the participants who donated their time, experiences and DNA to this research, and to the clinical and scientific teams that worked with them. We are deeply indebted to the investigators who comprise the PGC. The views expressed are those of the authors and not necessarily those of any funding or regulatory body. Analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org ) hosted by SURFsara, and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu).Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P<1x10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (GWS, p < 5x10-8) in the discovery GWAS were not GWS in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis 30 loci were GWS including 20 novel loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene-sets including regulation of insulin secretion and endocannabinoid signaling. BDI is strongly genetically correlated with schizophrenia, driven by psychosis, whereas BDII is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential new biological mechanisms for BD.This work was funded in part by the Brain and Behavior Research Foundation, Stanley Medical Research Institute, University of Michigan, Pritzker Neuropsychiatric Disorders Research Fund L.L.C., Marriot Foundation and the Mayo Clinic Center for Individualized Medicine, the NIMH Intramural Research Program; Canadian Institutes of Health Research; the UK Maudsley NHS Foundation Trust, NIHR, NRS, MRC, Wellcome Trust; European Research Council; German Ministry for Education and Research, German Research Foundation IZKF of Münster, Deutsche Forschungsgemeinschaft, ImmunoSensation, the Dr. Lisa-Oehler Foundation, University of Bonn; the Swiss National Science Foundation; French Foundation FondaMental and ANR; Spanish Ministerio de Economía, CIBERSAM, Industria y Competitividad, European Regional Development Fund (ERDF), Generalitat de Catalunya, EU Horizon 2020 Research and Innovation Programme; BBMRI-NL; South-East Norway Regional Health Authority and Mrs. Throne-Holst; Swedish Research Council, Stockholm County Council, Söderström Foundation; Lundbeck Foundation, Aarhus University; Australia NHMRC, NSW Ministry of Health, Janette M O'Neil and Betty C Lynch

Effect of natural and chimeric haemagglutinin genes on influenza A virus replication in baby hamster kidney cells.

Baby hamster kidney (BHK21) cells are used to produce vaccines against various viral veterinary diseases, including rabies and foot-and-mouth-disease. Although particular influenza virus strains replicate efficiently in BHK21 cells the general use of these cells for influenza vaccine production is prohibited by the poor replication of most strains, including model strain A/PR/8/34 [H1N1] (PR8). We now show that in contrast to PR8, the related strain A/WSN/33 [H1N1] (WSN) replicates efficiently in BHK21 cells. This difference is determined by the haemagglutinin (HA) protein since reciprocal reassortant viruses with swapped HAs behave similarly with respect to growth on BHK21 cells as the parental virus from which their HA gene is derived. The ability or inability of six other influenza virus strains to grow on BHK21 cells appears to be similarly dependent on the nature of the HA gene since reassortant PR8 viruses containing the HA of these strains grow to similar titres as the parental virus from which the HA gene was derived. However, the growth to low titres of a seventh influenza strain was not due to the nature of the HA gene since a reassortant PR8 virus containing this HA grew efficiently on BHK21 cells. Taken together, these results suggest that the HA gene often primarily determines influenza replication efficiency on BHK21 cells but that in some strains other genes are also involved. High virus titres could be obtained with reassortant PR8 strains that contained a chimeric HA consisting of the HA1 domain of PR8 and the HA2 domain of WSN. HA1 contains most antigenic sites and is therefore important for vaccine efficacy. This method of producing the HA1 domain as fusion to a heterologous HA2 domain could possibly also be used for the production of HA1 domains of other viruses to enable the use of BHK21 cells as a generic platform for veterinary influenza vaccine production

Effect of natural and chimeric haemagglutinin genes on influenza A virus replication in baby hamster kidney cells.

Baby hamster kidney (BHK21) cells are used to produce vaccines against various viral veterinary diseases, including rabies and foot-and-mouth-disease. Although particular influenza virus strains replicate efficiently in BHK21 cells the general use of these cells for influenza vaccine production is prohibited by the poor replication of most strains, including model strain A/PR/8/34 [H1N1] (PR8). We now show that in contrast to PR8, the related strain A/WSN/33 [H1N1] (WSN) replicates efficiently in BHK21 cells. This difference is determined by the haemagglutinin (HA) protein since reciprocal reassortant viruses with swapped HAs behave similarly with respect to growth on BHK21 cells as the parental virus from which their HA gene is derived. The ability or inability of six other influenza virus strains to grow on BHK21 cells appears to be similarly dependent on the nature of the HA gene since reassortant PR8 viruses containing the HA of these strains grow to similar titres as the parental virus from which the HA gene was derived. However, the growth to low titres of a seventh influenza strain was not due to the nature of the HA gene since a reassortant PR8 virus containing this HA grew efficiently on BHK21 cells. Taken together, these results suggest that the HA gene often primarily determines influenza replication efficiency on BHK21 cells but that in some strains other genes are also involved. High virus titres could be obtained with reassortant PR8 strains that contained a chimeric HA consisting of the HA1 domain of PR8 and the HA2 domain of WSN. HA1 contains most antigenic sites and is therefore important for vaccine efficacy. This method of producing the HA1 domain as fusion to a heterologous HA2 domain could possibly also be used for the production of HA1 domains of other viruses to enable the use of BHK21 cells as a generic platform for veterinary influenza vaccine production

Taxonomic classification and abundance estimation using 16S and WGS-A comparison using controlled reference samples

The assessment of microbiome biodiversity is the most common application of metagenomics. While 16S sequencing remains standard procedure for taxonomic profiling of metagenomic data, a growing number of studies have clearly demonstrated biases associated with this method. By using Whole Genome Shotgun sequencing (WGS) metagenomics, most of the known restrictions associated with 16S data are alleviated. However, due to the computationally intensive data analyses and higher sequencing costs, WGS based metagenomics remains a less popular option. Selecting the experiment type that provides a comprehensive, yet manageable amount of information is a challenge encountered in many metagenomics studies. In this work, we created a series of artificial bacterial mixes, each with a different distribution of skin-associated microbial species. These mixes were used to estimate the resolution of two different metagenomic experiments - 16S and WGS - and to evaluate several different bioinformatics approaches for taxonomic read classification. In all test cases, WGS approaches provide much more accurate results, in terms of taxa prediction and abundance estimation, in comparison to those of 16S. Furthermore, we demonstrate that a 16S dataset, analysed using different state of the art techniques and reference databases, can produce widely different results. In light of the fact that most forensic metagenomic analysis are still performed using 16S data, our results are especially important.Molecular Epidemiolog

A comprehensive assessment protocol including patient reported outcomes, physical tests, and biological sampling in newly diagnosed patients with head and neck cancer: is it feasible?

Purpose Large cohort studies are needed taking into account cancer-related, personal, biological, psychobehavioral, and lifestyle-related factors, to guide future research to improve treatment and supportive care. We aimed to evaluate the feasibility of a comprehensive baseline assessment of a cohort study evaluating the course of quality of life (QoL). Methods newly diagnosed head and neck cancer (HNC) patients were asked to participate. Assessments consisted of questionnaires (635 items), a home visit (including a psychiatric interview, physical tests, and blood and saliva collection), and tissue collection. Representativeness of the study sample was evaluated by comparing demographics, clinical factors, depression, anxiety, and QoL between responders and nonresponders. Feasibility was evaluated covering the number of questions, time investment, intimacy, and physical burden. Results During the inclusion period (4 months), 15 out of 26 (60%) patients agreed to participate. Less women participated, 13%in responders group versus 63%in non-responders group (p=0.008). No other differences were found between responders and non-responders. Responders completed more than 95% of the questionnaires’ items and rated the number of questions, time investment and intimacy as feasible, and the physical and psychological burden as low. It took on average 3 h to complete the questionnaires and 1.5 h for the home visit. Conclusions This study reveals that a comprehensive assessment including various questionnaires, physical measurements, and biological assessments is feasible according to patients with newly diagnosed HNC. A large prospective cohort study has started aiming to include 739 HNC patients and their informal caregivers in the Netherlands