Evaluation of DNA variants associated with androgenetic alopecia and their potential to predict male pattern baldness

Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics

Development of a mRNA profiling multiplex for the inference of organ tissues

Forensic characterisation of organ tissue generally occurs through histological and immunological assays of limited sensitivity. Here, we explore an alternative approach and examine a total of 41 candidate mRNA markers for their ability to differentiate between brain, lung, liver, skeletal muscle, heart, kidney and skin. Various selection rounds are applied involving 85 organ tissues (36 excised autopsy specimens and 49 frozen tissue sections, with at least ten specimens for each organ type), 20 commercially available RNAs from different human tissues and at least two specimens of blood, saliva, semen, vaginal mucosa, menstrual secretion or touch samples. Finally, 14 markers are regarded tissue-specific and included in an endpoint RT-PCR multiplex together with one general muscle, one blood and one housekeeping marker. This 17-plex is successfully used to analyse a blind test set of 20 specimens including mixtures, and samples derived from stabbing of organ tissues. With the blind test set samples, it is shown that an earlier described interpretation strategy for RNA cell typing results [1] is also effective for tissue inference. As organ-typing is embedded in a procedure of combined DNA/RNA extraction and analysis, both donor and organ type information is derived from the same sample. Some autopsy specimens presented DNA profiles characteristic for degraded DNA. Nevertheless, the organ-typing multiplex could generate full RNA profiles, which is probably due to small sizes of the amplicons. This assay provides a novel tool for analysis of samples from violent crime

mRNA profiling of mock casework samples: Results of a FoRNAP collaborative exercise

In recent years, forensic mRNA profiling has increasingly been used to identify the origin of human body fluids. By now, several laboratories have implemented mRNA profiling and also use it in criminal casework. In 2018 the FoRNAP (Forensic RNA Profiling) group was established among a number of these laboratories with the aim of sharing experiences, discussing optimization potential, identifying challenges and suggesting solutions with regards to mRNA profiling and casework. To compare mRNA profiling methods and results a collaborative exercise was organized within the FoRNAP group. Seven laboratories from four countries received 16 stains, comprising six pure body fluid / tissue stains and ten mock casework samples. The laboratories were asked to analyze the provided stains with their in-house method (PCR/CE or MPS) and markers of choice. Five laboratories used a DNA/RNA co-extraction strategy. Overall, up to 11 mRNA markers per body fluid were analyzed. We found that mRNA profiling using different extraction and analysis methods as well as different multiplexes can be applied to casework-like samples. In general, high input samples were typed with high accuracy by all laboratories, regardless of the method used. Irrespective of the analysis strategy, samples of low input or mixed stains were more challenging to analyze and interpret since, alike to DNA profiling, a higher number of markers dropped out and/or additional unexpected markers not consistent with the cell type in question were detected. It could be shown that a plethora of different but valid analysis and interpretation strategies exist and are successfully applied in the Forensic Genetics community. Nevertheless, efforts aiming at optimizing and harmonizing interpretation approaches in order to achieve a higher consistency between laboratories might be desirable in the future. The simultaneous extraction of DNA alongside RNA showed to be an effective approach to identify not only the body fluid present but also to identify the donor(s) of the stain. This allows investigators to gain valuable information about the origin of crime scene samples and the course of events in a crime case

Evaluation of the predictive capacity of DNA variants associated with straight hair in Europeans

DNA-based prediction of hair morphology, defined as straight, curly or wavy hair, could contribute to an improved description of an unknown offender and allow more accurate forensic reconstructions of physical appearance in the field of forensic DNA phenotyping. Differences in scalp hair morphology are significant at the worldwide scale and within Europe. The only genome-wide association study made to date revealed the Trichohyalin gene (TCHH) to be significantly associated with hair morphology in Europeans and reported weaker associations for WNT10A and FRAS1 genes. We conducted a study that centered on six SNPs located in these three genes with a sample of 528 individuals from Poland. The predictive capacity of the candidate DNA variants was evaluated using logistic regression; classification and regression trees; and neural networks, by applying a 10-fold cross validation procedure. Additionally, an independent test set of 142 males from six European populations was used to verify performance of the developed prediction models. Our study confirmed association of rs11803731 (TCHH), rs7349332 (WNT10A) and rs1268789 (FRAS1) SNPs with hair morphology. The combined genotype risk score for straight hair had an odds ratio of 2.7 and these predictors explained similar to 8.2% of the total variance. The selected three SNPs were found to predict straight hair with a high sensitivity but low specificity when a 10-fold cross validation procedure was applied and the best results were obtained using the neural networks approach (AUC = 0.688, sensitivity = 91.2%, specificity = 23.0%). Application of the neural networks model with 65% probability threshold on an additional test set gave high sensitivity (81.4%) and improved specificity (50.0%) with a total of 78.7% correct calls, but a high non-classification rate (66.9%). The combined TTGGGG SNP genotype for rs11803731, rs7349332, rs1268789 (European frequency = 4.5%) of all six straight hair-associated alleles was identified as the best predictor, giving >80% probability of straight hair. Finally, association testing of 44 SNPs previously identified to be associated with male pattern baldness revealed a suggestive association with hair morphology for rs4679955 on 3q25.1. The study results reported provide the starting point for the development of a predictive test for hair morphology in Europeans. More studies are now needed to discover additional determinants of hair morphology to improve the predictive accuracy of this trait in forensic analysis. (C) 2015 Elsevier Ireland Ltd. All rights reserved

Een uitbraak met Campylobacter fetus na het eten van rauwmelkse schapenkaas : Hoe traceer je de bron van een uitbraak

Campylobacter fetus is a species of gram-negative bacteria whose primary reservoir is the gastrointestinal tracts of cattle and sheep. Human infections are rare, though often invasive and sometimes fatal. In this paper, we studied an outbreak of six patients with a C. fetus infection and outlined their disease histories. In each case we were able to identify factors that led to a reduced resistance, including pre-existing illnesses and old age. Because of the unusually high number of patients that presented in a time period of only five months, the Community Health Services were commissioned to identify the source of infection. Using whole genome sequencing, we showed that 5 out of 6 patients belonged to the same cluster. This One Health approach resulted in the conclusion that the infection originated from unpasteurized sheep's milk processed into unripened cheese. Finally, various measures were put into place to prevent any further outbreaks

Evaluation of DNA Variants Associated with Androgenetic Alopecia and Their Potential to Predict Male Pattern Baldness

<div><p>Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near <i>AR</i>, rs1998076 in the 20p11 region, rs929626 in <i>EBF1</i>, rs12565727 in <i>TARDBP</i> and rs756853 in <i>HDAC9</i>. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics.</p></div

A DGGE system for comprehensive mutation screening of BRCA1 and BRCA2: Application in a Dutch cancer clinic setting

Rapid and reliable identification of deleterious changes in the breast cancer genes BRCA1 and BRCA2 has become one of the major issues in most DNA services laboratories. To rapidly detect all possible changes within the coding and splice site determining sequences of the breast cancer genes, we established a semiautomated denaturing gradient gel electrophoresis (DGGE) mutation scanning system. All exons of both genes are covered by the DGGE scan, comprising 120 amplicons. We use a semiautomated approach, amplifying all individual amplicons with the same PCR program, after which the amplicons are pooled. DGGE is performed using three slightly different gel conditions. Validation was performed using DNA samples with known sequence variants in 107 of the 120 amplicons; all variants were detected. This DGGE mutation scanning, in combination with a PCR test for two Dutch founder deletions in BRCA1 was then applied in 431 families in which 52 deleterious changes and 70 unclassified variants were found. Fifteen unclassified variants were not reported before. The system was easily adopted by five other laboratories, where in another 3,593 families both exons 11 were analyzed by the protein truncation test (PTT) and the remaining exons by DGGE. In total, a deleterious change (nonsense, frameshift, splice-site mutation, or large deletion) was found in 661 families (16.4%), 462 in BRCA1 (11.5%), 197 in BRCA2 (4.9%), and in two index cases a deleterious change in both BRCA1 and BRCA2 was identified. Eleven deleterious changes in BRCA1 and 36 in BRCA2 had not been reported before. In conclusion, this DGGE mutation screening method for BRCA1 and BRCA2 is proven to be highly sensitive and is easy to adopt, which makes screening of large numbers of patients feasible. The results of screening of BRCA1 and BRCA2 in more than 4,000 families present a valuable overview of mutations in the Dutch population

Parameters describing the accuracy of prediction of MPB using 20-SNP logistic regression prediction model.

<p>^*Four samples from phenotype categories 3 and 4 lacked data in one of the following SNPs: rs1160312, rs6625150, rs4679955 and therefore were excluded from the analyses.</p><p>Parameters describing the accuracy of prediction of MPB using 20-SNP logistic regression prediction model.</p

Genotype risk score associated with the risk of male pattern baldness.

<p>Genotype risk score associated with the risk of male pattern baldness.</p