Torben Tvedebrink

Estimating the probability of allelic drop-out of STR alleles in forensic genetics

In crime cases with available DNA evidence, the amount of DNA is often sparse due to the setting of the crime. In such cases, allelic drop-out of one or more true alleles in STR typing is possible. We present a statistical model for estimating the per locus and overall probability of allelic drop-out using the results of all STR loci in the case sample as reference. The methodology of logistic regression is appropriate for this analysis, and we demonstrate how to incorporate this in a forensic genetic framework.

Analysis of global variability in 15 established and 5 new European Standard Set (ESS) STRs using the CEPH human genome diversity panel

The CEPH human genome diversity cell line panel (CEPH-HGDP) of 51 globally distributed populations was used to analyze patterns of variability in 20 core human identification STRs. The markers typed comprised the 15 STRs of Identifiler, one of the most widely used forensic STR multiplexes, plus five recently introduced European Standard Set (ESS) STRs: D1S1656, D2S441, D10S1248, D12S391 and D22S1045. From the genotypes obtained for the ESS STRs we identified rare, intermediate or off-ladder alleles that had not been previously reported for these loci. Examples of novel ESS STR alleles found were characterized by sequence analysis. This revealed extensive repeat structure variation in three ESS STRs, with D12S391 showing particularly high variability for tandem runs of AGAT and AGAC repeat units. The global geographic distribution of the CEPH panel samples gave an opportunity to study in detail the extent of substructure shown by the 20 STRs amongst populations and between their parent population groups. An assessment was made of the forensic informativeness of the new ESS STRs compared to the loci they will replace: CSF1PO, D5S818, D7S820, D13S317 and TPOX, with results showing a clear enhancement of discrimination power using multiplexes that genotype the new ESS loci. We also measured the ability of Identifiler and ESS STRs to infer the ancestry of the CEPH-HGDP samples and demonstrate that forensic STRs in large multiplexes have the potential to differentiate the major population groups but only with sufficient reliability when used with other ancestry-informative markers such as single nucleotide polymorphisms. Finally we checked for possible association by linkage between the two ESS multiplex STRs closely positioned on chromosome-12: vWA and D12S391 by examining paired genotypes from the complete CEPH data set.

Statistical model for degraded DNA samples and adjusted probabilities for allelic drop-out

DNA samples found at a scene of crime or obtained from the debris of a mass disaster accident are often subject to degradation. When using the STR DNA technology, the DNA profile is observed via a so-called electropherogram (EPG), where the alleles are identified as signal peaks above a certain level or above a signal to noise threshold. Degradation implies that these peak intensities decrease in strength for longer short tandem repeat (STR) sequences. Consequently, long STR loci may fail to produce peak heights above the limit of detection resulting in allelic or locus drop-outs. In this paper, we present a method for measuring the degree of degradation of a sample and demonstrate how to incorporate this in estimating the probability of allelic drop-out. This is done by extending an existing method derived for non-degraded samples. The performance of the methodology is evaluated using data from degraded DNA, where cases with varying amounts of DNA and levels of degradation are investigated.

Allelic drop-out probabilities estimated by logistic regression—Further considerations and practical implementation

We discuss the model for estimating drop-out probabilities presented by Tvedebrink et al. [7] and the concerns, that have been raised. The criticism of the model has demonstrated that the model is not perfect. However, the model is very useful for advanced forensic genetic work, where allelic drop-out is occurring. With this discussion, we hope to improve the drop-out model, so that it can be used for practical forensic genetics and stimulate further discussions. We discuss how to estimate drop-out probabilities when using a varying number of PCR cycles and other experimental conditions.

Performance of two 17 locus forensic identification STR kits-Applied Biosystems's AmpFℓSTR® NGMSElect™ and Promega's PowerPlex® ESI17 kits.

We compared the performance of two recently released 17 loci STR multiplexes for human identification: Applied Biosystemss AmpFℓSTR(®) NGMSElect™ and Promegas PowerPlex(®) ESI17. The comparative parameters were chosen by their relevance in forensic identification and particularly in crime cases. The comparative analyses encompass: amplification ability, heterozygote balance, allelic drop-out, drop-in, stutter analysis and inter-locus balance. Four DNA profiles were analysed in various concentrations in a serial dilution experiment. The amounts of DNA in the PCR ranged from 3 pg to 420 pg and were analysed in triplicate using 28, 29 and 30 PCR cycles. In order to compare the kits, aliquots from each sample were analysed with both kits under identical conditions. Furthermore, DNA profiles from 200 reference profiles were analysed using both kits. The results from the statistical analyses did not indicate any substantial differences of practical relevance between the kits for forensic case work. For all parameters included in this comparative study, the two kits showed no departure from previously observed patterns relative to e.g. the amounts of DNA or amplicon lengths. Based on our analyses, both kits are considered applicable for forensic crime case work.

Overdispersion in allelic counts and θ-correction in forensic genetics

We present a statistical model for incorporating the extra variability in allelic counts due to subpopulation structures. In forensic genetics, this effect is modelled by the identical-by-descent parameter θ, which measures the relationship between pairs of alleles within a population relative to the relationship of alleles between populations (Weir, 2007). In our statistical approach, we demonstrate that θ may be defined as an overdispersion parameter capturing the subpopulation effects. This formulation allows derivation of maximum likelihood estimates of the allele probabilities and θ together with computation of the profile log-likelihood, confidence intervals and hypothesis testing. In order to compare our method with existing methods, we reanalysed FBI data from Budowle and Moretti (1999) with allele counts in six US subpopulations. Furthermore, we investigate properties of our methodology from simulation studies.

Association between use of asthma drugs and prevalence of demarcated opacities in permanent first molars in 6-to-8-year-old Danish children

OBJECTIVES Demarcated opacities in permanent first molars are common developmental tooth defects, characterized by areas with insufficient mineralization of the enamel. The defects present clinically as a continuum from creamy-white demarcated opacities, yellowish-brown demarcated opacities to macroscopic loss of tooth substance. The etiology is sparsely elucidated, but asthma drugs have been suspected to increase the prevalence. The aim of this study was to examine the prevalence of demarcated opacities in permanent first molars among 6-to-8-year-old children with prescriptions and without prescriptions for asthma drugs. METHODS In a cross-sectional study in two Danish municipalities, all children aged 6-8 years (n = 891) were included. A total of 745 (83.6%) went through a dental examination during which demarcated opacities and tooth substance loss due to these were recorded. The analyses were restricted to 647 children in whom all four permanent first molars had erupted. Data on use of asthma drugs from birth until the time of the dental examination were obtained from a population-based pharmaco-epidemiological prescription database. RESULTS Among 47 children with prescriptions for both inhaled beta(2)-agonists and inhaled corticosteroids before the age of 3 years, 15 (31.9%) had demarcated opacities of any type, and six children (12.8%) had opacity-related loss of tooth substance. Among 264 children with no prescriptions for either inhaled or oral asthma drugs from birth until the date of the dental examination, 96 (36.4%) had demarcated opacities of any type, and 13 (4.9%) had opacity-related loss of tooth substance. The odds ratio (OR) of any demarcated opacity, and of opacity-related loss of tooth substance in children with prescriptions for both inhaled beta(2)-agonists and inhaled corticosteroids before the age of 3 years was 0.82 (95% CI: 0.39-1.65), and 2.42 (95% CI: 0.70-7.43). CONCLUSIONS Children with prescriptions for inhaled asthma drugs before the age of 3 years did not have an overall increased risk of demarcated opacities in first permanent molar but they seemed to have an increased risk of the severe demarcated opacities, i.e. opacities resulting in macroscopic loss of tooth substance, and possibly a need for restorative care.

Identifying contributors of DNA mixtures by means of quantitative information of STR typing

Estimating the weight of evidence in forensic genetics is often done in terms of a likelihood ratio, LR. The LR evaluates the probability of the observed evidence under competing hypotheses. Most often, probabilities used in the LR only consider the evidence from the genomic variation identified using polymorphic genetic markers. However, modern typing techniques supply additional quantitative data, which contain very important information about the observed evidence. This is particularly true for cases of DNA mixtures, where more than one individual has contributed to the observed biological stain. This article presents a method for including the quantitative information of short tandem repeat (STR) DNA mixtures in the LR. Also, an efficient algorithmic method for finding the best matching combination of DNA mixture profiles is derived and implemented in an on-line tool for two- and three-person DNA mixtures. Finally, we demonstrate for two-person mixtures how this best matching pair of profiles can be used in estimating the likelihood ratio using importance sampling. The reason for using importance sampling for estimating the likelihood ratio is the often vast number of combinations of profiles needed for the evaluation of the weight of evidence. Online tool is available at http://people.math.aau.dk/~tvede/dna/.

Utilising allelic dropout probabilities estimated by logistic regression in casework

Some advanced methods for DNA profile interpretation require a probability for the event of dropout. Methods have been suggested based on logistic regression. Two of these respectively use a proxy for template that is constant across loci and one that is modelled using an exponential curve. Both of these methods allow different modelling constants from each locus. A variant of the model using an exponential curve is discussed. This variant constrains the constants to be the same for every locus. We test these two methods and the variant by developing the constants (training) on one set of data and testing them on another. This mimics the likely use in casework. We find that the new variant appears to be the most useful in that it performs better than the other two options when trained on one data set and used on another. The hypothesised reason for this is that locus to locus variation in amplification efficiency varies with time, multimix batch, or from sample to sample.

On the exact distribution of the numbers of alleles in DNA mixtures

When more than one individual contributes biological material to a forensic stain, the resulting DNA type is termed a DNA mixture. DNA mixtures occur frequently in forensic genetic casework, and in recent years, much research has been devoted to this subject. This paper presents a derivation of the exact distribution of the number of alleles for any number of profiles and investigated loci. The per locus number of observed alleles is of interest as it indicates the plausible range on the number of contributors. Hence, by specifying a prior distribution on the number of contributors, the locus distribution may be used to assess the number of contributors. Furthermore, the total number of alleles across all loci is used by some forensic geneticists to estimate the probability that an allele has failed to be detected (allelic drop-out).