The influence of relatives on the efficiency and error rate of familial searching

Decreased accuracy of forensic DNA mixture analysis for groups with lower genetic diversity

Forensic investigation of DNA samples from multiple contributors has become commonplace. These complex analyses use statistical frameworks accounting for multiple levels of uncertainty in allelic contributions from different individuals, particularly for samples containing few molecules of DNA. These methods have been thoroughly tested along some axes of variation, but less attention has been paid to accuracy across human genetic variation. Here, we quantify the accuracy of DNA mixture analysis over 244 human groups. We find higher false inclusion rates for mixtures with more contributors, and for groups with lower genetic diversity. Even for two-contributor mixtures where one contributor is known and the reference group is correctly specified, false inclusion rates are 1e-5 or higher for 56 out of 244 groups. This means that, depending on multiple testing, some false inclusions may be expected. These false positives could be lessened with more selective and conservative use of DNA mixture analysis.

Human-Genetic Ancestry Inference and False Positives in Forensic Familial Searching

In forensic familial search methods, a query DNA profile is tested against a database to determine if the query profile represents a close relative of a database entrant. One challenge for familial search is that the calculations may require specification of allele frequencies for the unknown population from which the query profile has originated. The choice of allele frequencies affects the rate at which non-relatives are erroneously classified as relatives, and allele-frequency misspecification can substantially inflate false positive rates compared to use of allele frequencies drawn from the same population as the query profile. Here, we use ancestry inference on the query profile to circumvent the high false positive rates that result from highly misspecified allele frequencies. In particular, we perform ancestry inference on the query profile and make use of allele frequencies based on its inferred genetic ancestry. In a test for sibling matches on profiles that represent unrelated individuals, we demonstrate that false positive rates for familial search with use of ancestry inference to specify the allele frequencies are similar to those seen when allele frequencies align with the population of origin of a profile. Because ancestry inference is possible to perform on query profiles, the extreme allele-frequency misspecifications that produce the highest false positive rates can be avoided. We discuss the implications of the results in the context of concerns about the forensic use of familial searching.

Artificially intelligent scoring and classification engine for forensic identification

Despite advances in genotyping technologies, traditional kinship analysis tools utilized in forensic identification have seen limited evolution and lack measures of accuracy. Here, we leverage artificial intelligence (AI) and extend the Elston-Stewart algorithm to deliver a method that provides an unprecedented level of flexibility to matching individuals with pedigrees by likelihood ratio. We designed an AI that utilizes a prediction cascade based on gradient descent logistic regression which allows for iterative solution of multi missing person scenarios. Furthermore, the AI can quantify the confidence underlying likelihood ratios across the spectrum of pedigrees, regardless of the amount of genetic information available and the number of missing persons. The algorithm accommodates an arbitrary number of generations and ancestral relationships, including multiple marriages, mutations, and consanguinity. We demonstrate that a properly trained AI significantly and reproducibly outperforms a human interpreter. We discuss published limitations of existing tools and demonstrate that they are not amenable to the size and complexity of this study. This novel method significantly improves the trade-off between sensitivity and specificity beyond the limits of traditional kinship analysis tools and introduces opportunities beyond the field of forensic genetics.

The effect of FBI CODIS Core STR Loci expansion on familial DNA database searching

1000 profiles chosen randomly from an in-house database of 6000 profiles were searched against the database for matches with at least one shared allele per locus. The database contains profiles that have been analyzed with Identifiler Plus (15 markers) for biological relationship and DNA identification purposes and both true and false matches are expected to be obtained. 100 pairs of at least one true paternity match and one false match were selected and were initially supplemented with 5 additional STRs representing the new Core CODIS set. Study of the LR value showed that when false matches were treated as paternity matches, the expansion of the marker set severely diminished the LR values obtained compared to true matches and the false positive ratio of familial database searching. When false matches were treated as full-sibling matches, the expansion to 20 STRs also diminished the number of false matches and the corresponding LR values compared to true full-sibling cases, but the effect was less dramatic. Addition of the SE33 marker, further promoted distinction between true and false matches both in paternity and full-sibling cases. Counting the number of shared alleles presented improved distinction efficiency between true and false matches after STR expansion to20 and 21 STRs but remains a less valuable method of familial DNA database searching compared to LR.

Statistical Detection of Relatives Typed with Disjoint Forensic and Biomedical Loci

In familial searching in forensic genetics, a query DNA profile is tested against a database to determine whether it represents a relative of a database entrant. We examine the potential for using linkage disequilibrium to identify pairs of profiles as belonging to relatives when the query and database rely on nonoverlapping genetic markers. Considering data on individuals genotyped with both microsatellites used in forensic applications and genome-wide SNPs, we find that ∼30%-32% of parent-offspring pairs and ∼35%-36% of sib pairs can be identified from the SNPs of one member of the pair and the microsatellites of the other. The method suggests the possibility of performing familial searches of microsatellite databases using query SNP profiles, or vice versa. It also reveals that privacy concerns arising from computations across multiple databases that share no genetic markers in common entail risks, not only for database entrants, but for their close relatives as well.

A TALE OF TWO MOLECULAR CALIFORNIAS

Molecular identification technologies are often framed in terms of their societal benefits. Forensic uses of DNA databases benefit society through the efficient identification of criminal suspects, while consumer DNA services empower individuals by identifying ethnic, health-related, and potentially sexual, molecular genealogies. Two examples of these technologies are California's criminological database CAL-DNA and the revitalized project to find a 'gay gene'. Both examples show how molecular identification technologies are also entangled with histories of coercion and stigmatization. The search for a 'gay gene' is premised on the historical stigmatization of homosexuality as deviant as well as contemporary concerns with resisting the idea that it is a lifestyle choice. The CAL-DNA database demonstrates that stigmatization still underpins contemporary identification technologies. This 'race-neutral' database puts racial minorities at increased risk of getting caught up in the criminal system precisely because of a racist history of identifying men of color as potential criminals. While the increasing criminological and consumer applications of molecular identification technologies are spearheaded in California, their uses emerge in a futurist culture that decontextualizes them from historic and contemporary coercion. The molecular identities these technologies create tell a tale of two Californias; one of empowerment and another of surveillance and stigma.

Genetic Diversity and Societally Important Disparities

The magnitude of genetic diversity within human populations varies in a way that reflects the sequence of migrations by which people spread throughout the world. Beyond its use in human evolutionary genetics, worldwide variation in genetic diversity sometimes can interact with social processes to produce differences among populations in their relationship to modern societal problems. We review the consequences of genetic diversity differences in the settings of familial identification in forensic genetic testing, match probabilities in bone marrow transplantation, and representation in genome-wide association studies of disease. In each of these three cases, the contribution of genetic diversity to social differences follows from population-genetic principles. For a fourth setting that is not similarly grounded, we reanalyze with expanded genetic data a report that genetic diversity differences influence global patterns of human economic development, finding no support for the claim. The four examples describe a limit to the importance of genetic diversity for explaining societal differences while illustrating a distinction that certain biologically based scenarios do require consideration of genetic diversity for solving problems to which populations have been differentially predisposed by the unique history of human migrations.