Polimorfismo a nivel genómico de los antígenos de histocompatibilidad de clase II en individuos normales y enfermos celíacos

Fil: Herrera Piñero, Mariana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

Making decisions in missing person identification cases with low statistical power

acceptedVersio

Second GHEP-ISFG exercise for DVI: “DNA-led” victims’ identification in a simulated air crash

The Spanish and Portuguese-Speaking Working Group of the International Society for Forensic Genetics (GHEP-ISFG) has organized a second collaborative exercise on a simulated case of Disaster Victim Identification (DVI), with the participation of eighteen laboratories. The exercise focused on the analysis of a simulated plane crash case of medium-size resulting in 66 victims with varying degrees of fragmentation of the bodies (with commingled remains). As an additional difficulty, this second exercise included 21 related victims belonging to 6 families among the 66 missings to be identified. A total number of 228 post-mortem samples were represented with aSTR and mtDNA profiles, with a proportion of partial aSTR profiles simulating charred remains. To perform the exercise, participants were provided with aSTR and mtDNA data of 51 reference pedigrees —some of which deficient—including 128 donors for identification purposes. The exercise consisted firstly in the comparison of the post-mortem genetic profiles in order to re-associate fragmented remains to the same individual and secondly in the identification of the re-associated remains by comparing aSTR and mtDNA profiles with reference pedigrees using pre-established thresholds to report a positive identification. Regarding the results of the post-mortem samples re-associations, only a small number of discrepancies among participants were detected, all of which were from just a few labs. However, in the identification process by kinship analysis with family references, there were more discrepancies in comparison to the correct results. The identification results of single victims yielded fewer problems than the identification of multiple related victims within the same family groups. Several reasons for the discrepant results were detected: a) the identity/non-identity hypotheses were sometimes wrongly expressed in the likelihood ratio calculations, b) some laboratories failed to use all family references to report the DNA match, c) In families with several related victims, some laboratories firstly identified some victims and then unnecessarily used their genetic information to identify the remaining victims within the family, d) some laboratories did not correctly use “prior odds” values for the Bayesian treatment of the episode for both post-mortem/post-mortem re-associations as well as the ante-mortem/post-mortem comparisons to evaluate the probability of identity. For some of the above reasons, certain laboratories failed to identify some victims. This simulated “DNA-led” identification exercise may help forensic genetic laboratories to gain experience and expertize for DVI or MPI in using genetic data and comparing their own results with the ones in this collaborative exercise.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.Peer reviewe

Polimorfismo a nivel genómico de los antígenos de histocompatibilidad de clase II en individuos normales y enfermos celíacos

Fil: Herrera Piñero, Mariana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

Prioritising family members for genotyping in missing person cases: A general approach combining the statistical power of exclusion and inclusion

Missing person identification typically involves genetic matching of a person of interest against relatives of the missing person. In cases with few available relatives, exhumations or other substantial efforts may be necessary in order to secure adequate statistical power. We propose a simulation approach for solving prioritisation problems arising in such cases. Conditioning on the already typed individuals we estimate the power of each alternative, both to detect the true person, and to exclude false candidates. Graphical summaries of the simulations are given in complementary power plots, facilitating interpretation and decision making. Through a series of examples originating from the well-known Missing grandchildren of Argentina we demonstrate that our method may untangle complex prioritisation problems and other power-related questions. In particular we offer novel insights in recent cases where only children of the potential match are available for testing. We also show that X-chromosomal markers may give high statistical power in missing person identification, but that this requires careful selection of relatives for genotyping. All simulations, power calculations and plots are done with the R package forrel

Prioritising family members for genotyping in missing person cases: A general approach combining the statistical power of exclusion and inclusion

Missing person identification typically involves genetic matching of a person of interest against relatives of the missing person. In cases with few available relatives, exhumations or other substantial efforts may be necessary in order to secure adequate statistical power. We propose a simulation approach for solving prioritisation problems arising in such cases. Conditioning on the already typed individuals we estimate the power of each alternative, both to detect the true person, and to exclude false candidates. Graphical summaries of the simulations are given in complementary power plots, facilitating interpretation and decision making. Through a series of examples originating from the well-known Missing grandchildren of Argentina we demonstrate that our method may untangle complex prioritisation problems and other power-related questions. In particular we offer novel insights in recent cases where only children of the potential match are available for testing. We also show that X-chromosomal markers may give high statistical power in missing person identification, but that this requires careful selection of relatives for genotyping. All simulations, power calculations and plots are done with the R package forrel

Making decisions in missing person identification cases with low statistical power

The present work proposes a general strategy for dealing with missing person identification cases through DNA-database search. Our main example is the identification of abducted children in the last civic-dictatorship of Argentina, known as the “Missing Grandchildren of Argentina”. Particularly we focus on those pedigrees where few, or only distant relatives of the missing person are available, resulting in low statistical power. For such complex cases we provide a statistical method for selecting a likelihood ratio (LR) threshold for each pedigree based on error rates. Furthermore, we provide an open-source user friendly software for computing LR thresholds and error rates. The strategy described in the paper could be applied to other large-scale cases of DNA-based identification hampered by low statistical power

Bayesian networks for DNA-based kinship analysis: Functionality and validation of the GENis missing person identification module

GENis is a recently published open-source multi-tier information system developed to run forensic DNA databases. It relies on a Bayesian Networks framework and it is particularly well suited to efficiently perform large-size queries against databases of missing individuals. In this contribution we present a validation of the missing person identification capabilities of GENis. To that end we introduce fbnet, a free-software package written in the R statistical language that implements the complete GENis functionality to perform kinship analysis based on DNA profiles. With the aid of fbnet, we could validate likelihood ratios against estimations draw with Familias and forrel (two well-recognized R packages for kinship quantification) for complex pedigrees provided by the Argentinian reference databank (Banco Nacional de Datos Geneticos, BNDG). We found that our methodological approach presented an excellent performance in terms of accuracy and computation times.Fil: Chernomoretz, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Marsico, Franco Leonel. Universidad Nacional de Jose Clemente Paz; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Iserte, Javier Alonso. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Herrera Piñero, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Escobar, Maria Soledad. Banco Nacional de Datos Geneticos; ArgentinaFil: Balparda, Manuel. Fundación Sadosky; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Sibilla, Gustavo. Fundación Sadosky; Argentin

Using DNA to reunify separated migrant families

Perceived lack of tools, and fears of the sensitivity of DNA data, should not be obstacle