Must the random man be unrelated? A lingering misconception in forensic genetics

A nearly universal practice among forensic DNA scientists includes mentioning an unrelated person as the possible alternative source of a DNA stain, when one in fact refers to an unknown person. Hence, experts typically express their conclusions with statements like: “The probability of the DNA evidence is X times higher if the suspect is the source of the trace than if another person unrelated to the suspect is the source of the trace.” Published forensic guidelines encourage such allusions to the unrelated person. However, as the authors show here, rational reasoning and population genetic principles do not require the conditioning of the evidential value on the unrelatedness between the unknown individual and the person of interest (e.g., a suspect). Surprisingly, this important semantic issue has been overlooked for decades, despite its potential to mislead the interpretation of DNA evidence by criminal justice system stakeholders. © 201

Cross-population validation of statistical distance as a measure of physiological dysregulation during aging

Abstract: Measuring physiological dysregulation during aging could be a key tool both to understand underlying aging mechanisms and to predict clinical outcomes in patients. However, most existing indices are either circular or hard to interpret biologically. Recently, we showed that statistical distance of 14 common blood biomarkers (a measure of how strange an individual’s biomarker profile is) was associated with age and mortality in the WHAS II data set, validating its use as a measure of physiological dysregulation. Here, we extend the analyses to other data sets (WHAS I and InCHIANTI) to assess the stability of the measure across populations. We found that the statistical criteria used to determine the original 14 biomarkers produced diverging results across populations; in other words, had we started with a different data set, we would have chosen a different set of markers. Nonetheless, the same 14 markers (or the subset of 12 available for InCHIANTI) produced highly similar predictions of age and mortality. We include analyses of all combinatorial subsets of the markers and show that results do not depend much on biomarker choice or data set, but that more markers produces a stronger signal. We conclude that statistical distance as a measure of physiological dysregulation is stable across populations in Europe and North America

The effective family size of immigrant founders predicts their long-term demographic outcome : From Québec settlers to their 20th-century descendants

Population history reconstruction, using extant genetic diversity data, routinely relies on simple demographic models to project the past through ascending genealogical-tree branches. Because genealogy and genetics are intimately related, we traced descending genealogies of the Québec founders to pursue their fate and to assess their contribution to the present-day population. Focusing on the female and male founder lines, we observed important sex-biased immigration in the early colony years and documented a remarkable impact of these early immigrants on the genetic make-up of 20th-century Québec. We estimated the immigrants’ survival ratio as a proportion of lineages found in the 1931–60 Québec to their number introduced within the immigration period. We assessed the effective family size, EFS, of all immigrant parents and their Québec-born descendants. The survival ratio of the earliest immigrants was the highest and declined over centuries in association with the immigrants’ EFS. Parents with high EFS left plentiful married descendants, putting EFS as the most important variable determining the parental demographic success throughout time for generations ahead. EFS of immigrant founders appears to predict their long-term demographic and, consequently, their genetic outcome. Genealogically inferred immigrants’ "autosomal" genetic contribution to 1931–60 Québec from consecutive immigration periods follow the same yearly pattern as the corresponding maternal and paternal lines. Québec genealogical data offer much broader information on the ancestral diversity distribution than genetic scrutiny of a limited population sample. Genealogically inferred population history could assist studies of evolutionary factors shaping population structure and provide tools to target specific health interventions

A novel measurement approach and evidence for multi-system physiological dysregulation during aging

Abstract: Previous studies have identified many biomarkers that are associated with aging and related outcomes, but the relevance of these markers for underlying processes and their relationship to hypothesized systemic dysregulation is not clear. We address this gap by presenting a novel method for measuring dysregulation via the joint distribution of multiple biomarkers and assessing associations of dysregulation with age and mortality. Using longitudinal data from the Women’s Health and Aging Study, we selected a 14-marker subset from 63 blood measures: those that diverged from the baseline population mean with age. For the 14 markers and all combinatorial sub-subsets we calculated a multivariate distance called the Mahalanobis distance (MHBD)2 for all observations, indicating how “strange” each individual’s biomarker profile was relative to the baseline population mean. In most models, MHBD correlated positively with age, MHBD increased within individuals over time, and higher MHBD predicted higher risk of subsequent mortality. Predictive power increased as more variables were incorporated into the calculation of MHBD. Biomarkers from multiple systems were implicated. These results support hypotheses of simultaneous dysregulation in multiple systems and confirm the need for longitudinal, multivariate approaches to understanding biomarkers in aging

Homeostatic dysregulation proceeds in parallel in multiple physiological systems

An increasing number of aging researchers believes that multi-system physiological dysregulation may be a key biological mechanism of aging, but evidence of this has been sparse. Here, we used biomarker data on nearly 33,000 individuals from four large datasets to test for the presence of multi-system dysregulation. We grouped 37 biomarkers into six a priori groupings representing physiological systems (lipids, immune, oxygen transport, liver function, vitamins, and electrolytes), then calculated dysregulation scores for each system in each individual using statistical distance. Correlations among dysregulation levels across systems were generally weak but significant. Comparison of these results to dysregulation in arbitrary ‘systems’ generated by random grouping of biomarkers showed that a priori knowledge effectively distinguished the true systems in which dysregulation proceeds most independently. In other words, correlations among dysregulation levels were higher using arbitrary systems, indicating that only a priori systems identified distinct dysregulation processes. Additionally, dysregulation of most systems increased with age and significantly predicted multiple health outcomes including mortality, frailty, diabetes, heart disease, and number of chronic diseases. The six systems differed in how well their dysregulation scores predicted health outcomes and age. These findings present the first unequivocal demonstration of integrated multi-system physiological dysregulation during aging, demonstrating that physiological dysregulation proceeds neither as a single global process nor as a completely independent process in different systems, but rather as a set of system-specific processes likely linked through weak feedback effects. These processes – probably many more than the six measured here – are implicated in aging

Inflamm‐aging does not simply reflect increases in pro‐inflammatory markers

Abstract: Many biodemographic studies use biomarkers of inflammation to understand or predict chronic disease and aging. Inflamm-aging, i.e. chronic low-grade inflammation during aging, is commonly characterized by pro-inflammatory biomarkers. However, most studies use just one marker at a time, sometimes leading to conflicting results due to complex interactions among the markers. A multidimensional approach allows a more robust interpretation of the various relationships between the markers. We applied principal component analysis (PCA) to 19 inflammatory biomarkers from the InCHIANTI study. We identified a clear, stable structure among the markers, with the first axis explaining inflammatory activation (both pro- and anti-inflammatory markers loaded strongly and positively) and the second axis innate immune response. The first but not the second axis was strongly correlated with age (r = 0.56, p < 0.0001, r = 0.08 p = 0.053), and both were strongly predictive of mortality (hazard ratios per PCA unit (95% CI): 1.33 (1.16–1.53) and 0.87 (0.76–0.98) respectively) and multiple chronic diseases, but in opposite directions. Both axes were more predictive than any individual markers for baseline chronic diseases and mortality. These results show that PCA can uncover a novel biological structure in the relationships among inflammatory markers, and that key axes of this structure play important roles in chronic disease

Statistical distance as a measure of physiological dysregulation is largely robust to variation in its biomarker composition

Physiological dysregulation may underlie aging and many chronic diseases, but is chal-lenging to quantify because of the complexity of the underlying systems. Recently, we de-scribed a measure of physiological dysregulation, DM, that uses statistical distance to assess the degree to which an individual’s biomarker profile is normal versus aberrant. However, the sensitivity of DM to details of the calculation method has not yet been sys-tematically assessed. In particular, the number and choice of biomarkers and the defini-tion of the reference population (RP, the population used to define a “normal” profile) may be important. Here, we address this question by validating the method on 44 common clinical biomarkers from three longitudinal cohort studies and one cross-sectional survey. DMs calculated on different biomarker subsets show that while the signal of physiological dysregulation increases with the number of biomarkers included, the value of additional markers diminishes as more are added and inclusion of 10-15 is generally sufficient. As long as enough markers are included, individual markers have little effect on the final met-ric, and even DMs calculated from mutually exclusive groups of markers correlate with each other at r~0.4-0.5. We also used data subsets to generate thousands of combina-tions of study populations and RPs to address sensitivity to differences in age range, sex, race, data set, sample size, and their interactions. Results were largely consistent (but not identical) regardless of the choice of RP; however, the signal was generally clearer with a younger and healthier RP, and RPs too different from the study population per-formed poorly. Accordingly, biomarker and RP choice are not particularly important in most cases, but caution should be used across very different populations or for fine-scale analyses. Biologically, the lack of sensitivity to marker choice and better performance of younger, healthier RPs confirm an interpretation of DM physiological dysregulation and as an emergent property of a complex system

Detection of a novel, integrative aging process suggests complex physiological integration

Abstract: Many studies of aging examine biomarkers one at a time, but complex systems theory and network theory suggest that interpretations of individual markers may be context-dependent. Here, we attempted to detect underlying processes governing the levels ofmany biomarkers simultaneously by applying principal components analysis to 43 common clinical biomarkers measured longitudinally in 3694 humans from three longitudinal cohort studies on two continents (Women’s Health and Aging I & II, InCHIANTI, and the Baltimore Longitudinal Study on Aging). The first axis was associated with anemia, inflammation, and low levels of calcium and albumin. The axis structure was precisely reproduced in all three populations and in all demographic sub-populations (by sex, race, etc.); we call the process represented by the axis “integrated albunemia.” Integrated albunemia increases and accelerates with age in all populations, and predicts mortality and frailty – but not chronic disease – even after controlling for age. This suggests a role in the aging process, though causality is not yet clear. Integrated albunemia behaves more stably across populations than its component biomarkers, and thus appears to represent a higher-order physiological process emerging from the structure of underlying regulatory networks. If this is correct, detection of this process has substantial implications for physiological organizationmore generally

Dispersion et génétique chez un oiseau marin longévif : l'albatros hurleur : dynamique de population, structure et diversité génétiques, consanguinité

L’impact écologique et évolutif de la dispersion et de la consanguinité peut être exacerbé chez les espèces insulaires. Les albatros, en particulier, ont un mode de vie exceptionnel qui soulève plusieurs questions à cet égard. Dans cette thèse j’aborde certaines de ces questions. En introduction (chapitre 1), j’énonce des hypothèses spécifiques à l’espèce d’étude, l’Albatros hurleur (Diomedea exulans), en lien avec la dispersion, la dynamique des populations, et la génétique. Cependant, la découverte fortuite d’une diversité génétique très pauvre chez cette espèce a nécessité une redéfinition majeure des objectifs et hypothèses initiaux de la thèse. Donc, les patrons de diversité génétique chez deux espèces « sœurs », les Albatros hurleurs et d’Amsterdam (D. amsterdamensis), sont d’abord étudiés au chapitre 2. Des simulations supportent l’hypothèse voulant que ces deux espèces aient hérité leur faible diversité de leur ancêtre commun qui vivait il y a quelque 0,8 million d’années. Par conséquent, les albatros semblent défier l’opinion répandue voulant qu’une faible diversité génétique réduit nécessairement la viabilité d’une espèce. L’objectif du chapitre 3 était d’identifier explicitement le modèle de dynamique populationnelle correspondant le mieux à la réalité des Albatros hurleurs. Les populations de l’ensemble de l’aire de répartition s’avèrent très peu différenciées au plan génétique. Tous les génotypes forment un seul groupe homogène selon une analyse de groupement, suggérant que les colonies actuelles pourraient descendre d’une même population ancestrale qui avait une faible diversité génétique. À l’opposé, les données de relecture de bagues indiquent qu’environ un oiseau par cohorte a émigré de son île natale au cours des dernières décennies. De ce fait, les données génétiques ne reflètent pas les faibles taux de dispersion contemporains, vraisemblablement parce que les populations n’ont pas atteint l’équilibre migration–dérive. Un modèle de dynamique de métapopulation impliquant la colonisation récente de plusieurs îles semble compatible avec les bas niveaux de diversité et de structure génétiques, bien que d’autres facteurs ont sans doute contribué au façonnement du patron génétique. La diversité et la structure génétiques limitées soulèvent des questions à propos de la consanguinité et de ses effets. Dans le chapitre 4, les données probantes relatives à la consanguinité chez l’Albatros hurleur sont passées en revue. L’hypothèse que le succès reproducteur décroît avec l’accroissement de la similarité génétique des partenaires a aussi été testée en utilisant des données moléculaires et sur l’histoire reproductive des couples. Bien que l’analyse ne supporte pas cette hypothèse, on ne peut exclure la possibilité que ce résultat découle du manque de résolution des marqueurs étant donné la très faible diversité génétique des albatros. Quelques perspectives sur des aspects reliés à la consanguinité (p. ex. son évitement, la purge génétique), basées sur la littérature récente, sont également proposées. En somme, l’étude du cas « albatros » mène à plusieurs hypothèses stimulantes et démontre la complexité de mettre au jour la dynamique de la consanguinité chez les espèces longévives. Dans le chapitre 5, à défaut de pouvoir faire des analyses d’assignation populationnelle (en raison du manque de résolution génétique), le jeu de données sur les albatros, ainsi qu’un second jeu sur le Saumon Atlantique (Salmo salar), ont servi à explorer le comportement d’une méthode d’assignation appliquée de façon routinière en biologie. Les résultats démontrent que des aspects importants (estimation du taux d’erreur, détection de migrants) sont liés à la conformité des données empiriques aux prémisses des tests. Ils soulignent aussi l’importance de valider la procédure d’assignation à l’aide de simulations préliminaires. Cette contribution méthologique se veut en quelque sorte une réponse au manque d’uniformité dans l’application de ces méthodes. Pour conclure, je passe en revue l’ensemble des connaissances sur la dispersion des Albatros hurleurs et je propose une perspective sur les causes de la dispersion et de son évolution chez ces oiseaux. Cette thèse apporte un éclairage nouveau sur la signification et l’impact du monomorphisme génétique dans les populations naturelles, sur la dispersion et la dynamique populationnelle chez une espèce longévive, et propose une vision sur l’interaction entre ces facteurs et l’histoire de vie.The ecological and evolutionary impact of dispersal and inbreeding may be exacerbated in insular species. Albatrosses, in particular, have an extreme way of life raising several questions in that regard. In this thesis, I address some of these questions. In the introduction (chapter 1), I enounce hypotheses that are specific to the study species, the wandering albatross (Diomedea exulans), in relation to dispersal, population dynamics, and genetics. However, the fortuitous discovery of a very poor genetic diversity in this species led to substantial modifications of the initial objectives and hypotheses of the thesis. Thus, the patterns of genetic diversity in two sister species, the wandering and Amsterdam (D. amsterdamensis) albatrosses, are studied in chapter 2. Simulations support the hypothesis that the two species inherited a poor genetic diversity from their common ancestor, some 0.8 million years ago. Albatrosses thus appear to challenge the widespread view about the negative consequences of genetic depletion on species survival. In chapter 3, the objective was to identify explicitly which model of population dynamics best applies to the wandering albatross. Populations exhibited little genetic differentiation across the species’ range. All genotypes grouped together in a cluster analysis, suggesting that current colonies have derived from one ancestral source that had a low genetic diversity. In contrast, band re-sighting data indicated that about one bird per cohort has dispersed among islands in the past decades. Therefore, low contemporary dispersal rates are not mirrored by genetic data, presumably because populations are not at migration–drift equilibrium. A metapopulation dynamics model involving the recent colonization of several islands seems consistent with the very low levels of both genetic diversity and structure within the wandering albatross. Yet, other factors likely contributed to shape current genetic patterns. The limited genetic diversity and structure raise questions about inbreeding and its effect. Thus, in chapter 4, evidence for inbreeding in the wandering albatross is reviewed. The hypothesis that reproductive success decreases with increasing genetic similarity between mates was also tested using molecular data and pair breeding histories. While the hypothesis was not supported, a lack of resolution from the markers cannot be ruled out given the very poor genetic diversity in albatrosses. Some perspectives about inbreeding-related aspects (e.g. inbreeding avoidance, purging) based on recent literature are also proposed. Overall, this wandering albatross case study leads to several stimulating hypotheses and shows how complex the understanding of inbreeding dynamics in a long-lived species may be. In chapter 5, failing to successfully apply population assignment methods (because of the lack of genetic resolution), data on Atlantic salmon (Salmo salar) were used in addition to the albatross dataset to explore the performance of an assignment method routinely used in biological investigations. Results show that critical aspects (error rate estimation, migrant detection) relate to how test assumptions are met by empirical data. They also stress the need to validate the assignment procedure with preliminary simulations. This methodological contribution is to some extent a response to the absence of uniformity in the way these methods are generally applied. To conclude, using empirical evidence on dispersal in wandering albatrosses, I suggest perspectives on the causes and the evolution of dispersal in these birds. This dissertation provides new insights about the significance and implications of genetic monomorphim in natural populations, about dispersal and population dynamics in a longlived seabird, and proposes a vision about the interaction between these factors and life history

Estimating dispersal, recruitment and survival in a biennially breeding species, the Wandering Albatross

International audienceThe study of dispersal or recruitment in long-lived birds using capture-recapture methods is challenging because temporary emigration is often a source of heterogeneity in detection probabilities. To deal with this problem, we introduced unobservable states in the multistate, spatial recruitment model of Lebreton et al. (Oikos 101:253-264, 2003) to study dispersal, recruitment and survival in the Wandering Albatross (Diomedea exulans), a species with a biennial reproduction (individuals skip breeding following a successful reproduction). We highlight some of the limitations and challenges encountered in using this approach. Our dataset came from a 36-year capture-recapture study conducted at three colonies of the Crozet archipelago. The model had five reproductive stages: pre-breeders, successful breeders, failed breeders, and birds in the year after a successful or a failed breeding attempt, which are unobservable. In adults, movements between colonies (i.e. breeding dispersal) were nested within reproductive stages. Several models with different constraints on survival equally fitted the data but had some rank deficiencies (i.e. non-identifiable parameters). Survival estimates were most biologically realistic (from 0.91 to 0.95) when survival was set equal between observable/unobservable states but free to vary between successful/failed breeders and among colonies. Age-specific recruitment probabilities peaked at 9-10 years and appeared well estimated despite limitations in setting the age of constant recruitment probability. Modelling natal dispersal and recruitment required a simplification of the structure of the model due to computer limitations. When applying the complete and reduced versions of the model to the same dataset, we found that survival was well estimated in both cases. Some transition probability estimates were also similar, but transitions from unobservable to observable states were poorly estimated in the simplified version. We conclude that the simplified version of the model should be limited to the estimation of natal dispersal and that the model with a full structure should be used to estimate breeding dispersal