Physiological Dysregulation Proceeds and Predicts Health Outcomes Similarly in Chinese and Western Populations.

BACKGROUND: A decade ago, we proposed an index of physiological dysregulation based on Mahalanobis distance (DM) that measures how far from the norm an individual biomarker profile is. While extensive validation has been performed, focus was mostly on Western populations with little comparison to developing countries, particularly at a physiological system level. The degree to which the approach would work in other sociocultural contexts and the similarity of dysregulation signatures across diverse populations are still open questions. METHODS: Using 2 data sets from China and 3 from Western countries (United States, United Kingdom, and Italy), we calculated DM globally and per physiological system. We assessed pairwise correlations among systems, difference with age, prediction of mortality and age-related diseases, and sensitivity to interchanging data sets with one another as the reference in DM calculation. RESULTS: Overall, results were comparable across all data sets. Different physiological systems showed distinct dysregulation processes. Association with age was moderate and often nonlinear, similarly for all populations. Mahalanobis distance predicted most health outcomes, although differently by physiological system. Using a Chinese population as the reference when calculating DM for Western populations, or vice versa, led to similar associations with health outcomes, with a few exceptions. CONCLUSIONS: While small differences were noticeable, they did not systematically emerge between Chinese and Western populations, but rather diffusively across all data sets. These findings suggest that DM presents similar properties, notwithstanding sociocultural backgrounds, and that it is equally effective in capturing the loss of homeostasis that occurs during aging in diverse industrial human populations.

Individual life histories: neither slow nor fast, just diverse.

The slow-fast continuum is a commonly used framework to describe variation in life-history strategies across species. Individual life histories have also been assumed to follow a similar pattern, especially in the pace-of-life syndrome literature. However, whether a slow-fast continuum commonly explains life-history variation among individuals within a population remains unclear. Here, we formally tested for the presence of a slow-fast continuum of life histories both within populations and across species using detailed long-term individual-based demographic data for 17 bird and mammal species with markedly different life histories. We estimated adult lifespan, age at first reproduction, annual breeding frequency, and annual fecundity, and identified the main axes of life-history variation using principal component analyses. Across species, we retrieved the slow-fast continuum as the main axis of life-history variation. However, within populations, the patterns of individual life-history variation did not align with a slow-fast continuum in any species. Thus, a continuum ranking individuals from slow to fast living is unlikely to shape individual differences in life histories within populations. Rather, individual life-history variation is likely idiosyncratic across species, potentially because of processes such as stochasticity, density dependence, and individual differences in resource acquisition that affect species differently and generate non-generalizable patterns across species.

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.

Genotype-by-environment interactions modulate the rate of microevolution in reproductive timing in humans.

Evidence from natural populations shows that changes in environmental conditions can cause rapid modifications in the evolutionary potential of phenotypes, partly through genotype-by-environment interactions (G×E). Therefore, the overall rate of microevolution should depend on fluctuations in environmental conditions, even when directional selection is sustained over several generations. We tested this hypothesis in a preindustrial human population that experienced a microevolutionary change in age at first reproduction (AFR) of mothers, using the annual infant mortality rate (IMR) as an indicator of environmental conditions during their early life. Using quantitative genetics analyses, we found that G×Es explained a nonnegligible fraction of the additive genetic variance in AFR and in relative fitness, as well as of the genetic covariance between AFR and fitness (i.e., the Robertson-Price covariance). The covariance was stronger for individuals exposed to unfavorable early-life environmental conditions. Our results unravel the presence of G×Es in an important life history trait and its impact on the rate of microevolution, which appears to have been sensitive to short-term fluctuations in local environmental conditions.

Determining the impact of unknown individuals in criminality using network analysis of DNA matches.

Criminal offenders missing from police files limit the capacity to reconstruct criminal networks for criminological research and operational purposes. Recent studies show that forensic DNA databanks offer potential to address this problem, through large-scale analysis of DNA matches, many of which involve unidentified offenders. Applying social network analysis (SNA) to 18 years of DNA match data from Québec, Canada, we found that 1400 unknowns do not occupy more marginal positions in the network than 13,000 known offenders, and explain up to 18% of SNA values (e.g., betweenness centrality) for the latter while supporting 46% of their clustering values. Our results contrast with previous studies, showing moreover that unknown individuals who are positioned centrally in a network may have a larger impact than previously expected on investigation policing with implications for forensic intelligence.

The dimensions of evolutionary potential in biological conservation.

It is now well admitted by ecologists that the conservation of biodiversity should imply preserving the evolutionary processes that will permit its adaptation to ongoing and future environmental changes. This is attested by the ever-growing reference to the conservation of evolutionary potential in the scientific literature. The impression that one may have when reading papers is that conserving evolutionary potential can only be a good thing, whatever biological system is under scrutiny. However, different objectives, such as maintaining species richness versus ecosystem services, may express different, when not conflicting, underlying values attributed to biodiversity. For instance, biodiversity can be intrinsically valued, as worth it to be conserved per se, or it can be conserved as a means for human flourishing. Consequently, both the concept of evolutionary potential and the prescriptions derived from the commitment to conserve it remain problematic, due to a lack of explicit mention of the norms underlying different conservation visions. Here, we contend that those who advocate for the conservation of evolutionary potential should position their conception along four dimensions: what vehicles instantiate the evolutionary potential relevant to their normative commitment; what temporality is involved; how measurable evolutionary potential is, and what degree of human influence is tolerated. We need to address these dimensions if we are to determine why and when the maintenance of evolutionary potential is an appropriate target for the conservation of biodiversity.

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.

Historical human remains identification through maternal and paternal genetic signatures in a founder population with extensive genealogical record.

OBJECTIVES: We describe a method to identify human remains excavated from unmarked graves in historical Québec cemeteries by combining parental-lineage genetic markers with the whole-population genealogy of Québec contained in the BALSAC database. MATERIALS AND METHODS: The remains of six men were exhumed from four historical cemeteries in the province of Québec, Canada. DNA was extracted from the remains and genotyped to reveal their mitochondrial and Y-chromosome haplotypes, which were compared to a collection of haplotypes of genealogically-anchored modern volunteers. Maternal and paternal genealogies were searched in the BALSAC genealogical record for parental couples matching the mitochondrial and the Y-chromosome haplotypic signatures, to identify candidate sons from whom the remains could have originated. RESULTS: Analysis of the matching genealogies identified the parents of one man inhumed in the cemetery of the investigated parish during its operating time. The candidate individual died in 1833 at the age of 58, a plausible age at death in light of osteological analysis of the remains. DISCUSSION: This study demonstrates the promising potential of coupling genetic information from living individuals to genealogical data in BALSAC to identify historical human remains. If genetic coverage is increased, the genealogical information in BALSAC could enable the identification of 87% of the men (n = 178,435) married in Québec before 1850, with high discriminatory power in most cases since >75% of the parental couples have unique biparental signatures in most regions. Genotyping and identifying Québec's historical human remains are a key to reconstructing the genomes of the founders of Québec and reinhuming archeological remains with a marked grave.

Inferring Transmission Histories of Rare Alleles in Population-Scale Genealogies.

Learning the transmission history of alleles through a family or population plays an important role in evolutionary, demographic, and medical genetic studies. Most classical models of population genetics have attempted to do so under the assumption that the genealogy of a population is unavailable and that its idiosyncrasies can be described by a small number of parameters describing population size and mate choice dynamics. Large genetic samples have increased sensitivity to such modeling assumptions, and large-scale genealogical datasets become a useful tool to investigate realistic genealogies. However, analyses in such large datasets are often intractable using conventional methods. We present an efficient method to infer transmission paths of rare alleles through population-scale genealogies. Based on backward-time Monte Carlo simulations of genetic inheritance, we use an importance sampling scheme to dramatically speed up convergence. The approach can take advantage of available genotypes of subsets of individuals in the genealogy including haplotype structure as well as information about the mode of inheritance and general prevalence of a mutation or disease in the population. Using a high-quality genealogical dataset of more than three million married individuals in the Quebec founder population, we apply the method to reconstruct the transmission history of chronic atrial and intestinal dysrhythmia (CAID), a rare recessive disease. We identify the most likely early carriers of the mutation and geographically map the expected carrier rate in the present-day French-Canadian population of Quebec.

Into the wild-WAMBAM goes to Canada.

The sixth Wild Animal Models Bi-Annual Meeting was held in July 2017 in Québec, with 42 participants. This report documents the evolution of questions asked and approaches used in evolutionary quantitative genetic studies of wild populations in recent decades, and how these questions and approaches were represented at the recent meeting. We explore how ideas from previous meetings in this series have developed to their present states, and consider how the format of the meetings may be particularly useful at fostering the rapid development and proliferation of ideas and approaches.

Mother's curse neutralizes natural selection against a human genetic disease over three centuries.

According to evolutionary theory, mitochondria could be poisoned gifts that mothers transmit to their sons. This is because mutations harmful to males are expected to accumulate in the mitochondrial genome, the so-called 'mother's curse'. However, the contribution of the mother's curse to the mutation load in nature remains largely unknown and hard to predict, because compensatory mechanisms could impede the spread of deleterious mitochondria. Here we provide evidence for the mother's curse in action over 290 years in a human population. We studied a mutation causing Leber's hereditary optical neuropathy, a disease with male-biased prevalence and which has long been suspected to be maintained in populations by the mother's curse. Male carriers showed a low fitness relative to non-carriers and to females, mostly explained by their high rate of infant mortality. Despite poor male fitness, selection analysis predicted a slight (albeit non-significant) increase in frequency, which sharply contrasts with the 35.5% per-generation decrease predicted if mitochondrial DNA transmission had been through males instead of females. Our results are therefore even suggestive of positive selection through the female line that may exacerbate effects of the mother's curse. This study supports a contribution of the mother's curse to the reduction of male lifespan, uncovering a large fitness effect associated with a single mitochondrial variant.

Eco-evolutionary dynamics in a contemporary human population.

Recent studies of the joint dynamics of ecological and evolutionary processes show that changes in genotype or phenotype distributions can affect population, community and ecosystem processes. Such eco-evolutionary dynamics are likely to occur in modern humans and may influence population dynamics. Here, we study contributions to population growth from detailed genealogical records of a contemporary human population. We show that evolutionary changes in women's age at first reproduction can affect population growth: 15.9% of variation in individual contribution to population growth over 108 years is explained by mean age at first reproduction and at least one-third of this variation (6.1%) is attributed to the genetic basis of this trait, which showed an evolutionary response to selection during the period studied. Our study suggests that eco-evolutionary processes have modulated the growth of contemporary human populations.

Optimal Versus Realized Trajectories of Physiological Dysregulation in Aging and Their Relation to Sex-Specific Mortality Risk.

While longitudinal changes in biomarker levels and their impact on health have been characterized for individual markers, little is known about how overall marker profiles may change during aging and affect mortality risk. We implemented the recently developed measure of physiological dysregulation based on the statistical distance of biomarker profiles in the framework of the stochastic process model of aging, using data on blood pressure, heart rate, cholesterol, glucose, hematocrit, body mass index, and mortality in the Framingham original cohort. This allowed us to evaluate how physiological dysregulation is related to different aging-related characteristics such as decline in stress resistance and adaptive capacity (which typically are not observed in the data and thus can be analyzed only indirectly), and, ultimately, to estimate how such dynamic relationships increase mortality risk with age. We found that physiological dysregulation increases with age; that increased dysregulation is associated with increased mortality, and increasingly so with age; and that, in most but not all cases, there is a decreasing ability to return quickly to baseline physiological state with age. We also revealed substantial sex differences in these processes, with women becoming dysregulated more quickly but with men showing a much greater sensitivity to dysregulation in terms of mortality risk.

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.

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 challenging to quantify because of the complexity of the underlying systems. Recently, we described 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 systematically assessed. In particular, the number and choice of biomarkers and the definition 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 metric, 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 combinations 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 performed 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.

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 of many 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 organization more generally.

Trajectories of physiological dysregulation predicts mortality and health outcomes in a consistent manner across three populations.

Mechanistic and evolutionary perspectives both agree that aging involves multiple integrated biochemical networks in the organism. In particular, the homeostatic physiological dysregulation (PD) hypothesis contends that aging is caused by the progressive breakdown of key regulatory processes. However, nothing is yet known about the specifics of how PD changes with age and affects health. Using a recently validated measure of PD involving the calculation of a multivariate distance (DM) from biomarker data, we show that PD trajectories predict mortality, frailty, and chronic diseases (cancer, cardiovascular diseases, and diabetes). Specifically, relative risks of outcomes associated with individual slopes in (i.e. rate of) dysregulation range 1.20-1.40 per unit slope. We confirm the results by replicating the analysis using two suites of biomarkers selected with markedly different criteria and, for mortality, in three longitudinal cohort-based studies. Overall, the consistence of effect sizes (direction and magnitude) across data sets, biomarker suites and outcomes suggests that the positive relationship between DM and health outcomes is a general phenomenon found across human populations. Therefore, the study of dysregulation trajectories should allow important insights into aging physiology and provide clinically meaningful predictors of outcomes.

Inflamm-aging does not simply reflect increases in pro-inflammatory markers.

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.

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

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 produce a stronger signal. We conclude that statistical distance as a measure of physiological dysregulation is stable across populations in Europe and North America.