Among major vertebrate groups, ray-finned fishes (Actinopterygii) collectively display a nearly unrivaled diversity of parental care activities. This fact, coupled with a growing body of phylogenetic data for Actinopterygii, makes these fishes a logical model system for analyzing the evolutionary histories of alternative parental care modes and associated reproductive behaviors. From an extensive literature review, we constructed a supertree for ray-finned fishes and used its phylogenetic topology to investigate the evolution of several key reproductive states including type of parental care (maternal, paternal, or biparental), internal versus external fertilization, internal versus external gestation, nest construction behavior, and presence versus absence of sexual dichromatism (as an indicator of sexual selection). Using a comparative phylogenetic approach, we critically evaluate several hypotheses regarding evolutionary pathways toward parental care. Results from maximum parsimony reconstructions indicate that all forms of parental care, including paternal, biparental, and maternal (both external and internal to the female reproductive tract) have arisen repeatedly and independently during ray-finned fish evolution. The most common evolutionary transitions were from external fertilization directly to paternal care and from external fertilization to maternal care via the intermediate step of internal fertilization. We also used maximum likelihood phylogenetic methods to test for statistical correlations and contingencies in the evolution of pairs of reproductive traits. Sexual dichromatism and nest construction proved to be positively correlated with the evolution of male parental care in species with external fertilization. Sexual dichromatism was also positively correlated with female-internal fertilization and gestation. No clear indication emerged that female-only care or biparental care were evolutionary outgrowths of male-only care, or that biparental care has been a common evolutionary stepping stone between paternal and maternal care. Results are discussed in the context of prior thought about the evolution of alternative parental care modes in vertebrates.

We compiled information from the literature on the taxonomic distributions in extant teleost fishes of alternative sex-determination systems: male-heterogametic (XY) gonochorism, female-heterogametic (ZW) gonochorism, hermaphroditism, unisexuality, and environmental dependency. Then, using recently published molecular phylogenies based on whole-genomic or partial mitochondrial DNA sequences, we inferred the histories and evolutionary transitions between these reproductive modes by employing maximum parsimony and maximum likelihood methods of phylogenetic character mapping. Across a broad teleost phylogeny involving 25 taxonomic orders, a highly patchy distribution of different sex-determination mechanisms was uncovered, implying numerous transitions between alternative modes, but this heterogeneity also precluded definitive statements about ancestral states for most clades. Closer inspection of family-level and genus-level phylogenies within each of four orders further bolstered the conclusion that shifts in sex-determining modes are evolutionarily frequent and involve a variety of distinct ancestral-descendant pathways. For possible reasons discussed herein, the evolutionary lability of sex-determining modes in fishes contrasts strikingly with the evolutionary conservatism of sex determination within both mammals and birds. © 2006 The Linnean Society of London.

Around the world, human populations have experienced large increases in average lifespan over the last 150 years, and while individuals are living longer, they are spending more years of life with multiple chronic morbidities. Researchers have used numerous laboratory animal models to understand the biological and environmental factors that influence aging, morbidity, and longevity. However, the most commonly studied animal species, laboratory mice and rats, do not experience environmental conditions similar to those to which humans are exposed, nor do we often diagnose them with many of the naturally occurring pathologies seen in humans. Recently, the companion dog has been proposed as a powerful model to better understand the genetic and environmental determinants of morbidity and mortality in humans. However, it is not known to what extent the age-related dynamics of morbidity, comorbidity, and mortality are shared between humans and dogs. Here, we present the first large-scale comparison of human and canine patterns of age-specific morbidity and mortality. We find that many chronic conditions that commonly occur in human populations (obesity, arthritis, hypothyroidism, and diabetes), and which are associated with comorbidities, are also associated with similarly high levels of comorbidity in companion dogs. We also find significant similarities in the effect of age on disease risk in humans and dogs, with neoplastic, congenital, and metabolic causes of death showing similar age trajectories between the two species. Overall, our study suggests that the companion dog may be an ideal translational model to study the many complex facets of human morbidity and mortality.

Cognitive deficits are a major biomedical challenge-and engagement of the brain in stimulating tasks improves cognition in aged individuals (Wilson et al., 2002; Gates et al., 2011) and rodents (Aidil-Carvalho et al., 2017), through unknown mechanisms. Whether cognitive stimulation alters specific metabolic pathways in the brain is unknown. Understanding which metabolic processes are involved in cognitive stimulation is important because it could lead to pharmacologic intervention that promotes biological effects of a beneficial behavior, toward the goal of effective medical treatments for cognitive deficits. Here we show using male mice that cognitive stimulation induced metabolic remodeling of the mouse hippocampus, and that pharmacologic treatment with the longevity hormone α-klotho (KL), mediated by its KL1 domain, partially mimicked this alteration. The shared, metabolic signature shared between cognitive stimulation and treatment with KL or KL1 closely correlated with individual mouse cognitive performance, indicating a link between metabolite levels and learning and memory. Importantly, the treatment of mice with KL1, an endogenous circulating factor that more closely mimicked cognitive stimulation than KL, acutely increased synaptic plasticity, a substrate of cognition. KL1 also improved cognition, itself, in young mice and countered deficits in old mice. Our data show that treatments or interventions mimicking the hippocampal metabolome of cognitive stimulation can enhance brain functions. Further, we identify the specific domain by which klotho promotes brain functions, through KL1, a metabolic mimic of cognitive stimulation.SIGNIFICANCE STATEMENT Cognitive deficits are a major biomedical challenge without truly effective pharmacologic treatments. Engaging the brain through cognitive tasks benefits cognition. Mimicking the effects of such beneficial behaviors through pharmacological treatment represents a highly valuable medical approach to treating cognitive deficits. We demonstrate that brain engagement through cognitive stimulation induces metabolic remodeling of the hippocampus that was acutely recapitulated by the longevity factor klotho, mediated by its KL1 domain. Treatment with KL1, a close mimic of cognitive stimulation, enhanced cognition and countered cognitive aging. Our findings shed light on how cognition metabolically alters the brain and provide a plausible therapeutic intervention for mimicking these alterations that, in turn, improves cognition in the young and aging brain.

In recent years, metabolomics has been used as a powerful tool to better understand the physiology of neurodegenerative diseases and identify potential biomarkers for progression. We used targeted and untargeted aqueous, and lipidomic profiles of the metabolome from human cerebrospinal fluid to build multivariate predictive models distinguishing patients with Alzheimer's disease (AD), Parkinson's disease (PD), and healthy age-matched controls. We emphasize several statistical challenges associated with metabolomic studies where the number of measured metabolites far exceeds sample size. We found strong separation in the metabolome between PD and controls, as well as between PD and AD, with weaker separation between AD and controls. Consistent with existing literature, we found alanine, kynurenine, tryptophan, and serine to be associated with PD classification against controls, while alanine, creatine, and long chain ceramides were associated with AD classification against controls. We conducted a univariate pathway analysis of untargeted and targeted metabolite profiles and find that vitamin E and urea cycle metabolism pathways are associated with PD, while the aspartate/asparagine and c21-steroid hormone biosynthesis pathways are associated with AD. We also found that the amount of metabolite missingness varied by phenotype, highlighting the importance of examining missing data in future metabolomic studies.

Quantifying the physiology of aging is essential for improving our understanding of age-related disease and the heterogeneity of healthy aging. Recent studies have shown that, in regression models using "-omic" platforms to predict chronological age, residual variation in predicted age is correlated with health outcomes, and suggest that these "omic clocks" provide measures of biological age. This paper presents predictive models for age using metabolomic profiles of cerebrospinal fluid (CSF) from healthy human subjects and finds that metabolite and lipid data are generally able to predict chronological age within 10 years. We use these models to predict the age of a cohort of subjects with Alzheimer's and Parkinson's disease and find an increase in prediction error, potentially indicating that the relationship between the metabolome and chronological age differs with these diseases. However, evidence is not found to support the hypothesis that our models will consistently overpredict the age of these subjects. In our analysis of control subjects, we find the carnitine shuttle, sucrose, biopterin, vitamin E metabolism, tryptophan, and tyrosine to be the most associated with age. We showcase the potential usefulness of age prediction models in a small data set (n = 85) and discuss techniques for drift correction, missing data imputation, and regularized regression, which can be used to help mitigate the statistical challenges that commonly arise in this setting. To our knowledge, this work presents the first multivariate predictive metabolomic and lipidomic models for age using mass spectrometry analysis of CSF.