Extra-pair paternity drives plumage colour elaboration in male passerines.

The elaborate ornamental plumage displayed by birds has largely been attributed to sexual selection, whereby the greater success of ornamented males in attaining mates drives a rapid elaboration of those ornaments. Indeed, plumage elaboration tends to be greatest in species with a high variance in reproductive success such as polygynous mating systems. Even among socially monogamous species, many males are extremely colourful. In their now-classic study, Møller and Birkhead (1994) suggested that increased variance in reproductive success afforded by extra-pair paternity should intensify sexual selection pressure and thus an elaboration of male plumage and sexual dichromatism, but the relatively few measures of extra-pair paternity at the time prevented a rigorous test of this hypothesis. In the nearly three decades since that paper's publication, hundreds of studies have been published on rates of extra-pair paternity and more objective measures of plumage colouration have been developed, allowing for a large-scale comparative test of Møller and Birkhead's (1994) hypothesis. Using an analysis of 186 socially monogamous passerine species with estimates of extra-pair paternity, our phylogenetically controlled analysis confirms Møller and Birkhead's (1994) early work, demonstrating that rates of extra-pair paternity are positively associated with male, but not female, colouration and with the extent of sexual dichromatism. Plumage evolution is complex and multifaceted, driven by phylogenetic, ecological, and social factors, but our analysis confirms a key role of extra-pair mate choice in driving the evolution of ornamental traits.

Evolution of winter molting strategies in European and North American migratory passerines.

Molt is critical for birds as it replaces damaged feathers and worn plumage, enhancing flight performance, thermoregulation, and communication. In passerines, molt generally occurs on the breeding grounds during the postbreeding period once a year. However, some species of migrant passerines that breed in the Nearctic and Western Palearctic regions have evolved different molting strategies that involve molting on the overwintering grounds. Some species forego molt on the breeding grounds and instead complete their prebasic molt on the overwintering grounds. Other species molt some or all feathers a second time (prealternate molt) during the overwintering period. Using phylogenetic analyses, we explored the potential drivers of the evolution of winter molts in Nearctic and Western Palearctic breeding passerines. Our results indicate an association between longer photoperiods and the presence of prebasic and prealternate molts on the overwintering grounds for both Nearctic and Western Palearctic species. We also found a relationship between prealternate molt and generalist and water habitats for Western Palearctic species. Finally, the complete prealternate molt in Western Palearctic passerines was linked to longer days on the overwintering grounds and longer migration distance. Longer days may favor the evolution of winter prebasic molt by increasing the time window when birds can absorb essential nutrients for molt. Alternatively, for birds undertaking a prealternate molt at the end of the overwintering period, longer days may increase exposure to feather-degrading ultra-violet radiation, necessitating the replacement of feathers. Our study underlines the importance of the overwintering grounds in the critical process of molt for many passerines that breed in the Nearctic and Western Palearctic regions.

Evolution of moult-migration is directly linked to aridity of the breeding grounds in North American passerines.

To avoid energy allocation conflicts, birds generally separate breeding, migration and moult during the annual cycle. North American passerines typically moult on the breeding grounds prior to autumn migration. However, some have evolved a moult-migration strategy in which they delay moult until stopping over during autumn migration. Rohwer et al. (2005) proposed the 'push-pull hypothesis' as an explanation for the evolution of this moult strategy, but it has not been empirically tested. Poor conditions on the breeding grounds at the end of the summer would push birds to depart prior to moult, while productive stopover locations would pull them. We tested for a relationship between moult-migration and breeding grounds aridity as measured by the normalized difference vegetation index. Our results strongly support the 'push' aspect of the push-pull hypothesis and indicate that arid breeding grounds, primarily in western North America, would drive species to evolve stopover moult-migration, although this relationship may depend upon migration distance.

Ethnic differences in maternal diet in pregnancy and infant eczema.

BACKGROUND: The global prevalence of childhood eczema has increased over the last few decades, with a marked increase in high-income countries. Differences in prevalence of childhood eczema between countries and ethnicities suggest that genetic and early modifiable environmental factors, such as dietary intake, may underlie this observation. To investigate the association between pregnancy diet and infant eczema in a consortium of prospective Canadian birth cohorts predominantly comprised of white Europeans and South Asians. METHODS: We evaluated the association of maternal dietary patterns reported during pregnancy (assessed at 24-28 weeks gestation using a semi-quantitiative food-frequency questionnaire) with parent-reported physician-diagnosed infant eczema at 1-year from 2,160 mother-infant pairs. Using three dietary patterns ("Western", "plant-based", and "Balanced") previously derived in this cohort using principal component analysis, we used multivariable logistic regression to determine the association of these dietary patterns with infant eczema, adjusted for potential confounders. RESULTS: We observed a lower odds of eczema in the full sample combining white Europeans and South Asians with greater adherence to a plant-based (OR = 0.65; 95% CI: 0.55, 0.76; <0.001) and Western dietary pattern (OR = 0.73; 95% CI: 0.60, 0.89; P<0.01), after adjusting for other known predictors of eczema, including ethnicity, which was not significant. No associations were observed for the balanced diet. An interaction between the Western diet and ethnicity was observed (P<0.001). Following stratification by ethnicity, a protective association between the plant-based diet and infant eczema was confirmed in both white Europeans (OR = 0.59; 95% CI: 0.47, 0.74; P<0.001) and South Asians (OR = 0.77; 95% CI: 0.61, 0.97; P = 0.025). In white Europeans only, a Western diet was associated with a lower odds of infant eczema (OR = 0.69; 95% CI: 0.56, 0.87; P = 0.001) while a balanced diet increased the odds of infant eczema (OR = 1.23; 95% CI: 1.02, 1.49; P = 0.03). Beyond a plant-based diet, no significant associations with other dietary patterns were observed in South Asians. CONCLUSION: A plant-based diet during pregnancy is associated with a lowered odds of infant eczema at 1 year in all participants. Future studies of the components of plant-based diet which underlie the lower risk of eczema are needed.

Evolution of altitudinal migration in passerines is linked to diet.

Bird migration is typically associated with a latitudinal movement from north to south and vice versa. However, many bird species migrate seasonally with an upslope or downslope movement in a process termed altitudinal migration. Globally, 830 of the 6,579 Passeriformes species are considered altitudinal migrants and this pattern has emerged multiple times across 77 families of this order. Recent work has indicated an association between altitudinal migration and diet, but none have looked at diet as a potential evolutionary driver. Here, we investigated potential evolutionary drivers of altitudinal migration in passerines around the world by using phylogenetic comparative methods. We tested for evolutionary associations between altitudinal migration and foraging guild and primary habitat preference in passerines species worldwide. Our results indicate that foraging guild is evolutionarily associated with altitudinal migration, but this relationship varies across zoogeographical regions. In the Nearctic, herbivorous and omnivorous species are associated with altitudinal migration, while only omnivorous species are associated with altitudinal migration in the Palearctic. Habitat was not strongly linked to the evolution of altitudinal migration. While our results point to diet as a potentially important driver of altitudinal migration, the evolution of this behavior is complex and certainly driven by multiple factors. Altitudinal migration varies in its use (for breeding or molting), within a species, population, and even at the individual level. As such, the evolution of altitudinal migration is likely driven by an ensemble of factors, but this study provides a beginning framework for understanding the evolution of this complex behavior.

Atypical Antipsychotics for Irritability in Pediatric Autism: A Systematic Review and Network Meta-Analysis.

OBJECTIVE: Irritability is common in pediatric autism spectrum disorder (ASD) patients. This can have major implications in child development, receptivity to behavioral therapy, as well as child and caregiver well-being. A systematic review and network meta-analysis were conducted to assess the efficacy and safety of atypical antipsychotics in treating irritability in these patients. METHODS: Studies were identified from Medline, Embase, and PsycINFO from inception to March 2018. The clinical trials database was reviewed. Studies were included if they were a double-blind, randomized controlled trial utilizing the Aberrant Behavior Checklist Irritability (ABC-I) to measure the efficacy of atypical antipsychotic monotherapy. Data extraction was carried out following the Preferred Reporting Items for Systematic Reviews and Meta-analyses for network meta-analysis guidelines. The main outcome was the reduction in irritability score using the ABC-I subscale from baseline. RESULTS: Eight trials comparing four interventions-risperidone, aripiprazole, lurasidone, and placebo in 878 patients, were included. Both risperidone and aripiprazole had significantly reduced ABC-I scores than placebo. Estimates of mean differences (95% credible intervals) were risperidone, -6.89 (-11.14, -2.54); aripiprazole, -6.62 (-10.88, -2.22); and lurasidone, -1.61 (-9.50, 6.23). Both risperidone and aripiprazole had similar safety. There were only eight studies included in the analysis, however, sample sizes were not small. Variance in reporting of adverse effects limited the quality of safety analysis. CONCLUSION: Risperidone and aripiprazole were the two best drugs, with comparable efficacy and safety in pediatric ASD patients. These two medications could be beneficial in improving irritability in these patients.

Bivariate random-effects meta-analysis models for diagnostic test accuracy studies using arcsine-based transformations.

Diagnostic or screening tests are widely used in medical fields to classify patients according to their disease status. Several statistical models for meta-analysis of diagnostic test accuracy studies have been developed to synthesize test sensitivity and specificity of a diagnostic test of interest. Because of the correlation between test sensitivity and specificity, modeling the two measures using a bivariate model is recommended. In this paper, we extend the current standard bivariate linear mixed model (LMM) by proposing two variance-stabilizing transformations: the arcsine square root and the Freeman-Tukey double arcsine transformation. We compared the performance of the proposed methods with the standard method through simulations using several performance measures. The simulation results showed that our proposed methods performed better than the standard LMM in terms of bias, root mean square error, and coverage probability in most of the scenarios, even when data were generated assuming the standard LMM. We also illustrated the methods using two real data sets.

Does the impact of a plant-based diet during pregnancy on birth weight differ by ethnicity? A dietary pattern analysis from a prospective Canadian birth cohort alliance.

OBJECTIVE: Birth weight is an indicator of newborn health and a strong predictor of health outcomes in later life. Significant variation in diet during pregnancy between ethnic groups in high-income countries provides an ideal opportunity to investigate the influence of maternal diet on birth weight. SETTING: Four multiethnic birth cohorts based in Canada (the NutriGen Alliance). PARTICIPANTS: 3997 full-term mother-infant pairs of diverse ethnic groups who had principal component analysis-derived diet pattern scores-plant-based, Western and health-conscious-and birth weight data. RESULTS: No associations were identified between the Western and health-conscious diet patterns and birth weight; however, the plant-based dietary pattern was inversely associated with birth weight (ß=-67.6 g per 1-unit increase; P<0.001), and an interaction with non-white ethnicity and birth weight was observed. Ethnically stratified analyses demonstrated that among white Europeans, maternal consumption of a plant-based diet associated with lower birth weight (ß=-65.9 g per 1-unit increase; P<0.001), increased risk of small-for-gestational age (SGA; OR=1.46; 95% CI 1.08 to 1.54;P=0.005) and reduced risk of large-for-gestational age (LGA; OR=0.71; 95% CI 0.53 to 0.95;P=0.02). Among South Asians, maternal consumption of a plant-based diet associated with a higher birth weight (ß=+40.5 g per 1-unit increase; P=0.01), partially explained by cooked vegetable consumption. CONCLUSIONS: Maternal consumption of a plant-based diet during pregnancy is associated with birth weight. Among white Europeans, a plant-based diet is associated with lower birth weight, reduced odds of an infant born LGA and increased odds of SGA, whereas among South Asians living in Canada, a plant-based diet is associated with increased birth weight.

Causes and consequences of gestational diabetes in South Asians living in Canada: results from a prospective cohort study.

BACKGROUND: The reasons for the increased risk of gestational diabetes among South Asian women are not well understood. We sought to identify the determinants of gestational diabetes and its impact on newborn health in a prospective birth cohort of South Asian women and their babies. METHODS: As part of the South Asian Birth Cohort (START) prospective birth cohort study in Ontario, we recruited 1012 South Asian women with singleton pregnancies in the second trimester of pregnancy between July 11, 2011, and Nov. 10, 2015. We collected health information and physical measurements and administered an oral glucose tolerance test. Birth weight and skinfold thickness measurements were obtained from their newborns, and cord blood glucose and insulin levels were measured. RESULTS: The incidence of gestational diabetes was 36.3% (95% confidence interval [CI] 33.3%-39.3%); the age-standardized rate was 40.7%. Factors associated with gestational diabetes included maternal age (odds ratio [OR] 1.08 [95% CI 1.04-1.12]), family history of diabetes (OR 1.65 [95% CI 1.26-2.17]), prepregnancy weight (OR 1.025 [95% CI 1.01-1.04]) and low diet quality (OR 1.57 [95% CI 1.16-2.12]). Maternal height was protective against gestational diabetes (OR 0.97 [95% CI 0.95-0.99]). The population attributable risk due to prepregnancy body mass index and low diet quality was 37.3%. Compared to newborns of women without gestational diabetes, those of women with gestational diabetes had a significantly higher birth weight (3267 [standard error (SE) 23] g v. 3181 [SE 17] g, p = 0.005), greater skinfold thickness (11.7 [SE 0.1] mm v. 11.2 [SE 0.1] mm, p = 0.007) and lower insulin sensitivity (glucose/insulin ratio 0.092 [SE 0.009] mmol/pmol v. 0.129 [SE 0.006] mmol/pmol, p = 0.001). INTERPRETATION: The modifiable risk factors of prepregnancy weight and low diet quality accounted for 37% of the population attributable risk of gestational diabetes in our cohort. Intervention studies to lower prepregnancy weight and to prevent gestational diabetes among South Asian women in high-income countries are needed.

Ethnic and diet-related differences in the healthy infant microbiome.

BACKGROUND: The infant gut is rapidly colonized by microorganisms soon after birth, and the composition of the microbiota is dynamic in the first year of life. Although a stable microbiome may not be established until 1 to 3 years after birth, the infant gut microbiota appears to be an important predictor of health outcomes in later life. METHODS: We obtained stool at one year of age from 173 white Caucasian and 182 South Asian infants from two Canadian birth cohorts to gain insight into how maternal and early infancy exposures influence the development of the gut microbiota. We investigated whether the infant gut microbiota differed by ethnicity (referring to groups of people who have certain racial, cultural, religious, or other traits in common) and by breastfeeding status, while accounting for variations in maternal and infant exposures (such as maternal antibiotic use, gestational diabetes, vegetarianism, infant milk diet, time of introduction of solid food, infant birth weight, and weight gain in the first year). RESULTS: We demonstrate that ethnicity and infant feeding practices independently influence the infant gut microbiome at 1 year, and that ethnic differences can be mapped to alpha diversity as well as a higher abundance of lactic acid bacteria in South Asians and a higher abundance of genera within the order Clostridiales in white Caucasians. CONCLUSIONS: The infant gut microbiome is influenced by ethnicity and breastfeeding in the first year of life. Ethnic differences in the gut microbiome may reflect maternal/infant dietary differences and whether these differences are associated with future cardiometabolic outcomes can only be determined after prospective follow-up.

Statistical models and computational algorithms for discovering relationships in microbiome data.

Microbiomes, populations of microscopic organisms, have been found to be related to human health and it is expected further investigations will lead to novel perspectives of disease. The data used to analyze microbiomes is one of the newest types (the result of high-throughput technology) and the means to analyze these data is still rapidly evolving. One of the distributions that have been introduced into the microbiome literature, the Dirichlet-Multinomial, has received considerable attention. We extend this distribution's use uncover compositional relationships between organisms at a taxonomic level. We apply our new method in two real microbiome data sets: one from human nasal passages and another from human stool samples.

Harmonization of Food-Frequency Questionnaires and Dietary Pattern Analysis in 4 Ethnically Diverse Birth Cohorts.

BACKGROUND: Canada is an ethnically diverse nation, which introduces challenges for health care providers tasked with providing evidence-based dietary advice. OBJECTIVES: We aimed to harmonize food-frequency questionnaires (FFQs) across 4 birth cohorts of ethnically diverse pregnant women to derive robust dietary patterns to investigate maternal and newborn outcomes. METHODS: The NutriGen Alliance comprises 4 prospective birth cohorts and includes 4880 Canadian mother-infant pairs of predominantly white European [CHILD (Canadian Healthy Infant Longitudinal Development) and FAMILY (Family Atherosclerosis Monitoring In earLY life)], South Asian [START (SouTh Asian birth cohoRT)-Canada], or Aboriginal [ABC (Aboriginal Birth Cohort)] origins. CHILD used a multiethnic FFQ based on a previously validated instrument designed by the Fred Hutchinson Cancer Research Center, whereas FAMILY, START, and ABC used questionnaires specifically designed for use in white European, South Asian, and Aboriginal people, respectively. The serving sizes and consumption frequencies of individual food items within the 4 FFQs were harmonized and aggregated into 36 common food groups. Principal components analysis was used to identify dietary patterns that were internally validated against self-reported vegetarian status and externally validated against a modified Alternative Healthy Eating Index (mAHEI). RESULTS: Three maternal dietary patterns were identified-"plant-based," "Western," and "health-conscious"-which collectively explained 29% of the total variability in eating habits observed in the NutriGen Alliance. These patterns were strongly associated with self-reported vegetarian status (OR: 3.85; 95% CI: 3.47, 4.29; r2 = 0.30, P < 0.001; for a plant-based diet), and average adherence to the plant-based diet was higher in participants in the fourth quartile of the mAHEI than in the first quartile (mean difference: 46.1%; r2 = 0.81, P < 0.001). CONCLUSION: Dietary data collected by using FFQs from ethnically diverse pregnant women can be harmonized to identify common dietary patterns to investigate associations between maternal dietary intake and health outcomes.

Testing genotypes-phenotype relationships using permutation tests on association rules.

Association rule mining is a knowledge discovery technique which informs researchers about relationships between variables in data. These relationships can be focused to a specific set of response variables. We propose an augmented version of this method to discover groups of genotypes which relate to specific outcomes. We derive the methodology to find these candidate groups of genotypes and illustrate how the method works on data regarding neuroinvasive complications of West Nile virus and through simulation.

A pseudo-EM algorithm for clustering incomplete longitudinal data.

A method for clustering incomplete longitudinal data, and gene expression time course data in particular, is presented. Specifically, an existing method that utilizes mixtures of multivariate Gaussian distributions with modified Cholesky-decomposed covariance structure is extended to accommodate incomplete data. Parameter estimation is carried out in a fashion that is similar to an expectation-maximization algorithm. We focus on the particular application of clustering incomplete gene expression time course data. In this application, our approach gives good clustering performance when compared to the results when there is no missing data. Possible extensions of this work are also suggested.