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Life history theory predicts that experiencing stress during the early period of life will result in accelerated growth and earlier maturation. Indeed, animal and some human studies documented a faster pace of growth in the offspring of stressed mothers. Recent advances in epigenetics suggest that the effects of early developmental stress might be passed across the generations. However, evidence for such intergenerational transmission is scarce, at least in humans. Here we report the results of the study investigating the association between childhood trauma in mothers and physical growth in their children during the first months of life. Anthropometric and psychological data were collected from 99 mothers and their exclusively breastfed children at the age of 5 months. The mothers completed the Early Life Stress Questionnaire to assess childhood trauma. The questionnaire includes questions about the most traumatic events that they had experienced before the age of 12 years. Infant growth was evaluated based on the anthropometric measurements of weight, length, and head circumference. Also, to control for the size of maternal investment, the composition of breast milk samples taken at the time of infant anthropometric measurements was investigated. The children of mothers with higher early life stress tended to have higher weight and bigger head circumference. The association between infant anthropometrics and early maternal stress was not affected by breast milk composition, suggesting that the effect of maternal stress on infant growth was independent of the size of maternal investment. Our results demonstrate that early maternal trauma may affect the pace of growth in the offspring and, in consequence, lead to a faster life history strategy. This effect might be explained via changes in offspring epigenetics.
Introduction: Body height is influenced by biological factors such as genetics, nutrition and health, but also by the social network, and environmental and economical factors. During centuries, the Japanese society has developed on islands. This setting provides ideal natural conditions for studying the influence of social networks on human height. Material and methods: We investigated body height of male Japanese students aged 17.5 years obtained in 47 prefectures, from the Japanese school health survey of the years 1955, 1975, 1995, and 2015. Results: Japanese students increased in height from 163.23 cm in 1955 to 170.84 cm in 1995, with no further increase thereafter (170.63 cm in 2015). Students living in neighboring prefectures were similar in height. The correlation of height between neighboring prefectures ranged between r = 0.79 and r = 0.49 among first degree neighbors, between r = 0.49 and r = 0.21 among second degree neighbors and dropped to insignificance among third degree neighbors indicating psychosocial effects of the community on body height. Tall stature and short stature prefectures did not remain tall or short throughout history. Autocorrelations of height within the same prefectures decreased from the 20 years periods of 1955-1975, 1975-1995 and 1995-2015 (r = 0.52, r = 0.61, r = 0.63, respectively) to the 40 years periods of 1955-1995 and 1975-2015 (r = 0.49, r = 0.52), down to the 60 years period of 1955-2015 (r = 0.27), indicating significant volatility of height. Conclusion: Body height of 17.5 years old Japanese students increased since 1955. Body height depended on height of the neighboring prefecture, but was volatile with decreasing autocorrelation during a period of 60 years.
Background: We investigated height of Norwegian conscripts in view of the hypothesis of a "community effect on height" using autocorrelation analysis of district heights within a time-span of 20 years at the end of the 19th century and correlations between neighboring districts at this time. Material and methods: After digitalizing available body height data of Norwegian draftees in 1877-1878, 1880 (averaged as 1878), and 1895-1897 (averaged as 1896) we calculated the magnitude of autocorrelation of body height within the same municipality at different time points. Furthermore, we generated three different neighborhood networks, (1) based on Euclidean distances, (2) a minimum spanning tree build on those distances, (3) a network founded on real world road connections. The networks were used to determine the correlation between body height of neighboring districts depending on the number of edges required to connect two municipalities. Results: The autocorrelation value for body heights was around r = 0.5 (for all p < 0.001) in the years 1878 and 1896. The correlation between neighboring districts varied in the Euclidean distance based network between 0.47 and 0.27 approximately for both years in a sorted order, descending from nearest (0-50 km) to farthest (150-200 km, for all p < 0.001). First order neighbors in the minimum spanning tree network correlation was 0.36 in 1878 and 0.42 in 1896 (for all p < 0.001). The values of neighbor correlation in the road connection based network ranged in 1878 from 0.42 (first order neighbors) to 0.17 (forth order neighbors, for all p < 0.01) and in 1896 from 0.46 (first order neighbors) to 0.12 (forth order neighbors, for all p < 0.05). Conclusion: This initial study of Norwegian conscript height data from the 19th century showed significant medium sized effects for the within district autocorrelation between 1878 and 1896 as well as medium neighborhood correlation, slightly lower in comparison to a recent study regarding Swiss conscripts. Digitalizing more data from other years in this and later time spans as well as using older road and ship connections instead of the actual road data might stabilize and improve those findings.
Background: Recent research reported height biased migration of taller individuals and a Monte Carlo simulation showed that such preferential migration of taller individuals into network hubs can induce a secular trend of height. In the simulation model taller agents in the hubs raise the overall height of all individuals in the network by a community effect. However, it could be seen that the actual network structure influences the strength of this effect. In this paper the background and the influence of the network structure on the strength of the secular trend by migration is investigated. Material and methods: Three principal network types are analyzed: networks derived from street connections in Switzerland, more regular fishing net like networks and randomly generated ones. Our networks have between 10 and 152 nodes and between 20 and 307 edges connecting the nodes. Depending on the network size between 5.000 and 90.000 agents with an average height of 170 cm (SD 6.5 cm) are initially released into the network. In each iteration new agents are regenerated based on the actual average body height of the previous iteration and, to a certain proportion, corrected by body heights in the neighboring nodes. After generating new agents, a certain number of them migrated into neighbor nodes, the model let preferentially taller agents migrate into network hubs. Migration is balanced by back migration of the same number of agents from nodes with high centrality measures to less connected nodes. The latter is random as well, but not biased by the agents height. Furthermore the distribution of agents per node and their correlation to the centrality of the nodes is varied in a systematic manner. After 100 iterations, the secular trend, i.e. the gain in body height for the different networks, is investigated in relation to the network properties. Results: We observe an increase of average agent body height after 100 iterations if height biased migration is enabled. The increase rate depends on the height of the neighboring factor, the population distribution, the relationship between population in the nodes and their centrality as well as on the network topology. Networks with uniform like distributions of the agents in the nodes, uncorrelated associations between node centrality and agent number per node, as well as very heterogeneous networks with very different node centralities lead to biggest gains in average body height. Conclusion: Our simulations show, that height biased migration into network hubs can possibly contribute to the secular trend of height increase in the human population. The strength of this "tall by migration" event depends on the actual properties of the underlying network. There is a possible significance of this mechanism for social networks, when hubs are represented by individuals and edges as their personal relationships. However, the required high number of iterations to achieve significant effects in more natural network structures in our models requires further studies to test the relevance and real effect sizes in real world scenarios.
The Western honey bee (Apis mellifera) is widely used as commercial pollinator in worldwide agriculture and, therefore, plays an important role in global food security. Among the parasites and pathogens threatening health and survival of honey bees are two species of microsporidia, Nosema apis and Nosema ceranae. Nosema ceranae is considered an emerging pathogen of the Western honey bee. Reports on the spread of N. ceranae suggested that this presumably highly virulent species is replacing its more benign congener N. apis in the global A. mellifera population. We here present a 12 year longitudinal cohort study on the prevalence of N. apis and N. ceranae in Northeast Germany. Between 2005 and 2016, a cohort of about 230 honey bee colonies originating from 23 apiaries was sampled twice a year (spring and autumn) resulting in a total of 5,600 bee samples which were subjected to microscopic and molecular analysis for determining the presence of infections with N. apis or/and N. ceranae. Throughout the entire study period, both N. apis- and N. ceranae-infections could be diagnosed within the cohort. Logistic regression analysis of the prevalence data demonstrated a significant increase of N. ceranae-infections over the last 12 years, both in autumn (reflecting the development during the summer) and in spring (reflecting the development over winter) samples. Cell culture experiments confirmed that N. ceranae has a higher proliferative potential than N. apis at 27. and 33 degrees C potentially explaining the increase in N. ceranae prevalence during summer. In autumn, characterized by generally low infection prevalence, this increase was accompanied by a significant decrease in N. apis- infection prevalence. In contrast, in spring, the season with a higher prevalence of infection, no significant decrease of N. apis infections despite a significant increase in N. ceranae infections could be observed. Therefore, our data do not support a general advantage of N. ceranae over N. apis and an overall replacement of N. apis by N. ceranae in the studied honey bee population.
The aim of the study was to investigate the correlation of heights of conscripts living in neighboring districts in Poland. The study used 10% of a nationally representative sample of 26,178 males 18.5-19.5 years old examined during the National survey of Polish conscripts conducted in 2001. The sample represented all regions and social strata of the country and included 354 different districts within 16 voivodships (provinces). Analyses were performed with the R statistical software. A small but significant correlation (0.24, p < 0.0001) was observed for height between 1st order neighboring districts. Correlations decreased with increased distances between neighboring districts, but remained significant for 7th node neighbors (0.18, p < 0.0001). Regarding voivodships (provinces), average height showed a geographical trend from the northwest (relatively tall) to the southeast (relatively short), and the correlation was stronger for first order neighboring provinces (0.796, p < 0.001). This study revealed clusters of tall people and short people, providing a support for hypothesis of the community effect in height. Small correlations between 1st order neighbors than in another country (Switzerland) may be associated with differences in geography, since in Poland there are no natural barriers (e.g., mountains) and road infrastructure is well-developed.
Modeling a secular trend by Monte Carlo simulation of height biased migration in a spatial network
(2017)
Background: In a recent Monte Carlo simulation, the clustering of body height of Swiss military conscripts within a spatial network with characteristic features of the natural Swiss geography was investigated. In this study I examined the effect of migration of tall individuals into network hubs on the dynamics of body height within the whole spatial network. The aim of this study was to simulate height trends. Material and methods: Three networks were used for modeling, a regular rectangular fishing net like network, a real world example based on the geographic map of Switzerland, and a random network. All networks contained between 144 and 148 districts and between 265-307 road connections. Around 100,000 agents were initially released with average height of 170 cm, and height standard deviation of 6.5 cm. The simulation was started with the a priori assumption that height variation within a district is limited and also depends on height of neighboring districts (community effect on height). In addition to a neighborhood influence factor, which simulates a community effect, body height dependent migration of conscripts between adjacent districts in each Monte Carlo simulation was used to re-calculate next generation body heights. In order to determine the direction of migration for taller individuals, various centrality measures for the evaluation of district importance within the spatial network were applied. Taller individuals were favored to migrate more into network hubs, backward migration using the same number of individuals was random, not biased towards body height. Network hubs were defined by the importance of a district within the spatial network. The importance of a district was evaluated by various centrality measures. In the null model there were no road connections, height information could not be delivered between the districts. Results: Due to the favored migration of tall individuals into network hubs, average body height of the hubs, and later, of the whole network increased by up to 0.1 cm per iteration depending on the network model. The general increase in height within the network depended on connectedness and on the amount of height information that was exchanged between neighboring districts. If higher amounts of neighborhood height information were exchanged, the general increase in height within the network was large (strong secular trend). The trend in the homogeneous fishnet like network was lowest, the trend in the random network was highest. Yet, some network properties, such as the heteroscedasticity and autocorrelations of the migration simulation models differed greatly from the natural features observed in Swiss military conscript networks. Autocorrelations of district heights for instance, were much higher in the migration models. Conclusion: This study confirmed that secular height trends can be modeled by preferred migration of tall individuals into network hubs. However, basic network properties of the migration simulation models differed greatly from the natural features observed in Swiss military conscripts. Similar network-based data from other countries should be explored to better investigate height trends with Monte Carlo migration approach.
Background: Multiple linear correlations between parameters can be shown in correlation matrices. Correlations can be ranked, but can also be visualized in network graphs. Yet, translating a correlation matrix into a network graph is not trivial. In view of a popular child game, we propose to name this method St. Nicolas House Analysis. Material and methods: We present a new method (St. Nicolas House Analysis) that helps translating correlation matrices into network graphs. The performance of this and other network reconstruction methods was tested in randomly created virtual scale-free networks, networks consisting of bands or hubs, using balanced classification rate and the F1-Score for correctly predicting existing and non-existing edges. Thereafter we analyzed anthropometric data and information on parental education, obtained from an anthropometric survey in 908 Indonesian boys and 808 Indonesian girls. Seven parameters were analyzed: child height standard deviation score (hSDS), child BMI standard deviation scores (BMI_SDS), mid-upper-arm circumference (MUAC), mean thickness of subscapular and triceps skinfold (mean SF), and elbow breadth; as well as maternal and paternal education (years of schooling). The parameters were considered as the nodes of the network; the edges represent the correlations between the nodes. Results: Performance measures, balanced classification rate and the F1-score, showed that St. Nicolas’ House Analysis was superior to methods using sophisticated correlation value thresholds and methods based on partial correlations for analyzing bands and hubs. We applied this method also in an Indonesia data set. Ranking correlations showed the direct association between parental education and child growth. Conclusion: St. Nicolas House Analysis confirmed that growth of Indonesian school children directly depends on maternal education, with no evidence that this effect is mediated by the state of nutrition.
Human growth data analysis and statistics – the 5th Gülpe International Student Summer School
(2023)
The Summer School in Gülpe (Ecological Station of the University of Potsdam) offers an exceptional learning opportunity for students to apply their knowledge and skills to real-world problems. With the guidance of experienced human biologists, statisticians, and programmers, students have the unique chance to analyze their own data and gain valuable insights. This interdisciplinary setting not only bridges different research areas but also leads to highly valuable outputs. The progress of students within just a few days is truly remarkable, especially when they are motivated and receive immediate feedback on their questions, problems, and results. The Summer School covers a wide range of topics, with this year’s focus mainly on two areas: understanding the impact of socioeconomic and physiological factors on human development and mastering statistical techniques for analyzing data such as changepoint analysis and the St. Nicolas House Analysis (SNHA) to visualize interacting variables. The latter technique, born out of the Summer School’s emphasis on gaining comprehensive data insights and understanding major relationships, has proven to be a valuable tool for researchers in the field. The articles in this special issue demonstrate that the Summer School in Gülpe stands as a testament to the power of practical learning and collaboration. Students who attend not only gain hands-on experience but also benefit from the expertise of professionals and the opportunity to engage with peers from diverse disciplines.
Identification of a super-functional Tfh-like subpopulation in murine lupus by pattern perception
(2020)
Dysregulated cytokine expression by T cells plays a pivotal role in the pathogenesis of autoimmune diseases. However, the identification of the corresponding pathogenic subpopulations is a challenge, since a distinction between physiological variation and a new quality in the expression of protein markers requires combinatorial evaluation. Here, we were able to identify a super-functional follicular helper T cell (Tfh)-like subpopulation in lupus-prone NZBxW mice with our binning approach "pattern recognition of immune cells (PRI)". PRI uncovered a subpopulation of IL-21(+) IFN-gamma(high) PD-1(low) CD40L(high) CXCR5(-) Bcl-6(-) T cells specifically expanded in diseased mice. In addition, these cells express high levels of TNF-alpha and IL-2, and provide B cell help for IgG production in an IL-21 and CD40L dependent manner. This super-functional T cell subset might be a superior driver of autoimmune processes due to a polyfunctional and high cytokine expression combined with Tfh-like properties.
The St. Nicolas House Algorithm (SNHA) finds association chains of direct dependent variables in a data set. The dependency is based on the correlation coefficient, which is visualized as an undirected graph. The network prediction is improved by a bootstrap routine. It enables the computation of the empirical p-value, which is used to evaluate the significance of the predicted edges. Synthetic data generated with the Monte Carlo method were used to firstly compare the Python package with the original R package, and secondly to evaluate the predicted network using the sensitivity, specificity, balanced classification rate and the Matthew's correlation coefficient (MCC). The Python implementation yields the same results as the R package. Hence, the algorithm was correctly ported into Python. The SNHA scores high specificity values for all tested graphs. For graphs with high edge densities, the other evaluation metrics decrease due to lower sensitivity, which could be partially improved by using bootstrap,while for graphs with low edge densities the algorithm achieves high evaluation scores. The empirical p-values indicated that the predicted edges indeed are significant.
Background: Human populations differ in height. Recent evidence suggests that social networks play an important role in the regulation of adolescent growth and adult height. We further investigated the effect of physical connectedness on height.
Material and methods: We considered Switzerland as a geographic network with 169 nodes (district capitals) and 335 edges (connecting roads) and studied effects of connectedness on height in Swiss conscript from 1884-1891, 1908-1910, and 2004-2009. We also created exponential-family random graph models to separate possible unspecific effects of geographic vicinity.
Results: In 1884-1891, in 1908-1910, and in 2004-2009, 1st, 2nd and 3rd order neighboring districts significantly correlate in height (p<0.01). The correlations depend on the order of connectedness, they decline with increasing distance. Short stature districts tend to have short, tall stature districts tend to have tall neighbors. Random network analyses suggest direct road effects on height. Whereas in 1884-1891, direct road effects were only visible between 1st order neighbors, direct road effects extended to 2nd and 3rd in 1908-1910, and in 2004-2009, also to 4th order neighbors, and might reflect historic improvements in transportation. The spatial correlations did not significantly change when height was controlled for goiter (1884-1889) and for median per capita income (2006), suggesting direct road effects also in goiter-allowed-for height and income-allowed-for height.
Conclusion: Height in a district depends on height of physically connected neighboring districts. The association decreases with increasing distance in the net. The present data suggest that people can be short because their neighbors are short; or tall because their neighbors are tall (community effect on growth). Psycho-biological effects seem to control growth and development within communities that go far beyond our current understanding of growth regulation.
BACKGROUND/OBJECTIVES: Recent evidence suggests clustering of human body height. We want to assess the consequences of connectedness in a spatial network on height clustering in an artificial society. SUBJECTS/METHODS: We used an agent-based computer modelling technique (Monte Carlo simulation) and compared simulated height in a spatial network with characteristics of the observed geographic height distribution of three historic cohorts of Swiss military conscripts (conscripted in 1884-1891; 1908-1910; and 2004-2009). RESULTS: Conscript height shows several characteristic features: (1) height distributions are overdispersed. (2) Conscripts from districts with direct inter-district road connections tend to be similar in height. (3) Clusters of tall and clusters of short stature districts vary over time. Autocorrelations in height between late 19th and early 21st century districts are low. (4) Mean district height depends on the number of connecting roads and on the number of conscripts per district. Using Monte Carlo simulation, we were able to generate these natural characteristics in an artificial society. Already 5% height information from directly connected districts is sufficient to simulate the characteristics of natural height distribution. Very similar observations in regular rectangular networks indicate that the characteristics of Swiss conscript height distributions do not so much result from the particular Swiss geography but rather appear to be general features of spatial networks. CONCLUSIONS: Spatial connectedness can affect height clustering in an artificial society, similar to that seen in natural cohorts of military conscripts, and strengthen the concept of connectedness being involved in the regulation of human height.
Animal societies are structured of dominance hierarchy (DH). DH can be viewed as networks and analyzed by graph theory. We study the impact of state-dependent feedback (winner-loser effect) on the emergence of local dominance structures after pairwise contests between initially equal-ranking members (equal resource-holding-power, RHP) of small and large social groups. We simulated pairwise agonistic contests between individuals with and without a priori higher RHP by Monte-Carlo-method. Random pairwise contests between equal-ranking competitors result in random dominance structures (‘Null variant’) that are low in transitive triads and high in pass along triads; whereas state-dependent feedback (‘Winner-loser variant’) yields centralized ‘star’ structured DH that evolve from competitors with initially equal RHP and correspond to hierarchies that evolve from keystone individuals. Monte-Carlo simulated DH following state-dependent feedback show motif patterns very similar to those of a variety of natural DH, suggesting that state-dependent feedback plays a pivotal role in robust self-organizing phenomena that transcend the specifics of the individual. Self-organization based on state-dependent feedback leads to social structures that correspond to those resulting from pre-existing keystone individuals. As the efficiency of centralized social networks benefits both, the individual and the group, centralization of social networks appears to be an important evolutionary goal.
Students learn by repetition. Repetition is essential, but repetition needs questioning, and questioning the repertoire belongs to the essential tasks of student education. Guiding students to questioning was and is our prime motive to offer our International Student Summer Schools. The data were critically discussed among the students, in the twilight of Just So Stories, common knowledge, and prompted questioning of contemporary solutions. For these schools, the students bring their own data, carry their preliminary concepts, and in group discussions, they may have to challenge these concepts. Catch-up growth is known to affect long bone growth, but different opinions exist to what extent it also affects body proportions. Skeletal age and dental development are considered appropriate measures of maturation, but it appears that both system develop independently and are regulated by different mechanisms. Body weight distributions are assumed to be skewed, yet, historic data disproved this assumption. Many discussions focused on current ideas of global growth standards as a common yardstick for all populations world-wide, with new statistical tools being developed including network reconstruction and evaluation of the reconstructs to determine the confidence of graph prediction methods.
Twenty-four scientists met at Aschauhof, Altenhof, Germany, to discuss the associations between child growth and development, and nutrition, health, environment and psychology. Meta-analyses of body height, height variability and household inequality, in historic and modern growth studies published since 1794, highlighting the enormously flexible patterns of child and adolescent height and weight increments throughout history which do not only depend on genetics, prenatal development, nutrition, health, and economic circumstances, but reflect social interactions. A Quality of Life in Short Stature Youth Questionnaire was presented to cross-culturally assess health-related quality of life in children. Changes of child body proportions in recent history, the relation between height and longevity in historic Dutch samples and also measures of body height in skeletal remains belonged to the topics of this meeting. Bayesian approaches and Monte Carlo simulations offer new statistical tools for the study of human growth.
Meeting Reports
(2019)
Thirty-one scientists met at Aschauhof, Germany to discuss the role of beliefs and self-perception on body size. In view of apparent growth stimulatory effects of dominance within the social group that is observed in social mammals, they discussed various aspects of competitive growth strategies and growth adjustments. Presentations included new data from Indonesia, a cohort-based prospective study from Merida, Yucatan, and evidence from recent meta-analyses and patterns of growth in the socially deprived. The effects of stress experienced during pregnancy and adverse childhood events were discussed, as well as obesity in school children, with emphasis on problems when using z-scores in extremely obese children. Aspects were presented on body image in African-American women, and body perception and the disappointments of menopause in view of feelings of attractiveness in different populations. Secular trends in height were presented, including short views on so called 'racial types' vs bio-plasticity, and historic data on early-life nutritional status and later-life socioeconomic outcomes during the Dutch potato famine. New tools for describing body proportions in patients with variable degrees of phocomelia were presented along with electronic growth charts. Bio-statisticians discussed the influence of randomness, community and network structures, and presented novel tools and methods for analyzing social network data.
Height and skeletal morphology strongly relate to life style. Parallel to the decrease in physical activity and locomotion, modern people are slimmer in skeletal proportions. In German children and adolescents, elbow breadth and particularly relative pelvic breadth (50th centile of bicristal distance divided by body height) have significantly decreased in recent years. Even more evident than the changes in pelvic morphology are the rapid changes in body height in most modern countries since the end-19th and particularly since the mid-20th century. Modern Japanese mature earlier; the age at take-off (ATO, the age at which the adolescent growth spurt starts) decreases, and they are taller at all ages. Preece-Baines modelling of six national samples of Japanese children and adolescents, surveyed between 1955 and 2000, shows that this gain in height is largely an adolescent trend, whereas height at take-off (HTO) increased by less than 3 cm since 1955; adolescent growth (height gain between ATO and adult age) increased by 6 cm. The effect of globalization on the modern post-war Japanese society ("community effect in height") on adolescent growth is discussed.