Dataset Information

Genetic regulation of linear growth.

ABSTRACT: Linear growth occurs at the growth plate. Therefore, genetic defects that interfere with the normal function of the growth plate can cause linear growth disorders. Many genetic causes of growth disorders have already been identified in humans. However, recent genome-wide approaches have broadened our knowledge of the mechanisms of linear growth, not only providing novel monogenic causes of growth disorders but also revealing single nucleotide polymorphisms in genes that affect height in the general population. The genes identified as causative of linear growth disorders are heterogeneous, playing a role in various growth-regulating mechanisms including those involving the extracellular matrix, intracellular signaling, paracrine signaling, endocrine signaling, and epigenetic regulation. Understanding the underlying genetic defects in linear growth is important for clinicians and researchers in order to provide proper diagnoses, management, and genetic counseling, as well as to develop better treatment approaches for children with growth disorders.

SUBMITTER: Yue S

PROVIDER: S-EPMC6449614 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genetic regulation of linear growth.

Yue Shanna S Whalen Philip P Jee Youn Hee YH

Annals of pediatric endocrinology & metabolism 20190331 1

Linear growth occurs at the growth plate. Therefore, genetic defects that interfere with the normal function of the growth plate can cause linear growth disorders. Many genetic causes of growth disorders have already been identified in humans. However, recent genome-wide approaches have broadened our knowledge of the mechanisms of linear growth, not only providing novel monogenic causes of growth disorders but also revealing single nucleotide polymorphisms in genes that affect height in the gene ...[more]

PMID: 30943674

Similar Datasets

Project description:The ability of a genotype to show diverse phenotypes in different environments is called phenotypic plasticity. Phenotypic plasticity helps populations to evade extinctions in novel environments, facilitates adaptation and fuels evolution. However, most studies focus on understanding the genetic basis of phenotypic regulation in specific environments. As a result, while it's evolutionary relevance is well established, genetic mechanisms regulating phenotypic plasticity and their overlap with the environment specific regulators is not well understood. Saccharomyces cerevisiae is highly sensitive to the environment, which acts as not just external stimulus but also as signalling cue for this unicellular, sessile organism. We used a previously published dataset of a biparental yeast population grown in 34 diverse environments and mapped genetic loci regulating variation in phenotypic plasticity, plasticity QTL, and compared them with environment-specific QTL. Plasticity QTL is one whose one allele exhibits high plasticity whereas the other shows a relatively canalised behaviour. We mapped phenotypic plasticity using two parameters-environmental variance, an environmental order-independent parameter and reaction norm (slope), an environmental order-dependent parameter. Our results show a partial overlap between pleiotropic QTL and plasticity QTL such that while some plasticity QTL are also pleiotropic, others have a significant effect on phenotypic plasticity without being significant in any environment independently. Furthermore, while some plasticity QTL are revealed only in specific environmental orders, we identify large effect plasticity QTL, which are order-independent such that whatever the order of the environments, one allele is always plastic and the other is canalised. Finally, we show that the environments can be divided into two categories based on the phenotypic diversity of the population within them and the two categories have differential regulators of phenotypic plasticity. Our results highlight the importance of identifying genetic regulators of phenotypic plasticity to comprehensively understand the genotype-phenotype map.

Project description:Undernutrition in early life underlies 45% of child deaths globally. Stunting malnutrition (suboptimal linear growth) also has long-term negative effects on childhood development. Linear growth deficits accrue in the first 1000 d of life. Understanding the patterns and timing of linear growth faltering or recovery during this period is critical to inform interventions to improve infant nutritional status.We aimed to identify the pattern and determinants of linear growth trajectories from birth through 24 mo of age in a cohort of Zimbabwean infants.We performed a secondary analysis of longitudinal data from a subset of 3338 HIV-unexposed infants in the Zimbabwe Vitamin A for Mothers and Babies trial. We used k-means clustering for longitudinal data to identify linear growth trajectories and multinomial logistic regression to identify covariates that were associated with each trajectory group.For the entire population, the mean length-for-age z score declined from -0.6 to -1.4 between birth and 24 mo of age. Within the population, 4 growth patterns were identified that were each characterized by worsening linear growth restriction but varied in the timing and severity of growth declines. In our multivariable model, 1-U increments in maternal height and education and infant birth weight and length were associated with greater relative odds of membership in the least-growth restricted groups (A and B) and reduced odds of membership in the more-growth restricted groups (C and D). Male infant sex was associated with reduced odds of membership in groups A and B but with increased odds of membership in groups C and D.In this population, all children were experiencing growth restriction but differences in magnitude were influenced by maternal height and education and infant sex, birth weight, and birth length, which suggest that key determinants of linear growth may already be established by the time of birth. This trial was registered at clinicaltrials.gov as NCT00198718.

Project description:ImportanceIrrespective of their genetic makeup, children living in an ideal home environment that supports healthy growth have similar growth potential. However, whether this potential is true for children residing at higher altitudes remains unknown.ObjectiveTo investigate whether altitude is associated with increased risk of linear growth faltering and evaluate the implications associated with the use of the 2006 World Health Organization growth standards, which have not been validated for populations residing 1500 m above sea level.Design, settings, and participantsAnalysis of 133 nationally representative demographic and health cross-sectional surveys administered in 59 low- and middle-income countries using local polynomial and multivariate regression was conducted. A total of 964 299 height records from 96 552 clusters at altitudes ranging from -372 to 5951 m above sea level were included. Demographic and Health Surveys were conducted between 1992 and 2018.ExposuresResidence at higher altitudes, above and below 1500 m above sea level, and in ideal home environments (eg, access to safe water, sanitation, and health care).Main outcomes and measuresThe primary outcome was child linear growth deficits expressed in length-for-age/height-for-age z scores (HAZ). Associations between altitude and height among all children and those residing in ideal home environments were assessed. Child growth trajectories above and below 1500 m above sea level were compared and the altitude-mediated height deficits were estimated using multivariable linear regression.ResultsIn 2010, a total of 842 million people in the global population (approximately 12%) lived 1500 m above sea level or higher, with 67% in Asia and Africa. Eleven percent of the sample was children who resided 1500 m above sea level or higher. These children were born at shorter length and remained on a lower growth trajectory than children residing in areas less than 1500 m above sea level. The negative association between altitude and HAZ was approximately linear through most part of the altitude distribution, indicating no clear threshold for an abrupt decrease in HAZ. A 1000-m above sea level increase in altitude was associated with a 0.163-unit (95% CI, -0.205 to -0.120 units) decrease in HAZ after adjusting for common risk factors using multivariable linear regressions. The HAZ distribution of children residing in ideal home environments was similar to the 2006 World Health Organization HAZ distribution, but only up to 500 m above sea level.Conclusions and relevanceThe findings of this study suggest that residing at a higher altitude may be associated with child growth slowing even for children living in ideal home environments. Interventions addressing altitude-mediated growth restrictions during pregnancy and early childhood should be identified and implemented.

Dataset Information

Genetic regulation of linear growth.

Publications

Genetic regulation of linear growth.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets