Complex Phenotypes: Mechanisms Underlying Variation in Human Stature

Muthuirulan, Pushpanathan; Capellini, Terence D.

doi:10.1007/s11914-019-00527-9

Cited by 16 publications

(9 citation statements)

References 209 publications

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“…Heritability, the proportion of phenotypic variance explained by genetic factors, has been studied for physical characteristics. Stature was shown as being highly heritable [ 1 ], but the extent of variation attributed to environmental influence is controversial [ 2 ]. This was demonstrated by studies of identical twins and families [ 3 ] and by genome-wide association studies (GWAS) [ 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

The heritability of body composition

et al. 2021

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Background Physical growth during childhood and adolescence is influenced by both genetic and environmental factors. Heritability, the proportion of phenotypic variance explained by genetic factors, has been demonstrated for stature and weight status. The aim of this study was to explore the heritability of body composition. Methods A real-life, observational study of the children and adolescents referred to the Endocrine Unit in a tertiary medical center. In January 2018, body composition by means of bioimpedance analysis (BIA) was implemented as part of the standard intake assessment of subjects referred for endocrine consultation. The clinic BIA database was searched for subjects with the term “observation of growth” as the sole reason for referral. BIA of 114 triads of healthy subjects aged 5–18 years and their parents were analyzed. The BIA report included the following data: fat mass, fat percentage, truncal fat percentage and muscle mass. Calculated variables included: appendicular skeletal muscle mass (ASMM = the sum of muscle mass of four limbs), muscle-to-fat ratio [MFR = ASMM (kg)/fat mass (kg)] and sarcopenic index [(SI = ASMM(kg)/height (meter)²]. Data collection from medical files included pubertal stage and home address for socioeconomic position grading. Results There were sex differences in body composition parameters in both the prepubertal and pubertal subjects. The boys among the prepubertal subjects had a lower fat percentage on average than girls (p = 0.020). Among the adolescents, boys on average had lower fat percentage (p = 0.011), higher sarcopenic index (p = 0.021), and higher muscle-to-fat ratio (p < 0.001), than adolescent girls. Correlation analyses between body composition parameters of all participants revealed significant correlations in the sarcopenic index of prepubertal children and their parents (boys-fathers: r = 0.380, p = 0.050; boys-mothers: r = 0.435, p = 0.026; girls-fathers: r = 0.462, p = 0.012; girls-mothers: r = 0.365, p = 0.050) and adiposity indices (fat percentage, truncal fat percentage and muscle-to-fat ratio) of prepubertal boys and their mothers (r = 0.438, p = 0.025; r = 0.420, p = 0.033, and r = 0.478, p = 0.014, respectively). There were no associations between body composition parameters of adolescents and their parents. Socioeconomic position adversely affected fat percentage in adolescent girls and mothers. Conclusions Heritable body composition traits were demonstrated in childhood but not in adolescence, suggesting that environmental influence has a more telling effect during teenage years.

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Section: Introductionmentioning

confidence: 99%

The heritability of body composition

et al. 2021

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“…На сегодняшний день известно, что рост -это полигенный признак с наследуемостью порядка 80%, следовательно, генетическая изменчивость является основным фактором, влияющим на значение показателя роста, особенно в пределах одной популяции людей [3,4]. Рост подчинен закону нормального распределения, при этом для небольшой части индивидуумов (3-5%) характерны крайние значения показателя, в то время как у основной части людей значения роста близки к среднему значению показателя [5]. Несколько полногеномных ассоциативных исследований, проведенных в последнее время, выявили сотни генетических вариантов, которые распространены в популяциях, и каждый из них оказывает крайне незначительное влияние на изменение показателя роста (<5 мм/аллель), приблизительно 1% вариантов оказывают умеренное влияние на изменение показателя роста (>5 мм/аллель) [2,5].…”

Section:  введениеunclassified

“…Рост подчинен закону нормального распределения, при этом для небольшой части индивидуумов (3-5%) характерны крайние значения показателя, в то время как у основной части людей значения роста близки к среднему значению показателя [5]. Несколько полногеномных ассоциативных исследований, проведенных в последнее время, выявили сотни генетических вариантов, которые распространены в популяциях, и каждый из них оказывает крайне незначительное влияние на изменение показателя роста (<5 мм/аллель), приблизительно 1% вариантов оказывают умеренное влияние на изменение показателя роста (>5 мм/аллель) [2,5]. Однако чем ближе значение показателя роста к крайним вариантам (<2,5-3 SD, что составляет приблизительно 0,1-0,6% популяции), тем чаще низкорослость вызвана мутацией в отдельном гене и является одним из фенотипических признаков генетического синдрома.…”

Section:  введениеunclassified

Genetically Determined Short Stature in the Practice of an Obstetrician-Gynecologist

Медведева¹,

Прибушеня²

2022

Репродуктивное Здоровье. Восточная Европа

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Низкий рост беременных женщин приводит к увеличению риска развития акушерских осложнений. Установление причины низкорослости помогает акушерам-гинекологам правильно оценить риск развития осложнений беременности и родов, проводить профилактику, своевременную диагностику и лечение для улучшения исходов для матери и плода и предотвращения перинатальных потерь. The low height of pregnant women leads to an increased risk of obstetric complications. Finding the cause of short stature helps obstetricians-gynecologists correctly assess the risk of complications of pregnancy and childbirth. It also helps to prevent diseases, perinatal losses and timely diagnose and find the right treatment to improve maternal and fetal outcomes.

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“…This comparably close relationship is surprising, considering that the complex processes of growth and development during childhood and adolescence are subdued to numerous influences, e.g. genetics, the individual constitutional disposition, endocrinologic factors, diet and diseases [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Altered DNA methylation at age-associated CpG sites in children with growth disorders: impact on age estimation?

et al. 2022

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Age estimation based on DNA methylation (DNAm) can be applied to children, adolescents and adults, but many CG dinucleotides (CpGs) exhibit different kinetics of age-associated DNAm across these age ranges. Furthermore, it is still unclear how growth disorders impact epigenetic age predictions, and this may be particularly relevant for a forensic application. In this study, we analyzed buccal mucosa samples from 95 healthy children and 104 children with different growth disorders. DNAm was analysed by pyrosequencing for 22 CpGs in the genes PDE4C, ELOVL2, RPA2, EDARADD and DDO. The relationship between DNAm and age in healthy children was tested by Spearman’s rank correlation. Differences in DNAm between the groups “healthy children” and the (sub-)groups of children with growth disorders were tested by ANCOVA. Models for age estimation were trained (1) based on the data from 11 CpGs with a close correlation between DNAm and age (R ≥ 0.75) and (2) on five CpGs that also did not present significant differences in DNAm between healthy and diseased children. Statistical analysis revealed significant differences between the healthy group and the group with growth disorders (11 CpGs), the subgroup with a short stature (12 CpGs) and the non-short stature subgroup (three CpGs). The results are in line with the assumption of an epigenetic regulation of height-influencing genes. Age predictors trained on 11 CpGs with high correlations between DNAm and age revealed higher mean absolute errors (MAEs) in the group of growth disorders (mean MAE 2.21 years versus MAE 1.79 in the healthy group) as well as in the short stature (sub-)groups; furthermore, there was a clear tendency for overestimation of ages in all growth disorder groups (mean age deviations: total growth disorder group 1.85 years, short stature group 1.99 years). Age estimates on samples from children with growth disorders were more precise when using a model containing only the five CpGs that did not present significant differences in DNAm between healthy and diseased children (mean age deviations: total growth disorder group 1.45 years, short stature group 1.66 years). The results suggest that CpGs in genes involved in processes relevant for growth and development should be avoided in age prediction models for children since they may be sensitive for alterations in the DNAm pattern in cases of growth disorders.

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Complex Phenotypes: Mechanisms Underlying Variation in Human Stature

Cited by 16 publications

References 209 publications

The heritability of body composition

The heritability of body composition

Genetically Determined Short Stature in the Practice of an Obstetrician-Gynecologist

Altered DNA methylation at age-associated CpG sites in children with growth disorders: impact on age estimation?

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