Suchergebnisse

The genetic contribution of blood pressure and heart rate (HR) varied widely between studies. Demographic factors such as ethnicity, age and/or sex might explain some of the heterogeneity. We performed a systematic review focusing on four phenotypes: systolic blood pressure (SBP), diastolic blood pressure (DBP), HR and pulse pressure (PP). Meta-regression was conducted to analyze potential factors in relation to SBP and DBP heritability. A total of 10,613 independent twins that came from 17 studies were included in the analysis. The weighted mean value of heritability for SBP and DBP was 0.54 (95% CIs: 0.48–0.60) and 0.49 (95% CIs: 0.42–0.56). Comparatively, three studies of HR and four studies of PP heritability were limited for the heterogeneity test. Meta-regression showed that, on average, SBP heritability with additive genes/unique environment (AE) model tend to have a higher heritability than additive genes/shared environment/unique environment (ACE) model (coefficient = 0.0947,p= .0142). A similar result was found for DBP as well. No other factors such as sex, age, ethnicity, publication year were significantly associated with heritability variance. Our study shows heritability estimates based on twin studies of both SBP and DBP are around 50%, using an AE rather than an ACE model; the variance due to C ended up in A, suggesting that the AE model may overestimate heritability if a small contribution of shared environment exists.

The Chinese National Twin Registry (CNTR), established in 2001, is the first and largest population-based twin registry in China. Based on the CNTR, a new twin cohort was recruited from 2011 to study the relationship between environmental risk factors and chronic diseases. So far, 33,874 twin pairs from nine provinces have been recruited, in which hundreds of disease-discordant twin pairs and even thousands of exposure-discordant twin pairs were found in this cohort. The updates of the CNTR will be introduced in detail in this article.

Obesity is associated with blood pressure (BP), but the associations between different obesity indicators and BP have not reached agreement. Besides, both obesity and BP are influenced by genetic and environmental factors. Whether they share the same genetic or environmental etiology has not been fully understood. We therefore analyzed the relationship between different obesity indicators and BP components as well as the genetic and environmental contributions to these relationships in a Chinese adult twin sample. Twins aged 18–79 years (n = 941) were included in this study. Body mass index (BMI) was used as the index of general obesity, whereas waist circumference (WC), waist-to-height ratio (WHtR), and waist-to-hip ratio (WHR) were used as the indicators of central obesity. BP components included systolic blood pressure (SBP) and diastolic blood pressure (DBP). Linear regression models and bivariate structural equation models were used to examine the relation of various obesity indicators with BP components, and genetic or environmental influences on these associations, respectively. A strong association of BP components with BMI—and a somewhat weaker association with WC, WHtR, and WHR—was found in both sexes, independent of familial factors. Of these phenotypic correlations between obesity indicators and BP components, 60–76% were attributed to genetic factors, whereas 24–40% were attributed to unique environmental factors. General obesity was most strongly associated with high BP in Chinese adult twins. There were common genetic backgrounds for obesity and BP, and unique environmental factors also played a role.

AbstractThe objective of this study was to investigate how different obesity measures link to circulating metabolites, and whether the connections are due to genetic or environmental factors. A cross-sectional analysis was performed on follow-up survey data at the Chinese National Twin Registry (CNTR), which was conducted in four areas of China (Shandong, Jiangsu, Zhejiang and Sichuan) in 2013. The survey collected detailed questionnaire information and conducted physical examinations, fasting blood sampling and untargeted metabolomic measurements among 439 adult twins. Linear regression models and bioinformatics analysis were used to examine the relation of obesity measures, including body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) with serum metabolite levels and related pathways. A co-twin control study was additionally conducted among 15 obesity-discordant monozygotic (MZ) pairs (intrapair BMI difference >3 kg/m2) to examine any differences in metabolites controlling for genetic factors. Eleven metabolites were associated with BMI, WC and WHR after controlling for genetic and shared environmental factors. Pathway analysis identified pathways such as phenylalanine metabolism, purine metabolism, valine, leucine and isoleucine biosynthesis that were associated with obesity. A wide range of unfavorable alterations in the serum metabolome was associated with obesity. Obesity-discordant twin analysis suggests that these associations are independent of genetic liability.

This study examined the genetic and environmental effects on variances in weight, height, and body mass index (BMI) under 18 years in a population-based sample from China. We selected 6,644 monozygotic and 5,969 dizygotic twin pairs from the Chinese National Twin Registry (CNTR) aged under 18 years (n= 12,613). Classic twin analyses with sex limitation were used to estimate the genetic and environmental components of weight, height, and BMI in six age groups. Sex-limitation of genetic and shared environmental effects was observed, especially when puberty begins. Heritability for weight, height, and BMI was low at 0–2 years old (less than 20% for both sexes) but increased over time, accounting for half or more of the variance in the 15–17 year age group for boys. For girls, heritabilities for weight, height and BMI was maintained at approximately 30% after puberty. Common environmental effects on all body measures were high for girls (59–87%) and presented a small peak during puberty. Genetics appear to play an increasingly important role in explaining the variation in weight, height, and BMI from early childhood to late adolescence, particularly in boys. Common environmental factors exert their strongest and most independent influence specifically in the pre-adolescent period and more significantly in girls. These findings emphasize the need to target family and social environmental interventions in early childhood years, especially for females. Further studies about puberty-related genes and social environment are needed to clarify the mechanism of sex differences.

AbstractIt is crucial to understand the genetic mechanisms and biological pathways underlying the relationship between obesity and serum lipid levels. Structural equation models (SEMs) were constructed to calculate heritability for body mass index (BMI), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and the genetic connections between BMI and the four classes of lipids using 1197 pairs of twins from the Chinese National Twin Registry (CNTR). Bivariate genomewide association studies (GWAS) were performed to identify genetic variants associated with BMI and lipids using the records of 457 individuals, and the results were further validated in 289 individuals. The genetic background affecting BMI may differ by gender, and the heritability of males and females was 71% (95% CI [.66, .75]) and 39% (95% CI [.15, .71]) respectively. BMI was positively correlated with TC, TG and LDL-C in phenotypic and genetic correlation, while negatively correlated with HDL-C. There were gender differences in the correlation between BMI and lipids. Bivariate GWAS analysis and validation stage found 7 genes (LOC105378740, LINC02506, CSMD1, MELK, FAM81A, ERAL1 and MIR144) that were possibly related to BMI and lipid levels. The significant biological pathways were the regulation of cholesterol reverse transport and the regulation of high-density lipoprotein particle clearance (p < .001). BMI and blood lipid levels were affected by genetic factors, and they were genetically correlated. There might be gender differences in their genetic correlation. Bivariate GWAS analysis found MIR144 gene and its related biological pathways may influence obesity and lipid levels.

Twins reared apart provide a fascinating experiment to distinguish genetic from environmental influences. However, there is as yet no broad report on distribution of twins reared apart, especially in the Chinese population. In this study, information on 18,295 volunteer twin pairs of all age groups was compiled in nine provinces or cities of China, and questionnaires were used for zygosity determination. It was discovered that twins reared apart from 0 to 10 years of age accounted for 2.2% of all twin interviewees, with the proportion of this 0–10 group separated before 1, 2, and 5 years old, accounting for 65.3%, 76.1%, and 91.3%, respectively. The proportion of twins reared apart is not significantly related to zygosity or gender, but it is related to region and twin age. As the age of twins lowers, the proportion of those reared apart gradually decreases. Twins reared apart will become rarer in the future and therefore should be cherished as a resource.

AbstractAging plays a crucial role in the mechanisms of the impacts of genetic and environmental factors on blood pressure and serum lipids. However, to our knowledge, how the influence of genetic and environmental factors on the correlation between blood pressure and serum lipids changes with age remains to be determined. In this study, data from the Chinese National Twin Registry (CNTR) were used. Resting blood pressure, including systolic and diastolic blood pressure (SBP and DBP), and fasting serum lipids, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglycerides (TGs) were measured in 2378 participants (1189 twin pairs). Univariate and bivariate structural equation models examined the genetic and environmental influences on blood pressure and serum lipids among three age groups. All phenotypes showed moderate to high heritability (0.37–0.59) and moderate unique environmental variance (0.30–0.44). The heritability of all phenotypes showed a decreasing trend with age. Among all phenotypes, SBP and DBP showed a significant monotonic decreasing trend. For phenotype-phenotype pairs, the phenotypic correlation (Rph) of each pair ranged from −0.04 to 0.23, and the additive genetic correlation (Ra) ranged from 0.00 to 0.36. For TC&SBP, TC&DBP, TG&SBP and TGs&DBP, both the Rph and Ra declined with age, and the Ra difference between the young group and the older adult group is statistically significant (p < .05). The unique environmental correlation (Re) of each pair did not follow any pattern with age and remained relatively stable with age. In summary, we observed that the heritability of blood pressure was affected by age. Moreover, blood pressure and serum lipids shared common genetic backgrounds, and age had an impact on the phenotypic correlation and genetic correlations.

The prevalence of overweight and obesity is growing rapidly in many countries. Socioeconomic inequalities might be important for this increase. The aim of this study was to determine associations of body mass index (BMI), overweight and obesity with educational level and marital status in Chinese twins. Participants were adult twins recruited through the Chinese National Twin Registry (CNTR), aged 18 to 79 years, and the sample comprised 10,448 same-sex twin pairs. Current height, weight, educational attainment, and marital status were self-reported. Regression analyses and structural equation models were conducted to evaluate BMI, overweight, and obesity associated with educational level and marital status in both sexes. At an individual level, both educational level and marital status were associated with higher BMI and higher risk of being overweight and obesity in men, while in women the effects of educational level on BMI were in the opposite direction. In within-Monozygotic (MZ) twin-pair analyses, the effects of educational level on BMI disappeared in females. Bivariate structural equation models showed that genetic factors and shared environmental confounded the relationship between education and BMI in females, whereas marital status was associated with BMI on account of significant positive unique environmental correlation apart in both sexes. The present data suggested that marital status and BMI were associated, independent of familiar factors, for both sexes of this study population, while common genetic and shared environmental factors contributed to education-associated disparities in BMI in females.

AbstractThe aim of the present study was to compare the rate of preterm birth (PTB) and growth from birth to 18 years between twins conceived by in vitro fertilization (IVF) and twins conceived by spontaneous conception (SC) in mainland China. The retrospective cohort study included 1164 twins resulting from IVF and 25,654 twins conceived spontaneously, of which 494 from IVF and 6338 from SC were opposite-sex twins. PTB and low birth weight (LBW), and growth, including length/height and weight, were compared between the two groups at five stages: infancy (0 year), toddler period (1–2 years), preschool (3–5 years), primary or elementary school (6–11 years), and adolescence (10–18 years). Few statistically significant differences were found for LBW and growth between the two groups after adjusting for PTB and other confounders. Twins born by IVF faced an increased risk of PTB compared with those born by SC (adjusted odds ratio [aOR] 8.21, 95% confidence interval [CI] [3.19, 21.13], p < .001 in all twins and aOR 10.12, 95% CI [2.32, 44.04], p = .002 in opposite-sex twins). Twins born by IVF experienced a similar growth at five stages (0–18 years old) when compared with those born by SC. PTB risk, however, is significantly higher for twins conceived by IVF than those conceived by SC.

AbstractThe Chinese National Twin Registry (CNTR), initiated in 2001, has now become the largest twin registry in Asia. From 2015 to 2018, the CNTR continued to receive Chinese government funding and had recruited 61,566 twin-pairs by 2019 to study twins discordant for specific exposures such as environmental factors, and twins discordant for disease outcomes or measures of morbidity. Omic data, including genetics, genomics, metabolomics, and proteomics, and gut microbiome will be tested. The integration of omics and digital technologies in public health will advance our understanding of precision public health. This review introduces the updates of the CNTR, including study design, sample size, biobank, zygosity assessment, advances in research and future systems epidemiologic research.

Funder: Government Department of Business ; Funder: Energy and Industrial Strategy (BEIS) ; Funder: Vice-Chancellor Fellowship from the University of Bristol ; Funder: Shanghai Thousand Talents Program ; Funder: Academy of Medical Sciences (AMS) Springboard Award ; Funder: BBSRC Innovation fellowship ; Funder: NIHR Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol ; BACKGROUND: This study was to systematically test whether previously reported risk factors for chronic kidney disease (CKD) are causally related to CKD in European and East Asian ancestries using Mendelian randomization. METHODS: A total of 45 risk factors with genetic data in European ancestry and 17 risk factors in East Asian participants were identified as exposures from PubMed. We defined the CKD by clinical diagnosis or by estimated glomerular filtration rate of 25 kg/m2. CONCLUSIONS: Eight cardiometabolic risk factors showed causal effects on CKD in Europeans and three of them showed causality in East Asians, providing insights into the design of future interventions to reduce the burden of CKD. ; This research has been conducted using the UK Biobank resource under Application Numbers '40135' and '15825'. J.Z. is funded by a Vice-Chancellor Fellowship from the University of Bristol. This research was also funded by the UK Medical Research Council Integrative Epidemiology Unit [MC_UU_00011/1, MC_UU_00011/4 and MC_UU_00011/7]. J.Z. is supported by the Academy of Medical Sciences (AMS) Springboard Award, the Wellcome Trust, the Government Department of Business, Energy and Industrial Strategy (BEIS), the British Heart Foundation and Diabetes UK [SBF006\1117]. This study was funded/supported by the NIHR Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol (G.D.S., T.R.G. and R.E.W.). This study received funding from the UK Medical Research Council [MR/R013942/1]. J.Z., Y.M.Z. and T.R.G are funded by a BBSRC Innovation fellowship. J.Z. is supported by the Shanghai Thousand Talents Program. Y.M.Z. is supported by the National Natural Science Foundation of China [81800636]. H.Z. is supported by the Training Program of the Major Research Plan of the National Natural Science Foundation of China [91642120], a grant from the Science and Technology Project of Beijing, China [D18110700010000] and the University of Michigan Health System–Peking University Health Science Center Joint Institute for Translational and Clinical Research [BMU2017JI007]. N.F. is supported by the National Institutes of Health awards R01-MD012765, R01-DK117445 and R21-HL140385. R.C. is funded by a Wellcome Trust GW4 Clinical Academic Training Fellowship [WT 212557/Z/18/Z]. The Trøndelag Health Study (the HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology), Trøndelag County Council, Central Norway Regional Health Authority and the Norwegian Institute of Public Health. M.C.B. is supported by the UK Medical Research Council (MRC) Skills Development Fellowship [MR/P014054/1]. S.F. is supported by a Wellcome Trust PhD studentship [WT108902/Z/15/Z]. Q.Y. is funded by a China Scholarship Council PhD scholarship [CSC201808060273]. Y.C. was supported by the National Key R&D Program of China [2016YFC0900500, 2016YFC0900501 and 2016YFC0900504]. The China Kadoorie Biobank baseline survey and the first resurvey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust [202922/Z/16/Z, 088158/Z/09/Z and 104085/Z/14/Z]. Japan-Kidney-Biobank was supported by AMED under Grant Number 20km0405210. P.C.H. is supported by Cancer Research UK [grant number: C18281/A19169]. A.K. was supported by DFG KO 3598/5–1. N.F. is supported by NIH awards R01-DK117445, R01-MD012765 and R21-HL140385. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.