DNA methylome profiling in identical twin pairs discordant for body mass index

Ribosomal DNA copy number is associated with body mass in humans and other mammals

Body mass results from a complex interplay between genetics and environment. Previous studies of the genetic contribution to body mass have excluded repetitive regions due to the technical limitations of platforms used for population scale studies. Here we apply genome-wide approaches, identifying an association between adult body mass and the copy number (CN) of 47S-ribosomal DNA (rDNA). rDNA codes for the 18 S, 5.8 S and 28 S ribosomal RNA (rRNA) components of the ribosome. In mammals, there are hundreds of copies of these genes. Inter-individual variation in the rDNA CN has not previously been associated with a mammalian phenotype. Here, we show that rDNA CN variation associates with post-pubertal growth rate in rats and body mass index in adult humans. rDNA CN is not associated with rRNA transcription rates in adult tissues, suggesting the mechanistic link occurs earlier in development. This aligns with the observation that the association emerges by early adulthood.

Co-methylation analyses identify CpGs associated with lipid traits in Chinese discordant monozygotic twins

To control genetic background and early life milieu in genome-wide DNA methylation analysis for blood lipids, we recruited Chinese discordant monozygotic twins to explore the relationships between DNA methylations and total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). 132 monozygotic (MZ) twins were included with discordant lipid levels and completed data. A linear mixed model was conducted in Epigenome-wide association study (EWAS). Generalized estimating equation model was for gene expression analysis. We conducted Weighted correlation network analysis (WGCNA) to build co-methylated interconnected network. Additional Qingdao citizens were recruited for validation. Inference about Causation through Examination of Familial Confounding (ICE FALCON) was used to infer the possible direction of these relationships. A total of 476 top CpGs reached suggestively significant level (P < 10-4), of which, 192 CpGs were significantly associated with TG (FDR < 0.05). They were used to build interconnected network and highlight crucial genes from WGCNA. Finally, four CpGs in GATA4 were validated as risk factors for TC; six CpGs at ITFG2-AS1 were negatively associated with TG; two CpGs in PLXND1 played protective roles in HDL-C. ICE FALCON indicated abnormal TC was regarded as the consequence of DNA methylation in CpGs at GATA4, rather than vice versa. Four CpGs in ITFG2-AS1 were both causes and consequences of modified TG levels. Our results indicated that DNA methylation levels of 12 CpGs in GATA4, ITFG2-AS1, and PLXND1 were relevant to TC, TG, and HDL-C, respectively, which might provide new epigenetic insights into potential clinical treatment of dyslipidemia.

Genetics and Epigenetics in Obesity: What Do We Know so Far?

PURPOSE OF REVIEW

Enormous progress has been made in understanding the genetic architecture of obesity and the correlation of epigenetic marks with obesity and related traits. This review highlights current research and its challenges in genetics and epigenetics of obesity.

RECENT FINDINGS

Recent progress in genetics of polygenic traits, particularly represented by genome-wide association studies, led to the discovery of hundreds of genetic variants associated with obesity, which allows constructing polygenic risk scores (PGS). In addition, epigenome-wide association studies helped identifying novel targets and methylation sites being important in the pathophysiology of obesity and which are essential for the generation of methylation risk scores (MRS). Despite their great potential for predicting the individual risk for obesity, the use of PGS and MRS remains challenging. Future research will likely discover more loci being involved in obesity, which will contribute to better understanding of the complex etiology of human obesity. The ultimate goal from a clinical perspective will be generating highly robust and accurate prediction scores allowing clinicians to predict obesity as well as individual responses to body weight loss-specific life-style interventions.

Epigenome-wide association study in Chinese monozygotic twins identifies DNA methylation loci associated with blood pressure

BACKGROUND

Hypertension is a crucial risk factor for developing cardiovascular disease and reducing life expectancy. We aimed to detect DNA methylation (DNAm) variants potentially related to systolic blood pressure (SBP) and diastolic blood pressure (DBP) by conducting epigenome-wide association studies in 60 and 59 Chinese monozygotic twin pairs, respectively.

METHODS

Genome-wide DNA methylation profiling in whole blood of twins was performed using Reduced Representation Bisulfite Sequencing, yielding 551,447 raw CpGs. Association between DNAm of single CpG and blood pressure was tested by applying generalized estimation equation. Differentially methylated regions (DMRs) were identified by comb-P approach. Inference about Causation through Examination of Familial Confounding was utilized to perform the causal inference. Ontology enrichment analysis was performed using Genomic Regions Enrichment of Annotations Tool. Candidate CpGs were quantified using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data.

RESULTS

The median age of twins was 52 years (95% range 40, 66). For SBP, 31 top CpGs (p < 1 × 10-4) and 8 DMRs were identified, with several DMRs within NFATC1, CADM2, IRX1, COL5A1, and LRAT. For DBP, 43 top CpGs (p < 1 × 10-4) and 12 DMRs were identified, with several DMRs within WNT3A, CNOT10, and DAB2IP. Important pathways, such as Notch signaling pathway, p53 pathway by glucose deprivation, and Wnt signaling pathway, were significantly enriched for SBP and DBP. Causal inference analysis suggested that DNAm at top CpGs within NDE1, MYH11, SRRM1P2, and SMPD4 influenced SBP, while SBP influenced DNAm at CpGs within TNK2. DNAm at top CpGs within WNT3A influenced DBP, while DBP influenced DNAm at CpGs within GNA14. Three CpGs mapped to WNT3A and one CpG mapped to COL5A1 were validated in a community population, with a hypermethylated and hypomethylated direction in hypertension cases, respectively. Gene expression analysis by WGCNA further identified some common genes and enrichment terms.

CONCLUSION

We detect many DNAm variants that may be associated with blood pressure in whole blood, particularly the loci within WNT3A and COL5A1. Our findings provide new clues to the epigenetic modification underlying hypertension pathogenesis.

DNA methylation and waist-to-hip ratio: an epigenome-wide association study in Chinese monozygotic twins

PURPOSE

Epigenetic signatures such as DNA methylation may be associated with specific obesity traits. We performed an epigenome-wide association study (EWAS) by combining with the waist-to-hip ratio (WHR)-discordant monozygotic (MZ) twin design in an attempt to identify genetically independent DNA methylation marks associated with abdominal obesity in Northern Han Chinese and to determine the causation underlying.

METHODS

A total of 60 WHR discordant MZ twin pairs were selected from the Qingdao Twin Registry, China. Generalized estimated equation (GEE) model was used to regress the methylation level of CpG sites on WHR. The Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON) was used to assess the temporal relationship between methylation and WHR. Gene expression analysis was conducted to validate the results of differentially methylated analyses.

RESULTS

EWAS identified 92 CpG sites with the level of P < 10^- 4 which were annotated to 32 genes, especially CADPS2, TUSC5, ZCCHC14, CORO7, COL23A1, CACNA1C, CYP26B1, and BCAT1. ICE FALCON showed significant causality between DNA methylation of several genes and WHR (P < 0.05). In region-based analysis, 14 differentially methylated regions (DMRs) located at 15 genes (slk-corrected P < 0.05) were detected. The gene expression analysis identified the significant correlation between expression levels of 5 differentially methylated genes and WHR (P < 0.05).

CONCLUSIONS

Our study identifies the associations between specific epigenetic variations and WHR in Northern Han Chinese. These DNA methylation signatures may have value as diagnostic biomarkers and provide novel insights into the molecular mechanisms of pathogenesis.

Recent progress in epigenetics of obesity

Nowadays, obesity is one of the largest public health problems worldwide. In the last few decades, there has been a marked increase in the obesity epidemic and its related comorbidities. Worldwide, more than 2.2 billion people (33%) are affected by overweight or obesity (712 million, 10%) and its associated metabolic complications. Although a high heritability of obesity has been estimated, the genetic variants conducted from genetic association studies only partially explain the variation of body mass index. This has led to a growing interest in understanding the potential role of epigenetics as a key regulator of gene-environment interactions on the development of obesity and its associated complications. Rapid advances in epigenetic research methods and reduced costs of epigenome-wide association studies have led to a great expansion of population-based studies. The field of epigenetics and metabolic diseases such as obesity has advanced rapidly in a short period of time. The main epigenetic mechanisms include DNA methylation, histone modifications, microRNA (miRNA)-mediated regulation and so on. DNA methylation is the most investigated epigenetic mechanism. Preliminary evidence from animal and human studies supports the effect of epigenetics on obesity. Studies of epigenome-wide association studies and genome-wide histone modifications from different biological specimens such as blood samples (newborn, children, adolescent, youth, woman, man, twin, race, and meta-analysis), adipose tissues, skeletal muscle cells, placenta, and saliva have reported the differential expression status of multiple genes before and after obesity interventions and have identified multiple candidate genes and biological markers. These findings may improve the understanding of the complex etiology of obesity and its related comorbidities, and help to predict an individual's risk of obesity at a young age and open possibilities for introducing targeted prevention and treatment strategies.

Genome-wide DNA methylation analysis of middle-aged and elderly monozygotic twins with age-related hearing loss in Qingdao, China

OBJECTIVE

To explore the differences in DNA methylation associated with age-related hearing loss in a study of 57 twin pairs from China.

DESIGN

Monozygotic twins were identified through the Qingdao Twin Registration system. The median age of participants was >50 years. Their hearing thresholds were measured using a multilevel pure-tone audiometry assessment. The pure-tone audiometry was calculated at low frequencies (0.5, 1.0, and 2.0 kHz), speech frequencies (0.5, 1.0, 2.0, and 4.0kHz), and high frequencies (4.0 and 8 kHz). The CpG sites were tested using a linear mixed-effects model, and the function of the cis-regulatory regions and ontological enrichments were predicted using the online Genomic Regions Enrichment of Annotations Tool. The differentially methylated regions were identified using a comb-p python library approach.

RESULTS

In each of the PTA categories (low-, speech-, high-frequency), age-related hearing loss was detected in 25.9%, 19.3%, and 52.8% of participants. In the low-, speech- and high-frequency categories we identified 18, 42, and 12 individual CpG sites and 6, 11, and 6 differentially methylated regions. The CpG site located near DUSP4 had the strongest association with low- and speech-frequency, while the strongest association with high-frequency was near C21orf58. We identified associations of ALG10 with high-frequency hearing, C3 and LCK with low- and speech-frequency hearing, and GBX2 with low-frequency hearing. Top pathways that may be related to hearing, such as the Notch signaling pathway, were also identified.

CONCLUSION

Our study is the first of its kind to identify these genes and their associated with DNA methylation may play essential roles in the hearing process. The results of our epigenome-wide association study on twins clarify the complex mechanisms underlying age-related hearing loss.

Genome-wide DNA methylation analysis of pulmonary function in middle and old-aged Chinese monozygotic twins

BACKGROUND

Previous studies have determined the epigenetic association between DNA methylation and pulmonary function among various ethnics, whereas this association is largely unknown in Chinese adults. Thus, we aimed to explore epigenetic relationships between genome-wide DNA methylation levels and pulmonary function among middle-aged Chinese monozygotic twins.

METHODS

The monozygotic twin sample was drawn from the Qingdao Twin Registry. Pulmonary function was measured by three parameters including forced expiratory volume the first second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio. Linear mixed effect model was used to regress the methylation level of CpG sites on pulmonary function. After that, we applied Genomic Regions Enrichment of Annotations Tool (GREAT) to predict the genomic regions enrichment, and used comb-p python library to detect differentially methylated regions (DMRs). Gene expression analysis was conducted to validate the results of differentially methylated analyses.

RESULTS

We identified 112 CpG sites with the level of P < 1 × 10-4 which were annotated to 40 genes. We identified 12 common enriched pathways of three pulmonary function parameters. We detected 39 DMRs located at 23 genes, of which PRDM1 was related to decreased pulmonary function, and MPL, LTB4R2, and EPHB3 were related to increased pulmonary function. The gene expression analyses validated DIP2C, ASB2, SLC6A5, and GAS6 related to decreased pulmonary function.

CONCLUSION

Our DNA methylation sequencing analysis on identical twins provides new references for the epigenetic regulation on pulmonary function. Several CpG sites, genes, biological pathways and DMRs are considered as possible crucial to pulmonary function.

Examining the association between adiposity and DNA methylation: A systematic review and meta-analysis

Obesity is associated with widespread differential DNA methylation (DNAm) patterns, though there have been limited overlap in the obesity-associated cytosine-guanine nucleotide pair (CpG) sites that have been identified in the literature. We systematically searched four databases for studies published until January 2020. Eligible studies included cross-sectional, longitudinal, or intervention studies examining adiposity and genome-wide DNAm in non-pregnant adults aged 18-75 in all tissue types. Study design and results were extracted in the descriptive review. Blood-based DNAm results in body mass index (BMI) and waist circumference (WC) were meta-analyzed using weighted sum of Z-score meta-analysis. Of the 10,548 studies identified, 46 studies were included in the systematic review with 18 and nine studies included in the meta-analysis of BMI and WC, respectively. In the blood, 77 and four CpG sites were significant in three or more studies of BMI and WC, respectively. Using a genome-wide threshold for significance, 52 blood-based CpG sites were significantly associated with BMI. These sites have previously been associated with many obesity-related diseases including type 2 diabetes, cardiovascular disease, Crohn's disease, and depression. Our study shows that DNAm at 52 CpG sites represent potential mediators of obesity-associated chronic diseases and may be novel intervention or therapeutic targets to protect against obesity-associated chronic diseases.

Genome-wide DNA methylation and gene expression analyses in monozygotic twins identify potential biomarkers of depression

Depression is currently the leading cause of disability around the world. We conducted an epigenome-wide association study (EWAS) in a sample of 58 depression score-discordant monozygotic twin pairs, aiming to detect specific epigenetic variants potentially related to depression and further integrate with gene expression profile data. Association between the methylation level of each CpG site and depression score was tested by applying a linear mixed effect model. Weighted gene co-expression network analysis (WGCNA) was performed for gene expression data. The association of DNA methylation levels of 66 CpG sites with depression score reached the level of P < 1 × 10^-4. These top CpG sites were located at 34 genes, especially PTPRN2, HES5, GATA2, PRDM7, and KCNIP1. Many ontology enrichments were highlighted, including Notch signaling pathway, Huntington disease, p53 pathway by glucose deprivation, hedgehog signaling pathway, DNA binding, and nucleic acid metabolic process. We detected 19 differentially methylated regions (DMRs), some of which were located at GRIK2, DGKA, and NIPA2. While integrating with gene expression data, HELZ2, PTPRN2, GATA2, and ZNF624 were differentially expressed. In WGCNA, one specific module was positively correlated with depression score (r = 0.62, P = 0.002). Some common genes (including BMP2, PRDM7, KCNIP1, and GRIK2) and enrichment terms (including complement and coagulation cascades pathway, DNA binding, neuron fate specification, glial cell differentiation, and thyroid gland development) were both identified in methylation analysis and WGCNA. Our study identifies specific epigenetic variations which are significantly involved in regions, functional genes, biological function, and pathways that mediate depression disorder.

Genetics of Obesity: What We Have Learned Over Decades of Research

There is a genetic component to human obesity that accounts for 40% to 50% of the variability in body weight status but that is lower among normal weight individuals (about 30%) and substantially higher in the subpopulation of individuals with obesity and severe obesity (about 60%-80%). The appreciation that heritability varies across classes of BMI represents an important advance. After controlling for BMI, ectopic fat and fat distribution traits are characterized by heritability levels ranging from 30% to 55%. Defects in at least 15 genes are the cause of monogenic obesity cases, resulting mostly from deficiencies in the leptin-melanocortin signaling pathway. Approximately two-thirds of the BMI heritability can be imputed to common DNA variants, whereas low-frequency and rare variants explain the remaining fraction. Diminishing allele effect size is observed as the number of obesity-associated variants expands, with most BMI-increasing or -decreasing alleles contributing only a few grams or less to body weight. Obesity-promoting alleles exert minimal effects in normal weight individuals but have larger effects in individuals with a proneness to obesity, suggesting a higher penetrance; however, it is not known whether these larger effect sizes precede obesity or are caused by an obese state. The obesity genetic risk is conditioned by thousands of DNA variants that make genetically based obesity prevention and treatment a major challenge.

Genome-wide DNA methylation analysis of cognitive function in middle and old-aged Chinese monozygotic twins

Cognitive ability plays an important role in mental and physical well-beings in the increasingly ageing populations. Here, based on a sample of 30 cognitive function-discordant monozygotic twin pairs, we aimed to detect specific epigenetic variants potentially related to cognitive function by conducting an epigenome-wide association study (EWAS). Association between methylation level of single CpG site with cognitive function score was tested by linear mixed effect model. Functions of cis-regulatory regions and ontology enrichments were predicted by Genomic Regions Enrichment of Annotations Tool (GREAT). Differentially methylated regions (DMRs) were detected by comb-p python library. A list of 28 CpG sites were identified to reach the level of P < 1 × 10-4, and the strongest association (cor = 0.138, P = 2.549 × 10-6) was detected for DNA CpG site (Chr17: 40,700,490 bp) located at HSD17B1P1. The identified 14,065 genomic CpG sites (P < 0.05) were mapped to 2646 genes, especially HSD17B1P1, CUL4A, INTS8, GFI1B, ZNF467, CDH15, and PSMA1. GREAT ontology enrichments mainly highlighted nicotine pharmacodynamics pathway, GABA-B receptor II/nicotinic acetylcholine receptor/hedgehog/endothelin/Wnt signaling pathways, Parkinson disease, Huntington disease, glycolysis, neuronal system, and toll-like receptor binding. We detected 15 DMRs located at/near 16 genes, especially LINC01551, LINC02282, and FAM32A. And 32 cognitive function-associated differentially methylated genes could be replicated, such as SHANK2, ABCA2, PRDM16, NCOR2, and INPP5A. Our EWAS in monozygotic twins identify specific epigenetic variations which are significantly involved in functional genes, biological function and pathways that mediate cognitive function. The findings provide clues to further identify new diagnostic biomarkers and therapeutic targets for cognitive dysfunction.

Twin Registries Moving Forward and Meeting the Future: A Review

Twin registries have developed as a valuable resource for the study of many aspects of disease and society over the years in many different countries. A number of these registries include large numbers of twins with data collected at varying information levels for twin cohorts over the past several decades. More recent expansion of twin datasets has allowed for the collection of genetic data, together with many other levels of 'omic' information along with multiple demographic, physiological, health outcomes and other measures typically used in epidemiologic research. Other twin data sources outside these registries reflect research interests in particular aspects of disease or specific phenotypic assessment. Twin registries have the potential to play a key role in many aspects of the artificial intelligence/machine learning-driven projects of the future and will continue to keep adapting to the changing research landscape.