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Objective

To use a unique obesity-discordant sib-pair study design to combine differential expression analysis, expression quantitative trait loci (eQTLs) mapping, and a co-expression regulatory network approach in subcutaneous human adipose tissue to identify genes relevant to the obese state.

Study design

Genome-wide transcript expression in subcutaneous human adipose tissue was measured using Affymetrix U133+2.0 microarrays and genomewide genotyping data was obtained using an Applied Biosystems SNPlex linkage panel.

Subjects

154 Swedish families ascertained through an obese proband (Body Mass Index >30kg/m2) with a discordant sibling (BMI>10kg/m2 less than proband).

Results

Approximately one-third of the transcripts were differentially expressed between lean and obese siblings. The cellular adhesion molecules (CAMs) KEGG grouping contained the largest number of differentially expressed genes under cis-acting genetic control. By using a novel approach to contrast CAMs co-expression networks between lean and obese siblings, a subset of differentially regulated genes was identified, with the previously GWAS obesity-associated NEGR1 as a central hub. Independent analysis using mouse data demonstrated that this finding for NEGR1 is conserved across species.

Conclusion

Our data suggests that, in addition to its reported role in the brain, NEGR1 is also expressed in subcutaneous adipose tissue and acts as a central “hub” in an obesity-related transcript network.

Human intelligence, as measured by intelligence quotient (IQ) tests, demonstrates one of the highest heritabilities among human quantitative traits. Nevertheless, studies to identify quantitative trait loci responsible for intelligence face challenges because of the small effect sizes of individual genes. Phenotypically discordant monozygotic (MZ) twins provide a feasible way to minimize the effects of irrelevant genetic and environmental factors, and should yield more interpretable results by finding epigenetic or gene expression differences between twins. Here we conducted array-based genome-wide DNA methylation and gene expression analyses using 17 pairs of healthy MZ twins discordant intelligently. ARHGAP18, related to Rho GTPase, was identified in pair-wise methylation status analysis and validated via direct bisulfite sequencing and quantitative RT-PCR. To perform expression profile analysis, gene set enrichment analysis (GSEA) between the groups of twins with higher IQ and their co-twins revealed up-regulated expression of several ribosome-related genes and DNA replication-related genes in the group with higher IQ. To focus more on individual pairs, we conducted pair-wise GSEA and leading edge analysis, which indicated up-regulated expression of several ion channel-related genes in twins with lower IQ. Our findings implied that these groups of genes may be related to IQ and should shed light on the mechanism underlying human intelligence.

Background

The acquired component of complex traits is difficult to dissect in humans. Obesity represents such a trait, in which the metabolic and molecular consequences emerge from complex interactions of genes and environment. With the substantial morbidity associated with obesity, a deeper understanding of the concurrent metabolic changes is of considerable importance. The goal of this study was to investigate this important acquired component and expose obesity-induced changes in biological pathways in an identical genetic background.

Methods and Findings

We used a special study design of “clonal controls,” rare monozygotic twins discordant for obesity identified through a national registry of 2,453 young, healthy twin pairs. A total of 14 pairs were studied (eight male, six female; white), with a mean ± standard deviation (SD) age 25.8 ± 1.4 y and a body mass index (BMI) difference 5.2 ± 1.8 kg/m2. Sequence analyses of mitochondrial DNA (mtDNA) in subcutaneous fat and peripheral leukocytes revealed no aberrant heteroplasmy between the co-twins. However, mtDNA copy number was reduced by 47% in the obese co-twin's fat. In addition, novel pathway analyses of the adipose tissue transcription profiles exposed significant down-regulation of mitochondrial branched-chain amino acid (BCAA) catabolism (p < 0.0001). In line with this finding, serum levels of insulin secretion-enhancing BCAAs were increased in obese male co-twins (9% increase, p = 0.025). Lending clinical relevance to the findings, in both sexes the observed aberrations in mitochondrial amino acid metabolism pathways in fat correlated closely with liver fat accumulation, insulin resistance, and hyperinsulinemia, early aberrations of acquired obesity in these healthy young adults.

Conclusions

Our findings emphasize a substantial role of mitochondrial energy- and amino acid metabolism in obesity and development of insulin resistance.

Leena Peltonen and colleagues uncover the metabolic changes that result from obesity through an analysis of genetically identical twin pairs in which one was obese and the other was not.

Editors' Summary

Background.

Around the world, the proportion of people who are obese (people with an unhealthy amount of body fat) is increasing. In the US, for example, 1 adult in 7 was obese in the mid 1970s. That is, their body mass index (BMI)—their weight in kilograms divided by their height in meters squared—was more than 30. Nowadays, 1 US adult in 3 has a BMI this high and, by 2025, it is predicted that 1 in 2 will be obese. This obesity epidemic is being driven by lifestyle changes that encourage the over-consumption of energy-rich foods and discourage regular physical activity. The resultant energy imbalance leads to weight gain (the excess energy is stored as body fat or adipose tissue) and also triggers numerous metabolic changes, alterations in the chemical processes that convert food into the energy and various substances needed to support life. These obesity-related metabolic changes increase a person's risk of developing adverse health conditions such as diabetes, a condition in which dangerously high levels of sugar from food accumulate in the blood.

Why Was This Study Done?

The changes in human fat in obesity have not been completely understood, although the abnormal metabolism of adipose tissue is increasingly seen as playing a critical part in excessive weight gain. It has been very difficult to decipher which molecular and metabolic changes associated with obesity are the result of becoming obese, and which might contribute towards the acquisition of obesity in humans in the first place. To discover more about the influence of environment on obesity-induced metabolic changes, the researchers in this study have investigated these changes in pairs of genetically identical twins.

What Did the Researchers Do and Find?

The researchers recruited 14 pairs of genetically identical Finnish twins born between 1975 and 1979 who were “obesity discordant”—that is, one twin of each pair had a BMI of about 25 (not obese); the other had a BMI of about 30 (obese). The researchers took fat and blood samples from each twin, determined the insulin sensitivity of each, and measured the body composition and various fat stores of each. They found that the obese twins had more subcutaneous, intra-abdominal, and liver fat and were less insulin sensitive than the non-obese twins. Insulin sensitivity correlated with the amount of liver fat. Analysis of gene expression in the fat samples showed that 19 gene pathways (mainly inflammatory pathways) were expressed more strongly (up-regulated) in the obese twins than the non-obese twins, whereas seven pathways were down-regulated. The most highly down-regulated pathway was a mitochondrial pathway involved in amino acid breakdown, but mitochondrial energy metabolism pathways were also down-regulated. Finally, mitochondrial DNA copy number in fat was reduced in the obese twins by nearly half, a novel observation that could partly account for the obesity-induced metabolic defects of these individuals.

What Do These Findings Mean?

These and other findings identify several pathways that are involved in the development of obesity and insulin resistance. In particular, they suggest that changes in mitochondrial energy production pathways and in mitochondrial amino acid metabolism pathways could play important roles in the development of obesity and of insulin resistance and in the accumulation of liver fat even in young obese people. The study design involving identical twins has here produced some evidence for aberrations in molecules critical for acquired obesity. The results suggest that careful management of obesity by lifestyle changes has the potential to correct the obesity-related metabolic changes in fat that would otherwise lead to diabetes and other adverse health conditions in obese individuals. In addition, they suggest that the development of therapies designed to correct mitochondrial metabolism might help to reduce the illnesses associated with obesity.

Additional Information.

Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050051.

The MedlinePlus encyclopedia has pages on obesity and diabetes (in English and Spanish)

The US Centers for Disease Control and Prevention provides information on all aspects of obesity (in English and Spanish)

The UK National Health Service's health Web site (NHS Direct) provides information about obesity

The International Obesity Taskforce provides information about preventing obesity and on diabetes and obesity

The UK Foods Standards Agency and the United States Department of Agriculture provide online tools and useful advice about healthy eating for adults and children

Information is available for patients and carers from the US National Diabetes Information Clearinghouse on diabetes, including information on insulin resistance

Large-scale genome-wide association studies (GWAS) have identified many loci associated with body mass index (BMI), but few studies focused on obesity as a binary trait. Here we report the results of a GWAS and candidate SNP genotyping study of obesity, including extremely obese cases and never overweight controls as well as families segregating extreme obesity and thinness. We first performed a GWAS on 520 cases (BMI>35 kg/m2) and 540 control subjects (BMI<25 kg/m2), on measures of obesity and obesity-related traits. We subsequently followed up obesity-associated signals by genotyping the top ∼500 SNPs from GWAS in the combined sample of cases, controls and family members totaling 2,256 individuals. For the binary trait of obesity, we found 16 genome-wide significant signals within the FTO gene (strongest signal at rs17817449, P = 2.5×10−12). We next examined obesity-related quantitative traits (such as total body weight, waist circumference and waist to hip ratio), and detected genome-wide significant signals between waist to hip ratio and NRXN3 (rs11624704, P = 2.67×10−9), previously associated with body weight and fat distribution. Our study demonstrated how a relatively small sample ascertained through extreme phenotypes can detect genuine associations in a GWAS.

Objective:

Epigenetic mechanisms are increasingly being recognized as an important factor for obesity. The serotonin transporter gene (SLC6A4) has a critical role in regulating food intake, body weight and energy balance. This study examines the potential association between SLC6A4 promoter methylation and obesity measures in a monozygotic (MZ) twin sample.

Methods:

We studied 84 MZ twin pairs drawn from the Vietnam Era Twin Registry. Obesity measures include body mass index (BMI), body weight, waist circumference (WC) and waist-hip ratio (WHR). The SLC6A4 promoter methylation profile in peripheral blood leukocytes was quantified by bisulfite pyrosequencing. The association between methylation variation and obesity parameters was examined by mixed-model regression and matched pair analysis, adjusting for age, smoking, alcohol consumption, physical activity and total daily energy intake. Multiple testing was controlled using the adjusted false discovery rate (q-value).

Results:

Mean methylation level was positively correlated with BMI (r=0.29; P=0.0002), body weight (r=0.31; P<0.0001) and WC (r=0.20; P=0.009), but not WHR. Intra-pair differences in mean methylation were significantly correlated with intra-pair differences in BMI, body weight and WC, but not WHR. On average, a 1% increase in mean methylation was associated with 0.33 kg m−2 increase in BMI (95% CI: 0.02–0.65; P=0.03), 1.16 kg increase in body weight (95% CI, 0.16–2.16; P=0.02) and 0.78 cm increase in WC (95% CI, 0.05–1.50; P=0.03) after controlling for potential confounders.

Conclusions:

SLC6A4 promoter hypermethylation is significantly associated with an increased prevalence of obesity within a MZ twin study.

Osteoporosis is a complex disorder and commonly leads to fractures in elderly persons. Genome-wide association studies (GWAS) have become an unbiased approach to identify variations in the genome that potentially affect health. However, the genetic variants identified so far only explain a small proportion of the heritability for complex traits. Due to the modest genetic effect size and inadequate power, true association signals may not be revealed based on a stringent genome-wide significance threshold. Here, we take advantage of SNP and transcript arrays and integrate GWAS and expression signature profiling relevant to the skeletal system in cellular and animal models to prioritize the discovery of novel candidate genes for osteoporosis-related traits, including bone mineral density (BMD) at the lumbar spine (LS) and femoral neck (FN), as well as geometric indices of the hip (femoral neck-shaft angle, NSA; femoral neck length, NL; and narrow-neck width, NW). A two-stage meta-analysis of GWAS from 7,633 Caucasian women and 3,657 men, revealed three novel loci associated with osteoporosis-related traits, including chromosome 1p13.2 (RAP1A, p = 3.6×10−8), 2q11.2 (TBC1D8), and 18q11.2 (OSBPL1A), and confirmed a previously reported region near TNFRSF11B/OPG gene. We also prioritized 16 suggestive genome-wide significant candidate genes based on their potential involvement in skeletal metabolism. Among them, 3 candidate genes were associated with BMD in women. Notably, 2 out of these 3 genes (GPR177, p = 2.6×10−13; SOX6, p = 6.4×10−10) associated with BMD in women have been successfully replicated in a large-scale meta-analysis of BMD, but none of the non-prioritized candidates (associated with BMD) did. Our results support the concept of our prioritization strategy. In the absence of direct biological support for identified genes, we highlighted the efficiency of subsequent functional characterization using publicly available expression profiling relevant to the skeletal system in cellular or whole animal models to prioritize candidate genes for further functional validation.

Author Summary

BMD and hip geometry are two major predictors of osteoporotic fractures, the most severe consequence of osteoporosis in elderly persons. We performed sex-specific genome-wide association studies (GWAS) for BMD at the lumbar spine and femor neck skeletal sites as well as hip geometric indices (NSA, NL, and NW) in the Framingham Osteoporosis Study and then replicated the top findings in two independent studies. Three novel loci were significant: in women, including chromosome 1p13.2 (RAP1A) for NW; in men, 2q11.2 (TBC1D8) for NSA and 18q11.2 (OSBPL1A) for NW. We confirmed a previously reported region on 8q24.12 (TNFRSF11B/OPG) for lumbar spine BMD in women. In addition, we integrated GWAS signals with eQTL in several tissues and publicly available expression signature profiling in cellular and whole-animal models, and prioritized 16 candidate genes/loci based on their potential involvement in skeletal metabolism. Among three prioritized loci (GPR177, SOX6, and CASR genes) associated with BMD in women, GPR177 and SOX6 have been successfully replicated later in a large-scale meta-analysis, but none of the non-prioritized candidates (associated with BMD) did. Our results support the concept of using expression profiling to support the candidacy of suggestive GWAS signals that may contain important genes of interest.

Background

Monozygotic twin pairs who are genetically identical would be potentially useful in gene expression study for specific traits as cases and controls, because there would be much less gene expression variation within pairs compared to two unrelated individuals. However the twin pair has to be discordant for the particular trait or phenotype excluding those resulting from known confounders. Such discordant monozygotic twin pairs are rare and very few studies have explored the potential usefulness of this approach.

Results

We studied genome-wide gene expression in primary osteoblast-like culture from marrow aspirates obtained from three pairs of monozygotic twins. We used the latest Affymetrix microchip contains probe sets for more than 20,000 genes. Two pairs were discordant for bone mineral density at the hip by more than one standard deviation, and the third pair was unrelated concordant and used as control. Only 1.5% on average of genes showed variation in expression within pairs as compared to 5% between pairs or over 15% from the literature. Importantly we identified several groups of genes showing variations within the discordant pairs and not within the concordant pair such as chondroitin beta 1,4 N-acetylgalactosaminyltransferase, inhibin beta A, interleukin 1 beta and colony stimulating factor 1 macrophage. These genes are known to have potential roles in bone physiology relating to bone density, osteoporosis and osteoarthritis.

Conclusion

Using the example of osteoblast-like cells in our monozygotic discordant twins for osteoporosis, we identified genes showing differential expression. Although without further experiment, we cannot confirm or conclude these are genes definitely related to bone physiology, we believe we have shown the potential and cost-effectiveness of further gene expression studies in discordant monozygotic twin pairs. A replication study for confirmation is essential.

Background

Genome-wide association studies (GWAS) have recently identified several new genetic variants associated with obesity. The majority of the variants are within introns or between genes, suggesting they affect gene expression, although it is not clear which of the nearby genes they affect. Understanding the regulation of these genes will be key to determining the role of these variants in the development of obesity and will provide support for a role of these genes in the development of obesity.

Methods

We examined the expression of 19 GWAS obesity genes in the brain and specifically the hypothalamus, adipose tissue and liver of mice by real-time quantitative PCR. To determine whether these genes are nutritionally regulated, as may be expected for genes affecting obesity, we compared tissues from fasting and non-fasting animals and tissues from mice consuming a high fat high sucrose diet in comparison to standard rodent chow.

Results

We found complex, tissue-dependent patterns of nutritional regulation of most of these genes. For example, Bat2 expression was increased ~10-fold in the brain of fed mice but was lower or unchanged in the hypothalamus and adipose tissue. Kctd15 expression was upregulated in the hypothalamus, brain and adipose tissue of fed mice and downregulated by high fat feeding in liver, adipose tissue and the hypothalamus but not the remainder of the brain. Sh2b1 expression in the brain and Faim2 expression in adipose tissue were specifically increased >20-fold in fed mice. Tmem18 expression in adipose tissue but not the brain was reduced 80% by high fat feeding. Few changes in the expression of these genes were observed in liver.

Conclusions

These data show nutritional regulation of nearly all these GWAS obesity genes, particularly in the brain and adipose tissue, and provide support for their role in the development of obesity. The complex patterns of nutritional and tissue-dependent regulation also highlight the difficulty that may be encountered in determining how the GWAS genetic variants affect gene expression and consequent obesity risk in humans where access to tissues is constrained.

The regulation of gene expression plays a pivotal role in complex phenotypes, and epigenetic mechanisms such as DNA methylation are essential to this process. The availability of next-generation sequencing technologies allows us to study epigenetic variation at an unprecedented level of resolution. Even so, our understanding of the underlying sources of epigenetic variability remains limited. Twin studies have played an essential role in estimating phenotypic heritability, and these now offer an opportunity to study epigenetic variation as a dynamic quantitative trait. High monozygotic twin discordance rates for common diseases suggest that unexplained environmental or epigenetic factors could be involved. Recent genome-wide epigenetic studies in disease-discordant monozygotic twins emphasize the power of this design to successfully identify epigenetic changes associated with complex traits. We describe how large-scale epigenetic studies of twins can improve our understanding of how genetic, environmental and stochastic factors impact upon epigenetics, and how such studies can provide a comprehensive understanding of how epigenetic variation affects complex traits.

Background

Causative gene mutations have been identified in about 2% of those with amyotrophic lateral sclerosis (ALS), often, but not always, when there is a strong family history. There is an assumption that there is a genetic component to all ALS, but genome-wide association studies have yet to produce a robustly replicated result. A definitive estimate of ALS heritability is therefore required to determine whether ongoing efforts to find susceptibility genes are worth while.

Methods

The authors performed two twin studies, one population- and one clinic-based. The authors used structural equation modelling to perform a meta-analysis of data from these studies and an existing twin study to estimate ALS heritability, and identified 171 twin pairs in which at least one twin had ALS.

Results and discussion

Five monozygotic twin pairs were concordant-affected, and 44 discordant-affected. No dizygotic twin pairs were concordant-affected, and 122 discordant-affected. The heritability of sporadic ALS was estimated as 0.61 (0.38 to 0.78) with the unshared environmental component 0.39 (0.22 to 0.62). ALS has a high heritability, and efforts to find causative genes should continue.

Objectives

BMI is highly heritable. Yet, trends in obesity highlight environmental influences on body weight. Monozygotic (MZ) twins discordant for overweight offer a unique opportunity to examine these factors.

Methods

MZ male (n = 8 pairs) and female twins (n = 10 pairs) discordant for overweight (defined as the BMI of one twin being at least 24.5, and the BMI of his/her co-twin being below 24.5 and at least three points lower) were identified from the Mid-Atlantic Twin Registry. Variables were assessed via self-report questionnaires.

Results

One overweight and two non-overweight females met criteria for bulimia nervosa. Rates of dieting and binge eating were high among all males and females. Hunger scores were higher among non-overweight females; disinhibition scores were higher among overweight males. Only one non-overweight and three overweight males smoked; 90% of non-overweight and 40% of overweight females smoked.

Conclusions

Assessing tobacco use and eating disorders may be important when sampling on the basis of family members who are discordant for BMI. Finally, results suggest possibilities for interventions in individuals at-risk for overweight.

Background

Recent genome-wide association (GWA) analyses have identified common single nucleotide polymorphisms (SNPs) that are associated with obesity. However, the reported genetic variation in obesity explains only a minor fraction of the total genetic variation expected to be present in the population. Thus many genetic variants controlling obesity remain to be identified. The aim of this study was to use GWA followed by multiple stepwise validations to identify additional genes associated with obesity.

Methods

We performed a GWA analysis in 164 morbidly obese subjects (BMI:body mass index > 40 kg/m2) and 163 Swedish subjects (> 45 years) who had always been lean. The 700 SNPs displaying the strongest association with obesity in the GWA were analyzed in a second cohort comprising 460 morbidly obese subjects and 247 consistently lean Swedish adults. 23 SNPs remained significantly associated with obesity (nominal P< 0.05) and were in a step-wise manner followed up in five additional cohorts from Sweden, France, and Germany together comprising 4214 obese and 5417 lean or population-based control individuals. Three samples, n = 4133, were used to investigate the population-based associations with BMI. Gene expression in abdominal subcutaneous adipose tissue in relation to obesity was investigated for14 adults.

Results

Potassium channel, calcium activated, large conductance, subfamily M, alpha member (KCNMA1) rs2116830*G and BDNF rs988712*G were associated with obesity in five of six investigated case-control cohorts. In meta-analysis of 4838 obese and 5827 control subjects we obtained genome-wide significant allelic association with obesity for KCNMA1 rs2116830*G with P = 2.82 × 10-10 and an odds ratio (OR) based on cases vs controls of 1.26 [95% C.I. 1.12-1.41] and for BDNF rs988712*G with P = 5.2 × 10-17and an OR of 1.36 [95% C.I. 1.20-1.55]. KCNMA1 rs2116830*G was not associated with BMI in the population-based samples. Adipose tissue (P = 0.0001) and fat cell (P = 0.04) expression of KCNMA1 was increased in obesity.

Conclusions

We have identified KCNMA1 as a new susceptibility locus for obesity, and confirmed the association of the BDNF locus at the genome-wide significant level.

Recent genome-wide association studies (GWAS) have identified a number of novel genetic associations with complex human diseases. In spite of these successes, results from GWAS generally explain only a small proportion of disease heritability, an observation termed the ‘missing heritability problem’. Several sources for the missing heritability have been proposed, including the contribution of many common variants with small individual effect sizes, which cannot be reliably found using the standard GWAS approach. The goal of our study was to explore a complimentary approach, which combines GWAS results with functional data in order to identify novel genetic associations with small effect sizes. To do so, we conducted a GWAS for lymphocyte count, a physiologic quantitative trait associated with asthma, in 462 Hutterites. In parallel, we performed a genome-wide gene expression study in lymphoblastoid cell lines from 96 Hutterites. We found significant support for genetic associations using the GWAS data when we considered variants near the 193 genes whose expression levels across individuals were most correlated with lymphocyte counts. Interestingly, these variants are also enriched with signatures of an association with asthma susceptibility, an observation we were able to replicate. The associated loci include genes previously implicated in asthma susceptibility as well as novel candidate genes enriched for functions related to T cell receptor signaling and adenosine triphosphate synthesis. Our results, therefore, establish a new set of asthma susceptibility candidate genes. More generally, our observations support the notion that many loci of small effects influence variation in lymphocyte count and asthma susceptibility.

Phenotypically discordant monozygotic twins offer the possibility of gene discovery through delineation of molecular abnormalities in one member of the twin pair. One proposed mechanism of discordance is postzygotically occurring genomic alterations resulting from mitotic recombination and other somatic changes. Detection of altered genomic fragments can reveal candidate gene loci that can be verified through additional analyses. We investigated this hypothesis using array comparative genomic hybridization; the 50K and 250K Affymetrix GeneChip® SNP arrays and an Illumina custom array consisting of 1,536 SNPs, to scan for genomic alterations in a sample of monozygotic twin pairs with discordant cleft lip and/or palate phenotypes. Paired analysis for deletions, amplifications and loss of heterozygosity, along with sequence verification of SNPs with discordant genotype calls did not reveal any genomic discordance between twin pairs in lymphocyte DNA samples. Our results demonstrate that postzygotic genomic alterations are not a common cause of monozygotic twin discordance for isolated cleft lip and/or palate. However, rare or balanced genomic alterations, tissue-specific events and small aberrations beyond the detection level of our experimental approach cannot be ruled out. The stability of genomes we observed in our study samples also suggests that detection of discordant events in other monozygotic twin pairs would be remarkable and of potential disease significance.

Genetic individuality is the foundation of personalized medicine, yet its determinants are currently poorly understood. One issue is the difference between monozygotic twins that are assumed identical and have been extensively used in genetic studies for decades [1]. Here, we report genome-wide alterations in two nuclear families each with a pair of monozygotic twins discordant for schizophrenia evaluated by the Affymetrix 6.0 human SNP array. The data analysis includes characterization of copy number variations (CNVs) and single nucleotide polymorphism (SNPs). The results have identified genomic differences between twin pairs and a set of new provisional schizophrenia genes. Samples were found to have between 35 and 65 CNVs per individual. The majority of CNVs (∼80%) represented gains. In addition, ∼10% of the CNVs were de novo (not present in parents), of these, 30% arose during parental meiosis and 70% arose during developmental mitosis. We also observed SNPs in the twins that were absent from both parents. These constituted 0.12% of all SNPs seen in the twins. In 65% of cases these SNPs arose during meiosis compared to 35% during mitosis. The developmental mitotic origin of most CNVs that may lead to MZ twin discordance may also cause tissue differences within individuals during a single pregnancy and generate a high frequency of mosaics in the population. The results argue for enduring genome-wide changes during cellular transmission, often ignored in most genetic analyses.

Obesity in humans is a complex polygenic trait with high inter-individual heritability estimated at 40–70%. Candidate gene, DNA linkage and genome-wide association studies (GWAS) have allowed for the identification of a large set of genes and genomic regions associated with obesity. Structural chromosome abnormalities usually result in congenital anomalies, growth retardation and developmental delay. Occasionally, they are associated with hyperphagia and obesity rather than growth delay. We report four new individuals with structural chromosome abnormalities involving 10q22.3-23.2, 16p11.2 and Xq27.1-q28 chromosomal regions with early childhood obesity and developmental delay. We also searched and summarized the literature for structural chromosome abnormalities reported in association with childhood obesity.

The factors controlling immunoglobulin (Ig) gene repertoire formation are poorly understood. Studies on monozygotic twins have helped discern the contributions of genetic versus environmental factors on expressed traits. In the present experiments, we applied a novel anchored PCR-ELISA system to compare the heavy chain V gene (V(H)) subgroup repertoires of mu and gamma expressing B lymphocytes from ten pairs of adult monozygotic twins, including eight pairs who are concordant or discordant for rheumatoid arthritis. The results disclosed that the relative expression of each Ig V(H) gene subgroup is not precisely proportional to its relative genomic size. The monozygotic twins had more similar IgM V(H) gene repertoires than did unrelated subjects. Moreover, monozygotic twins who are discordant for RA also use highly similar IgM V(H) gene-subgroup repertoires. Finally, the V(H) gene repertoire remained stable over time. Collectively, these data reveal that genetic factors predominantly control V(H) gene repertoire formation.

Monozygotic (MZ) twin pair discordance for childhood-onset Type 1 Diabetes (T1D) is ∼50%, implicating roles for genetic and non-genetic factors in the aetiology of this complex autoimmune disease. Although significant progress has been made in elucidating the genetics of T1D in recent years, the non-genetic component has remained poorly defined. We hypothesized that epigenetic variation could underlie some of the non-genetic component of T1D aetiology and, thus, performed an epigenome-wide association study (EWAS) for this disease. We generated genome-wide DNA methylation profiles of purified CD14+ monocytes (an immune effector cell type relevant to T1D pathogenesis) from 15 T1D–discordant MZ twin pairs. This identified 132 different CpG sites at which the direction of the intra-MZ pair DNA methylation difference significantly correlated with the diabetic state, i.e. T1D–associated methylation variable positions (T1D–MVPs). We confirmed these T1D–MVPs display statistically significant intra-MZ pair DNA methylation differences in the expected direction in an independent set of T1D–discordant MZ pairs (P = 0.035). Then, to establish the temporal origins of the T1D–MVPs, we generated two further genome-wide datasets and established that, when compared with controls, T1D–MVPs are enriched in singletons both before (P = 0.001) and at (P = 0.015) disease diagnosis, and also in singletons positive for diabetes-associated autoantibodies but disease-free even after 12 years follow-up (P = 0.0023). Combined, these results suggest that T1D–MVPs arise very early in the etiological process that leads to overt T1D. Our EWAS of T1D represents an important contribution toward understanding the etiological role of epigenetic variation in type 1 diabetes, and it is also the first systematic analysis of the temporal origins of disease-associated epigenetic variation for any human complex disease.

Author Summary

Type 1 diabetes (T1D) is a complex autoimmune disease affecting >30 million people worldwide. It is caused by a combination of genetic and non-genetic factors, leading to destruction of insulin-secreting cells. Although significant progress has recently been made in elucidating the genetics of T1D, the non-genetic component has remained poorly defined. Epigenetic modifications, such as methylation of DNA, are indispensable for genomic processes such as transcriptional regulation and are frequently perturbed in human disease. We therefore hypothesized that epigenetic variation could underlie some of the non-genetic component of T1D aetiology, and we performed a genome-wide DNA methylation analysis of a specific subset of immune cells (monocytes) from monozygotic twins discordant for T1D. This revealed the presence of T1D–specific methylation variable positions (T1D–MVPs) in the T1D–affected co-twins. Since these T1D–MVPs were found in MZ twins, they cannot be due to genetic differences. Additional experiments revealed that some of these T1D–MVPs are found in individuals before T1D diagnosis, suggesting they arise very early in the process that leads to overt T1D and are not simply due to post-disease associated factors (e.g. medication or long-term metabolic changes). T1D–MVPs may thus potentially represent a previously unappreciated, and important, component of type 1 diabetes risk.

The first generation of genome-wide association studies (GWA studies) for psychiatric disorders has led to new insights regarding the genetic architecture of these disorders. We now start to realize that a larger number of genes, each with a small contribution, are likely to explain the heritability of psychiatric diseases. The contribution of a large number of genes to complex traits can be analyzed with genome-wide profiling. In a discovery sample, a genetic risk profile for depression was defined based on a GWA study of 1738 adult cases and 1802 controls. The genetic risk scores were tested in two population-based samples of elderly participants. The genetic risk profiles were evaluated for depression and anxiety in the Rotterdam Study cohort and the Erasmus Rucphen Family (ERF) study. The genetic risk scores were significantly associated with different measures of depression and explained up to ∼0.7% of the variance in depression in Rotterdam Study and up to ∼1% in ERF study. The genetic score for depression was also significantly associated with anxiety explaining up to 2.1% in Rotterdam study. These findings suggest the presence of many genetic loci of small effect that influence both depression and anxiety. Remarkably, the predictive value of these profiles was as large in the sample of elderly participants as in the middle-aged samples.

Recent genome-wide association (GWA) studies have identified a number of novel genes/variants predisposing to obesity. However, most GWA studies have focused on individual single-nucleotide polymorphism (SNPs)/genes with a strong statistical association with a phenotypic trait without considering potential biological interplay of the tested genes. In this study, we performed biological pathway-based GWA analysis for BMI and body fat mass. We used individual level genotype data generated from 1,000 unrelated US whites that were genotyped for ~500,000 SNPs. Statistical analysis of pathways was performed using a modification of the Gene Set Enrichment Algorithm. A total of 963 pathways extracted from the BioCarta, Kyoto Encyclopedia of Genes and Genomes (KEGG), Ambion GeneAssist, and Gene Ontology (GO) databases were analyzed. Among all of the pathways analyzed, the vasoactive intestinal peptide (VIP) pathway was most strongly associated with fat mass (nominal P = 0.0009) and was the third most strongly associated pathway with BMI (nominal P = 0.0006). After multiple testing correction, the VIP pathway achieved false-discovery rate (FDR) q values of 0.042 and 0.120 for fat mass and BMI, respectively. Our study is the first to demonstrate that the VIP pathway may play an important role in development of obesity. The study also highlights the importance of pathway-based GWA analysis in identification of additional genes/variants for complex human diseases.

Candidate gene and genome-wide association studies have led to the discovery of nine loci involved in Mendelian forms of obesity and 58 loci contributing to polygenic obesity. These loci explain a small fraction of the heritability for obesity and many genes remain to be discovered. However, efforts in obesity gene identification greatly modified our understanding of this disorder. In this review, we propose an overlook of major lessons learned from 15 years of research in the field of genetics and obesity. We comment on the existence of the genetic continuum between monogenic and polygenic forms of obesity that pinpoints the role of genes involved in the central regulation of food intake and genetic predisposition to obesity. We explain how the identification of novel obesity predisposing genes has clarified unsuspected biological pathways involved in the control of energy balance that have helped to understand past human history and to explore causality in epidemiology. We provide evidence that obesity predisposing genes interact with the environment and influence the response to treatment relevant to disease prediction.

Background

Epidemiological studies consistently show associations between asthma and obesity. Shared genetics may account for this association.

Objective

To identify genetic variants associated with both asthma and obesity.

Methods

Based on a literature search, we identified genes from: 1) Genome-wide association studies (GWAS) of Body Mass Index (BMI) (n=17 genes), 2) GWAS of asthma (n=14) and 3) candidate gene studies of BMI and asthma (n=7). We used GWAS data from the Childhood Asthma Management Program (CAMP) to analyze associations between single nucleotide polymorphisms (SNPs) in these genes and asthma (n=359 subjects) and BMI (n=537).

Results

One top BMI GWAS SNP from the literature, rs10938397 near GNPDA2, was associated with both BMI (p=4 × 10−4) and asthma (p=0.03). Of the top asthma GWAS SNPs and the candidate gene SNPs, none was found to be associated with both BMI and asthma. Gene-based analyses that included all available SNPs in each gene found associations (p<0.05) with both phenotypes for several genes: NEGR1, ROBO1, DGKG, FAIM2, FTO and CHST8 among the BMI GWAS genes; ILRL1/IL18R1, DPP10, PDE4D, MYB, PDE10A, IL33 and especially PTPRD among the asthma GWAS genes; and PRKCA among the BMI and asthma candidate genes.

Conclusions

SNPs within several genes showed associations to BMI and asthma at a gene level, but none of these associations were significant after correction for multiple testing. Our analysis of known candidate genes reveals some evidence for shared genetics between asthma and obesity, but other shared genetic determinants are likely to be identified in novel loci.

There are hints of an altered mitochondrial function in obesity. Nuclear-encoded genes are relevant for mitochondrial function (3 gene sets of known relevant pathways: (1) 16 nuclear regulators of mitochondrial genes, (2) 91 genes for oxidative phosphorylation and (3) 966 nuclear-encoded mitochondrial genes). Gene set enrichment analysis (GSEA) showed no association with type 2 diabetes mellitus in these gene sets. Here we performed a GSEA for the same gene sets for obesity. Genome wide association study (GWAS) data from a case-control approach on 453 extremely obese children and adolescents and 435 lean adult controls were used for GSEA. For independent confirmation, we analyzed 705 obesity GWAS trios (extremely obese child and both biological parents) and a population-based GWAS sample (KORA F4, n = 1,743). A meta-analysis was performed on all three samples. In each sample, the distribution of significance levels between the respective gene set and those of all genes was compared using the leading-edge-fraction-comparison test (cut-offs between the 50th and 95th percentile of the set of all gene-wise corrected p-values) as implemented in the MAGENTA software. In the case-control sample, significant enrichment of associations with obesity was observed above the 50th percentile for the set of the 16 nuclear regulators of mitochondrial genes (pGSEA,50 = 0.0103). This finding was not confirmed in the trios (pGSEA,50 = 0.5991), but in KORA (pGSEA,50 = 0.0398). The meta-analysis again indicated a trend for enrichment (pMAGENTA,50 = 0.1052, pMAGENTA,75 = 0.0251). The GSEA revealed that weak association signals for obesity might be enriched in the gene set of 16 nuclear regulators of mitochondrial genes.

Despite the considerable enthusiasm about the yield of novel and replicated discoveries of genetic associations from the new generation of genome-wide association studies (GWAS), the proportion of the heritability of most complex diseases that have been studied to date remains small. Some of this “dark matter” could be due to gene-environment (G×E) interactions or more complex pathways involving multiple genes and exposures. We review the basic epidemiologic study design and statistical analysis approaches to studying G×E interactions individually and then consider more comprehensive approaches to studying entire pathways or GWAS data. In addition to the usual issues in genetic association studies, particular care is needed in exposure assessment and very large sample sizes are required. Although hypothesis-driven pathway-based and “agnostic” GWAS approaches are generally viewed as opposite poles, we suggest that the two can be usefully married using hierarchical modeling strategies that exploit external pathway knowledge in mining genome-wide data.

Genome-wide genotyping of a cohort using pools rather than individual samples has long been proposed as a cost-saving alternative for performing genome-wide association (GWA) studies. However, successful disease gene mapping using pooled genotyping has thus far been limited to detecting common variants with large effect sizes, which tend not to exist for many complex common diseases or traits. Therefore, for DNA pooling to be a viable strategy for conducting GWA studies, it is important to determine whether commonly used genome-wide SNP array platforms such as the Affymetrix 6.0 array can reliably detect common variants of small effect sizes using pooled DNA. Taking obesity and age at menarche as examples of human complex traits, we assessed the feasibility of genome-wide genotyping of pooled DNA as a single-stage design for phenotype association. By individually genotyping the top associations identified by pooling, we obtained a 14- to 16-fold enrichment of SNPs nominally associated with the phenotype, but we likely missed the top true associations. In addition, we assessed whether genotyping pooled DNA can serve as an inexpensive screen as the second stage of a multi-stage design with a large number of samples by comparing the most cost-effective 3-stage designs with 80% power to detect common variants with genotypic relative risk of 1.1, with and without pooling. Given the current state of the specific technology we employed and the associated genotyping costs, we showed through simulation that a design involving pooling would be 1.07 times more expensive than a design without pooling. Thus, while a significant amount of information exists within the data from pooled DNA, our analysis does not support genotyping pooled DNA as a means to efficiently identify common variants contributing small effects to phenotypes of interest. While our conclusions were based on the specific technology and study design we employed, the approach presented here will be useful for evaluating the utility of other or future genome-wide genotyping platforms in pooled DNA studies.