Genome-wide association study suggested copy number variation may be associated with body mass index in the Chinese population

The complex web of obesity: from genetics to precision medicine

INTRODUCTION

Obesity is a growing public health concern affecting both children and adults. Since it involves both genetic and environmental components, the management of obesity requires both, an understanding of the underlying genetics and changes in lifestyle. The knowledge of obesity genetics will enable the possibility of precision medicine in anti-obesity medications.

AREAS COVERED

Here, we explore health complications and the prevalence of obesity. We discuss disruptions in energy balance as a symptom of obesity, examining evolutionary theories, its multi-factorial origins, and heritability. Additionally, we discuss monogenic and polygenic obesity, the converging biological pathways, potential pharmacogenomics applications, and existing anti-obesity medications - specifically focussing on the leptin-melanocortin and incretin pathways. Comparisons between childhood and adult obesity genetics are made, along with insights into structural variants, epigenetic changes, and environmental influences on epigenetic signatures.

EXPERT OPINION

With recent advancements in anti-obesity drugs, genetic studies pinpoint new targets and allow for repurposing existing drugs. This creates opportunities for genotype-informed treatment options. Also, lifestyle interventions can help in the prevention and treatment of obesity by altering the epigenetic signatures. The comparison of genetic architecture in adults and children revealed a significant overlap. However, more robust studies with diverse ethnic representation is required in childhood obesity.

Illuminating the neuropeptide Y4 receptor and its ligand pancreatic polypeptide from a structural, functional, and therapeutic perspective

The neuropeptide Y4 receptor (Y4R), a rhodopsin-like G protein-coupled receptor (GPCR) and the hormone pancreatic polypeptide (PP) are members of the neuropeptide Y family consisting of four receptors (Y1R, Y2R, Y4R, Y5R) and three highly homologous peptide ligands (neuropeptide Y, peptide YY, PP). In this family, the Y4R is of particular interest as it is the only subtype with high affinity to PP over NPY. The Y4R, as a mediator of PP signaling, has a pivotal role in appetite regulation and energy homeostasis, offering potential avenues for the treatment of metabolic disorders such as obesity. PP as anorexigenic peptide is released postprandial from the pancreas in response to food intake, induces satiety signals and contributes to hamper excessive food intake. Moreover, this system was also described to be associated with different types of cancer: overexpression of Y4R have been found in human adenocarcinoma cells, while elevated levels of PP are related to the development of pancreatic endocrine tumors. The pharmacological relevance of the Y4R advanced the search for potent and selective ligands for this receptor subtype, which will be significantly progressed through the elucidation of the active state PP-Y4R cryo-EM structure. This review summarizes the development of novel PP-derived ligands, like Obinepitide as dual Y2R/Y4R agonist in clinical trials or UR-AK86c as small hexapeptide agonist with picomolar affinity, as well as the first allosteric modulators that selectively target the Y4R, e.g. VU0506013 as potent Y4R positive allosteric modulator or (S)-VU0637120 as allosteric antagonist. Here, we provide valuable insights into the complex physiological functions of the Y4R and PP and the pharmacological relevance of the system in appetite regulation to open up new avenues for the development of tool compounds for targeted therapies with potential applications in metabolic disorders.

Detection of genome-wide copy number variation in Murrah buffaloes

Riverine Buffaloes, especially the Murrah breed because of their adaptability to harsh climatic conditions, is farmed in many countries to convert low-quality feed into valuable dairy products and meat. Here, we investigated the copy number variations (CNVs) in 296 Murrah buffalo using the Axiom® Buffalo Genotyping Array 90K (Affymetrix, Santa Clara, CA, USA). The CNVs were detected on the autosomes, using the Copy Number Analysis Module (CNAM) using the univariate analysis. 7937 CNVs were detected in 279 Buffaloes, the average length of the CNVs was 119,048.87 bp that ranged between 7800 and 4,561,030 bp. These CNVs were accounting for 10.33% of the buffalo genome, which was comparable to cattle, sheep, and goat CNV analyses. Further, CNVs were merged and 1541 CNVRs were detected using the Bedtools-mergeBed command. 485 genes were annotated within 196 CNVRs that were identified in at least 10 animals of Murrah population. Out of these, 40 CNVRs contained 59 different genes that were associated with 69 different traits. Overall, the study identified a significant number of CNVs and CNVRs in the Murrah breed of buffalo, with a wide range of lengths and frequencies across the autosomes. The identified CNVRs contained genes associated with important traits related to production and reproduction, making them potentially important targets for future breeding and genetic improvement efforts.

DNA copy number and structural variation (CNV) contributions to adult and childhood obesity

In recent years, obesity has reached epidemic proportions globally and has become a major public health concern. The development of obesity is likely caused by several behavioral, environmental, and genetic factors. Genomic variability among individuals is largely due to copy number variations (CNVs). Recent genome-wide association studies (GWAS) have successfully identified many loci containing CNV related to obesity. These obesity-related CNVs are informative to the diagnosis and treatment of genomic diseases. A more comprehensive classification of CNVs may provide the basis for determining how genomic diversity impacts the mechanisms of expression for obesity in children and adults of a variety of genders and ethnicities. In this review, we summarize current knowledge on the relationship between obesity and the CNV of several genomic regions, with an emphasis on genes at the following loci: 11q11, 1p21.1, 10q11.22, 10q26.3, 16q12.2, 16p12.3, and 4q25.

Copy number variant analysis and expression profiling of the olfactory receptor-rich 11q11 region in obesity predisposition

Genome-wide copy number surveys associated chromosome 11q11 with obesity. As this is an olfactory receptor-rich region, we hypothesize that genetic variation in olfactory receptor genes might be implicated in the pathogenesis of obesity. Multiplex Amplicon Quantification analysis was applied to screen for copy number variants at chromosome 11q11 in 627 patients with obesity and 330 healthy-weight individuals. A ± 80 kb deletion with an internally 1.3 kb retained segment was identified, covering the three olfactory receptor genes OR4C11, OR4P4, and OR4S2. A significant increase in copy number loss(es) was perceived in our patient cohort (MAF = 27%; p = 0.02). Gene expression profiling in metabolic relevant tissues was performed to evaluate the functional impact of the obesity susceptible locus. All three 11q11 genes were present in visceral and subcutaneous adipose tissue while no expression was perceived in the liver. These results support the 'metabolic system' hypothesis and imply that gene disruption of OR4C11, OR4P4, and OR4S2 will negatively influence energy metabolism, ultimately leading to fat accumulation and obesity. Our study thus demonstrates a role for structural variation within olfactory receptor-rich regions in complex diseases and defines the 11q11 deletion as a risk factor for obesity.

Genetics of Obesity in East Asians

Obesity has become a public health problem worldwide. Compared with Europe, people in Asia tend to suffer from type 2 diabetes with a lower body mass index (BMI). Genome-wide association studies (GWASs) have identified over 750 loci associated with obesity. Although the majority of GWAS results were conducted in individuals of European ancestry, a recent GWAS in individuals of Asian ancestry has made a significant contribution to the identification of obesity susceptibility loci. Indeed, owing to the multifactorial character of obesity with a strong environmental component, the revealed loci may have distinct contributions in different ancestral genetic backgrounds and in different environments as presented through diet and exercise among other factors. Uncovering novel, yet unrevealed genes in non-European ancestries may further contribute to explaining the missing heritability for BMI. In this review, we aimed to summarize recent advances in obesity genetics in individuals of Asian ancestry. We therefore compared proposed mechanisms underlying susceptibility loci for obesity associated with individuals of European and Asian ancestries and discussed whether known genetic variants might explain ethnic differences in obesity risk. We further acknowledged that GWAS implemented in individuals of Asian ancestries have not only validated the potential role of previously specified obesity susceptibility loci but also exposed novel ones, which have been missed in the initial genetic studies in individuals of European ancestries. Thus, multi-ethnic studies have a great potential not only to contribute to a better understanding of the complex etiology of human obesity but also potentially of ethnic differences in the prevalence of obesity, which may ultimately pave new avenues in more targeted and personalized obesity treatments.

Copy number determination of the gene for the human pancreatic polypeptide receptor NPY4R using read depth analysis and droplet digital PCR

Background

Copy number variation (CNV) plays an important role in human genetic diversity and has been associated with multiple complex disorders. Here we investigate a CNV on chromosome 10q11.22 that spans NPY4R, the gene for the appetite-regulating pancreatic polypeptide receptor Y4. This genomic region has been challenging to map due to multiple repeated elements and its precise organization has not yet been resolved. Previous studies using microarrays were interpreted to show that the most common copy number was 2 per genome.

Results

We have investigated 18 individuals from the 1000 Genomes project using the well-established method of read depth analysis and the new droplet digital PCR (ddPCR) method. We find that the most common copy number for NPY4R is 4. The estimated number of copies ranged from three to seven based on read depth analyses with Control-FREEC and CNVnator, and from four to seven based on ddPCR. We suggest that the difference between our results and those published previously can be explained by methodological differences such as reference gene choice, data normalization and method reliability. Three high-quality archaic human genomes (two Neanderthal and one Denisova) display four copies of the NPY4R gene indicating that a duplication occurred prior to the human-Neanderthal/Denisova split.

Conclusions

We conclude that ddPCR is a sensitive and reliable method for CNV determination, that it can be used for read depth calibration in CNV studies based on already available whole-genome sequencing data, and that further investigation of NPY4R copy number variation and its consequences are necessary due to the role of Y4 receptor in food intake regulation.

Electronic supplementary material

The online version of this article (10.1186/s12896-019-0523-9) contains supplementary material, which is available to authorized users.

Established and emerging strategies to crack the genetic code of obesity

Tremendous progress has been made in the genetic elucidation of obesity over the past two decades, driven largely by technological, methodological and organizational innovations. Current strategies for identifying obesity-predisposing loci/genes, including cytogenetics, linkage analysis, homozygosity mapping, admixture mapping, candidate gene studies, genome-wide association studies, custom genotyping arrays, whole-exome sequencing and targeted exome sequencing, have achieved differing levels of success, and the identified loci in aggregate explain only a modest fraction of the estimated heritability of obesity. This review outlines the successes and limitations of these approaches and proposes novel strategies, including the use of exceptionally large sample sizes, the study of diverse ethnic groups and deep phenotypes and the application of innovative methods and study designs, to identify the remaining obesity-predisposing genes. The use of both established and emerging strategies has the potential to crack the genetic code of obesity in the not-too-distant future. The resulting knowledge is likely to yield improvements in obesity prediction, prevention and care.

Low Salivary Amylase Gene (AMY1) Copy Number Is Associated with Obesity and Gut Prevotella Abundance in Mexican Children and Adults

Genome-wide association studies (GWAS) have identified copy number variants (CNVs) associated with obesity in chromosomal regions 1p31.1, 10q11.22, 11q11, 16p12.3, and recently 1p21.1, which contains the salivary amylase gene (AMY1). Recent evidence suggests this enzyme may influence gut microbiota composition through carbohydrate (mainly starch) degradation. The role of these CNVs in obesity has been scarcely explored in the Latino population, and thus the aim of our study was to evaluate the association of 1p31.1, 10q11.22, 11q11, 16p12.3 and 1p21.1 CNVs with obesity in 921 Mexican children, to replicate significant associations in 920 Mexican adults, and to analyze the association of AMY1 copy number with gut microbiota in 75 children and 45 adults. Of the five CNVs analyzed, 1q11 CNV was significantly associated with obesity in children, but not in adults. Only AMY1 CNV was significantly associated with obesity in both age groups. Moreover, gut microbiota analyses revealed a positive correlation between AMY1 copy number and Prevotella abundance. This genus has enzymes and gene clusters essential for complex polysaccharide degradation and utilization. To our knowledge, this is the first study to analyze the association of these five CNVs in the Mexican population and to report a correlation between AMY1 CN and gut microbiota in humans.

Copy number of pancreatic polypeptide receptor gene NPY4R correlates with body mass index and waist circumference

Multiple genetic studies have linked copy number variation (CNV) in different genes to body mass index (BMI) and obesity. A CNV on chromosome 10q11.22 has been associated with body weight. This CNV region spans NPY4R, the gene encoding the pancreatic polypeptide receptor Y4, which has been described as a satiety-stimulating receptor. We have investigated CNV of the NPY4R gene and analysed its relationship to BMI, waist circumference and self-reported dietary intake from 558 individuals (216 men and 342 women) representing a wide BMI range. The copy number for NPY4R ranged from 2 to 8 copies (average 4.6±0.8). Rather than the expected negative correlation, we observed a positive correlation between NPY4R copy number and BMI as well as waist circumference in women (Pearson’s r = 0.267, p = 2.65×10⁻⁷ and r = 0.256, p = 8×10⁻⁷, respectively). Each additional copy of NPY4R correlated with 2.6 kg/m² increase in BMI and 5.67 cm increase in waist circumference (p = 2.8×10⁻⁵ and p = 6.2×10⁻⁵, respectively) for women. For men, there was no statistically significant correlation between CNV and BMI. Our results suggest that NPY4R genetic variation influences body weight in women, but the exact role of this receptor appears to be more complex than previously proposed.

Ethnic and population differences in the genetic predisposition to human obesity

Obesity rates have escalated to the point of a global pandemic with varying prevalence across ethnic groups. These differences are partially explained by lifestyle factors in addition to genetic predisposition to obesity. This review provides a comprehensive examination of the ethnic differences in the genetic architecture of obesity. Using examples from evolution, heritability, admixture, monogenic and polygenic studies of obesity, we provide explanations for ethnic differences in the prevalence of obesity. The debate over definitions of race and ethnicity, the advantages and limitations of multi-ethnic studies and future directions of research are also discussed. Multi-ethnic studies have great potential to provide a better understanding of ethnic differences in the prevalence of obesity that may result in more targeted and personalized obesity treatments.

Recent progress in genetics, epigenetics and metagenomics unveils the pathophysiology of human obesity

In high-, middle- and low-income countries, the rising prevalence of obesity is the underlying cause of numerous health complications and increased mortality. Being a complex and heritable disorder, obesity results from the interplay between genetic susceptibility, epigenetics, metagenomics and the environment. Attempts at understanding the genetic basis of obesity have identified numerous genes associated with syndromic monogenic, non-syndromic monogenic, oligogenic and polygenic obesity. The genetics of leanness are also considered relevant as it mirrors some of obesity's aetiologies. In this report, we summarize ten genetically elucidated obesity syndromes, some of which are involved in ciliary functioning. We comprehensively review 11 monogenic obesity genes identified to date and their role in energy maintenance as part of the leptin-melanocortin pathway. With the emergence of genome-wide association studies over the last decade, 227 genetic variants involved in different biological pathways (central nervous system, food sensing and digestion, adipocyte differentiation, insulin signalling, lipid metabolism, muscle and liver biology, gut microbiota) have been associated with polygenic obesity. Advances in obligatory and facilitated epigenetic variation, and gene-environment interaction studies have partly accounted for the missing heritability of obesity and provided additional insight into its aetiology. The role of gut microbiota in obesity pathophysiology, as well as the 12 genes associated with lipodystrophies is discussed. Furthermore, in an attempt to improve future studies and merge the gap between research and clinical practice, we provide suggestions on how high-throughput '-omic' data can be integrated in order to get closer to the new age of personalized medicine.

The evolution and population diversity of human-specific segmental duplications

Segmental duplications contribute to human evolution, adaptation and genomic instability but are often poorly characterized. We investigate the evolution, genetic variation and coding potential of human-specific segmental duplications (HSDs). We identify 218 HSDs based on analysis of 322 deeply sequenced archaic and contemporary hominid genomes. We sequence 550 human and nonhuman primate genomic clones to reconstruct the evolution of the largest, most complex regions with protein-coding potential (n=80 genes/33 gene families). We show that HSDs are non-randomly organized, associate preferentially with ancestral ape duplications termed “core duplicons”, and evolved primarily in an interspersed inverted orientation. In addition to Homo sapiens-specific gene expansions (e.g., TCAF1/2), we highlight ten gene families (e.g., ARHGAP11B and SRGAP2C) where copy number never returns to the ancestral state, there is evidence of mRNA splicing, and no common gene-disruptive mutations are observed in the general population. Such duplicates are candidates for the evolution of human-specific adaptive traits.

From Genome-Wide Association Study to Phenome-Wide Association Study: New Paradigms in Obesity Research

Obesity is a condition in which excess body fat has accumulated over an extent that increases the risk of many chronic diseases. The current clinical classification of obesity is based on measurement of body mass index (BMI), waist-hip ratio, and body fat percentage. However, these measurements do not account for the wide individual variations in fat distribution, degree of fatness or health risks, and genetic variants identified in the genome-wide association studies (GWAS). In this review, we will address this important issue with the introduction of phenome, phenomics, and phenome-wide association study (PheWAS). We will discuss the new paradigm shift from GWAS to PheWAS in obesity research. In the era of precision medicine, phenomics and PheWAS provide the required approaches to better definition and classification of obesity according to the association of obese phenome with their unique molecular makeup, lifestyle, and environmental impact.

CNV analysis and mutation screening indicate an important role for the NPY4R gene in human obesity

OBJECTIVE

Genome-wide copy number variation (CNV) analyses have associated the 10q11.22 CNV with obesity. As the NPY4R gene is the most interesting candidate gene in this region, it was hypothesized that both genetic and structural variation in NPY4R might be implicated in the pathogenesis of obesity.

METHODS

In the first part of this study, 326 children and adolescents with obesity and 298 healthy lean individuals were screened for CNV in the NPY4R-containing chr.10q11.22 region. In the second part of this study, a mutation screen for variants in the NPY4R coding region was performed in 356 children and adolescents with obesity and 337 healthy lean adults.

RESULTS

Our CNV analysis demonstrated a significantly higher frequency of NPY4R containing 10q11.22 CNV loss in the patient population (P = 0.0003), while CNV gain in this region was more prevalent in the control population (P = 0.031). Mutation analysis resulted in the identification of 15 rare non-synonymous heterozygous variants. For two variants that could only be identified in the patient population, receptor dysfunction and thus a pathogenic effect were demonstrated.

CONCLUSIONS

In conclusion, these data support an essential role for genetic and structural variation within the NPY4R gene in the pathogenesis of obesity.

Genetics of Adiposity in Large Animal Models for Human Obesity-Studies on Pigs and Dogs

The role of domestic mammals in the development of human biomedical sciences has been widely documented. Among these model species the pig and dog are of special importance. Both are useful for studies on the etiology of human obesity. Genome sequences of both species are known and advanced genetic tools [eg, microarray SNP for genome wide association studies (GWAS), next generation sequencing (NGS), etc.] are commonly used in such studies. In the domestic pig the accumulation of adipose tissue is an important trait, which influences meat quality and fattening efficiency. Numerous quantitative trait loci (QTLs) for pig fatness traits were identified, while gene polymorphisms associated with these traits were also described. The situation is different in dog population. Generally, excessive accumulation of adipose tissue is considered, similar to humans, as a complex disease. However, research on the genetic background of canine obesity is still in its infancy. Between-breed differences in terms of adipose tissue accumulation are well known in both animal species. In this review we show recent advances of studies on adipose tissue accumulation in pigs and dogs, and their potential importance for studies on human obesity.

CNV Analysis Associates AKNAD1 with Type-2 Diabetes in Jordan Subpopulations

Previous studies have identified a number of single nucleotide polymorphisms (SNPs) associated with type-2 diabetes (T2D), but copy number variation (CNV) association has rarely been addressed, especially in populations from Jordan. To investigate CNV associations for T2D in populations in Jordan, we conducted a CNV analysis based on intensity data from genome-wide SNP array, including 34 T2D cases and 110 healthy controls of Chechen ethnicity, as well as 34 T2D cases and 106 healthy controls of Circassian ethnicity. We found a CNV region in protein tyrosine phosphatase receptor type D (PTPRD) with significant association with T2D. PTPRD has been reported to be associated with T2D in genome-wide association studies (GWAS). We additionally identified 16 CNV regions associated with T2D which overlapped with gene exons. Of particular interest, a CNV region in the gene AKNA Domain Containing 1 (AKNAD1) surpassed the experiment-wide significance threshold. Endoplasmic reticulum (ER)-related pathways were significantly enriched among genes which are predicted to be functionally associated with human or mouse homologues of AKNAD1. This is the first CNV analysis of a complex disease in populations of Jordan. We identified and experimentally validated a significant CNVR in gene AKNAD1 associated with T2D.

Genome Wide Distributions and Functional Characterization of Copy Number Variations between Chinese and Western Pigs

Copy number variations (CNVs) refer to large insertions, deletions and duplications in the genomic structure ranging from one thousand to several million bases in size. Since the development of next generation sequencing technology, several methods have been well built for detection of copy number variations with high credibility and accuracy. Evidence has shown that CNV occurring in gene region could lead to phenotypic changes due to the alteration in gene structure and dosage. However, it still remains unexplored whether CNVs underlie the phenotypic differences between Chinese and Western domestic pigs. Based on the read-depth methods, we investigated copy number variations using 49 individuals derived from both Chinese and Western pig breeds. A total of 3,131 copy number variation regions (CNVRs) were identified with an average size of 13.4 Kb in all individuals during domestication, harboring 1,363 genes. Among them, 129 and 147 CNVRs were Chinese and Western pig specific, respectively. Gene functional enrichments revealed that these CNVRs contribute to strong disease resistance and high prolificacy in Chinese domestic pigs, but strong muscle tissue development in Western domestic pigs. This finding is strongly consistent with the morphologic characteristics of Chinese and Western pigs, indicating that these group-specific CNVRs might have been preserved by artificial selection for the favored phenotypes during independent domestication of Chinese and Western pigs. In this study, we built high-resolution CNV maps in several domestic pig breeds and discovered the group specific CNVs by comparing Chinese and Western pigs, which could provide new insight into genomic variations during pigs’ independent domestication, and facilitate further functional studies of CNV-associated genes.

Interactions between obesity-related copy number variants and dietary behaviors in childhood obesity

Copy number variants (CNVs) have been implicated as an important genetic marker of obesity, and gene-environment interaction has been found to modulate risk of obesity. To evaluate the associations between CNVs and childhood obesity, as well as the interactions between CNVs and dietary behaviors, we recruited 534 obese children and 508 controls from six cities in China and six candidate CNVs were screened through published genome-wide studies (GWAS) on childhood obesity. We found three loci (10q11.22, 4q25 and 11q11) to be significantly associated with obesity after false discovery rate (FDR) correction (all the p ≤ 0.05). Cumulative effect of the three positive loci was measured by the genetic risk score (GRS), showing a significant relationship with the risk of obesity (Ptrend < 0.001). The OR of obesity increased to 21.38 (95% CI = 21.19-21.55) among the 10q11.22 deletion carriers who had meat-based diets, indicating prominent multiplicative interaction (MI) between deletions of 10q11.22 and preference for a meat-based diet. Simultaneous deletions of 5q13.2 and duplications of 6q14.1 had significant MI with a preference for salty foods. Our results suggested that CNVs may contribute to the genetic susceptibility of childhood obesity, and the CNV-diet interactions modulate the risk of obesity.

Obesity and genomics: role of technology in unraveling the complex genetic architecture of obesity

Obesity is a complex and multifactorial disease that occurs as a result of the interaction between "obesogenic" environmental factors and genetic components. Although the genetic component of obesity is clear from the heritability studies, the genetic basis remains largely elusive. Successes have been achieved in identifying the causal genes for monogenic obesity using animal models and linkage studies, but these approaches are not fruitful for polygenic obesity. The developments of genome-wide association approach have brought breakthrough discovery of genetic variants for polygenic obesity where tens of new susceptibility loci were identified. However, the common SNPs only accounted for a proportion of heritability. The arrival of NGS technologies and completion of 1000 Genomes Project have brought other new methods to dissect the genetic architecture of obesity, for example, the use of exome genotyping arrays and deep sequencing of candidate loci identified from GWAS to study rare variants. In this review, we summarize and discuss the developments of these genetic approaches in human obesity.

Identification and computational analysis of gene regulatory elements

Over the last two decades, advances in experimental and computational technologies have greatly facilitated genomic research. Next-generation sequencing technologies have made de novo sequencing of large genomes affordable, and powerful computational approaches have enabled accurate annotations of genomic DNA sequences. Charting functional regions in genomes must account for not only the coding sequences, but also noncoding RNAs, repetitive elements, chromatin states, epigenetic modifications, and gene regulatory elements. A mix of comparative genomics, high-throughput biological experiments, and machine learning approaches has played a major role in this truly global effort. Here we describe some of these approaches and provide an account of our current understanding of the complex landscape of the human genome. We also present overviews of different publicly available, large-scale experimental data sets and computational tools, which we hope will prove beneficial for researchers working with large and complex genomes.

A Copy Number Variant on Chromosome 20q13.3 Implicated in Thinness and Severe Obesity

BACKGROUND/OBJECTIVES

To identify copy number variants (CNVs) which are associated with body mass index (BMI).

SUBJECTS/METHODS

CNVs were identified using array comparative genomic hybridization (aCGH) on members of pedigrees ascertained through severely obese (BMI ≥ 35 kg/m(2)) sib pairs (86 pedigrees) and thin (BMI ≤ 23 kg/m(2)) probands (3 pedigrees). Association was inferred through pleiotropy of BMI with CNV log⁡2 intensity ratio.

RESULTS

A 77-kilobase CNV on chromosome 20q13.3, confirmed by real-time qPCR, exhibited deletions in the obese subjects and duplications in the thin subjects (P = 2.2 × 10(-6)). Further support for the presence of a deletion derived from inference by likelihood analysis of null alleles for SNPs residing in the region.

CONCLUSIONS

One or more of 7 genes residing in a chromosome 20q13.3 CNV region appears to influence BMI. The strongest candidate is ARFRP1, which affects glucose metabolism in mice.

The ethnoepidemiology of obesity

The prevalence of overweight and obesity varies significantly across ethnic groups and among aboriginal people in Canada and appears to be increasing overall in children and youth, which will have significant health consequences in the future. Individual health behaviours, genetic predisposition, and community-level factors all contribute to the high burden of overweight and obesity across communities in Canada. Preliminary studies indicate that individuals who live in neighbourhoods in Canada with increased walkability, fewer fast food outlets, and higher socioeconomic status have lower rates of overweight/obesity when compared with other neighbourhoods. However, more research is required to understand the impact of community level factors on overweight/obesity trends in Canadian ethnic groups, including children and youth, and aboriginal people.

Analysis of genome-wide copy number variations in Chinese indigenous and western pig breeds by 60 K SNP genotyping arrays

Copy number variations (CNVs) represent a substantial source of structural variants in mammals and contribute to both normal phenotypic variability and disease susceptibility. Although low-resolution CNV maps are produced in many domestic animals, and several reports have been published about the CNVs of porcine genome, the differences between Chinese and western pigs still remain to be elucidated. In this study, we used Porcine SNP60 BeadChip and PennCNV algorithm to perform a genome-wide CNV detection in 302 individuals from six Chinese indigenous breeds (Tongcheng, Laiwu, Luchuan, Bama, Wuzhishan and Ningxiang pigs), three western breeds (Yorkshire, Landrace and Duroc) and one hybrid (Tongcheng×Duroc). A total of 348 CNV Regions (CNVRs) across genome were identified, covering 150.49 Mb of the pig genome or 6.14% of the autosomal genome sequence. In these CNVRs, 213 CNVRs were found to exist only in the six Chinese indigenous breeds, and 60 CNVRs only in the three western breeds. The characters of CNVs in four Chinese normal size breeds (Luchuan, Tongcheng and Laiwu pigs) and two minipig breeds (Bama and Wuzhishan pigs) were also analyzed in this study. Functional annotation suggested that these CNVRs possess a great variety of molecular function and may play important roles in phenotypic and production traits between Chinese and western breeds. Our results are important complementary to the CNV map in pig genome, which provide new information about the diversity of Chinese and western pig breeds, and facilitate further research on porcine genome CNVs.

Low copy number of the salivary amylase gene predisposes to obesity

Common multi-allelic copy number variants (CNVs) appear enriched for phenotypic associations compared to their biallelic counterparts. Here we investigated the influence of gene dosage effects on adiposity through a CNV association study of gene expression levels in adipose tissue. We identified significant association of a multi-allelic CNV encompassing the salivary amylase gene (AMY1) with body mass index (BMI) and obesity, and we replicated this finding in 6,200 subjects. Increased AMY1 copy number was positively associated with both amylase gene expression (P = 2.31 × 10(-14)) and serum enzyme levels (P < 2.20 × 10(-16)), whereas reduced AMY1 copy number was associated with increased BMI (change in BMI per estimated copy = -0.15 (0.02) kg/m(2); P = 6.93 × 10(-10)) and obesity risk (odds ratio (OR) per estimated copy = 1.19, 95% confidence interval (CI) = 1.13-1.26; P = 1.46 × 10(-10)). The OR value of 1.19 per copy of AMY1 translates into about an eightfold difference in risk of obesity between subjects in the top (copy number > 9) and bottom (copy number < 4) 10% of the copy number distribution. Our study provides a first genetic link between carbohydrate metabolism and BMI and demonstrates the power of integrated genomic approaches beyond genome-wide association studies.

Etiology of Obesity Over the Life Span: Ecological and Genetic Highlights from Asian Countries

Obesity is a worldwide pandemic, and the prevalence rate has doubled since the 1980s. Asian countries are also experiencing the global epidemic of obesity with its related health consequences. The prevalence of overweight and obesity are increasing at an alarming rate across all age groups in Asia. These increases are mainly attributed to rapid economic growth, which leads to socio-economic, nutrition and lifestyle transitions, resulting in a positive energy balance. In addition, fat mass and obesity-associated gene variants, copy number variants in chromosomes and epigenetic modifications have shown positive associations with the risk of obesity among Asians. In this review highlights of prevalence and related ecological and genetic factors that could influence the rapid rise in obesity among Asian populations are discussed.

Genetic modifiers of obesity and bariatric surgery outcomes

Obesity is a highly heritable trait. While acute and chronic changes in body weight or obesity-related comorbidities are heavily influenced by environmental factors, there are still strong genomic modifiers that help account for inter-subject variability in baseline traits and in response to interventions. This review is intended to provide an up-to-date overview of our current understanding of genetic influences on obesity, with emphasis on genetic modifiers of baseline traits and responses to intervention. We begin by reviewing how genetic variants can influence obesity. We then examine genetic modifiers of weight loss via different intervention strategies, focusing on known and potential modifiers of surgical weight loss outcomes. We will pay particular attention to the effects of patient age on outcomes, addressing the risks and benefits of adopting early intervention strategies. Finally, we will discuss how the field of bariatric surgery can leverage knowledge of genetic modifiers to adopt a personalized medicine approach for optimal outcomes across this widespread and diverse patient population.

Genetic aspects of human obesity

Obesity and its related metabolic consequences represent a major public health problem. Huge changes within the environment have undoubtedly contributed to the increased prevalence of obesity but genetic factors are also critical in determining an individual's predisposition to gain weight. The last two decades have seen a huge increase in the understanding of the mechanisms controlling appetitive behavior, body composition, and energy expenditure. Many regions throughout the central nervous system play critical roles in these processes but the hypothalamus, in particular, receives and orchestrates a variety of signals to bring about coordinated changes in energy balance. Reviewing data from human genetic and model organism studies, we consider how disruptions of hypothalamic pathways evolved to maintain energy homeostasis and go on to cause obesity. We highlight ongoing technological developments which continue to lead to novel insights and discuss how this increased knowledge may lead to effective therapeutic interventions in the future.

Combined linkage and association analyses identify a novel locus for obesity near PROX1 in Asians

OBJECTIVE

Although genome-wide association studies (GWAS) have substantially contributed to understanding the genetic architecture, unidentified variants for complex traits remain an issue. One of the efficient approaches is the improvement of the power of GWAS scan by weighting P values with prior linkage signals. Our objective was to identify the novel candidates for obesity in Asian populations by using genemapping strategies that combine linkage and association analyses.

DESIGN AND METHODS

To obtain linkage information for body mass index (BMI) and waist circumference (WC), we performed a multipoint genome-wide linkage study in an isolated Mongolian sample of 1,049 individuals from 74 families. Next, a family-based GWAS, which integrates within- and between-family components, was performed using the genotype data of 756 individuals of the Mongolian sample, and P values for association were weighted using linkage information obtained previously.

RESULTS

For both BMI (LOD = 3.3) and WC (LOD = 2.6), the highest linkage peak was discovered at chromosome 10q11.22. In family-based GWAS combined with linkage information, six single-nucleotide polymorphisms (SNPs) for BMI and five SNPs for WC reached a significant level of association (linkage weighted P < 1 × 10(-5) ). Of these, only one of the SNPs associated with WC (rs1704198) was replicated in 327 Korean families comprising 1,301 individuals. This SNP was located in the proximity of the prosperorelated homeobox 1 (PROX1) gene, the function of which was validated previously in a mouse model.

CONCLUSION

Our powerful strategic analysis enabled the discovery of a novel candidate gene, PROX1, associated with WC in an Asian population.

Identification of both copy number variation-type and constant-type core elements in a large segmental duplication region of the mouse genome

Background

Copy number variation (CNV), an important source of diversity in genomic structure, is frequently found in clusters called CNV regions (CNVRs). CNVRs are strongly associated with segmental duplications (SDs), but the composition of these complex repetitive structures remains unclear.

Results

We conducted self-comparative-plot analysis of all mouse chromosomes using the high-speed and large-scale-homology search algorithm SHEAP. For eight chromosomes, we identified various types of large SD as tartan-checked patterns within the self-comparative plots. A complex arrangement of diagonal split lines in the self-comparative-plots indicated the presence of large homologous repetitive sequences. We focused on one SD on chromosome 13 (SD13M), and developed SHEPHERD, a stepwise ab initio method, to extract longer repetitive elements and to characterize repetitive structures in this region. Analysis using SHEPHERD showed the existence of 60 core elements, which were expected to be the basic units that form SDs within the repetitive structure of SD13M. The demonstration that sequences homologous to the core elements (>70% homology) covered approximately 90% of the SD13M region indicated that our method can characterize the repetitive structure of SD13M effectively. Core elements were composed largely of fragmented repeats of a previously identified type, such as long interspersed nuclear elements (LINEs), together with partial genic regions. Comparative genome hybridization array analysis showed that whereas 42 core elements were components of CNVR that varied among mouse strains, 8 did not vary among strains (constant type), and the status of the others could not be determined. The CNV-type core elements contained significantly larger proportions of long terminal repeat (LTR) types of retrotransposon than the constant-type core elements, which had no CNV. The higher divergence rates observed in the CNV-type core elements than in the constant type indicate that the CNV-type core elements have a longer evolutionary history than constant-type core elements in SD13M.

Conclusions

Our methodology for the identification of repetitive core sequences simplifies characterization of the structures of large SDs and detailed analysis of CNV. The results of detailed structural and quantitative analyses in this study might help to elucidate the biological role of one of the SDs on chromosome 13.

From obesity genetics to the future of personalized obesity therapy

Obesity is a disorder characterized by an excess accumulation of body fat resulting from a mismatch between energy intake and expenditure. Incidence of obesity has increased dramatically in the past few years, almost certainly fuelled by a shift in dietary habits owing to the widespread availability of low-cost, hypercaloric foods. However, clear differences exist in obesity susceptibility among individuals exposed to the same obesogenic environment, implicating genetic risk factors. Numerous genes have been shown to be involved in the development of monofactorial forms of obesity. In genome-wide association studies, a large number of common variants have been associated with adiposity levels, each accounting for only a small proportion of the predicted heritability. Although the small effect sizes of obesity variants identified in genome-wide association studies currently preclude their utility in clinical settings, screening for a number of monogenic obesity variants is now possible. Such regular screening will provide more informed prognoses and help in the identification of at-risk individuals who could benefit from early intervention, in evaluation of the outcomes of current obesity treatments, and in personalization of the clinical management of obesity. This Review summarizes current advances in obesity genetics and discusses the future of research in this field and the potential relevance to personalized obesity therapy.

Multiphasic analysis of whole exome sequencing data identifies a novel mutation of ACTG1 in a nonsyndromic hearing loss family

BACKGROUND

The genetic heterogeneity of sensorineural hearing loss is a major hurdle to the efficient discovery of disease-causing genes. We designed a multiphasic analysis of copy number variation (CNV), linkage, and single nucleotide variation (SNV) of whole exome sequencing (WES) data for the efficient discovery of mutations causing nonsyndromic hearing loss (NSHL).

RESULTS

From WES data, we identified five distinct CNV loci from a NSHL family, but they were not co-segregated among patients. Linkage analysis based on SNVs identified six candidate loci (logarithm of odds [LOD] >1.5). We selected 15 SNVs that co-segregated with NSHL in the family, which were located in six linkage candidate loci. Finally, the novel variant p.M305T in ACTG1 (DFNA20/26) was selected as a disease-causing variant.

CONCLUSIONS

Here, we present a multiphasic CNV, linkage, and SNV analysis of WES data for the identification of a candidate mutation causing NSHL. Our stepwise, multiphasic approach enabled us to expedite the discovery of disease-causing variants from a large number of patient variants.

Rare genomic structural variants in complex disease: lessons from the replication of associations with obesity

The limited ability of common variants to account for the genetic contribution to complex disease has prompted searches for rare variants of large effect, to partly explain the ‘missing heritability’. Analyses of genome-wide genotyping data have identified genomic structural variants (GSVs) as a source of such rare causal variants. Recent studies have reported multiple GSV loci associated with risk of obesity. We attempted to replicate these associations by similar analysis of two familial-obesity case-control cohorts and a population cohort, and detected GSVs at 11 out of 18 loci, at frequencies similar to those previously reported. Based on their reported frequencies and effect sizes (OR≥25), we had sufficient statistical power to detect the large majority (80%) of genuine associations at these loci. However, only one obesity association was replicated. Deletion of a 220 kb region on chromosome 16p11.2 has a carrier population frequency of 2×10⁻⁴ (95% confidence interval [9.6×10⁻⁵–3.1×10⁻⁴]); accounts overall for 0.5% [0.19%–0.82%] of severe childhood obesity cases (P = 3.8×10⁻¹⁰; odds ratio = 25.0 [9.9–60.6]); and results in a mean body mass index (BMI) increase of 5.8 kg.m⁻² [1.8–10.3] in adults from the general population. We also attempted replication using BMI as a quantitative trait in our population cohort; associations with BMI at or near nominal significance were detected at two further loci near KIF2B and within FOXP2, but these did not survive correction for multiple testing. These findings emphasise several issues of importance when conducting rare GSV association, including the need for careful cohort selection and replication strategy, accurate GSV identification, and appropriate correction for multiple testing and/or control of false discovery rate. Moreover, they highlight the potential difficulty in replicating rare CNV associations across different populations. Nevertheless, we show that such studies are potentially valuable for the identification of variants making an appreciable contribution to complex disease.

The Role of Copy Number Variation in African Americans with Type 2 Diabetes-Associated End Stage Renal Disease

This study investigated the association of copy number variants (CNVs) in type 2 diabetes (T2D) and T2D-associated end-stage renal disease (ESRD) in African Americans. Using the Affymetrix 6.0 array, >900,000 CNV probes spanning the genome were interrogated in 965 African Americans with T2D-ESRD and 1029 non-diabetic African American controls. Previously identified and novel CNVs were separately analyzed and were evaluated for insertion/deletion status and then used as predictors in a logistic regression model to test for association. One common CNV insertion on chromosome 1 was significantly associated with T2D-ESRD (p=6.17×10^-5, OR=1.63) after multiple comparison correction. This CNV region encompasses the genes AMY2A and AMY2B, which encode amylase isoenzymes produced by the pancreas. Additional common and novel CNVs approaching significance with disease were also detected. These exploratory results require further replication but suggest the involvement of the AMY2A/AMY2B CNV in T2D and/or T2D-ESRD, and indicate that CNVs may contribute to susceptibility for these diseases.

A comprehensive survey of copy number variation in 18 diverse pig populations and identification of candidate copy number variable genes associated with complex traits

Background

Copy number variation (CNV) is a major source of structural variants and has been commonly identified in mammalian genome. It is associated with gene expression and may present a major genetic component of phenotypic diversity. Unlike many other mammalian genomes where CNVs have been well annotated, studies of porcine CNV in diverse breeds are still limited.

Result

Here we used Porcine SNP60 BeadChip and PennCNV algorithm to identify 1,315 putative CNVs belonging to 565 CNV regions (CNVRs) in 1,693 pigs from 18 diverse populations. Total 538 out of 683 CNVs identified in a White Duroc × Erhualian F₂ population fit Mendelian transmission and 6 out of 7 randomly selected CNVRs were confirmed by quantitative real time PCR. CNVRs were non-randomly distributed in the pig genome. Several CNV hotspots were found on pig chromosomes 6, 11, 13, 14 and 17. CNV numbers differ greatly among different pig populations. The Duroc pigs were identified to have the most number of CNVs per individual. Among 1,765 transcripts located within the CNVRs, 634 genes have been reported to be copy number variable genes in the human genome. By integrating analysis of QTL mapping, CNVRs and the description of phenotypes in knockout mice, we identified 7 copy number variable genes as candidate genes for phenotypes related to carcass length, backfat thickness, abdominal fat weight, length of scapular, intermuscle fat content of logissimus muscle, body weight at 240 day, glycolytic potential of logissimus muscle, mean corpuscular hemoglobin, mean corpuscular volume and humerus diameter.

Conclusion

We revealed the distribution of the unprecedented number of 565 CNVRs in pig genome and investigated copy number variable genes as the possible candidate genes for phenotypic traits. These findings give novel insights into porcine CNVs and provide resources to facilitate the identification of trait-related CNVs.

Copy number variations associated with obesity-related traits in African Americans: a joint analysis between GENOA and HyperGEN

Obesity is a highly heritable trait and a growing public health problem. African Americans (AAs) are a genetically diverse, yet understudied population with a high prevalence of obesity (BMI >30 kg/m(2)). Recent studies based upon single-nucleotide polymorphisms (SNPs) have identified genetic markers associated with obesity. However, a large proportion of the heritability of obesity remains unexplained. Copy number variation (CNV) has been cited as a possible source of missing heritability in common diseases such as obesity. We conducted a CNV genome-wide association study of BMI in two African-American cohorts from Genetic Epidemiology Network of Arteriopathy (GENOA) and Hypertension Genetic Epidemiology Network (HyperGEN). We performed independent and identical association analyses in each study, then combined the results in a meta-analysis. We identified three CNVs associated with BMI, obesity, and other obesity-related traits after adjusting for multiple testing. These CNVs overlap the PARK2, GYPA, and SGCZ genes. Our results suggest that CNV may play a role in the etiology of obesity in AAs.

Novel association approach for variable number tandem repeats (VNTRs) identifies DOCK5 as a susceptibility gene for severe obesity

Variable number tandem repeats (VNTRs) constitute a relatively under-examined class of genomic variants in the context of complex disease because of their sequence complexity and the challenges in assaying them. Recent large-scale genome-wide copy number variant mapping and association efforts have highlighted the need for improved methodology for association studies using these complex polymorphisms. Here we describe the in-depth investigation of a complex region on chromosome 8p21.2 encompassing the dedicator of cytokinesis 5 (DOCK5) gene. The region includes two VNTRs of complex sequence composition which flank a common 3975 bp deletion, all three of which were genotyped by polymerase chain reaction and fragment analysis in a total of 2744 subjects. We have developed a novel VNTR association method named VNTRtest, suitable for association analysis of multi-allelic loci with binary and quantitative outcomes, and have used this approach to show significant association of the DOCK5 VNTRs with childhood and adult severe obesity (P(empirical)= 8.9 × 10(-8) and P= 3.1 × 10(-3), respectively) which we estimate explains ~0.8% of the phenotypic variance. We also identified an independent association between the 3975 base pair (bp) deletion and obesity, explaining a further 0.46% of the variance (P(combined)= 1.6 × 10(-3)). Evidence for association between DOCK5 transcript levels and the 3975 bp deletion (P= 0.027) and both VNTRs (P(empirical)= 0.015) was also identified in adipose tissue from a Swedish family sample, providing support for a functional effect of the DOCK5 deletion and VNTRs. These findings highlight the potential role of DOCK5 in human obesity and illustrate a novel approach for analysis of the contribution of VNTRs to disease susceptibility through association studies.

Association of genetic variation in FTO with risk of obesity and type 2 diabetes with data from 96,551 East and South Asians

AIMS/HYPOTHESIS

FTO harbours the strongest known obesity-susceptibility locus in Europeans. While there is growing evidence for a role for FTO in obesity risk in Asians, its association with type 2 diabetes, independently of BMI, remains inconsistent. To test whether there is an association of the FTO locus with obesity and type 2 diabetes, we conducted a meta-analysis of 32 populations including 96,551 East and South Asians.

METHODS

All studies published on the association between FTO-rs9939609 (or proxy [r (2) > 0.98]) and BMI, obesity or type 2 diabetes in East or South Asians were invited. Each study group analysed their data according to a standardised analysis plan. Association with type 2 diabetes was also adjusted for BMI. Random-effects meta-analyses were performed to pool all effect sizes.

RESULTS

The FTO-rs9939609 minor allele increased risk of obesity by 1.25-fold/allele (p = 9.0 × 10(-19)), overweight by 1.13-fold/allele (p = 1.0 × 10(-11)) and type 2 diabetes by 1.15-fold/allele (p = 5.5 × 10(-8)). The association with type 2 diabetes was attenuated after adjustment for BMI (OR 1.10-fold/allele, p = 6.6 × 10(-5)). The FTO-rs9939609 minor allele increased BMI by 0.26 kg/m(2) per allele (p = 2.8 × 10(-17)), WHR by 0.003/allele (p = 1.2 × 10(-6)), and body fat percentage by 0.31%/allele (p = 0.0005). Associations were similar using dominant models. While the minor allele is less common in East Asians (12-20%) than South Asians (30-33%), the effect of FTO variation on obesity-related traits and type 2 diabetes was similar in the two populations.

CONCLUSIONS/INTERPRETATION

FTO is associated with increased risk of obesity and type 2 diabetes, with effect sizes similar in East and South Asians and similar to those observed in Europeans. Furthermore, FTO is also associated with type 2 diabetes independently of BMI.

Association of copy number variation in the AHI1 gene with risk of obesity in the Chinese population

OBJECTIVE

The prevalence of obesity has increased dramatically over the past decade. Gene copy number variants (CNVs) have been recognized as a hereditable source of susceptibility in human complex diseases including obesity. Recent studies have shown that Abelson helper integration site 1 (Ahi1) gene has a significant contribution in the homeostasis regulation in mouse models of obesity. A study was therefore carried out to investigate whether CNVs in AHI1 gene contribute to human obesity.

SUBJECTS AND METHODS

We analyzed samples from 70 Chinese overweight adults and 74 healthy controls for DNA copy number change using the Affymetrix single-nucleotide polymorphism (SNP) 6.0 array. Validation of CNVs of AHI1 was achieved by real-time PCR using the ΔΔC(t) method.

RESULTS

Copy number gain analysis revealed significant gains (P=0.0017) of AHI1 gene copy number in 17 of 70 (24.3%) samples but only four of 74 (5.4%) controls overall. Then we studied the frequency distribution of CNVs in AHI1 gene according to body mass index (BMI) grade. Five out of 28 (18.5%) at-risk obese, six out of 26 (26.9%) moderate obese, and six out of 17 (29.4%) severe obese subjects studied showed increased AHI1 gene copy number.

CONCLUSIONS

The result suggested that there was a significant linear trend for increasing AHI1 gene copy number frequencies with increasing BMI.

Ethnic differentiation of copy number variation on chromosome 16p12.3 for association with obesity phenotypes in European and Chinese populations

OBJECTIVE

Genomic copy number variations (CNVs) have been strongly implicated as important genetic factors for obesity. A recent genome-wide association study identified a novel variant, rs12444979, which is in high linkage disequilibrium with CNV 16p12.3, for association with obesity in Europeans. The aim of this study was to directly examine the relationship between the CNV 16p12.3 and obesity phenotypes, including body mass index (BMI) and body fat mass.

SUBJECTS

Subjects were a multi-ethnic sample, including 2286 unrelated subjects from a European population and 1627 unrelated Han subjects from a Chinese population. Body fat mass was measured using dual energy X-ray absorptiometry.

RESULTS

Using Affymetrix Genome-Wide Human SNP Array 6.0, we directly detected CNV 16p12.3, with the deletion frequency of 27.26 and 0.8% in the European and Chinese populations, respectively. We confirmed the significant association between this CNV and obesity (BMI: P=1.38 × 10(-2); body fat mass: P=2.13 × 10(-3)) in the European population. Less copy numbers were associated with lower BMI and body fat mass, and the effect size was estimated to be 0.62 (BMI) and 1.41 (body fat mass), respectively. However, for the Chinese population, we did not observe significant association signal, and the frequencies of this deletion CNV are quite different between the European and Chinese populations (P<0.001).

CONCLUSION

Our findings first suggest that CNV 16p12.3 might be ethnic specific and cause ethnic phenotypic diversity, which may provide some new clues into the understanding of the genetic architecture of obesity.

Behavioural genetics of childhood disorders

After a general introduction into genetic risk factors for child psychiatric disorders, four specific child psychiatric disorders with a strong genetic component, namely, Autism Spectrum Disorders, Attention Deficit / Hyperactivity Disorder, Nocturnal Enuresis, and obesity, are discussed in detail. Recent evidence of linkage, candidate gene, and genome-wide association studies are presented. This chapter ends with a prospectus on further research needs.

Copy number variants in obesity-related syndromes: review and perspectives on novel molecular approaches

In recent decades, obesity has reached epidemic proportions worldwide and became a major concern in public health. Despite heritability estimates of 40 to 70% and the long-recognized genetic basis of obesity in a number of rare cases, the list of common obesity susceptibility variants by the currently published genome-wide association studies (GWASs) only explain a small proportion of the individual variation in risk of obesity. It was not until very recently that GWASs of copy number variants (CNVs) in individuals with extreme phenotypes reported a number of large and rare CNVs conferring high risk to obesity, and specifically deletions on chromosome 16p11.2. In this paper, we comment on the recent advances in the field of genetics of obesity with an emphasis on the genes and genomic regions implicated in highly penetrant forms of obesity associated with developmental disorders. Array genomic hybridization in this patient population has afforded discovery opportunities for CNVs that have not previously been detectable. This information can be used to generate new diagnostic arrays and sequencing platforms, which will likely enhance detection of known genetic conditions with the potential to elucidate new disease genes and ultimately help in developing a next-generation sequencing protocol relevant to clinical practice.

Molecular basis of obesity: current status and future prospects

Obesity is a global health problem that is gradually affecting each continent of the world. Obesity is a heterogeneous disorder, and the biological causes of obesity are complex. The rapid increase in obesity prevalence during the past few decades is due to major societal changes (sedentary lifestyle, over-nutrition) but who becomes obese at the individual level is determined to a great extent by genetic susceptibility. In this review, we evidence that obesity is a strongly heritable disorder, and provide an update on the molecular basis of obesity. To date, nine loci have been involved in Mendelian forms of obesity and 58 loci contribute to polygenic obesity, and rare and common structural variants have been reliably associated with obesity. Most of the obesity genes remain to be discovered, but promising technologies, methodologies and the use of “deep phenotyping” lead to optimism to chip away at the ‘missing heritability’ of obesity in the near future. In the longer term, the genetic dissection of obesity will help to characterize disease mechanisms, provide new targets for drug design, and lead to an early diagnosis, treatment, and prevention of obesity.

Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV

MOTIVATION

The ability to detect copy-number variation (CNV) and loss of heterozygosity (LOH) from exome sequencing data extends the utility of this powerful approach that has mainly been used for point or small insertion/deletion detection.

RESULTS

We present ExomeCNV, a statistical method to detect CNV and LOH using depth-of-coverage and B-allele frequencies, from mapped short sequence reads, and we assess both the method's power and the effects of confounding variables. We apply our method to a cancer exome resequencing dataset. As expected, accuracy and resolution are dependent on depth-of-coverage and capture probe design.

AVAILABILITY

CRAN package 'ExomeCNV'.

CONTACT

fsathira@fas.harvard.edu; snelson@ucla.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.