On the association of common and rare genetic variation influencing body mass index: a combined SNP and CNV analysis

High Olfactory Receptor-Rich 11q11 Copy Number in Girls and African American Children

Copy number variants (CNVs) provide numerous genetic differences between individuals, and they have been linked with multiple human diseases. Obesity is one of the highly heritable complex disorders, which is associated with copy number variance (CNV). A recent report shows that the 11q11 gene, a novel olfactory receptor, and its copy number variants are involved in the early onset of obesity. In the current study, we analyzed the 11q11 gene copy number variance (CNV) based on gender in White/European American (EA) and African American (AA) normal weight and overweight/obese children. Sixty-nine boys and fifty-eight girls between the ages of 6 and 10 years belonging to either EA or AA ethnicity were involved in this study. As per World Health Organization (WHO) guidelines, each participant’s body weight and height were recorded. DNA was extracted from saliva, and the copy number variants for the 11q11 gene were measured using digital PCR. The descriptive analysis of the 11q11 copy number showed significantly more copies in girls compared to boys; similarly, AA participants had significantly increased CNV compared to EA. The normal weight (NW) and overweight/obese (OW/OB) girls were significantly less likely to belong to the low copy number variant (LCNV) group of 11q11 compared to boys; similarly, NW and OW/OB AA children were significantly less likely to belong to the LCNV group. The AA girls in LCNV had significantly higher BMI z-scores. Our findings suggest that the 11q11 copy number in children is race and gender-specific.

Weighting approaches for a genetic risk score and an oxidative stress score for predicting the incidence of obesity

BACKGROUND

We aimed to predict the incidence of obesity in a Korean population using a genetic risk score (GRS) constructed with obesity-related single nucleotide polymorphisms (SNPs) along with an oxidative stress score (OSS).

METHODS

A total of 9460 Korean subjects and 356 974 SNPs were included. The GRS was constructed using three significant obesity-related SNP loci, and the OSS was calculated with three reliable oxidative stress biomarkers.

RESULTS

The GRS showed a more significant association with increased obesity (OR = 2.879) than did individual SNPs after adjusting for age and sex. Three oxidative stress biomarkers, including malondialdehyde, oxidized low-density lipoprotein, and 8-epi-prostaglandin F_2α , showed significantly high levels in the obese group. The OSS, which was the sum of each oxidative stress biomarker score, showed a markedly high association with the incidence of obesity, with an OR of 3.213. Based on the results of the regression tests and a receiver-operating characteristic (ROC) curve analysis, we found that HOMA-IR, high-sensitivity C-reactive protein (hs-CRP), the GRS, and the OSS were the most relevant factors for the increased risk of obesity and were significantly associated with the incidence of obesity. The area under the ROC curve was improved when the GRS was added to the model (from 74.2% to 75.1%).

CONCLUSIONS

We first identified that subjects with an obesity GRS and a high OSS might have a higher risk of obesity. Our findings and weighting approaches were effective in predicting the incidence of obesity; furthermore, the GRS is a relevant factor that significantly predicts the risk of obesity.

Simultaneous detection of target CNVs and SNVs of thalassemia by multiplex PCR and next‑generation sequencing

Thalassemia is caused by complex mechanisms, including copy number variants (CNVs) and single nucleotide variants (SNVs). The CNV types of α‑thalassemia are typically detected by gap‑polymerase chain reaction (PCR). The SNV types are detected by Sanger sequencing. In the present study, a novel method was developed that simultaneously detects CNVs and SNVs by multiplex PCR and next‑generation sequencing (NGS). To detect CNVs, 33 normal samples were used as a cluster of control values to build a baseline, and the A, B, C, and D ratios were developed to evaluate‑SEA, ‑α4.2, ‑α3.7, and compound or homozygous CNVs, respectively. To detect other SNVs, sequencing data were analyzed using the system's software and annotated using Annovar software. In a test of performance, 128 patients with thalassemia were detected using the method developed and were confirmed by Sanger sequencing and gap‑PCR. Four different CNV types were clearly distinguished by the developed algorithm, with ‑SEA, ‑α3.7, ‑α4.2, and compound or homozygous deletions. The sensitivities for each CNV type were 96.72% (59/61), 97.37% (37/38), 83.33% (10/12) and 95% (19/20), and the specificities were 93.94% (32/33), 93.94% (32/33), 100% (33/33) and 100% (33/33), respectively. The SNVs detected were consistent with those of the Sanger sequencing.

Effect of Auriculotherapy on the Plasma Concentration of Biomarkers in Individuals with Knee Osteoarthritis

Knee osteoarthritis (KOA) is one of the most frequent noncommunicable diseases with pain associated symptoms and affects the musculoskeletal system. Various forms of treatment can be indicated, and nonpharmacological treatment is also an available option for the management of KOA individuals. For instance, auriculotherapy (AT) is one possible procedure associated with the Traditional Chinese Medicine for dealing with KOA. It is believed that the concentration of certain biomarkers could be altered in individuals with KOA after AT. The aim of this study was to evaluate the effect of AT on plasma concentration of biomarkers in KOA individuals. This intervention is a controlled trial. Twenty-one subjects were grouped in two groups and submitted to AT with the stimulation of the Shen Men, kidney, and knee points in the treatment group or different points in the control group, once a week for 5 weeks. Blood was collected before the beginning of protocols and a week after the last session. Kolmogorov-Smirnov and Wilcoxon tests were performed, and a p ≤ 0.05 was considered statistically significant. Hematological parameters did not show any significant variation between the control group and treated group. Concerning the biochemical parameters, a significant reduction of direct bilirubin (from 43.31 ± 22.10 to 21.21 ± 5.30 μmol/L, p = 0.003), aspartate aminotransferase (from 0.48 ± 0.16 to 0.38 ± 0.09 μKat/L, p = 0.010), and triglycerides (from 7.04 ± 2.90 to 5.45 ± 2.57 mmol/L, p = 0.008) in the treated group was obtained. In conclusion, the analysis of results suggests that AT might be a useful intervention for the management of KOA individuals.

Estimating the causal effect of body mass index on hay fever, asthma and lung function using Mendelian randomization

BACKGROUND

Observational studies have shown that body mass index (BMI) is positively associated with asthma. However, observational data are prone to confounding and reverse causation. In Mendelian randomization, genetic variants are used as unconfounded markers of exposures to examine causal effects. We examined the causal effect of BMI on asthma, hay fever, allergic sensitization, serum total immunoglobulin E (IgE), forced expiratory volume in one-second (FEV1) and forced vital capacity (FVC).

METHODS

We included 490 497 participants in the observational and 162 124 participants in the genetic analyses. A genetic risk score (GRS) was created using 26 BMI-associated single nucleotide polymorphisms (SNPs). Results were pooled in meta-analyses and expressed as odds ratios (ORs) or β-estimates with 95% confidence interval (CI).

RESULTS

The GRS was significantly associated with asthma (OR=1.009; 95% CI: 1.004, 1.013), but not with hay fever (OR= 0.998; 95% CI: 0.994, 1.002) or allergic sensitization (OR=0.999; 95% CI: 0.986, 1.012) per BMI-increasing allele. The GRS was significantly associated with decrease in FEV1: β=-0.0012 (95% CI: -0.0019, -0.0006) and FVC: β=-0.0022 (95% CI: -0.0031, -0.0014) per BMI-increasing allele. Effect sizes estimated by instrumental variable analyses were OR=1.07 (95% CI: 1.03, 1.10) for asthma, a 9 ml decrease in FEV1 (95% CI: 2.0-15 mL decrease) and a 16 ml decrease in FVC (95% CI: 7.0-24 mL decrease) per 1 kg/m² higher BMI.

CONCLUSIONS

The results support the conclusion that increasing BMI is causally related to higher prevalence of asthma and decreased lung function, but not with hay fever or biomarkers of allergy.

CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits

There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01–0.2%), with large effects on height (>2.4 cm), weight (>5 kg), and body mass index (BMI) (>3.5 kg/m²). Burden analysis shows a 0.41 cm decrease in height, a 0.003 increase in waist-to-hip ratio and increase in BMI by 0.14 kg/m² for each Mb of total deletion burden (P = 2.5 × 10⁻¹⁰, 6.0 × 10⁻⁵, and 2.9 × 10⁻³). Our study provides evidence that the same genes (e.g., MC4R, FIBIN, and FMO5) harbor both common and rare variants affecting body size and that anthropometric traits share genetic loci with developmental and psychiatric disorders.

Individual SNPs have small effects on anthropometric traits, yet the impact of CNVs has remained largely unknown. Here, Kutalik and co-workers perform a large-scale genome-wide meta-analysis of structural variation and find rare CNVs associated with height, weight and BMI with large effect sizes.

BMI prediction within a Korean population

BACKGROUND

Body Mass Index (BMI) is widely regarded as an important clinical trait for obesity and other diseases such as Type 2 diabetes, coronary heart disease, and osteoarthritis.

METHODS

This study uses 6,011 samples of genotype data from ethnic Korean subjects. The data was retrieved from the Korea Association Resource. To identify the BMI-related markers within the Korean population, we collected genome-wide association study (GWAS) markers using a GWAS catalog and also obtained other markers from nearby regions. Of the total 6,011 samples, 5,410 subjects were used as part of a single nucleotide polymorphism (SNP) selection set in order to identify the overlapping BMI-associated SNPs within a 10-fold cross validation.

RESULTS

We selected nine SNPs (rs12566985 (FPGT-TNNI3K), rs6545809 (ADCY3), rs2943634 (located near LOC646736), rs734597 (located near TFAP2B), rs11030104 (BDNF), rs7988412 (GTF3A), rs2241423 (MAP2K5), rs7202116 (FTO), and rs6567160 (located near LOC105372152) to assist in BMI prediction. The calculated weighted genetic risk scores based on the selected 9 SNPs within the SNP selection set were applied to the final validation set consisting of 601 samples. Our results showed upward trends in the BMI values (P < 0.0001) within the 10-fold cross validation process for R² > 0.22. These trends were also observed within the validation set for all subjects, as well as within the validation sets divided by gender (P < 0.0001, R² > 0.46).

DISCUSSION

The set of nine SNPs identified in this study may be useful for prospective predictions of BMI.

Copy number variations in "classical" obesity candidate genes are not frequently associated with severe early-onset obesity in children

BACKGROUND

Obesity is genetically heterogeneous and highly heritable, although polymorphisms explain the phenotype in only a small proportion of obese children. We investigated the presence of copy number variations (CNVs) in "classical" genes known to be associated with (monogenic) early-onset obesity in children.

METHODS

In 194 obese Caucasian children selected for early-onset and severe obesity from our obesity cohort we screened for deletions and/or duplications by multiplex ligation-dependent probe amplification reaction (MLPA). As we found one MLPA probe to interfere with a polymorphism in SIM1 we investigated its association with obesity and other phenotypic traits in our extended cohort of 2305 children.

RESULTS

In the selected subset of most severely obese children, we did not find CNV with MLPA in POMC, LEP, LEPR, MC4R, MC3R or MC2R genes. However, one SIM1 probe located at exon 9 gave signals suggestive for SIM1 insufficiency in 52 patients. Polymerase chain reaction (PCR) analysis identified this as a false positive result due to interference with single nucleotide polymorphism (SNP) rs3734354/rs3734355. We, therefore, investigated for associations of this polymorphism with obesity and metabolic traits in our extended cohort. We found rs3734354/rs3734355 to be associated with body mass index-standard deviation score (BMI-SDS) (p = 0.003), but not with parameters of insulin metabolism, blood pressure or food intake.

CONCLUSIONS

In our modest sample of severely obese children, we were unable to find CNVs in well-established monogenic obesity genes. Nevertheless, we found an association of rs3734354 in SIM1 with obesity of early-onset type in children, although not with obesity-related traits.

Nutrigenomics in the modern era

The concept that interactions between nutrition and genetics determine phenotype was established by Garrod at the beginning of the 20th century through his ground-breaking work on inborn errors of metabolism. A century later, the science and technologies involved in sequencing of the human genome stimulated development of the scientific discipline which we now recognise as nutritional genomics (nutrigenomics). Much of the early hype around possible applications of this new science was unhelpful and raised expectations, which have not been realised as quickly as some would have hoped. However, major advances have been made in quantifying the contribution of genetic variation to a wide range of phenotypes and it is now clear that for nutrition-related phenotypes, such as obesity and common complex diseases, the genetic contribution made by SNP alone is often modest. There is much scope for innovative research to understand the roles of less well explored types of genomic structural variation, e.g. copy number variants, and of interactions between genotype and dietary factors, in phenotype determination. New tools and models, including stem cell-based approaches and genome editing, have huge potential to transform mechanistic nutrition research. Finally, the application of nutrigenomics research offers substantial potential to improve public health e.g. through the use of metabolomics approaches to identify novel biomarkers of food intake, which will lead to more objective and robust measures of dietary exposure. In addition, nutrigenomics may have applications in the development of personalised nutrition interventions, which may facilitate larger, more appropriate and sustained changes in eating (and other lifestyle) behaviours and help to reduce health inequalities.

Weighted Genetic Risk Scores and Prediction of Weight Gain in Solid Organ Transplant Populations

Background

Polygenic obesity in Solid Organ Transplant (SOT) populations is considered a risk factor for the development of metabolic abnormalities and graft survival. Few studies to date have studied the genetics of weight gain in SOT recipients. We aimed to determine whether weighted genetic risk scores (w-GRS) integrating genetic polymorphisms from GWAS studies (SNP group#1 and SNP group#2) and from Candidate Gene studies (SNP group#3) influence BMI in SOT populations and if they predict ≥10% weight gain (WG) one year after transplantation. To do so, two samples (n_A = 995, n_B = 156) were obtained from naturalistic studies and three w-GRS were constructed and tested for association with BMI over time. Prediction of 10% WG at one year after transplantation was assessed with models containing genetic and clinical factors.

Results

w-GRS were associated with BMI in sample A and B combined (BMI increased by 0.14 and 0.11 units per additional risk allele in SNP group#1 and #2, respectively, p-values<0.008). w-GRS of SNP group#3 showed an effect of 0.01 kg/m² per additional risk allele when combining sample A and B (p-value 0.04). Models with genetic factors performed better than models without in predicting 10% WG at one year after transplantation.

Conclusions

This is the first study in SOT evaluating extensively the association of w-GRS with BMI and the influence of clinical and genetic factors on 10% of WG one year after transplantation, showing the importance of integrating genetic factors in the final model. Genetics of obesity among SOT recipients remains an important issue and can contribute to treatment personalization and prediction of WG after transplantation.

Associations of genetic risk scores based on adult adiposity pathways with childhood growth and adiposity measures

BACKGROUND

Results from genome-wide association studies (GWAS) identified many loci and biological pathways that influence adult body mass index (BMI). We aimed to identify if biological pathways related to adult BMI also affect infant growth and childhood adiposity measures.

METHODS

We used data from a population-based prospective cohort study among 3,975 children with a mean age of 6 years. Genetic risk scores were constructed based on the 97 SNPs associated with adult BMI previously identified with GWAS and on 28 BMI related biological pathways based on subsets of these 97 SNPs. Outcomes were infant peak weight velocity, BMI at adiposity peak and age at adiposity peak, and childhood BMI, total fat mass percentage, android/gynoid fat ratio, and preperitoneal fat area. Analyses were performed using linear regression models.

RESULTS

A higher overall adult BMI risk score was associated with infant BMI at adiposity peak and childhood BMI, total fat mass, android/gynoid fat ratio, and preperitoneal fat area (all p-values < 0.05). Analyses focused on specific biological pathways showed that the membrane proteins genetic risk score was associated with infant peak weight velocity, and the genetic risk scores related to neuronal developmental processes, hypothalamic processes, cyclicAMP, WNT-signaling, membrane proteins, monogenic obesity and/or energy homeostasis, glucose homeostasis, cell cycle, and muscle biology pathways were associated with childhood adiposity measures (all p-values <0.05). None of the pathways were associated with childhood preperitoneal fat area.

CONCLUSIONS

A genetic risk score based on 97 SNPs related to adult BMI was associated with peak weight velocity during infancy and general and abdominal fat measurements at the age of 6 years. Risk scores based on genetic variants linked to specific biological pathways, including central nervous system and hypothalamic processes, influence body fat development from early life onwards.

A genome-wide assessment of rare copy number variants in colorectal cancer

Colorectal cancer (CRC) is a complex disease with an estimated heritability of approximately 35%. However, known CRC-related common single nucleotide polymorphisms (SNPs) can only explain ~0.65% of the heritability. This “missing heritability” may be explained partially by rare copy number variants (CNVs). In this study, we performed a genome-wide scan using Illumina Human-Omni Express BeadChip, 694 sporadic CRC cases and 1641 controls were eventually included in our analysis after quality control. The global burden analysis revealed a 1.53-fold excess of rare CNVs in CRC cases compared with controls (P < 1 × 10⁻⁶), and the difference being more pronounced for genic rare CNVs and CNVs overlapped with coding regions (1.65-fold and 1.84-fold, respectively, both P < 1 × 10⁻⁶). Interestingly, both the cases in the lowest and middle tertile of age carried a higher burden of rare CNVs comparing to the highest tertile. Furthermore, 639 CNV-disrupted genes exclusive to CRC cases were found to be significantly enriched in gene ontology (GO) terms concerning nucleosome assembly and olfactory receptor activity. Our study was the first to evaluate the burden of rare CNVs in sporadic CRC and suggested that rare CNVs contributed to the missing heritability of CRC.

Genome-wide identification of copy number variations between two chicken lines that differ in genetic resistance to Marek's disease

Background

Copy number variation (CNV) is a major source of genome polymorphism that directly contributes to phenotypic variation such as resistance to infectious diseases. Lines 6₃ and 7₂ are two highly inbred experimental chicken lines that differ greatly in susceptibility to Marek’s disease (MD), and have been used extensively in efforts to identify the genetic and molecular basis for genetic resistance to MD. Using next generation sequencing, we present a genome-wide assessment of CNVs that are potentially associated with genetic resistance to MD.

Methods

Three chickens randomly selected from each line were sequenced to an average depth of 20×. Two popular software, CNVnator and Pindel, were used to call genomic CNVs separately. The results were combined to obtain a union set of genomic CNVs in the two chicken lines.

Results

A total of 5,680 CNV regions (CNVRs) were identified after merging the two datasets, of which 1,546 and 1,866 were specific to the MD resistant or susceptible line, respectively. Over half of the line-specific CNVRs were shared by 2 or more chickens, reflecting the reduced diversity in both inbred lines. The CNVRs fixed in the susceptible lines were significantly enriched in genes involved in MAPK signaling pathway. We also found 67 CNVRs overlapping with 62 genes previously shown to be strong candidates of the underlying genes responsible for the susceptibility to MD.

Conclusions

Our findings provide new insights into the genetic architecture of the two chicken lines and additional evidence that MAPK signaling pathway may play an important role in host response to MD virus infection. The rich source of line-specific CNVs is valuable for future disease-related association studies in the two chicken lines.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2080-5) contains supplementary material, which is available to authorized users.

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.