Using epigenomic studies in monozygotic twins to improve our understanding of cancer

Cancer is a set of diseases that exhibit not only genetic mutations but also a profoundly distorted epigenetic landscape. Over the last two decades, great advances have been made in identifying these alterations and their importance in the initiation and progression of cancer. Epigenetic changes can be seen from the very early stages in tumorigenesis and dysregulation of the epigenome has an increasingly acknowledged pathogenic role. Epigenomic twin studies have great potential to contribute to our understanding of complex diseases, such as cancer. This is because the use of monozygotic twins discordant for cancer enables epigenetic variation analysis without the confounding influence of the constitutive genetic background, age or cohort effects. It therefore allows the identification of susceptibility loci that may be sensitive to modification by the environment. These studies into cancer etiology will potentially lead to robust epigenetic markers for the detection and risk assessment of cancer.

An integrated epigenomic analysis for type 2 diabetes susceptibility loci in monozygotic twins

DNA methylation has a great potential for understanding the aetiology of common complex traits such as Type 2 diabetes (T2D). Here we perform genome-wide methylated DNA immunoprecipitation sequencing (MeDIP-seq) in whole-blood-derived DNA from 27 monozygotic twin pairs and follow up results with replication and integrated omics analyses. We identify predominately hypermethylated T2D-related differentially methylated regions (DMRs) and replicate the top signals in 42 unrelated T2D cases and 221 controls. The strongest signal is in the promoter of the MALT1 gene, involved in insulin and glycaemic pathways, and related to taurocholate levels in blood. Integrating the DNA methylome findings with T2D GWAS meta-analysis results reveals a strong enrichment for DMRs in T2D-susceptibility loci. We also detect signals specific to T2D-discordant twins in the GPR61 and PRKCB genes. These replicated T2D associations reflect both likely causal and consequential pathways of the disease. The analysis indicates how an integrated genomics and epigenomics approach, utilizing an MZ twin design, can provide pathogenic insights as well as potential drug targets and biomarkers for T2D and other complex traits.

Type 2 diabetes (T2D) is a highly heterogeneous disease with a strong genetic component. Here the authors examine genome-wide methylation patterns in T2D-discordant, T2D-concordant and healthy concordant monozygotic twin pairs, and identify DNA methylation signals that may represent new biomarkers or drug targets for T2D.

Human-specific CpG 'beacons' identify human-specific prefrontal cortex H3K4me3 chromatin peaks

BACKGROUND

Targeted recruitment of chromatin-modifying enzymes to clusters of CpG dinucleotides contributes toward the formation of accessible chromatin. By interprimate comparison we previously identified the set of nonpolymorphic human-specific CpGs (CpG 'beacons') and revealed that these loci were enriched for human disease traits. Due to their human-specific CpG density change, extreme CpG 'beacon' clusters (≥20 CpG beacons/kb) were predicted to identify permissive chromatin peaks within the human genome.

AIM

We set out to explore these sequence-defined regions for evidence of an active chromatin signature.

RESULTS

Using available comparative primate epigenomic data from neurons of the prefrontal cortex, we show that these CpG 'beacon' clusters are indeed enriched for being human-specific H3K4me3 peaks (χ(2): p < 2.2 × 10(-16)) and thus predictive of permissive chromatin states. These sequence regions had a higher predictive value than previous selective analyses. We also show that both human-specific H3K4me3 and CpG 'beacon' clusters are increased within current and ancestral telomeric regions, supporting an association with recombination, which is higher towards the distal ends of chromosomes.

CONCLUSION

Therefore, CpG-focused comparative sequence analysis can precisely pinpoint chromatin structures that contribute to the human-specific phenotype and further supports an integrated approach in genomic and epigenomic studies.

Human-specific epigenetic variation in the immunological Leukotriene B4 Receptor (LTB4R/BLT1) implicated in common inflammatory diseases

BACKGROUND

Common human diseases are caused by the complex interplay of genetic susceptibility as well as environmental factors. Due to the environment's influence on the epigenome, and therefore genome function, as well as conversely the genome's facilitative effect on the epigenome, analysis of this level of regulation may increase our knowledge of disease pathogenesis.

METHODS

In order to identify human-specific epigenetic influences, we have performed a novel genome-wide DNA methylation analysis comparing human, chimpanzee and rhesus macaque.

RESULTS

We have identified that the immunological Leukotriene B4 receptor (LTB4R, BLT1 receptor) is the most epigenetically divergent human gene in peripheral blood in comparison with other primates. This difference is due to the co-ordinated active state of human-specific hypomethylation in the promoter and human-specific increased gene body methylation. This gene is significant in innate immunity and the LTB4/LTB4R pathway is involved in the pathogenesis of the spectrum of human inflammatory diseases. This finding was confirmed by additional neutrophil-only DNA methylome and lymphoblastoid H3K4me3 chromatin comparative data. Additionally we show through functional analysis that this receptor has increased expression and a higher response to the LTB4 ligand in human versus rhesus macaque peripheral blood mononuclear cells. Genome-wide we also find human species-specific differentially methylated regions (human s-DMRs) are more prevalent in CpG island shores than within the islands themselves, and within the latter are associated with the CTCF motif.

CONCLUSIONS

This result further emphasises the exclusive nature of the human immunological system, its divergent adaptation even from very closely related primates, and the power of comparative epigenomics to identify and understand human uniqueness.

The long-time chronoamperometric current at an inlaid microband (or laminar) electrode

In this article, we derive an approximate asymptotic analytical expression for the long-time chronoamperometric current response at an inlaid microband (or laminar) electrode. The expression is applicable when the length of the microband is much greater than the width, so that the diffusion of the electrochemical species can be regarded as two-dimensional. We extend the previously known result for the diffusion-limited current response (Aoki, K. et al. J. Electroanal. Chem. 1987, 225, 19–32 and Phillips, C.G. J. Electroanal. Chem. 1992, 333, 11–32) to accommodate quasi-reversible reactions and unequal diffusion coefficients of the oxidant and the reductant. Comparison with numerical calculations validates the analytical expression, and we demonstrate that unequal diffusion coefficients can substantially change the current response. Finally, we discuss the form of the long-time current response for a one-step, one-electron redox reaction if the rate constants are modelled in the Butler–Volmer framework, and indicate the importance of choosing the width of the microband appropriately to allow accurate experimental determination of the standard kinetic rate constant and the electron transfer coefficient.

Human-specific CpG "beacons" identify loci associated with human-specific traits and disease

Regulatory change has long been hypothesized to drive the delineation of the human phenotype from other closely related primates. Here we provide evidence that CpG dinucleotides play a special role in this process. CpGs enable epigenome variability via DNA methylation, and this epigenetic mark functions as a regulatory mechanism. Therefore, species-specific CpGs may influence species-specific regulation. We report non-polymorphic species-specific CpG dinucleotides (termed “CpG beacons”) as a distinct genomic feature associated with CpG island (CGI) evolution, human traits and disease. Using an inter-primate comparison, we identified 21 extreme CpG beacon clusters (≥ 20/kb peaks, empirical p < 1.0 × 10⁻³) in humans, which include associations with four monogenic developmental and neurological disease related genes (Benjamini-Hochberg corrected p = 6.03 × 10⁻³). We also demonstrate that beacon-mediated CpG density gain in CGIs correlates with reduced methylation in these species in orthologous CGIs over time, via human, chimpanzee and macaque MeDIP-seq. Therefore mapping into both the genomic and epigenomic space the identified CpG beacon clusters define points of intersection where a substantial two-way interaction between genetic sequence and epigenetic state has occurred. Taken together, our data support a model for CpG beacons to contribute to CGI evolution from genesis to tissue-specific to constitutively active CGIs.

Identification of type 1 diabetes-associated DNA methylation variable positions that precede disease diagnosis

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.

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.

Integration of genomic and epigenomic DNA methylation data in common complex diseases by haplotype-specific methylation analysis

The analysis of complex diseases was revolutionized by the ability to genotype at a genome-wide level tagging common SNPs in sufficiently large, and therefore adequately powered, population sample sets. This technological breakthrough has led to thousands of genetic variants being robustly associated with a multitude of phenotypic traits. These findings have illuminated novel genes and previously unknown pathways in the pathogenesis of disease, although in the majority of loci the functional mechanism remains unknown. The integration of this genomic information with epigenomic and transcriptomic data from these regions is one of the next steps in unraveling their biological significance. Allele-specific methylation influences allele-specific expression; therefore, the methylation state of the haplotypes within genetically associated regions can determine epigenetic differences with potential functional effects. DNA methylation data and association-determined risk and nonrisk haplotypes can be compared by a haplotype-specific methylation analysis. These are the first forays into what will become an increasingly routine multidimensional analysis as whole-genome, epigenome and transcriptome sequencing data become easily obtainable, with existing second- and soon to be available third-generation sequencing analyzers. Concise understanding of the functional implications of these genome-wide association-derived risk factors, plus rare variants discovered from deep sequencing experiments currently underway, will enable personalized risk and prevention profiling, as well as treatment, to come to fruition.

Integrated genetic and epigenetic analysis identifies haplotype-specific methylation in the FTO type 2 diabetes and obesity susceptibility locus

Recent multi-dimensional approaches to the study of complex disease have revealed powerful insights into how genetic and epigenetic factors may underlie their aetiopathogenesis. We examined genotype-epigenotype interactions in the context of Type 2 Diabetes (T2D), focussing on known regions of genomic susceptibility. We assayed DNA methylation in 60 females, stratified according to disease susceptibility haplotype using previously identified association loci. CpG methylation was assessed using methylated DNA immunoprecipitation on a targeted array (MeDIP-chip) and absolute methylation values were estimated using a Bayesian algorithm (BATMAN). Absolute methylation levels were quantified across LD blocks, and we identified increased DNA methylation on the FTO obesity susceptibility haplotype, tagged by the rs8050136 risk allele A (p = 9.40×10⁻⁴, permutation p = 1.0×10⁻³). Further analysis across the 46 kb LD block using sliding windows localised the most significant difference to be within a 7.7 kb region (p = 1.13×10⁻⁷). Sequence level analysis, followed by pyrosequencing validation, revealed that the methylation difference was driven by the co-ordinated phase of CpG-creating SNPs across the risk haplotype. This 7.7 kb region of haplotype-specific methylation (HSM), encapsulates a Highly Conserved Non-Coding Element (HCNE) that has previously been validated as a long-range enhancer, supported by the histone H3K4me1 enhancer signature. This study demonstrates that integration of Genome-Wide Association (GWA) SNP and epigenomic DNA methylation data can identify potential novel genotype-epigenotype interactions within disease-associated loci, thus providing a novel route to aid unravelling common complex diseases.

The epigenomic interface between genome and environment in common complex diseases

The epigenome plays the pivotal role as interface between genome and environment. True genome-wide assessments of epigenetic marks, such as DNA methylation (methylomes) or chromatin modifications (chromatinomes), are now possible, either through high-throughput arrays or increasingly by second-generation DNA sequencing methods. The ability to collect these data at this level of resolution enables us to begin to be able to propose detailed questions, and interrogate this information, with regards to changes that occur due to development, lineage and tissue-specificity, and significantly those caused by environmental influence, such as ageing, stress, diet, hormones or toxins. Common complex traits are under variable levels of genetic influence and additionally epigenetic effect. The detection of pathological epigenetic alterations will reveal additional insights into their aetiology and how possible environmental modulation of this mechanism may occur. Due to the reversibility of these marks, the potential for sequence-specific targeted therapeutics exists. This review surveys recent epigenomic advances and their current and prospective application to the study of common diseases.

Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus

BACKGROUND

Diabetic nephropathy is a serious complication of diabetes mellitus and is associated with considerable morbidity and high mortality. There is increasing evidence to suggest that dysregulation of the epigenome is involved in diabetic nephropathy. We assessed whether epigenetic modification of DNA methylation is associated with diabetic nephropathy in a case-control study of 192 Irish patients with type 1 diabetes mellitus (T1D). Cases had T1D and nephropathy whereas controls had T1D but no evidence of renal disease.

METHODS

We performed DNA methylation profiling in bisulphite converted DNA from cases and controls using the recently developed Illumina Infinium HumanMethylation27 BeadChip, that enables the direct investigation of 27,578 individual cytosines at CpG loci throughout the genome, which are focused on the promoter regions of 14,495 genes.

RESULTS

Singular Value Decomposition (SVD) analysis indicated that significant components of DNA methylation variation correlated with patient age, time to onset of diabetic nephropathy, and sex. Adjusting for confounding factors using multivariate Cox-regression analyses, and with a false discovery rate (FDR) of 0.05, we observed 19 CpG sites that demonstrated correlations with time to development of diabetic nephropathy. Of note, this included one CpG site located 18 bp upstream of the transcription start site of UNC13B, a gene in which the first intronic SNP rs13293564 has recently been reported to be associated with diabetic nephropathy.

CONCLUSION

This high throughput platform was able to successfully interrogate the methylation state of individual cytosines and identified 19 prospective CpG sites associated with risk of diabetic nephropathy. These differences in DNA methylation are worthy of further follow-up in replication studies using larger cohorts of diabetic patients with and without nephropathy.

Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus

BACKGROUND

Diabetic nephropathy is a serious complication of diabetes mellitus and is associated with considerable morbidity and high mortality. There is increasing evidence to suggest that dysregulation of the epigenome is involved in diabetic nephropathy. We assessed whether epigenetic modification of DNA methylation is associated with diabetic nephropathy in a case-control study of 192 Irish patients with type 1 diabetes mellitus (T1D). Cases had T1D and nephropathy whereas controls had T1D but no evidence of renal disease.

METHODS

We performed DNA methylation profiling in bisulphite converted DNA from cases and controls using the recently developed Illumina Infinium HumanMethylation27 BeadChip, that enables the direct investigation of 27,578 individual cytosines at CpG loci throughout the genome, which are focused on the promoter regions of 14,495 genes.

RESULTS

Singular Value Decomposition (SVD) analysis indicated that significant components of DNA methylation variation correlated with patient age, time to onset of diabetic nephropathy, and sex. Adjusting for confounding factors using multivariate Cox-regression analyses, and with a false discovery rate (FDR) of 0.05, we observed 19 CpG sites that demonstrated correlations with time to development of diabetic nephropathy. Of note, this included one CpG site located 18 bp upstream of the transcription start site of UNC13B, a gene in which the first intronic SNP rs13293564 has recently been reported to be associated with diabetic nephropathy.

CONCLUSION

This high throughput platform was able to successfully interrogate the methylation state of individual cytosines and identified 19 prospective CpG sites associated with risk of diabetic nephropathy. These differences in DNA methylation are worthy of further follow-up in replication studies using larger cohorts of diabetic patients with and without nephropathy.

Age-dependent DNA methylation of genes that are suppressed in stem cells is a hallmark of cancer

Polycomb group proteins (PCGs) are involved in repression of genes that are required for stem cell differentiation. Recently, it was shown that promoters of PCG target genes (PCGTs) are 12-fold more likely to be methylated in cancer than non-PCGTs. Age is the most important demographic risk factor for cancer, and we hypothesized that its carcinogenic potential may be referred by irreversibly stabilizing stem cell features. To test this, we analyzed the methylation status of over 27,000 CpGs mapping to promoters of approximately 14,000 genes in whole blood samples from 261 postmenopausal women. We demonstrate that stem cell PCGTs are far more likely to become methylated with age than non-targets (odds ratio = 5.3 [3.8-7.4], P < 10(-10)), independently of sex, tissue type, disease state, and methylation platform. We identified a specific subset of 69 PCGT CpGs that undergo hypermethylation with age and validated this methylation signature in seven independent data sets encompassing over 900 samples, including normal and cancer solid tissues and a population of bone marrow mesenchymal stem/stromal cells (P < 10(-5)). We find that the age-PCGT methylation signature is present in preneoplastic conditions and may drive gene expression changes associated with carcinogenesis. These findings shed substantial novel insights into the epigenetic effects of aging and support the view that age may predispose to malignant transformation by irreversibly stabilizing stem cell features.

Molecular confirmation of pathological specimen integrity in Australasia

AIM

Investigations into 14 suspected pathology sample identification errors and mix-ups were performed, as a service for several public hospital and private laboratories, from 2005 to 2007.

METHODS

Analyses were performed with the forensic ABI Identifiler kit of 16 microsatellites (15 autosomal and amelogenin) on DNA from paraffin-embedded tissues or blood specimens and compared to independently verified (single or multiple) patient samples.

RESULTS

Of 23 unique patient specimens referred for sample integrity confirmation because of pathologist, clinician or patient concern, six (26.1%) were demonstrated to be discordant, indicating that specimen identification errors or mix-ups had occurred.

CONCLUSIONS

Due to their great sensitivity and high discrimination power, forensic identity multiplex systems using either microsatellites or single nucleotide polymorphisms (SNPs) can resolve concerns about pathology specimen identity and integrity.

Advances in the identification and analysis of allele-specific expression

Allele-specific expression (ASE) is essential for normal development and many cellular processes but, if impaired, can result in disease. ASE is a feature of organisms with genomes consisting of more than one set of homologous chromosomes. The higher the number of chromosome sets (ploidy) per cell, the higher the potential complexity of ASE. Humans, for instance, are diploid (except germ cells, which are haploid), resulting in multiple possible expression states in time and space for each set of alleles. ASE is invoked and modulated by both genetic and epigenetic changes, affecting the underlying DNA sequence or chromatin of each allele, respectively. Although numerous methods have been developed to assay ASE, they usually require RNA to be available and are dependent upon genetic polymorphisms (such as single nucleotide polymorphisms (SNPs)) to differentiate between allelic transcripts. The rapid convergence to second-generation sequencing as the method of choice to examine genomic, epigenomic and transcriptomic data enables an integrated and more general approach to define and predict ASE, independent of SNPs. This 'Omni-Seq' approach has the potential to advance our understanding of the biology and pathophysiology of ASE-mediated processes by elucidating subtle combinatorial effects, leading to the accurate delineation of sub-phenotypes with consequential benefit for improved insight into disease etiology.

Macroscopic modeling of the surface tension of polymer-surfactant systems

Polymer-surfactant mixtures are increasingly being used in a wide range of applications. Weakly interacting systems, such as SDS/PEO and SDS/PVP, comprise ionic surfactants and neutral polymers, while strongly interacting systems, such as SDS/POLYDMDAAC and C12TAB/NaPSS, comprise ionic surfactants and oppositely charged ionic polymers. The complex nature of interactions in the mixtures leads to interesting and surprising surface tension profiles as the concentrations of polymer and surfactant are varied. The purpose of our research has been to develop a model to explain these surface tension profiles and to understand how they relate to the formation of different complexes in the bulk solution. In this paper we show how an existing model based on the law of mass action can be extended to model the surface tension of weakly interacting systems, and we also extend it further to produce a model for the surface tension of strongly interacting systems. Applying the model to a variety of strongly interacting systems gives remarkable agreement with the experimental results. The model provides a sound theoretical basis for comparing and contrasting the behavior of different systems and greatly enhances our understanding of the features observed.

Measurement of the clinical utility of a combined mutation detection protocol in carriers of Duchenne and Becker muscular dystrophy

BACKGROUND

Recent methodological advances have improved the detection rate for dystrophin mutations, but there are no published studies that have measured the clinical utility of these protocols for carrier detection compared with conventional carrier testing protocols that use pedigree, serum creatine kinase levels and linkage analysis.

METHODS AND SUBJECTS

The clinical utility of a combined mutation detection protocol was measured. It involved quantitative PCR procedures followed by DNA sequence analysis for the identification of dystrophin mutation carriers in 2101 women at risk of being carriers from 348 mutation-known Duchenne or Becker muscular dystrophy pedigrees.

RESULTS

The combined mutation detection protocol identified a mutation in 96% and 82% of index cases of Duchenne muscular dystrophy and Becker muscular dystrophy, respectively. An additional 692 (33%) potential carriers were correctly classified by the combined mutation detection protocol compared with pedigree, serum creatine kinase levels and linkage analysis. Significantly lower mutation carrier rates were identified in the mothers of isolated cases with deletion mutations than predicted from theoretical considerations, but these findings were not confirmed for duplication and DNA sequence mutations.

CONCLUSIONS

There are significant clinical benefits to be gained from a combined mutation detection protocol for carrier detection. It is recommended that mutation-specific carrier frequencies for the different classes of dystrophin mutations should be taken into account in genetic counselling practice.

No contribution of angiotensin-converting enzyme (ACE) gene variants to severe obesity: a model for comprehensive case/control and quantitative cladistic analysis of ACE in human diseases

Candidate gene analyses are often inconclusive owing to genetic or phenotypic heterogeneity, low statistical power, selection of nonfunctional SNPs, and inadequate statistical analysis of the genetic architecture. Angiotensin-converting enzyme (ACE) is involved in adipocyte growth and function and the ACE-processed angiotensin II inhibits adipocyte differentiation. Associations between body mass index (BMI) and ACE polymorphisms have been reported in general populations, but the contribution to severe obesity of this gene, which is located under an obesity genome-scan linkage peak on 17q23, is unknown. ACE is one of the most studied genes and markers responsible for variation in circulating ACE enzyme levels have been extensively characterised. Eight of these variants were genotyped in 1054 severely obese cases and 918 nonobese controls, as well as 116 nuclear families from the genome scan (n=447), enabling the known clades to be inferred. Qualitative analysis of individual single-nucleotide polymorphisms (SNPs), haplotypes, clades, and diploclades demonstrated no significant associations (P<0.05) after minimal correction for multiple testing. Quantitative analysis of clades and diploclades for BMI, waist-to-hip ratio, or ZBMI in children were also not significant. This rigorous, large-scale study of common, well-defined, severe polygenic obesity provides strong evidence that functionally relevant sequence variation in ACE, whether it is defined at the level of SNPs, haplotypes, or clades, is not associated with severe obesity in French Caucasians. Such a study design exemplifies the strategy needed to clearly define the contribution of the ACE gene to the plethora of complex genetic diseases where weak associations have been previously reported.

Mutations in the gene encoding the PML nuclear body protein Sp110 are associated with immunodeficiency and hepatic veno-occlusive disease

We describe mutations in the PML nuclear body protein Sp110 in the syndrome veno-occlusive disease with immunodeficiency, an autosomal recessive disorder of severe hypogammaglobulinemia, combined T and B cell immunodeficiency, absent lymph node germinal centers, absent tissue plasma cells and hepatic veno-occlusive disease. This is the first report of the involvement of a nuclear body protein in a human primary immunodeficiency and of high-penetrance genetic mutations in hepatic veno-occlusive disease.

Association of melanin-concentrating hormone receptor 1 5' polymorphism with early-onset extreme obesity

Murine models have been highly effective in identifying the monogenic forms of human obesity discovered to date. Melanin-concentrating hormone receptor 1 (MCHR1) has been shown to be significant in the downstream orexigenic activity of the leptin-melanocortin pathway by such models. In this study, the human MCHR1 gene was extensively characterized by sequencing 3.5 kb of coding, untranslated and intronic regions plus 1 kb of putative promoter region in 180 morbidly obese adults and 87 morbidly obese children, a total of >2.4 Mb of sequencing. Thirty-nine single nucleotide polymorphisms (SNPs) were found, seven of which encode an amino acid change. One mutation, R248Q, appeared to cosegregate with the obesity trait in one pedigree but was also found to be a rare polymorphism in control samples. To investigate the possible polygenic role of MCHR1, the six common SNPs (minor allele frequency >5%) found in the sequenced regions were then screened in 557 morbidly obese adults, 552 obese children, and 1,195 nonobese nondiabetic control subjects. The plausible promoter SNP, rs133068, was found to be associated with protection against obesity in obese children only (allele frequency P = 0.006 and genotype frequency P = 0.004). Most significant results were found when using a dominant model (P = 0.001, odds ratio 0.695 [95% CI 0.560-0.863]). However, similar associations were found when both adults and children were analyzed together (P = 0.006, 0.783 [0.658-0.930]), suggesting that severe forms of obesity with early onset may be associated with SNPs in MCHR1.

Analysis of sequence variability in the CART gene in relation to obesity in a Caucasian population

Background

Cocaine and amphetamine regulated transcript (CART) is an anorectic neuropeptide located principally in hypothalamus. CART has been shown to be involved in control of feeding behavior, but a direct relationship with obesity has not been established. The aim of this study was to evaluate the effect of polymorphisms within the CART gene with regards to a possible association with obesity in a Caucasian population.

Results

Screening of the entire gene as well as a 3.7 kb region of 5' upstream sequence revealed 31 SNPs and 3 rare variants ; 14 of which were subsequently genotyped in 292 French morbidly obese subjects and 368 controls. Haplotype analysis suggested an association with obesity which was found to be mainly due to SNP-3608T>C (rs7379701) (p = 0.009). Genotyping additional cases and controls also of European Caucasian origin supported further this possible association between the CART SNP -3608T>C T allele and obesity (global p-value = 0.0005). Functional studies also suggested that the SNP -3608T>C could modulate nuclear protein binding.

Conclusion

CART SNP -3608T>C may possibly contribute to the genetic risk for obesity in the Caucasian population. However confirmation of the importance of the role of the CART gene in energy homeostasis and obesity will require investigation and replication in further populations.