Multiple genes influence BMI on chromosome 7q31-34: the NHLBI Family Heart Study

Genetic polymorphism of pleiotrophin is associated with pain experience in Japanese adults: Case-control study

Genetic factors play a role in individual differences in pain experience. Here, we performed a genome-wide association study (GWAS) to identify novel loci regulating pain processing. We conducted a 2-stage GWAS and the candidate single-nucleotide polymorphisms (SNPs) association study on pain experience using an exploratory cohort of patients with cancer pain. The confirmatory cohort comprised of participants from the general population with and without habitual use of analgesic medication. In the exploratory cohort, we evaluated pain intensity using a numerical rating scale, recorded daily opioid dosages, and calculated pain reduction rate. In the confirmatory cohort, pain experience was defined as habitual nonsteroidal anti-inflammatory drug usage. Using linear regression models, we identified candidate SNP in the exploratory samples, and tested the association between phenotype and experienced pain in the confirmatory samples. We found 1 novel SNP (rs11764598)-located on the gene encoding for pleiotrophin on chromosome 7-that passed the genome-wide suggestive significance at 20% false discovery rate (FDR) correction in the exploratory samples of patients with cancer pain (P = 1.31 × 10-7, FDR = 0.101). We confirmed its significant association with daily analgesic usage in the confirmatory cohort (P = .028), although the minor allele affected pain experience in an opposite manner. We identified a novel genetic variant associated with pain experience. Further studies are required to validate the role of pleiotrophin in pain processing.

Multi-scale inference of genetic trait architecture using biologically annotated neural networks

In this article, we present Biologically Annotated Neural Networks (BANNs), a nonlinear probabilistic framework for association mapping in genome-wide association (GWA) studies. BANNs are feedforward models with partially connected architectures that are based on biological annotations. This setup yields a fully interpretable neural network where the input layer encodes SNP-level effects, and the hidden layer models the aggregated effects among SNP-sets. We treat the weights and connections of the network as random variables with prior distributions that reflect how genetic effects manifest at different genomic scales. The BANNs software uses variational inference to provide posterior summaries which allow researchers to simultaneously perform (i) mapping with SNPs and (ii) enrichment analyses with SNP-sets on complex traits. Through simulations, we show that our method improves upon state-of-the-art association mapping and enrichment approaches across a wide range of genetic architectures. We then further illustrate the benefits of BANNs by analyzing real GWA data assayed in approximately 2,000 heterogenous stock of mice from the Wellcome Trust Centre for Human Genetics and approximately 7,000 individuals from the Framingham Heart Study. Lastly, using a random subset of individuals of European ancestry from the UK Biobank, we show that BANNs is able to replicate known associations in high and low-density lipoprotein cholesterol content.

Membrane shape as determinant of protein properties

Membrane lipids play a role in the modulation of a variety of biological processes. This is often achieved through fine-tuned changes in membrane physical and chemical properties. While some membrane physical properties (e.g., curvature, lipid domains, fluidity) have received increased scientific attention over the years, only recently has membrane shape emerged as an active modulator of protein properties. Biological membranes are mostly found organized into a lipid bilayer arrangement, in which the spontaneous shape is an intrinsically flat, planar morphology (in relation to the size of proteins). However, it is known that many cells and organelles have non-planar morphologies. In addition, perturbations in membrane morphology occur in a variety of biological processes. Recent studies have shown that membrane shape can modulate a variety of biological processes by determining protein properties. While membrane shape generation modulates proteins via changes in membrane mechanical properties, membrane shape recognition regulates proteins by providing the optimal surface for interaction. Hence, membranes have evolved an elegant mechanism to couple mesoscopic perturbations to molecular properties and vice-versa. In this review, the regulation of the enzymatic properties of two isoforms of mammalian diacylglycerol kinase, which play important roles in cellular signal transductions, will be used to exemplify the recent advancements in the field of membrane shape recognition, as well as future challenges and perspectives.

Reprogramming fatty acyl specificity of lipid kinases via C1 domain engineering

C1 domains are lipid-binding modules that regulate membrane activation of kinases, nucleotide exchange factors and other C1-containing proteins to trigger signal transduction. Despite annotation of typical C1 domains as diacylglycerol (DAG) and phorbol ester sensors, the function of atypical counterparts remains ill-defined. Here, we assign a key role for atypical C1 domains in mediating DAG fatty acyl specificity of diacylglycerol kinases (DGKs) in live cells. Activity-based proteomics mapped C1 probe binding as a principal differentiator of type 1 DGK active sites that combined with global metabolomics revealed a role for C1s in lipid substrate recognition. Protein engineering by C1 domain swapping demonstrated that exchange of typical and atypical C1s is functionally tolerated and can directly program DAG fatty acyl specificity of type 1 DGKs. Collectively, we describe a protein engineering strategy for studying metabolic specificity of lipid kinases to assign a role for atypical C1 domains in cell metabolism.

Diacylglycerol Kinases as Emerging Potential Drug Targets for a Variety of Diseases: An Update

Ten mammalian diacylglycerol kinase (DGK) isozymes (α–κ) have been identified to date. Our previous review noted that several DGK isozymes can serve as potential drug targets for cancer, epilepsy, autoimmunity, cardiac hypertrophy, hypertension and type II diabetes (Sakane et al., 2008). Since then, recent genome-wide association studies have implied several new possible relationships between DGK isozymes and diseases. For example, DGKθ and DGKκ have been suggested to be associated with susceptibility to Parkinson's disease and hypospadias, respectively. In addition, the DGKη gene has been repeatedly identified as a bipolar disorder (BPD) susceptibility gene. Intriguingly, we found that DGKη-knockout mice showed lithium (BPD remedy)-sensitive mania-like behaviors, suggesting that DGKη is one of key enzymes of the etiology of BPD. Because DGKs are potential drug targets for a wide variety of diseases, the development of DGK isozyme-specific inhibitors/activators has been eagerly awaited. Recently, we have identified DGKα-selective inhibitors. Because DGKα has both pro-tumoral and anti-immunogenic properties, the DGKα-selective inhibitors would simultaneously have anti-tumoral and pro-immunogenic (anti-tumor immunogenic) effects. Although the ten DGK isozymes are highly similar to each other, our current results have encouraged us to identify and develop specific inhibitors/activators against every DGK isozyme that can be effective regulators and drugs against a wide variety of physiological events and diseases.

Linkage and association analysis of obesity traits reveals novel loci and interactions with dietary n-3 fatty acids in an Alaska Native (Yup'ik) population

OBJECTIVE

To identify novel genetic markers of obesity-related traits and to identify gene-diet interactions with n-3 polyunsaturated fatty acid (n-3 PUFA) intake in Yup'ik people.

MATERIAL AND METHODS

We measured body composition, plasma adipokines and ghrelin in 982 participants enrolled in the Center for Alaska Native Health Research (CANHR) Study. We conducted a genome-wide SNP linkage scan and targeted association analysis, fitting additional models to investigate putative gene-diet interactions. Finally, we performed bioinformatic analysis to uncover likely candidate genes within the identified linkage peaks.

RESULTS

We observed evidence of linkage for all obesity-related traits, replicating previous results and identifying novel regions of interest for adiponectin (10q26.13-2) and thigh circumference (8q21.11-13). Bioinformatic analysis revealed DOCK1, PTPRE (10q26.13-2) and FABP4 (8q21.11-13) as putative candidate genes in the newly identified regions. Targeted SNP analysis under the linkage peaks identified associations between three SNPs and obesity-related traits: rs1007750 on chromosome 8 and thigh circumference (P=0.0005), rs878953 on chromosome 5 and thigh skinfold (P=0.0004), and rs1596854 on chromosome 11 for waist circumference (P=0.0003). Finally, we showed that n-3 PUFA modified the association between obesity related traits and two additional variants (rs2048417 on chromosome 3 for adiponectin, P for interaction=0.0006 and rs730414 on chromosome 11 for percentage body fat, P for interaction=0.0004).

CONCLUSIONS

This study presents evidence of novel genomic regions and gene-diet interactions that may contribute to the pathophysiology of obesity-related traits among Yup'ik people.

Familial risk for alcohol dependence and developmental changes in BMI: the moderating influence of addiction and obesity genes

AIM

Familial loading for alcohol dependence (AD) and variation in genes reported to be associated with AD or BMI were tested in a longitudinal study.

MATERIALS & METHODS

Growth curve analyses of BMI data collected at approximately yearly intervals and obesity status (BMI > 30) were examined.

RESULTS

High-risk males were found to have higher BMI than low-risk males, beginning at age 15 years (2.0 kg/m(2) difference; p = 0.046), persisting through age 19 years (3.3 kg/m(2) difference; p = 0.005). CHRM2 genotypic variance predicted longitudinal BMI and obesity status. Interactions with risk status and sex were also observed for DRD2 and FTO gene variation.

CONCLUSION

Variation at loci implicated in addiction may be influential in determining susceptibility to increased BMI in childhood and adolescence.

mRNA expression of diacylglycerol kinase isoforms in insulin-sensitive tissues: effects of obesity and insulin resistance

Diacylglycerol kinase (DGK) isoforms regulate signal transduction and lipid metabolism. DGKδ deficiency leads to hyperglycemia, peripheral insulin resistance, and metabolic inflexibility. Thus, dysregulation of other DGK isoforms may play a role in metabolic dysfunction. We investigated DGK isoform mRNA expression in extensor digitorum longus (EDL) and soleus muscle, liver as well as subcutaneous and epididymal adipose tissue in C57BL/6J mice and obese and insulin-resistant ob/ob mice. All DGK isoforms, except for DGKκ, were detectable, although with varying mRNA expression. Liver DGK expression was generally lowest, with several isoforms undetectable. In soleus muscle, subcutaneous and epididymal adipose tissue, DGKδ was the most abundant isoform. In EDL muscle, DGKα and DGKζ were the most abundant isoforms. In liver, DGKζ was the most abundant isoform. Comparing obese insulin-resistant ob/ob mice to lean C57BL/6J mice, DGKβ, DGKι, and DGKθ were increased and DGKε expression was decreased in EDL muscle, while DGKβ, DGKη and DGKθ were decreased and DGKδ and DGKι were increased in soleus muscle. In liver, DGKδ and DGKζ expression was increased in ob/ob mice. DGKη was increased in subcutaneous fat, while DGKζ was increased and DGKβ, DGKδ, DGKη and DGKε were decreased in epididymal fat from ob/ob mice. In both adipose tissue depots, DGKα and DGKγ were decreased and DGKι was increased in ob/ob mice. In conclusion, DGK mRNA expression is altered in an isoform- and tissue-dependent manner in obese insulin-resistant ob/ob mice. DGK isoforms likely have divergent functional roles in distinct tissues, which may contribute to metabolic dysfunction.

Who gains? Genetic and neurophysiological correlates of BMI gain upon college entry in women

The present investigation examined P3 event-related electroencephalographic potentials and a short and selected list of addiction-related candidate gene single nucleotide polymorphisms (SNPs) within 84 female students, aged 18-20 yrs. The students were assigned to groups defined by the presence versus absence of a positive body mass index (BMI) change from the pre-college physical exam to the current day. Analyses revealed significantly greater P3 latencies and reduced P3 amplitudes during a response inhibition task among students who exhibited a BMI gain. BMI gain was also significantly associated with a ANKK1 SNP previously implicated in substance dependence risk. In logistic regression analyses, P3 latencies at the frontal electrode and this ANKK1 genotype correctly classified 71.1% of the students into the BMI groups. The present findings suggest that heritable indicators of impaired response inhibition can differentiate students who may be on a path toward an overweight or obese body mass.

Genome-wide linkage analysis of carotid artery lumen diameter: the strong heart family study

BACKGROUND

A significant proportion of the variability in carotid artery lumen diameter is attributable to genetic factors.

METHODS

Carotid ultrasonography and genotyping were performed in the 3300 American Indian participants in the Strong Heart Family Study (SHFS) to identify chromosomal regions harboring novel genes associated with inter-individual variation in carotid artery lumen diameter. Genome-wide linkage analysis was conducted using standard variance component linkage methods, implemented in SOLAR, based on multipoint identity-by-descent matrices.

RESULTS

Genome-wide linkage analysis revealed a significant evidence for linkage for a locus for left carotid artery diastolic and systolic lumen diameters in Arizona SHFS participants on chromosome 7 at 120 cM (lod = 4.85 and 3.77, respectively, after sex and age adjustment, and lod = 3.12 and 2.72, respectively, after adjustment for sex, age, height, weight, systolic and diastolic blood pressure, diabetes mellitus and current smoking). Other regions with suggestive evidence of linkage for left carotid artery diastolic and systolic lumen diameter were found on chromosome 12 at 153 cM (lod = 2.20 and 2.60, respectively, after sex and age adjustment, and lod = 2.44 and 2.16, respectively, after full covariate adjustment) in Oklahoma SHFS participants; suggestive linkage for right carotid artery diastolic and systolic lumen diameter was found on chromosome 9 at 154 cM (lod = 2.72 and 3.19, respectively after sex and age adjustment, and lod = 2.36 and 2.21, respectively, after full covariate adjustment) in Oklahoma SHFS participants.

CONCLUSION

We found significant evidence for loci influencing carotid artery lumen diameter on chromosome 7q and suggestive linkage on chromosomes 12q and 9q.

Wrapper-based selection of genetic features in genome-wide association studies through fast matrix operations

BACKGROUND

Through the wealth of information contained within them, genome-wide association studies (GWAS) have the potential to provide researchers with a systematic means of associating genetic variants with a wide variety of disease phenotypes. Due to the limitations of approaches that have analyzed single variants one at a time, it has been proposed that the genetic basis of these disorders could be determined through detailed analysis of the genetic variants themselves and in conjunction with one another. The construction of models that account for these subsets of variants requires methodologies that generate predictions based on the total risk of a particular group of polymorphisms. However, due to the excessive number of variants, constructing these types of models has so far been computationally infeasible.

RESULTS

We have implemented an algorithm, known as greedy RLS, that we use to perform the first known wrapper-based feature selection on the genome-wide level. The running time of greedy RLS grows linearly in the number of training examples, the number of features in the original data set, and the number of selected features. This speed is achieved through computational short-cuts based on matrix calculus. Since the memory consumption in present-day computers can form an even tighter bottleneck than running time, we also developed a space efficient variation of greedy RLS which trades running time for memory. These approaches are then compared to traditional wrapper-based feature selection implementations based on support vector machines (SVM) to reveal the relative speed-up and to assess the feasibility of the new algorithm. As a proof of concept, we apply greedy RLS to the Hypertension - UK National Blood Service WTCCC dataset and select the most predictive variants using 3-fold external cross-validation in less than 26 minutes on a high-end desktop. On this dataset, we also show that greedy RLS has a better classification performance on independent test data than a classifier trained using features selected by a statistical p-value-based filter, which is currently the most popular approach for constructing predictive models in GWAS.

CONCLUSIONS

Greedy RLS is the first known implementation of a machine learning based method with the capability to conduct a wrapper-based feature selection on an entire GWAS containing several thousand examples and over 400,000 variants. In our experiments, greedy RLS selected a highly predictive subset of genetic variants in a fraction of the time spent by wrapper-based selection methods used together with SVM classifiers. The proposed algorithms are freely available as part of the RLScore software library at http://users.utu.fi/aatapa/RLScore/.

Polymorphisms in human muscarinic receptor subtype genes

A wide range of polymorphisms have been reported in muscarinic receptor subtype genes, mostly in M₁ and M₂ and, to a lesser extent, M₃ receptors. Most studies linking such genetic variability to phenotype have been performed for brain functions, but a more limited amount of information is also available for cardiac and airway function. Unfortunately, for none of the phenotypes under investigation a robust association with genotype has emerged. Moreover, it remains mostly unclear whether a reported association indicates a causative role of the polymorphism under investigation or merely a role as indicator of other polymorphisms affecting expression and/or function of the receptor. Also, most data on genotype-phenotype associations of muscarinic receptor subtypes are based on cross-sectional samples. Mechanistic studies linking polymorphisms to molecular, cellular, and tissue functions are largely missing. Finally, studies on a possible impact of muscarinic receptor polymorphisms on drug responsiveness are also largely missing. Thus, the field of genomics of muscarinic receptor subtypes is still in an early stage and a considerably greater number of studies will be required to judge the role of muscarinic receptor gene variability in physiology, pathophysiology, and drug treatment.

Variations of six transmembrane epithelial antigen of prostate 4 (STEAP4) gene are associated with metabolic syndrome in a female Uygur general population

BACKGROUND AND AIMS

Metabolic syndrome (MetS) is linked with visceral obesity and is associated with a clustering of abnormalities (including impaired glucose tolerance, insulin resistance, dyslipidemia and hypertension). Six transmembrane epithelial antigen of prostate 4 (STEAP4) was associated with human obesity. STEAP4 gene represents a strong biological and positional candidate for a susceptibility factor for MetS. Uygur Chinese is a relatively isolated population with a relatively homogeneous environment and a high prevalence of MetS. We undertook this study to investigate the relationship between STEAP4 gene variations and MetS in a Uygur general population.

METHODS

The functional regions of STEAP4 gene were sequenced in Uygur patients with MetS. Four representative variations, rs1981529, rs34741656, rs8122 and 6031T/G (unsuccessfully genotyped), selected with a r² cutoff of 0.8 and minor allele frequency of >5%, were genotyped in 858 MetS and 687 non-MetS controls.

RESULTS

Fourteen novel and six known single nucleotide polymorphisms (SNPs) including 2 nonsynonymous SNPs in the STEAP4 gene were identified. SNPs rs8122 and rs1981529 were significantly associated with MetS phenotype in females [additive p = 0.032 and p = 0.011; ORs (95% CI) adjusted for age 0.772 (0.625-0.954) and 0.740 (0.582-0.941), respectively]. Two common haplotypes 1 (rs8122/rs1981529/rs34741656, G-A-G) and 2 (A-G-G) had significantly higher (permutation p = 0.044) and lower (permutation p = 0.009) frequency in MetS than that in controls in females. Multiple linear regression analysis revealed a significant association of the SNPs rs8122 and rs1981529 with HDL-c level in MetS cases (p = 0.001 and 0.024) and in a combined sample (p = 0.004 and 0.009).

CONCLUSIONS

STEAP4 genetic variations are likely to be associated with metabolic syndrome in a female Uygur general population.