Food Volume Computation for Self Dietary Assessment Applications

There is great demand for easily-accessible, user-friendly dietary self-management applications. Yet accurate, fully-automatic estimation of nutritional intake using computer vision methods remains an open research problem. One key element of this problem is the volume estimation, which can be computed from 3D models obtained using multi-view geometry. The paper presents a computational system for volume estimation based on the processing of two meal images. A 3D model of the served meal is reconstructed using the acquired images and the volume is computed from the shape. The algorithm was tested on food models (dummy foods) with known volume and on real served food. Volume accuracy was in the order of 90 %, while the total execution time was below 15 seconds per image pair. The proposed system combines simple and computational affordable methods for 3D reconstruction, remained stable throughout the experiments, operates in near real time, and places minimum constraints on users.

Characterization of the potential role for RNA-binding protein FUS in DNA damage response: A quantitative proteomic approach

FUS/TLS (fused in sarcoma/translocated in liposarcoma) is a ubiquitously expressed protein of the hnRNP family, that has been discovered as fused to transcription factors in several human sarcomas and found in protein aggregates in neurons of patients with an inherited form of Amyotrophic Lateral Sclerosis [Vance C. et al., 2009]. FUS is a 53 kDa nuclear protein that contains structural domains, such as a RNA Recognition Motif (RRM) and a zinc finger motif, that give to FUS the ability to bind to both RNA and DNA sequences. It has been implicated in a variety of cellular processes, such as pre-mRNA splicing, miRNA processing, gene expression control and transcriptional regulation [Fiesel FC. and Kahle PJ., 2011]. Moreover, some evidences link FUS to genome stability control and DNA damage response: mice lacking FUS are hypersensitive to ionizing radiation (IR) and show high levels of chromosome instability and, in response to double-strand breaks, FUS is phosphorylated by the protein kinase ATM [Kuroda M. et al., 2000; Hicks GG. et al., 2000; Gardiner M. et al., 2008]. Furthermore, preliminary results of mass spectrometric identification of FUS interacting proteins in HEK293 cells, expressing a recombinant flag-tagged FUS protein, highlighted the interactions with proteins involved in DNA damage response, such as DNA-PK, XRCC-5/-6, and ERCC-6, raising the possibilities that FUS is involved in this pathway, even though its role still needs to be clarified. This study aims to investigate the biological roles of FUS in human cells and in particular the putative role in DNA damage response through the characterization of the proteomic profile of the neuroblastoma cell line SH-SY5Y upon FUS inducible depletion, by a quantitative proteomic approach. The SH-SY5Y cell line that will be used in this study expresses, in presence of tetracycline, a shRNA that targets FUS mRNA, leading to FUS protein depletion (SH-SY5Y FUS iKD cells). To quantify changes in proteins expression levels a SILAC strategy (Stable Isotope Labeling by Amino acids in Cell culture) will be conducted on SH-SY5Y FUS iKD cells and a control SH-SY5Y cell line (that expresses a mock shRNA) and the relative changes in proteins levels will be evaluated after five and seven days upon FUS depletion, by nanoliquid chromatography coupled to tandem mass spectrometry (nLC-MS/MS) and bioinformatics analysis. Preliminary experiments demonstrated that the SH-SY5Y FUS iKD cells, when subjected to genotoxic stress (high dose of IR), upon inducible depletion of FUS, showed a increased phosphorylation of gH2AX with respect to control cells, suggesting an higher activation of the DNA damage response.

Subgingival microbiota of Sri Lankan tea labourers naïve to oral hygiene measures.

AIM To characterize the subgingival microbiota within a cohort of adult males (n = 32) naïve to oral hygiene practices, and to compare the composition of bacterial taxa present in periodontal sites with various probing depths. MATERIAL AND METHODS Subgingival plaque samples were collected from single shallow pocket [pocket probing depth (PPD)≤3 mm] and deep pocket (PPD≥6 mm) sites from each subject. A polymerase chain reaction based strategy was used to construct a clone library of 16S ribosomal RNA (rRNA) genes for each site. The sequences of ca. 30-60 plasmid clones were determined for each site to identify resident taxa. Microbial composition was compared using a variety of statistical and bioinformatics approaches. RESULTS A total of 1887 cloned 16S rRNA gene sequences were analysed, which were assigned to 318 operational taxonomic units (98% identity cut-off). The subgingival microbiota was dominated by Firmicutes (69.8%), Proteobacteria (16.3%), and Fusobacteria (8.0%). The overall composition of microbial communities in shallow sites was significantly different from those within deep sites (∫-Libshuff, p < 0.001). CONCLUSIONS A taxonomically diverse subgingival microbiota was present within this cohort; however, the structures of the microbial communities present in the respective subjects exhibited limited variation. Deep and shallow sites contained notably different microbial compositions, but this was not correlated with the rate of periodontal progression.

DNA testing in neurologic diseases

DNA testing is available for a growing number of hereditary diseases in neurology and other specialties. In addition to guiding breeding decisions, DNA tests are important tools in the diagnosis of diseases, particularly in conditions for which clinical signs are relatively nonspecific. DNA testing also can provide valuable insight into the risk of hereditary disease when decisions about treating comorbidities are being made. Advances in technology and bioinformatics will make broad screening for potential disease-causing mutations available soon. As DNA tests come into more common use, it is critical that clinicians understand the proper application and interpretation of these test results.

Screening, Identification and Preliminary Investigation of Target Transporters in Pregnancy Pathologies

Screening, Identification and Preliminary Investigation of Target Transporters in Pregnancy Pathologies. INTRODUCTION: Pre-eclampsia (PE), intrauterine growth restriction (IUGR) and gestational diabetes mellitus (GDM) are major sources of clinical morbidity and mortality in pregnant women worldwide. The mechanisms underlying these gestational diseases are complex and not yet fully understood, but one factor contributing to their development is impaired maternal-fetal nutrient transport. Therefore, we aimed to identify candidate membrane transporters involved in transplacental nutrient transfer associated with PE/IUGR or GDM. METHODS: Using in silico strategies, we analysed various gene expression data sets generated on different platforms focusing on solute carriers, ABC transporters and TRP channels in order to identify transporters that are differently expressed between patients and gestational age-matched controls. These bioinformatic analyses were combined with literature data to define a catalogue of target transporters that could be involved in the development of PE/IUGR or GDM. Transporters of interest were then analysed for gene expression using qRT-PCR in placental tissues of patients and controls. For validating the results on protein and functional level, we started to establish an in vitro assay using freshly isolated primary cytotrophoblast cells polarized on the Transwell® system. RESULTS: Using bioinformatics approaches, we initially identified 37 target membrane proteins which were mainly associated with the transport of amino acids, vitamins, and trace elements. At the current state of analysis, the amino acid transporters SLC7A7, SLC38A2, SLC38A5, and the thiamine transporter SLC19A3 showed significant differences in placental mRNA expression between controls and patients affected by PE and/or IUGR. Subsequent gene expression analysis in our in-house GDM placental tissue bank is still ongoing. CONCLUSIONS: Based on our in silico analyses, literature data and first follow-up in vitro validations, we were able to define potentially interesting candidate transporters implicated in PE/IUGR or GDM. To date, additional newly defined candidate targets are being analysed on mRNA level in PE/IUGR and GDM. Subsequent analyses on protein and functional level will reveal whether these targets could be of diagnostic or therapeutical interest in these pregnancy pathologies.

PDB-Explorer: a web-based interactive map of the protein data bank in shape space

Background The RCSB Protein Data Bank (PDB) provides public access to experimentally determined 3D-structures of biological macromolecules (proteins, peptides and nucleic acids). While various tools are available to explore the PDB, options to access the global structural diversity of the entire PDB and to perceive relationships between PDB structures remain very limited. Methods A 136-dimensional atom pair 3D-fingerprint for proteins (3DP) counting categorized atom pairs at increasing through-space distances was designed to represent the molecular shape of PDB-entries. Nearest neighbor searches examples were reported exemplifying the ability of 3DP-similarity to identify closely related biomolecules from small peptides to enzyme and large multiprotein complexes such as virus particles. The principle component analysis was used to obtain the visualization of PDB in 3DP-space. Results The 3DP property space groups proteins and protein assemblies according to their 3D-shape similarity, yet shows exquisite ability to distinguish between closely related structures. An interactive website called PDB-Explorer is presented featuring a color-coded interactive map of PDB in 3DP-space. Each pixel of the map contains one or more PDB-entries which are directly visualized as ribbon diagrams when the pixel is selected. The PDB-Explorer website allows performing 3DP-nearest neighbor searches of any PDB-entry or of any structure uploaded as protein-type PDB file. All functionalities on the website are implemented in JavaScript in a platform-independent manner and draw data from a server that is updated daily with the latest PDB additions, ensuring complete and up-to-date coverage. The essentially instantaneous 3DP-similarity search with the PDB-Explorer provides results comparable to those of much slower 3D-alignment algorithms, and automatically clusters proteins from the same superfamilies in tight groups. Conclusion A chemical space classification of PDB based on molecular shape was obtained using a new atom-pair 3D-fingerprint for proteins and implemented in a web-based database exploration tool comprising an interactive color-coded map of the PDB chemical space and a nearest neighbor search tool. The PDB-Explorer website is freely available at www.​cheminfo.​org/​pdbexplorer and represents an unprecedented opportunity to interactively visualize and explore the structural diversity of the PDB.

Whole-exome sequencing reveals a C-terminal germline variant in CEBPA-associated acute myeloid leukemia: 45-year follow-up of a large family.

Familial acute myeloid leukemia is rare and linked to germline mutations in RUNX1, GATA2 or CCAAT/enhancer binding protein-α (CEBPA). We re-evaluated a large family with acute myeloid leukemia originally seen at NIH in 1969. We utilized whole-exome sequencing to study this family, and conducted in silico bioinformatics analysis, protein structural modeling and laboratory experiments to assess the impact of the identified CEBPA Q311P mutation. Unlike most previously identified germline mutations in CEBPA, which were N-terminal frameshift mutations, we identified a novel Q311P variant that was located in the C-terminal bZip domain of C/EBPα. Protein structural modeling suggested that the Q311P mutation alters the ability of the CEBPA dimer to bind DNA. Electrophoretic mobility shift assays showed that the Q311P mutant had attenuated binding to DNA, as predicted by the protein modeling. Consistent with these findings, we found that the Q311P mutation has reduced transactivation, consistent with a loss-of-function mutation. From 45 years of follow-up, we observed incomplete penetrance (46%) of CEBPA Q311P. This study of a large multi-generational pedigree reveals that a germline mutation in the C-terminal bZip domain can alter the ability of C/EBP-α to bind DNA and reduces transactivation, leading to acute myeloid leukemia.

Cytochrome P450 4F isoforms in different species: Identification, gene regulation and putative roles in inflammation

The cytochrome P450 4F subfamily comprises a group of enzymes that metabolize derivatives of arachidonic acid such as prostaglandins, lipoxins leukotrienes and hydroxyeicosatetraenoic acids, which are important mediators involved in the inflammatory response. Therefore, we speculate that CYP4Fs might be able to modulate the extent of the inflammation by controlling of the tissue levels of these inflammatory mediators, especially, leukotriene B4. One way to provide support for this hypothesis is to test whether the expression of CYP4Fs changes under inflammatory conditions, since these changes are required to adjust the levels of inflammatory mediators. ^ A lipopolysacchride (LPS) induced rat inflammation model was used to analyze the expressions of rat CYP4F4 and CYP4F5 in liver and kidney. LPS administration did not change the constitutive expression level of CYP4F4 and CYP4F5. In liver, the expressions of CYP4F4 and CYP4F5 decreased to 50–60% of the untreated level. The same effect of LPS on CYP4F4 and CYP4F5 expression can be mimicked in hepatocyte primary cultures treated with LPS, indicating a direct of effect of LPS on hepatocytes. LPS treatment also decreased the activity of liver microsomes towards chlorpromazine, however, antibody inhibition study revealed that liver CYP4Fs are not the only players in metabolizing chlorpromazine. To study further the underlying mechanism, CYP4F5 gene was isolated, characterized, and the promoter region was defined. ^ Accumulating evidence showed that peroxisome proliferator-activated receptors (PPARs) play an active role in inflammation. To investigate the possible role of PPARα in regulating CYP4F expression by inflammation or by clofibrate treatment, the expressions of two new mouse 4F isoforms were analyzed in PPARα knockout mice upon LPS or clofibrate challenge. A novel induction of CYP4F15 by LPS and clofibrate was observed in kidney, and this effect is totally dependent on the presence of PPARα. Renal CYP4F16 expression was not affected by LPS or clofibrate in both (+/+) and (−/−) mice. In contrast, hepatic expressions of CYP4F15 and CYP4F16 were reduced significantly in (+/+) mice, but much less in (−/−) mice, suggesting that PPARα is partially responsible for this down-regulation. Clofibrate treatment reduced the expression of CYP4F16 in liver, but has no effect on CYP4F15 and PPARα does not have a role in hepatic CYP4F expression regulated by clofibrate. In general, CYP4Fs are regulated in an isoform-, tissue- and species-specific manner. ^ A human CYP4F isoform, CYP4F11, was isolated. The genomic structure was also solved by using database mining and bioinformatics tools. Localization of CYP4F11 to chromosome 19, 16 kb upstream of CYP4F2, suggests that human CYP4F genes may form a cluster on chromosome 19. This novel human 4F is highly expressed in liver, as well as in kidney, heart and skeletal muscle. Further study of the activity and gene regulation on CYP4F11 will provide us more insights into the physiological functions of CYP4F subfamily. ^

The genetic basis of thoracic aortic aneurysms and dissections: Genetic heterogeneity and mapping of TAAD1 and TAAD2 loci

Thoracic aortic aneurysms leading to aortic dissections (TAAD) are a major cause of morbidity and mortality in the United States. TAAD is a complication of some known genetic disorders, such as Marfan syndrome and Turner syndrome, but the majority of familial cases are not due to a known genetic syndrome. Previous studies by our group have established that nonsyndromic, familial TAAD is inherited in an autosomal dominant manner with decreased penetrance and variable expression. Using one large family with multiple members with TAAD for the genome wide scan, a major locus for familial TAAD was mapped to 5q13–14 (TAAD1). Nine out of 15 families studied were linked to this locus, establishing that TAAD1 was a major locus, and that there was genetic heterogeneity for the condition. Mapping of TAAD2 locus was accomplished using a single large family with multiple members with TAAD not linked to known loci of aneurysm formation. This established a second novel locus for familial TAAD on 3p24–25 (LOD score of 4.3), termed the TAAD2 locus. Two putative loci with suggestive LOD scores were mapped on 4q and 12q through a genome scan carried out using three families. TAAD phenotype in 12 families did not segregate with known loci, indicating further genetic heterogeneity. An STS-tagged BAC based contig was constructed for 7.8Mb and 25Mb critical interval of TAAD1 and TAAD2 respectively and characterized to identify the defective gene. The hypothesis that the defective genes responsible for the TAAD1 and TAAD2 encoded extracellular matrix (ECM) proteins, the major components of the elastic fiber system in the aortic media was tested. Four genes encoding ECM proteins, versican, thrombospondin-3, CRTL1, on TAAD1 and FBLN2 at TAAD2 were sequenced, but no disease-causing mutations were identified. Studies to identify the defective gene are initiated through the positional candidate gene approach using combination of bioinformatics and expression studies. The identification of the TAAD susceptibility genes will allow for presymptomatic diagnosis of individuals at risk for this life threatening disease. The identification of the molecular defects that contribute to TAAD will also further our understanding of the proteins that provide structural integrity to the aortic wall. ^

Regulation and transcript analysis of the ceroperon responsible for quorum sensing in Rhodobacter sphaeroides 2.4.1

Rhodobacter sphaeroides 2.4.1 is a Gram negative facultative photoheterotrophic bacterium that has been shown to have an N-acyl homoserine lactone-based quorum sensing system called cer for c&barbelow;ommunity e&barbelow;scape r&barbelow;esponse. The cer ORFs are cerR, the transcriptional regulator, cerI, the autoinducer synthase and cerA , whose function is unknown. The autoinducer molecule, 7,8- cis-N-(tetradecenoyl) homoserine lactone, has been characterized. The objective of this study was to identify an environmental stimulus that influences the regulation of cerRAI and, to characterize transcription of the cer operon. ^ A cerR::lacZ transcriptional fusion was made and β-Galactosidase assays were performed in R. sphaeroides 2.4.1 strains, wild type, AP3 (CerI−) and AP4 (CerR−). The cerR::lacZ β-Galactosidase assays were used as an initial survey of the mode of regulation of the Cer system. A cerA::lacZ translational fusion was created and was used to show that cerA can be translated. The presence of 7,8-cis-N-(tetradecenoyl) homoserine lactone was detected from R. sphaeroides strains wild type and AP4 (CerR−) using a lasR::lacZ translational fusion autoinducer bioassay. The cerR::lacZ transcriptional fusion in R. sphaeroides 2.4.1 wild type was tested under different environmental stimuli, such as various carbon sources, oxygen tensions, light intensities and culture media to determine if they influence transcription of the cer ORFs. Although lacZ assay data implicated high light intensity at 100 W/m2 to stimulate cer transcription, quantitative Northern RNA data of the cerR transcript showed that low light intensity at 3 W/m2 is at least one environmental stimulus that induces cer transcription. This finding was supported by DNA microarray analysis. Northern analysis of the cerRAI transcript provided evidence that the cer ORFs are co-transcribed, and that the cer operon contains two additional genes. Bioinformatics was used to identify genes that may be regulated by the Cer system by identifying putative lux box homologue sequences in the presumed promoter region of these genes. Genes that were identified were fliQ, celB and calsymin, all implicated in interacting with plants. Primer extension was used to help localize cis-elements in the promoter region. The cerR::lacZ transcriptional fusion was monitored in a subset of different global DNA binding transcriptional regulator mutant strains of R. sphaeroides 2.4.1. Those regulators involved in maintaining an anaerobic photosynthetic lifestyle appeared to have an effect. Collectively, the data imply that R. sphaeroides 2.4.1 activates the Cer system when grown anaerobic photosynthetically at low light intensity, 3 W/m2, and it may be involved in an interaction with plants. ^

Application of cell line based genomic predictors to predict response to targeted therapies in breast cancer

Cancer cell lines can be treated with a drug and the molecular comparison of responders and non-responders may yield potential predictors that could be tested in the clinic. It is a bioinformatics challenge to apply the cell line-derived multivariable response predictors to patients who respond to therapy. Using the gene expression data from 23 breast cancer cell lines, I developed three predictors of dasatinib sensitivity by selecting differentially expressed genes and applying different classification algorithms. The performance of these predictors on independent cell lines with known dasatinib response was tested. The predictor based on weighted voting method has the best overall performance. It correctly predicted dasatinib sensitivity in 11 out of 12 (92%) breast and 17 out of 23 (74%) lung cancer cell lines. These predictors were then applied to the gene expression data from 133 breast cancer patients in an attempt to predict how the patients might respond to dasatinib therapy. Two predictors identified 13 patients in common to be dasatinib sensitive. Sixty two percent of these cases are triple negative (ER-negative, HER2-negative and PR-negative) and 76% are double negative. The result is consistent with the findings from other studies, which identified a target population for dasatinib treatment to be triple negative or basal breast cancer subtype. In conclusion, we think that the cell line-derived dasatinib classifiers can be applied to the human patients. ^

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

Genome-wide gene-gene interaction analysis for cardiovascular disease

Numerous studies have been carried out to try to better understand the genetic predisposition for cardiovascular disease. Although it is widely believed that multifactorial diseases such as cardiovascular disease is the result from effects of many genes which working alone or interact with other genes, most genetic studies have been focused on identifying of cardiovascular disease susceptibility genes and usually ignore the effects of gene-gene interactions in the analysis. The current study applies a novel linkage disequilibrium based statistic for testing interactions between two linked loci using data from a genome-wide study of cardiovascular disease. A total of 53,394 single nucleotide polymorphisms (SNPs) are tested for pair-wise interactions, and 8,644 interactions are found to be significant with p-values less than 3.5×10-11. Results indicate that known cardiovascular disease susceptibility genes tend not to have many significantly interactions. One SNP in the CACNG1 (calcium channel, voltage-dependent, gamma subunit 1) gene and one SNP in the IL3RA (interleukin 3 receptor, alpha) gene are found to have the most significant pair-wise interactions. Findings from the current study should be replicated in other independent cohort to eliminate potential false positive results.^

Identification and characterization of mutations in SMC contractile genes involved in thoracic aortic aneurysms and dissections

Aortic aneurysms and dissections are the 15th most common cause of death in the United States. Genetic factors contribute to the pathogenesis of thoracic aortic aneurysms and dissections (TAAD). Currently, six loci and four genes have been identified for familial TAAD. Notably, mutations in smooth muscle cell (SMC) contractile genes, ACTA2 and MYH11, are responsible for 15% of familial TAAD, suggesting that proper SMC contraction is important for normal aorta function. Therefore, we hypothesize that mutations in other genes encoding SMC contractile proteins also cause familial TAAD. ^ To test this hypothesis, we used a candidate gene approach to identify causative mutations in SMC contractile genes for familial TAAD. Sequencing DNA in 80 TAAD patients from unrelated families, we identified putative mutations in eight contractile genes. We chose myosin light chain kinase (MLCK ) S1759P for further study for the following reasons: (1) Serine 1759 is conserved between vertebrates and invertebrates. (2) S1759P is predicted to be functionally deleterious by bioinformatics. (3) Low blood pressure is observed in SMC-selective MLCK-deficient mice. ^ In the presence of Ca2+/Calmodulin (CaM), MLCK containing CaM binding and kinase domains are activated to phosphorylate myosin light chain, thereby initiate SMC contraction. The CaM binding sequence of MLCK forms an α-helix structure required for CaM binding. MLCK Serine 1759 is located within the CaM binding domain. S1759P is predicted to decrease the α-helix composition in the CaM binding domain. Hence, we hypothesize that MLCK mutations cause TAAD through disturbing CaM binding and MLCK activity. ^ We further sequenced MLCK in DNA samples from additional 86 probands with familial TAAD. Two more mutations, MLCK A1754T and R1480Stop, were identified, supporting that MLCK mutations cause familial TAAD. ^ To define whether MLCK mutations disrupted CaM binding and MLCK activity, we performed co-immunoprecipitation and kinase assays. Decreased CaM binding and kinase activity was detected in A1754T and S1759P. Moreover, R1480Stop is predicted to truncate kinase and CaM binding domains. We conclude that MLCK mutations disrupt CaM binding and MLCK activity. ^ Collectively, our study is first to show mutations in genes regulating SMC contraction cause TAAD. This finding further highlights the importance of SMC contraction in maintaining aorta function. ^