Shaoqi Rao

Identification of an angiogenic factor that when mutated causes susceptibility to Klippel–Trenaunay syndrome

Angiogenic factors are critical to the initiation of angiogenesis and maintenance of the vascular network. Here we use human genetics as an approach to identify an angiogenic factor, VG5Q, and further define two genetic defects of VG5Q in patients with the vascular disease Klippel–Trenaunay syndrome (KTS). One mutation is chromosomal translocation t(5;11), which increases VG5Q transcription. The second is mutation E133K identified in five KTS patients, but not in 200 matched controls. VG5Q protein acts as a potent angiogenic factor in promoting angiogenesis, and suppression of VG5Q expression inhibits vessel formation. E133K is a functional mutation that substantially enhances the angiogenic effect of VG5Q. VG5Q shows strong expression in blood vessels and is secreted as vessel formation is initiated. VG5Q can bind to endothelial cells and promote cell proliferation, suggesting that it may act in an autocrine fashion. We also demonstrate a direct interaction of VG5Q with another secreted angiogenic factor, TWEAK (also known as TNFSF12). These results define VG5Q as an angiogenic factor, establish VG5Q as a susceptibility gene for KTS, and show that increased angiogenesis is a molecular pathogenic mechanism of KTS.

Premature Myocardial Infarction Novel Susceptibility Locus on Chromosome 1P34-36 Identified by Genomewide Linkage Analysis

The most frequent causes of death and disability in the Western world are atherosclerotic coronary artery disease (CAD) and acute myocardial infarction (MI). This common disease is thought to have a polygenic basis with a complex interaction with environmental factors. Here, we report results of a genomewide search for susceptibility genes for MI in a well-characterized U.S. cohort consisting of 1,613 individuals in 428 multiplex families with familial premature CAD and MI: 712 with MI, 974 with CAD, and average age of onset of 44.4+/-9.7 years. Genotyping was performed at the National Heart, Lung, and Blood Institute Mammalian Genotyping Facility through use of 408 markers that span the entire human genome every 10 cM. Linkage analysis was performed with the modified Haseman-Elston regression model through use of the SIBPAL program. Three genomewide scans were conducted: single-point, multipoint, and multipoint performed on of white pedigrees only (92% of the cohort). One novel significant susceptibility locus was detected for MI on chromosomal region 1p34-36, with a multipoint allele-sharing P value of <10(-12) (LOD=11.68). Validation by use of a permutation test yielded a pointwise empirical P value of.00011 at this locus, which corresponds to a genomewide significance of P<.05. For the less restrictive phenotype of CAD, no genetic locus was detected, suggesting that CAD and MI may not share all susceptibility genes. The present study thus identifies a novel genetic-susceptibility locus for MI and provides a framework for the ultimate cloning of a gene for the complex disease MI.

Genomewide linkage scan identifies a novel susceptibility locus for restless legs syndrome on chromosome 9p.

Restless legs syndrome (RLS) is a common neurological disorder that affects 5%-12% of all whites. To genetically dissect this complex disease, we characterized 15 large and extended multiplex pedigrees, consisting of 453 subjects (134 affected with RLS). A familial aggregation analysis was performed, and SAGE FCOR was used to quantify the total genetic contribution in these families. A weighted average correlation of 0.17 between first-degree relatives was obtained, and heritability was estimated to be 0.60 for all types of relative pairs, indicating that RLS is a highly heritable trait in this ascertained cohort. A genomewide linkage scan, which involved >400 10-cM-spaced markers and spanned the entire human genome, was then performed for 144 individuals in the cohort. Model-free linkage analysis identified one novel significant RLS-susceptibility locus on chromosome 9p24-22 with a multipoint nonparametric linkage (NPL) score of 3.22. Suggestive evidence of linkage was found on chromosome 3q26.31 (NPL score 2.03), chromosome 4q31.21 (NPL score 2.28), chromosome 5p13.3 (NPL score 2.68), and chromosome 6p22.3 (NPL score 2.06). Model-based linkage analysis, with the assumption of an autosomal-dominant mode of inheritance, validated the 9p24-22 linkage to RLS in two families (two-point LOD score of 3.77; multipoint LOD score of 3.91). Further fine mapping confirmed the linkage result and defined this novel RLS disease locus to a critical interval. This study establishes RLS as a highly heritable trait, identifies a novel genetic locus for RLS, and will facilitate further cloning and identification of the genes for RLS.

Four SNPs on Chromosome 9p21 in a South Korean Population Implicate a Genetic Locus That Confers High Cross-Race Risk for Development of Coronary Artery Disease

Objective—Recent genome-wide association studies have identified 4 SNPs on chromosome 9p21 associated with CAD (rs10757274 and rs2383206) and myocardial infarction (MI: rs2383207 and rs10757278) in White populations in Northern Europe and North America. We aimed to determine whether this locus confers significant susceptibility to CAD in a South Korean population, and thus cross-race susceptibility to CAD. Methods and Results—We performed a case-control association study with 611 unrelated CAD patients and 294 normal controls from South Korea. Allelic associations of SNPs and SNP haplotypes with CAD were evaluated. Multivariate logistic regression analysis was used to adjust effects of clinical covariates. We found that 4 SNPs on chromosome 9p21 were associated with susceptibility to CAD in a South Korean population. The association remained significant after adjusting for significant clinical covariates (P=0.001 to 0.024). We identified one risk haplotype (GGGG; P=0.017) and one protective haplotype (AAAA; P=0.007) for development of CAD. Further analysis suggested that the SNPs probably confer susceptibility to CAD in a dominance model (covariates-adjusted P=0.001 to 0.024; OR=2.37 to 1.54). This represents the first study that expands association of these 9p21 SNPs with CAD beyond White populations. Conclusion—Chromosome 9p21 is an important susceptibility locus that confers high cross-race risk for development of CAD.

ASSOCIATION BETWEEN FOUR SNPS ON CHROMOSOME 9P21 AND MYOCARDIAL INFARCTION IS REPLICATED IN AN ITALIAN POPULATION

AbstractGenome-wide single nucleotide polymorphism (SNP) association studies recently identified four SNPs (rs10757274, rs2383206, rs2383207, and rs10757278) on chromosome 9p21 that were associated with coronary artery disease (CAD) and myocardial infarction (MI) in Caucasian populations from northern Europe and North America. Our aim was to determine whether these SNPs were associated with MI in a southern Europe/Mediterranean population. We employed a case–control association design involving 416 MI patients and 308 non-MI controls from Italy. Significant allelic association was identified between all four SNPs and MI. The association remained significant after adjusting for covariates for MI (P = 0.007–0.029). One risk haplotype (GGGG; P = 0.028) and one protective haplotype (AAAA; P = 0.047) were identified. Genotypic association analysis demonstrated that the SNPs conferred susceptibility to MI most likely in a dominant model (P = 0.0007–0.013). When the case cohort was divided into a group of MI patients with a family history (n = 248) and one group without it (n = 168), the positive, significant association was identified only in the group with the family history. These results indicate that chromosome 9p21 confers risk for development of MI in an Italian population.

Towards precise classification of cancers based on robust gene functional expression profiles

BackgroundDevelopment of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. The accumulated experiment evidence supports the assumption that genes express and perform their functions in modular fashions in cells. Therefore, there is an open space for development of the timely and relevant computational algorithms that use robust functional expression profiles towards precise classification of complex human diseases at the modular level.ResultsInspired by the insight that genes act as a module to carry out a highly integrated cellular function, we thus define a low dimension functional expression profile for data reduction. After annotating each individual gene to functional categories defined in a proper gene function classification system such as Gene Ontology applied in this study, we identify those functional categories enriched with differentially expressed genes. For each functional category or functional module, we compute a summary measure (s) for the raw expression values of the annotated genes to capture the overall activity level of the module. In this way, we can treat the gene expressions within a functional module as an integrative data point to replace the multiple values of individual genes. We compare the classification performance of decision trees based on functional expression profiles with the conventional gene expression profiles using four publicly available datasets, which indicates that precise classification of tumour types and improved interpretation can be achieved with the reduced functional expression profiles.ConclusionThis modular approach is demonstrated to be a powerful alternative approach to analyzing high dimension microarray data and is robust to high measurement noise and intrinsic biological variance inherent in microarray data. Furthermore, efficient integration with current biological knowledge has facilitated the interpretation of the underlying molecular mechanisms for complex human diseases at the modular level.

Genome-Wide Linkage Scan Identifies a Novel Genetic Locus on Chromosome 5p13 for Neonatal Atrial Fibrillation Associated With Sudden Death and Variable Cardiomyopathy

Background—Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and patients with AF have a significantly increased risk for ischemic stroke. Approximately 15% of all strokes are caused by AF. The molecular basis and underlying mechanisms and pathophysiology of AF remain largely unknown. Methods and Results—We have identified a large AF family with an autosomal recessive inheritance pattern. The AF in the family manifests with early onset at the fetal stage and is associated with neonatal sudden death and, in some cases, ventricular tachyarrhythmias and waxing and waning cardiomyopathy. Genome-wide linkage analysis was performed for 36 family members and generated a 2-point logarithm of the odds (LOD) score of 3.05 for marker D5S455. The maximum multipoint LOD score of 4.10 was obtained for 4 markers: D5S426, D5S493, D5S455, and D5S1998. Heterozygous carriers have significant prolongation of P-wave duration on ECGs compared with noncarriers (107 versus 85 ms on average; P=0.000012), but no differences between these 2 groups were detected for the PR interval, QRS complex, ST-segment duration, T-wave duration, QTc, and R-R interval (P>0.05). Conclusions—Our findings demonstrate that AF can be inherited as an autosomal recessive trait and define a novel genetic locus for AF on chromosome 5p13 (arAF1). A genetic link between AF and prolonged P-wave duration was identified. This study provides a framework for the ultimate cloning of the arAF1 gene, which will increase the understanding of the fundamental molecular mechanisms of atrial fibrillation.

An LRP8 Variant Is Associated with Familial and Premature Coronary Artery Disease and Myocardial Infarction

Our previous genomewide linkage scan of 428 nuclear families (GeneQuest) identified a significant genetic susceptibility locus for premature myocardial infarction (MI) on chromosome 1p34-36. We analyzed candidate genes in the locus with a population-based association study involving probands with premature coronary artery disease (CAD) and/or MI from the GeneQuest families (381 cases) and 560 controls without stenosis detectable by coronary angiography. A nonconservative substitution, R952Q, in LRP8 was significantly associated with susceptibility to premature CAD and/or MI by use of both population-based and family-based designs. Three additional white populations were used for follow-up replication studies: another independent cohort of CAD- and/or MI-affected families (GeneQuest II: 441 individuals from 22 pedigrees), an Italian cohort with familial MI (248 cases) and 308 Italian controls, and a separate Cleveland GeneBank cohort with sporadic MI (1,231 cases) and 560 controls. The association was significantly replicated in two independent populations with a family history of CAD and/or MI, the GeneQuest II family-based replication cohort and the Italian cohort, but not in the population with sporadic disease. The R952Q variant of LRP8 increased activation of p38 mitogen-activated protein kinase by oxidized low-density lipoprotein. This extensive study, involving multiple independent populations, provides the first evidence that genetic variants in LRP8 may contribute to the development of premature and familial CAD and MI.

Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

BackgroundIt is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks.ResultsIn particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network) to address the underlying regulations of genes that can span any unit(s) of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings.ConclusionWe established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex gene regulations related to the development, aging and progressive pathogenesis of a complex disease where potential dependences between different experiment units might occurs.

Constructing disease-specific gene networks using pair-wise relevance metric: Application to colon cancer identifies interleukin 8, desmin and enolase 1 as the central elements

BackgroundWith the advance of large-scale omics technologies, it is now feasible to reversely engineer the underlying genetic networks that describe the complex interplays of molecular elements that lead to complex diseases. Current networking approaches are mainly focusing on building genetic networks at large without probing the interaction mechanisms specific to a physiological or disease condition. The aim of this study was thus to develop such a novel networking approach based on the relevance concept, which is ideal to reveal integrative effects of multiple genes in the underlying genetic circuit for complex diseases.ResultsThe approach started with identification of multiple disease pathways, called a gene forest, in which the genes extracted from the decision forest constructed by supervised learning of the genome-wide transcriptional profiles for patients and normal samples. Based on the newly identified disease mechanisms, a novel pair-wise relevance metric, adjusted frequency value, was used to define the degree of genetic relationship between two molecular determinants. We applied the proposed method to analyze a publicly available microarray dataset for colon cancer. The results demonstrated that the colon cancer-specific gene network captured the most important genetic interactions in several cellular processes, such as proliferation, apoptosis, differentiation, mitogenesis and immunity, which are known to be pivotal for tumourigenesis. Further analysis of the topological architecture of the network identified three known hub cancer genes [interleukin 8 (IL8) (p ≈ 0), desmin (DES) (p = 2.71 × 10-6) and enolase 1 (ENO1) (p = 4.19 × 10-5)], while two novel hub genes [RNA binding motif protein 9 (RBM9) (p = 1.50 × 10-4) and ribosomal protein L30 (RPL30) (p = 1.50 × 10-4)] may define new central elements in the gene network specific to colon cancer. Gene Ontology (GO) based analysis of the colon cancer-specific gene network and the sub-network that consisted of three-way gene interactions suggested that tumourigenesis in colon cancer resulted from dysfunction in protein biosynthesis and categories associated with ribonucleoprotein complex which are well supported by multiple lines of experimental evidence.ConclusionThis study demonstrated that IL8, DES and ENO1 act as the central elements in colon cancer susceptibility, and protein biosynthesis and the ribosome-associated function categories largely account for the colon cancer tumuorigenesis. Thus, the newly developed relevancy-based networking approach offers a powerful means to reverse-engineer the disease-specific network, a promising tool for systematic dissection of complex diseases.