Anbupalam Thalamuthu

A common BIM deletion polymorphism mediates intrinsic resistance and inferior responses to tyrosine kinase inhibitors in cancer

Tyrosine kinase inhibitors (TKIs) elicit high response rates among individuals with kinase-driven malignancies, including chronic myeloid leukemia (CML) and epidermal growth factor receptor–mutated non–small-cell lung cancer (EGFR NSCLC). However, the extent and duration of these responses are heterogeneous, suggesting the existence of genetic modifiers affecting an individuals response to TKIs. Using paired-end DNA sequencing, we discovered a common intronic deletion polymorphism in the gene encoding BCL2-like 11 (BIM). BIM is a pro-apoptotic member of the B-cell CLL/lymphoma 2 (BCL2) family of proteins, and its upregulation is required for TKIs to induce apoptosis in kinase-driven cancers. The polymorphism switched BIM splicing from exon 4 to exon 3, which resulted in expression of BIM isoforms lacking the pro-apoptotic BCL2-homology domain 3 (BH3). The polymorphism was sufficient to confer intrinsic TKI resistance in CML and EGFR NSCLC cell lines, but this resistance could be overcome with BH3-mimetic drugs. Notably, individuals with CML and EGFR NSCLC harboring the polymorphism experienced significantly inferior responses to TKIs than did individuals without the polymorphism (P = 0.02 for CML and P = 0.027 for EGFR NSCLC). Our results offer an explanation for the heterogeneity of TKI responses across individuals and suggest the possibility of personalizing therapy with BH3 mimetics to overcome BIM-polymorphism–associated TKI resistance.

A Genome-Wide Association Study Identifies Novel and Functionally Related Susceptibility Loci for Kawasaki Disease

Kawasaki disease (KD) is a pediatric vasculitis that damages the coronary arteries in 25% of untreated and approximately 5% of treated children. Epidemiologic data suggest that KD is triggered by unidentified infection(s) in genetically susceptible children. To investigate genetic determinants of KD susceptibility, we performed a genome-wide association study (GWAS) in 119 Caucasian KD cases and 135 matched controls with stringent correction for possible admixture, followed by replication in an independent cohort and subsequent fine-mapping, for a total of 893 KD cases plus population and family controls. Significant associations of 40 SNPs and six haplotypes, identifying 31 genes, were replicated in an independent cohort of 583 predominantly Caucasian KD families, with NAALADL2 (rs17531088, p combined = 1.13×10−6) and ZFHX3 (rs7199343, p combined = 2.37×10−6) most significantly associated. Sixteen associated variants with a minor allele frequency of >0.05 that lay within or close to known genes were fine-mapped with HapMap tagging SNPs in 781 KD cases, including 590 from the discovery and replication stages. Original or tagging SNPs in eight of these genes replicated the original findings, with seven genes having further significant markers in adjacent regions. In four genes (ZFHX3, NAALADL2, PPP1R14C, and TCP1), the neighboring markers were more significantly associated than the originally associated variants. Investigation of functional relationships between the eight fine-mapped genes using Ingenuity Pathway Analysis identified a single functional network (p = 10−13) containing five fine-mapped genes—LNX1, CAMK2D, ZFHX3, CSMD1, and TCP1—with functional relationships potentially related to inflammation, apoptosis, and cardiovascular pathology. Pair-wise blood transcript levels were measured during acute and convalescent KD for all fine-mapped genes, revealing a consistent trend of significantly reduced transcript levels prior to treatment. This is one of the first GWAS in an infectious disease. We have identified novel, plausible, and functionally related variants associated with KD susceptibility that may also be relevant to other cardiovascular diseases.

Evaluation and comparison of gene clustering methods in microarray analysis

MOTIVATION Microarray technology has been widely applied in biological and clinical studies for simultaneous monitoring of gene expression in thousands of genes. Gene clustering analysis is found useful for discovering groups of correlated genes potentially co-regulated or associated to the disease or conditions under investigation. Many clustering methods including hierarchical clustering, K-means, PAM, SOM, mixture model-based clustering and tight clustering have been widely used in the literature. Yet no comprehensive comparative study has been performed to evaluate the effectiveness of these methods. RESULTS In this paper, six gene clustering methods are evaluated by simulated data from a hierarchical log-normal model with various degrees of perturbation as well as four real datasets. A weighted Rand index is proposed for measuring similarity of two clustering results with possible scattered genes (i.e. a set of noise genes not being clustered). Performance of the methods in the real data is assessed by a predictive accuracy analysis through verified gene annotations. Our results show that tight clustering and model-based clustering consistently outperform other clustering methods both in simulated and real data while hierarchical clustering and SOM perform among the worst. Our analysis provides deep insight to the complicated gene clustering problem of expression profile and serves as a practical guideline for routine microarray cluster analysis.

Association Analysis of CFH, C2, BF, and HTRA1 Gene Polymorphisms in Chinese Patients with Polypoidal Choroidal Vasculopathy

PURPOSE Polypoidal choroidal vasculopathy (PCV) is a major cause of serosanguinous maculopathy in Chinese patients with age-related macular degeneration (AMD). Variants in the CFH and HTRA1/LOC387715 genes are strongly associated with AMD in Caucasians and Chinese. Variants in the C2 and BF genes have been found to confer a significantly reduced risk of AMD. This study was undertaken to determine whether these associations occur in Chinese patients with PCV. METHODS Patients of Chinese ethnicity with clinically and angiographically diagnosed PCV and normal control subjects were recruited from the Singapore National Eye Centre. Five single-nucleotide polymorphisms (SNPs) in the CFH gene, two each within the C2 and BF genes and two variants located in the LOC387715 and HTRA1 genes, were screened in all patients and control subjects. RESULTS Seventy-two patients with PCV and 93 normal control subjects were studied. A significant association was noted with CFH variants rs3753394 and rs800292 among the PCV cases (P = 0.0015 and P = 0.0045, respectively). Individuals homozygous for the TT genotype of rs3753394 had a significantly higher risk (P = 0.0076) of PCV (OR = 4.29; 95% CI: 1.47-12.50) than those carrying a single copy of the T allele (P = 0.3210; OR = 1.69; 95% CI: 0.60-4.78), after adjustment for such risk factors as age and sex. The genotype frequencies of rs11200638 and rs10490924 in HTRA1 and LOC387715, respectively, were also found to be significantly different between patients with PCV and normal control subjects (P = 0.00032 and P = 0.003, respectively). The AA genotype of rs11200638 and TT genotype of rs10490924 conferred a 4.9-fold (95% CI: 1.85-12.95) and 4.89-fold (95% CI: 1.85-12.90) increased risk of PCV, respectively, after adjustment for age and sex. The Y402H variant of CFH (rs1061170) and the BF and C2 variants were not significantly different in patients and normal control subjects. CONCLUSIONS The SNPs rs3753394 and rs800292 of CFH and rs11200638 of HTRA1 are significantly associated with the risk of PCV in Chinese patients.

Association of LOXL1 Gene Polymorphisms with Pseudoexfoliation in the Japanese

PURPOSE The single nucleotide polymorphisms (SNPs) rs1048661, rs3825942, and rs2165241 within the LOXL1 gene were recently found to confer risk of pseudoexfoliation glaucoma (XFG) through pseudoexfoliation syndrome (XFS) in Caucasians. The purpose of this study was to test this association in Japanese subjects with XFS/XFG. METHODS Japanese subjects with clinically diagnosed XFS/XFG and normal control subjects were recruited. Genomic DNA was extracted and the three SNPs of the LOXL1 gene were genotyped by bidirectional sequencing. The association of individual SNPs with XFG/XFS was evaluated by using chi(2) and the Fisher exact test. RESULTS Two hundred nine Japanese patients (106 XFG and 103 XFS) and 172 control subjects were studied. Strong associations were observed for all three SNPs of LOXL1 for XFS (odds ratio [OR] = 13.56, P = 3.39 x 10(-28) for allele T of rs1048661; OR = 10.71, P = 1.49 x 10(-7) for allele G of rs3825942; and OR = 4.55, P = 5.33 x 10(-4) for allele C of rs2165241) and XFG (OR = 25.21, P = 1.44 x 10(-34) for allele T of rs1048661; OR = 11.02, P = 1.40 x 10(-7) for allele G of rs3825942; and OR = 11.89, P = 4.76 x 10(-6) for allele C of rs2165241). The risk-associated alleles of rs1048661 and rs2165241 differed between the Japanese and Caucasians, whereas allele G of rs3825942 was associated with disease in both populations. Conditional analysis indicated that rs3825942 was not independent but correlated highly with rs1048661. The at-risk haplotype T-G-C was present at an approximately two times higher rate (94.7% vs. 50.6%, P = 4.22 x 10(-43)) in cases than in control subjects and conferred a 2.9-fold (95% confidence interval [CI], 2.357-3.464) increased likelihood of XFS. CONCLUSIONS Polymorphisms in the LOXL1 gene confer risk to XFS/XFG in the Japanese, but there are different risk-associated alleles and haplotypes in the Japanese.

Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept.

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.

A Genome Wide Association Study of Hepatitis B Vaccine Response in an Indonesian Population Reveals Multiple Independent Risk Variants in the HLA Region

We performed a two-stage genome-wide association study (GWAS) of antibody titer in 3614 hepatitis B vaccine recipients from Indonesias Riau Archipelago, leading to the identification of at least three independent signals within the human leukocyte antigen (HLA) complex. These appear to implicate HLA-DR [rs3135363; P= 6.53 × 10(-22); odds ratio (OR) = 1.53, 95% confidence interval (CI) = 1.35-1.74]; HLA-DP, previously associated with the risk of chronic hepatitis B infection (rs9277535; P= 2.91 × 10(-12); OR = 0.72, 95% CI = 0.63-0.81); and a gene rich HLA Class III interval (rs9267665; P = 1.24 × 10(-17); OR = 2.05, CI = 1.64-2.57). The substantial overlap of these variants and those identified by GWAS of chronic hepatitis B infection confirms vaccine response as a model for infection, while suggesting that the vaccine is least effective in those most at risk of lifelong infection, following exposure to the virus.

Association tests using kernel-based measures of multi-locus genotype similarity between individuals

In a genetic association study, it is often desirable to perform an overall test of whether any or all single‐nucleotide polymorphisms (SNPs) in a gene are associated with a phenotype. Several such tests exist, but most of them are powerful only under very specific assumptions about the genetic effects of the individual SNPs. In addition, some of the existing tests assume that the direction of the effect of each SNP is known, which is a highly unlikely scenario. Here, we propose a new kernel‐based association test of joint association of several SNPs. Our test is non‐parametric and robust, and does not make any assumption about the directions of individual SNP effects. It can be used to test multiple correlated SNPs within a gene and can also be used to test independent SNPs or genes in a biological pathway. Our test uses an analysis of variance paradigm to compare variation between cases and controls to the variation within the groups. The variation is measured using kernel functions for each marker, and then a composite statistic is constructed to combine the markers into a single test. We present simulation results comparing our statistic to the U‐statistic‐based method by Schaid et al. ([2005] Am. J. Hum. Genet. 76:780–793) and another statistic by Wessel and Schork ([2006] Am. J. Hum. Genet. 79:792–806). We consider a variety of different disease models and assumptions about how many SNPs within the gene are actually associated with disease. Our results indicate that our statistic has higher power than other statistics under most realistic conditions. Genet. Epidemiol. 34: 213–221, 2010.

Genetic influences on schizophrenia and subcortical brain volumes

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.

Large-Scale Functional Organization of Long-Range Chromatin Interaction Networks

SUMMARY Chromatin interactions play important roles in transcription regulation. To better understand the underlying evolutionary and functional constraints of these interactions, we implemented a systems approach to examine RNA polymerase-II-associated chromatin interactions in human cells. We found that 40% of the total genomic elements involved in chromatin interactions converged to a giant, scale-free-like, hierarchical network organized into chromatin communities. The communities were enriched in specific functions and were syntenic through evolution. Disease-associated SNPs from genome-wide association studies were enriched among the nodes with fewer interactions, implying their selection against deleterious interactions by limiting the total number of interactions, a model that we further reconciled using somatic and germline cancer mutation data. The hubs lacked disease-associated SNPs, constituted a nonrandomly interconnected core of key cellular functions, and exhibited lethality in mouse mutants, supporting an evolutionary selection that favored the nonrandom spatial clustering of the least-evolving key genomic domains against random genetic or transcriptional errors in the genome. Altogether, our analyses reveal a systems-level evolutionary framework that shapes functionally compartmentalized and error-tolerant transcriptional regulation of human genome in three dimensions.