The-more-the-better and the-less-the-better.
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Computational Biology↗
Biomedical subjects
Wentian Li
Publications and source records attributed to Wentian Li.
Large-scale oscillation of structure-related DNA sequence features in human chromosome 21.
Human chromosome 21 is the only chromosome in the human genome that exhibits oscillation of the (G+C) content of a cycle length of hundreds kilobases (kb) ( 500 kb near the right telomere). We aim at establishing the existence of a similar periodicity in structure-related sequence features in order to relate this (G+C)% oscillation to other biological phenomena. The following quantities are shown to oscillate with the same 500 kb periodicity in human chromosome 21: binding energy calculated by two sets of dinucleotide-based thermodynamic parameters, AA/TT and AAA/TTT bi- and tri-nucleotide density, 5'-TA-3' dinucleotide density, and signal for 10- or 11-base periodicity of AA/TT or AAA/TTT. These intrinsic quantities are related to structural features of the double helix of DNA molecules, such as base-pair binding, untwisting or unwinding, stiffness, and a putative tendency for nucleosome formation.
Base Composition↗
Monoclonal antibody classification based on epitope-binding using differential antigen disruption.
Currently, classifying a population of specific antigen-reactive monoclonal antibodies (mAbs) according to their epitope-binding properties has been limited to competition assays. Such assays are time consuming, labor intensive and restricted to the number of mAbs in the experiment. To overcome this problem, a differential antigen disruption-based antibody profiling procedure was developed. This procedure rapidly classifies specific antigen-reactive mAbs into epitope-related groups by measuring the binding signal of the antibodies to a set of structurally disrupted antigens and then clustering the antibodies according to the similarity of their binding profiles. The clustering results generated by differential antigen disruption showed a significant concordance with those generated by competition experiments. Therefore, differential antigen disruption method opens an opportunity to assess the entire population of antigen-reactive mAbs according to their epitope-binding properties. In doing so, a set of representative antibodies can be drawn to describe the epitope complexity for systematically exploring their functions.
Animals↗
Inferring causal relationships among intermediate phenotypes and biomarkers: a case study of rheumatoid arthritis.
MOTIVATION: Genetic association analysis is based on statistical correlations which do not assign any cause-to-effect arrows between the two correlated variables. Normally, such assignment of cause and effect label is not necessary in genetic analysis since genes are always the cause and phenotypes are always the effect. However, among intermediate phenotypes and biomarkers, assigning cause and effect becomes meaningful, and causal inference can be useful. RESULTS: We show that causal inference is possible by an example in a study of rheumatoid arthritis. With the help of genotypic information, the shared epitope, the causal relationship between two biomarkers related to the disease, anti-cyclic citrullinated peptide (anti-CCP) and rheumatoid factor (RF) has been established. We emphasize the fact that third variable must be a genotype to be able to resolve potential ambiguities in causal inference. Two non-trivial conclusions have been reached by the causal inference: (1) anti-CCP is a cause of RF and (2) it is unlikely that a third confounding factor contributes to both anti-CCP and RF.
Arthritis, Rheumatoid↗
Elevated serum levels of interferon-regulated chemokines are biomarkers for active human systemic lupus erythematosus.
BACKGROUND: Systemic lupus erythematosus (SLE) is a serious systemic autoimmune disorder that affects multiple organ systems and is characterized by unpredictable flares of disease. Recent evidence indicates a role for type I interferon (IFN) in SLE pathogenesis; however, the downstream effects of IFN pathway activation are not well understood. Here we test the hypothesis that type I IFN-regulated proteins are present in the serum of SLE patients and correlate with disease activity. METHODS AND FINDINGS: We performed a comprehensive survey of the serologic proteome in human SLE and identified dysregulated levels of 30 cytokines, chemokines, growth factors, and soluble receptors. Particularly striking was the highly coordinated up-regulation of 12 inflammatory and/or homeostatic chemokines, molecules that direct the movement of leukocytes in the body. Most of the identified chemokines were inducible by type I IFN, and their levels correlated strongly with clinical and laboratory measures of disease activity. CONCLUSIONS: These data suggest that severely disrupted chemokine gradients may contribute to the systemic autoimmunity observed in human SLE. Furthermore, the levels of serum chemokines may serve as convenient biomarkers for disease activity in lupus.
Adult↗
Comparing single-nucleotide polymorphism marker-based and microsatellite marker-based linkage analyses.
We compared linkage analysis results for an alcoholism trait, ALDX1 (DSM-III-R and Feigner criteria) using a nonparametric linkage analysis method, which takes into account allele sharing among several affected persons, for both microsatellite and single-nucleotide polymorphism (SNP) markers (Affymetrix and Illumina) in the Collaborative Study on the Genetics of Alcoholism (COGA) dataset provided to participants at the Genetic Analysis Workshop 14 (GAW14). The two sets of linkage results from the dense Affymetrix SNP markers and less densely spaced Illumina SNP markers are very similar. The linkage analysis results from microsatellite and SNP markers are generally similar, but the match is not perfect. Strong linkage peaks were found on chromosome 7 in three sets of linkage analyses using both SNP and microsatellite marker data. We also observed that for SNP markers, using the given genetic map and using the map by converting 1 megabase pair (1 Mb) to 1 centimorgan (cM), did not change the linkage results. We recommend the use of the 1 Mb-to-1 cM converted map in a first round of linkage analysis with SNP markers in which map integration is an issue.
Chromosomes, Human, Pair 7↗
Universal 1/f noise, crossovers of scaling exponents, and chromosome-specific patterns of guanine-cytosine content in DNA sequences of the human genome.
Spatial fluctuations of guanine and cytosine base content (GC%) are studied by spectral analysis for the complete set of human genomic DNA sequences. We find that (i) 1/ f(alpha) decay is universally observed in the power spectra of all 24 chromosomes, and (ii) the exponent alpha approximately 1 extends to about 10(7) bases, one order of magnitude longer than has previously been observed. We further find that (iii) almost all human chromosomes exhibit a crossover from alpha(1) approximately 1 (1/ f (alpha(1))) at lower frequency to alpha(2) <1 (1/ f (alpha(2))) at higher frequency, typically occurring at around 30,000-100,000 bases, while (iv) the crossover in this frequency range is virtually absent in human chromosome 22. In addition to the universal 1/ f(alpha) noise in power spectra, we find (v) several lines of evidence for chromosome-specific correlation structures, including a 500,000 base long oscillation in human chromosome 21. The universal 1/ f(alpha) spectrum in the human genome is further substantiated by a resistance to reduction in variance of guanine and cytosine content when the window size is increased.
Base Composition↗
Analysis of families in the multiple autoimmune disease genetics consortium (MADGC) collection: the PTPN22 620W allele associates with multiple autoimmune phenotypes.
Autoimmune disorders constitute a diverse group of phenotypes with overlapping features and a tendency toward familial aggregation. It is likely that common underlying genes are involved in these disorders. Until very recently, no specific alleles--aside from a few common human leukocyte antigen class II genes--had been identified that clearly associate with multiple different autoimmune diseases. In this study, we describe a unique collection of 265 multiplex families assembled by the Multiple Autoimmune Disease Genetics Consortium (MADGC). At least two of nine "core" autoimmune diseases are present in each of these families. These core diseases include rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), multiple sclerosis (MS), autoimmune thyroid disease (Hashimoto thyroiditis or Graves disease), juvenile RA, inflammatory bowel disease (Crohn disease or ulcerative colitis), psoriasis, and primary Sjogren syndrome. We report that a recently described functional single-nucleotide polymorphism (rs2476601, encoding R620W) in the intracellular tyrosine phosphatase (PTPN22) confers risk of four separate autoimmune phenotypes in these families: T1D, RA, SLE, and Hashimoto thyroiditis. MS did not show association with the PTPN22 risk allele. These findings suggest a common underlying etiologic pathway for some, but not all, autoimmune disorders, and they suggest that MS may have a pathogenesis that is distinct from RA, SLE, and T1D. DNA and clinical data for the MADGC families are available to the scientific community; these data will provide a valuable resource for the dissection of the complex genetic factors that underlie the various autoimmune phenotypes.
Autoimmune Diseases↗
Regulation of anti-cyclic citrullinated peptide antibodies in rheumatoid arthritis: contrasting effects of HLA-DR3 and the shared epitope alleles.
OBJECTIVE: To examine the association between HLA-DRB1 alleles and the production of anti-cyclic citrullinated peptide (anti-CCP) and rheumatoid factor (RF) autoantibodies in patients with rheumatoid arthritis (RA). METHODS: We studied 1,723 Caucasian RA patients enrolled in the North American Rheumatoid Arthritis Consortium (NARAC) family cohort and the Study of New Onset Rheumatoid Arthritis (SONORA) cohort. All patients were tested for anti-CCP antibodies (by enzyme-linked immunosorbent assay), RF (by nephelometry), and HLA-DR genotype (by polymerase chain reaction and sequence-specific oligonucleotide hybridization). RESULTS: When controlled for the presence of RF, anti-CCP positivity was strongly associated with the HLA-DRB1 shared epitope (SE). In RF+ patients, the presence of the SE was very significantly associated with anti-CCP positivity, with an odds ratio (OR) of 5.8 and a 95% confidence interval (95% CI) of 4.1-8.3. This relationship was also seen in RF- patients (OR 3.1 [95% CI 1.8-5.3]). In contrast, RF positivity was not significantly associated with presence of the SE independently of anti-CCP antibodies. Strikingly, HLA-DRB1*03 was strongly associated with reduced anti-CCP titers, even after controlling for the presence of the SE and restricting the analysis to anti-CCP+ patients. HLA-DR3 was also associated with anti-CCP- RA in our population. CONCLUSION: The HLA-DRB1 SE is strongly associated with the production of anti-CCP antibodies, but not RF. In contrast, HLA-DR3 alleles are associated with anti-CCP- disease and with lower levels of anti-CCP antibodies, even when controlling for the SE. These data emphasize the complexity of the genetic effects of the major histocompatibility complex on the RA phenotype.
Adult↗
Rapid self-organized criticality: Fractal evolution in extreme environments.
We introduce the phenomenon of rapid self-organized criticality (RSOC) and show that, like some models of self-organized criticality (SOC), RSOC generates scale-invariant event distributions and 1/f noise. Unlike SOC, however, RSOC persists despite more than an order of magnitude variation in driving rate and displays extremely thick and dynamic branching geometry. Starting with an initial set of parameter values, we perform two numerical experiments in which nonequilibrium RSOC systems are tuned towards their critical points. The approach to the critical state is tracked using average branching rates, which must equal 1 if systems are genuinely critical.
Journal Article↗
Reconstructing haplotypes in pedigrees: importance of parental information.
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Genotype↗
Identification of two novel female-specific non-major histocompatibility complex loci regulating collagen-induced arthritis severity and chronicity, and evidence of epistasis.
OBJECTIVE: To identify additional sex-specific and epistatic quantitative trait loci (QTL) regulating collagen-induced arthritis (CIA) severity overall, as well as within different stages during the disease course, in an intercross between major histocompatibility complex-identical inbred rat strains DA/Bkl (susceptible) and ACI/Hsd (resistant). METHODS: Arthritic male (DA x ACI)F2 intercross offspring (n = 143) were analyzed separately from the females (n = 184). Phenotypic extremes (maximum arthritis scores [MAS]) were genotyped and used for QTL analysis. All 327 rats were genotyped with the simple sequence-length polymorphism (SSLP) markers closest to the peak of Cia7 and Cia10, the major loci previously identified in this intercross, and with SSLPs covering chromosomes 12 and 18. Phenotypes studied were disease onset, arthritis severity scores on days 14-39, MAS, mean and cumulative arthritis scores, delayed-type hypersensitivity, and antibody responses to rat type II collagen. RESULTS: A new female-specific arthritis-severity recessive locus was identified on rat chromosome 12 (Cia25), with a maximum effect observed on day 28 (logarithm of odds [LOD] 4.7). The homozygous DA genotype at Cia25 was associated with a 45% higher median arthritis score in females. Sequencing analyses of the Cia25 candidate gene Ncf1 revealed polymorphisms between DA and ACI. The previously identified locus, Cia10, was found to be male-specific. A 2-locus interaction model analysis identified a novel recessive chromosome 18 QTL, Cia26, which was dependent on Cia7, with its maximum effect observed at later stages during the disease course (peak LOD score of 3.6 for arthritis scores on day 39). CONCLUSION: This study identified 2 novel female-specific loci, and 1 male-specific locus. Cia25 regulates MAS and disease severity during the mid-to-late stages of the disease course and may be accounted for by Ncf1 polymorphisms. Cia26 is in epistasis with Cia7 and regulates later stages of disease, suggesting an involvement in disease perpetuation and/or chronicity.
Animals↗
An unusual 500,000 bases long oscillation of guanine and cytosine content in human chromosome 21.
An oscillation with a period of around 500 kb in guanine and cytosine content (GC%) is observed in the DNA sequence of human chromosome 21. This oscillation is localized in the rightmost one-eighth region of the chromosome, from 43.5 Mb to 46.5 Mb. Five cycles of oscillation are observed in this region with six GC-rich peaks and five GC-poor valleys. The GC-poor valleys comprise regions with low density of CpG islands and, alternating between the two DNA strands, low gene density regions. Consequently, the long-range oscillation of GC% result in spacing patterns of both CpG island density, and to a lesser extent, gene densities.
Base Composition↗
Extreme value distribution based gene selection criteria for discriminant microarray data analysis using logistic regression.
One important issue commonly encountered in the analysis of microarray data is to decide which and how many genes should be selected for further studies. For discriminant microarray data analyses based on statistical models, such as the logistic regression models, gene selection can be accomplished by a comparison of the maximum likelihood of the model given the real data, L(D|M), and the expected maximum likelihood of the model given an ensemble of surrogate data with randomly permuted label, L(D(0)|M). Typically, the computational burden for obtaining L(D(0)M) is immense, often exceeding the limits of available computing resources by orders of magnitude. Here, we propose an approach that circumvents such heavy computations by mapping the simulation problem to an extreme-value problem. We present the derivation of an asymptotic distribution of the extreme-value as well as its mean, median, and variance. Using this distribution, we propose two gene selection criteria, and we apply them to two microarray datasets and three classification tasks for illustration.
Chromosome Mapping↗
Correlation between quantitative traits and correlation between corresponding LOD scores: detection of pleiotropic effects.
BACKGROUND: We address the question of whether statistical correlations among quantitative traits lead to correlation of linkage results of these traits. Five measured quantitative traits (total cholesterol, fasting glucose, HDL cholesterol, blood pressure, and triglycerides), and one derived quantitative trait (total cholesterol divided by the HDL cholesterol) are used for phenotype correlation studies. Four of them are used for linkage analysis. RESULTS: We show that although correlation among phenotypes partially reflects the correlation among linkage analysis results, the LOD-score correlations are on average low. The most significant peaks found by using different traits do not often overlap. CONCLUSION: Studying covariances at specific locations in LOD scores may provide clues for further bivariate linkage analyses.
Adult↗
Gene discovery in bladder cancer progression using cDNA microarrays.
To identify gene expression changes along progression of bladder cancer, we compared the expression profiles of early-stage and advanced bladder tumors using cDNA microarrays containing 17,842 known genes and expressed sequence tags. The application of bootstrapping techniques to hierarchical clustering segregated early-stage and invasive transitional carcinomas into two main clusters. Multidimensional analysis confirmed these clusters and more importantly, it separated carcinoma in situ from papillary superficial lesions and subgroups within early-stage and invasive tumors displaying different overall survival. Additionally, it recognized early-stage tumors showing gene profiles similar to invasive disease. Different techniques including standard t-test, single-gene logistic regression, and support vector machine algorithms were applied to identify relevant genes involved in bladder cancer progression. Cytokeratin 20, neuropilin-2, p21, and p33ING1 were selected among the top ranked molecular targets differentially expressed and validated by immunohistochemistry using tissue microarrays (n = 173). Their expression patterns were significantly associated with pathological stage, tumor grade, and altered retinoblastoma (RB) expression. Moreover, p33ING1 expression levels were significantly associated with overall survival. Analysis of the annotation of the most significant genes revealed the relevance of critical genes and pathways during bladder cancer progression, including the overexpression of oncogenic genes such as DEK in superficial tumors or immune response genes such as Cd86 antigen in invasive disease. Gene profiling successfully classified bladder tumors based on their progression and clinical outcome. The present study has identified molecular biomarkers of potential clinical significance and critical molecular targets associated with bladder cancer progression.
Aged↗
Isochores merit the prefix 'iso'.
The isochore concept in the human genome sequence was challenged in an analysis by the International Human Genome Sequencing Consortium (IHGSC). We argue here that a statement in the IHGSC's analysis concerning the existence of isochores is misleading, because the homogeneity was not examined at a large enough length scale and consequently an inappropriate statistical test was applied. A test of the existence of isochores should be equivalent to a test of homogeneity or equality of windowed GC%. The statistical test applied in the IHGSC's analysis, the binomial test, is a test of whether individual bases are independent and identically-distributed (iid). For testing the existence of isochores, or homogeneity in windowed GC%, we propose to use another statistical test: the analysis of variance (ANOVA). It can be shown that DNA sequences that are rejected by the binomial test may not be rejected by the ANOVA test.
Analysis of Variance↗
Zipf's law in importance of genes for cancer classification using microarray data.
Using a measure of how differentially expressed a gene is in two biochemically/phenotypically different conditions, we can rank all genes in a microarray dataset. We have shown that the falling-off of this measure (normalized maximum likelihood in a classification model such as logistic regression) as a function of the rank is typically a power-law function. This power-law function in other similar ranked plots are known as the Zipf's law, observed in many natural and social phenomena. The presence of this power-law function prevents an intrinsic cutoff point between the "important" genes and "irrelevant" genes. We have shown that similar power-law functions are also present in permuted dataset, and provide an explanation from the well-known chi(2) distribution of likelihood ratios. We discuss the implication of this Zipf's law on gene selection in a microarray data analysis, as well as other characterizations of the ranked likelihood plots such as the rate of fall-off of the likelihood.
Diagnosis, Differential↗