Myopia, or nearsightedness, is a common ocular genetic disease for which over 20 candidate genomic loci have been identified. The high-grade myopia locus, MYP3, has been reported on chromosome 12q21–23 by four independent linkage studies.
We performed a genetic association study of the MYP3 locus in a family-based high-grade myopia cohort (n = 82) by genotyping 768 single-nucleotide polymorphisms (SNPs) within the linkage region. Qualitative testing for high-grade myopia (sphere ≤ −5 D affected, > −0.5 D unaffected) and quantitative testing on the average dioptric sphere were performed.
Several genetic markers were nominally significantly associated with high-grade myopia in qualitative testing, including rs3803036, a missense mutation in PTPRR (P = 9.1 × 10−4) and rs4764971, an intronic SNP in UHRF1BP1L (P = 6.1 × 10−4). Quantitative testing determined statistically significant SNPs rs4764971, also found by qualitative testing (P = 3.1 × 10−6); rs7134216, in the 3′ untranslated region (UTR) of DEPDC4 (P = 5.4 × 10−7); and rs17306116, an intronic SNP within PPFIA2 (P < 9 × 10−4). Independently conducted whole genome expression array analyses identified protein tyrosine phosphatase genes PTPRR and PPFIA2, which are in the same gene family, as differentially expressed in normal rapidly growing fetal relative to normal adult ocular tissue (confirmed by RT-qPCR).
In an independent high-grade myopia cohort, an intronic SNP in UHRF1BP1L, rs4764971, was validated for quantitative association, and SNPs within PTPRR (quantitative) and PPFIA2 (qualitative and quantitative) approached significance. Three genes identified by our association study and supported by ocular expression and/or replication, UHRF1BP1L, PTPRR, and PPFIA2, are novel candidates for myopic development within the MYP3 locus that should be further studied.
Association mapping of the MYP3 locus reveals novel candidate genes.
To evaluate the utility of subchondral bone texture from a baseline x-ray image for predicting 3-year knee osteoarthritis (OA) progression.
A total of 138 participants in the Prediction of Osteoarthritis Progression (POP) study were evaluated at baseline and 3 years. Fixed-flexion knee radiographs of the 248 non-replaced knees underwent fractal analysis of the medial subchondral tibial plateau using a commercially available software tool. OA progression was defined as a 1-grade change in joint space narrowing (JSN) or osteophyte based on a standardized knee atlas. Statistical analysis of fractal signatures was performed using a new method based on modeling the overall shape of fractal dimension versus radius curves.
Baseline fractal signature of the medial tibial plateau was predictive of medial knee JSN progression (area under the curve [AUC] of Receiver Operating Characteristic plot of 0.75), but not progression based on osteophyte or progression of the lateral compartment. The traditional covariates (age, gender, body mass index, knee pain), general bone mineral content, and baseline joint space width fared little better than random variables for predicting OA progression (AUC 0.52–0.58). The maximal predictive model combined baseline fractal signature, knee alignment, traditional covariates, and bone mineral content (AUC 0.79).
We identified a prognostic marker of OA that is readily extracted from a plain radiograph by fractal signature analysis. The global shape approach to analyzing these data is a potentially efficient means of identifying individuals at risk of knee OA progression that needs to be validated in a second cohort.
osteoarthritis; imaging; biomarker; subchondral bone
To evaluate the association of serum and synovial fluid cartilage oligomeric matrix protein (COMP) with systemic and local measures of osteoarthritis (OA) activity by bone scintigraphy.
Knee joint synovial fluid (total 275 knees) and serum were obtained from 159 participants with symptomatic OA of at least one knee. Technetium-99m-methylene diphosphonate (Tc-MDP) bone scintigraphy was performed and early phase knee scans and late phase whole body bone scans of 15 additional joint sites were scored semi-quantitatively. Correlations of bone scan scores with COMP utilized generalized linear modelling to control for within subject correlation of knee data. Principal components analysis was used to explore the contribution of each joint site to the variance in serum COMP.
The correlation of synovial fluid and serum COMP was significant (r=0.206, p=0.006). Synovial fluid COMP correlated most strongly with early phase knee bone scan scores (p=0.0003), even after adjustment for OA severity by late phase bone scan (p=0.015), as well as with synovial fluid volume (p<0.0001). Serum COMP correlated with total body bone scan scores (r=0.188, p=0.018) and with a factor composed of bone scan scores of the shoulders, spine, lateral knees and sacroiliac joints (p=0.0004).
Synovial fluid COMP correlated strongly with two indicators of knee joint inflammation: early phase bone scintigraphy and synovial fluid volume. Serum COMP correlated with total body joint disease severity by late phase bone scintigraphy, supporting the hypothesis that whole body bone scintigraphy is a means of quantifying total body burden of OA for systemic biomarker validation.
osteoarthritis; biomarkers; bone scintigraphy; principal components analysis; COMP
We evaluated the information content of knee bone scintigraphy, including pattern, localization and intensity of retention relative to radiographic features of knee osteoarthritis (rOA), knee alignment, and knee symptoms.
A total of 308 knees (159 subjects) with symptomatic and radiographic knee OA (rOA) of at least one knee were assessed by late phase technetium-99m-methylene disphosphonate bone scintigraph, fixed-flexion knee radiograph, full limb radiograph for knee alignment, and for self-reported knee symptom severity. Generalized linear models were used to control for within subject correlation of knee data.
The compartmental localization (medial versus lateral) and intensity of knee bone scan retention were associated with the pattern (varus versus valgus) (p<0.001) and severity (p=0.0008) of knee malalignment, and localization and severity of rOA (p<0.0001). Bone scan agent retention in the tibiofemoral, but not patellofemoral compartment, was associated with severity of knee symptoms (p=0.0009), and persisted after adjusting for rOA (p=0.0012).
To our knowledge, this is the first study describing a relationship between knee malalignment, joint symptom severity, and compartment specific abnormalities by bone scintigraphy. This work demonstrates that bone scintigraphy as a sensitive and quantitative indicator of symptomatic knee OA. Used selectively, bone scintigraphy is a dynamic imaging modality that holds great promise as a clinical trial screening tool and outcome measure.
osteoarthritis; bone scintigraphy; malalignment; knee
Positive species interactions (facilitation) play an important role in shaping the structures and species diversity of ecological communities, particularly under stressful environmental conditions. Epiphytes in rainforests often grow in multiple-species clumps, suggesting interspecies facilitation. However, little is known about the patterns and mechanisms of epiphyte co-occurrence. We assessed the interactions of two widespread epiphyte species, Asplenium antiquum and Haplopteris zosterifolia, by examining their co-occurrence and size-class association in the field. To elucidate factors controlling their interactions, we conducted reciprocal-removal and greenhouse-drought experiments, and nutrient and isotope analyses. Forty-five percent of H. zosterifolia co-occurred with A. antiquum, whereas only 17% of A. antiquum co-occurred with H. zosterifolia. Removing the fronds plus substrate of A. antiquum reduced the relative frond length and specific leaf area of H. zosterifolia, but removing fronds only had little effect. Removing H. zosterifolia had no significant effects on the growth of A. antiquum. H. zosterifolia co-occurring and not co-occurring with A. antiquum had similar foliar nutrient concentrations and δ15N values, suggesting that A. antiquum does not affect the nutrient status of H. zosterifolia. Reduced growth of H. zosterifolia with the removal of A. antiquum substrate, together with higher foliar δ13C for H. zosterifolia growing alone than those co-occurring with A. antiquum, suggest that A. antiquum enhances water availability to H. zosterifolia. This enhancement probably resulted from water storage in the substrate of A. antiquum, which could hold water up to 6.2 times its dry weight, and from reduced evapotranspiration due to shading of A. antiquum fronds. Greater water loss occurred in the frond-clipped group than the unclipped group between days 3–13 of the drought treatment. Our results imply that drought mitigation by substrate-forming epiphytes is important for maintaining epiphyte diversity in tropic and subtropic regions with episodic water limitations, especially in the context of anthropogenic climate change.
The aim of this study was to assess the cryoprotective effect of static magnetic fields (SMFs) on human erythrocytes during the slow cooling procedure. Human erythrocytes suspended in 20% glycerol were slowly frozen with a 0.4-T or 0.8-T SMF and then moved to a −80°C freezer for 24 hr. The changes in survival rate, morphology, and metabolites of the thawed erythrocytes were examined. To understand possible cryoprotective mechanisms of SMF, membrane fluidity and dehydration stability of SMF-exposed erythrocytes were tested. For each test, sham-exposed erythrocytes were used as controls. Our results showed that freezing coupled with 0.4-T or 0.8-T SMFs significantly increased the relative survival ratios of the frozen-thawed erythrocytes by 10% and 20% (p<0.001), respectively. The SMFs had no effect on erythrocyte morphology and metabolite levels. However, membrane fluidity of the samples exposed to 0.8-T SMF decreased significantly (p<0.05) in the hydrophobic regions. For the dehydration stability experiments, the samples exposed to 0.8-T SMF exhibited significantly lower (p<0.05) hemolysis. These results demonstrate that a 0.8-T SMF decreases membrane fluidity and enhances erythrocyte membrane stability to resist dehydration damage caused by slow cooling procedures.
Extracorporeal shockwave therapy (ESWT) shows chondroprotective effect in osteoarthritis of the rat knees. However, the ideal number of ESWT is unknown. This study investigated the effects of different numbers of ESWT in osteoarthritis of the knee in rats.
Forty-five male Sprague-Dawley rats were divided into five groups. Group I underwent sham arthrotomy without anterior cruciate ligament transection (ACLT) or medial meniscectomy (MM) and received no ESWT. Group II underwent ACLT + MM and received no ESWT. Group III underwent ACLT + MM, and received ESWT once a week for one treatment. Group IV underwent ACLT + MM and received ESWT twice a week for 2 treatments. Group V underwent ACLT + MM and received ESWT three times a week for 3 treatments. Each treatment consisted of 800 impulses of shockwave at 14 Kv to the medial tibia condyle. The evaluations included radiographs of the knee, histomorphological examination and immunohistochemical analysis at 12 weeks.
At 12 weeks, group II and V showed more radiographic arthritis than groups I, III and IV. On histomorphological examination, the Safranin O matrix staining in groups III and IV are significantly better than in groups II and V, and the Mankin scores in groups III and IV are less than groups II and V. Groups III and IV showed significant decreases of Mankin score and increase of Safranin O stain as compared to group I. Group V showed significant increases of Mankin score and a decrease of Safranin O stain as compared to group II. In articular cartilage, group II showed significant increase of MMP13 and decrease of collagen II as compared to group I. Groups III and IV showed significant decrease of MMP13 and increase of collagen II as compared to group I. Group V showed significant increase of MMP13 and decrease of collagen II as compared to group II. In subchondral bone, vWF, VEGF, BMP-2 and osteocalcin significantly decreased in groups II and V, but increased in groups III and IV relative to group I.
ESWT shows a number of treatment related chondroproctective effect in osteoarthritis of the knee in rats.
Shockwave; Number of treatment; Chondroprotective; Osteoarthritis; Knee; Rats
Two distinct nuclear factor κB (NFκB) signaling pathways have been described; the canonical pathway that mediates inflammatory responses, and the non-canonical pathway that is involved in immune cell differentiation and maturation and secondary lymphoid organogenesis. The former is dependent on the IκB kinase adaptor molecule NEMO, the latter is independent of it. Here, we review the molecular mechanisms of regulation in each signaling axis and attempt to relate the apparent regulatory logic to the physiological function. Further, we review the recent evidence for extensive cross-regulation between these two signaling axes and summarize them in a wiring diagram. These observations suggest that NEMO-dependent and -independent signaling should be viewed within the context of a single NFκB signaling system, which mediates signaling from both inflammatory and organogenic stimuli in an integrated manner. As in other regulatory biological systems, a systems approach including mathematical models that include quantitative and kinetic information will be necessary to characterize the network properties that mediate physiological function, and that may break down to cause or contribute to pathology.
NFκB; inflammation; immune response; immune development; mathematical model; signaling crosstalk
To investigate quantitative trait loci linked to refractive error, we performed a genome-wide quantitative trait linkage analysis using single nucleotide polymorphism markers and family data from five international sites.
Genomic DNA samples from 254 families were genotyped by the Center for Inherited Disease Research using the Illumina Linkage Panel IVb. Quantitative trait linkage analysis was performed on 225 Caucasian families and 4,656 markers after accounting for linkage disequilibrium and quality control exclusions. Two refractive quantitative phenotypes, sphere (SPH) and spherical equivalent (SE), were analyzed. The SOLAR program was used to estimate identity by descent probabilities and to conduct two-point and multipoint quantitative trait linkage analyses.
We found 29 markers and 11 linkage regions reaching peak two-point and multipoint logarithms of the odds (LODs)>1.5. Four linkage regions revealed at least one LOD score greater than 2: chromosome 6q13–6q16.1 (LOD=1.96 for SPH, 2.18 for SE), chromosome 5q35.1–35.2 (LOD=2.05 for SPH, 1.80 for SE), chromosome 7q11.23–7q21.2 (LOD=1.19 for SPH, 2.03 for SE), and chromosome 3q29 (LOD=1.07 for SPH, 2.05 for SE). Among these, the chromosome 6 and chromosome 5 regions showed the most consistent results between SPH and SEM. Four linkage regions with multipoint scores above 1.5 are near or within the known myopia (MYP) loci of MYP3, MYP12, MYP14, and MYP16. Overall, we observed consistent linkage signals across the SPH and SEM phenotypes, although scores were generally higher for the SEM phenotype.
Our quantitative trait linkage analyses of a large myopia family cohort provided additional evidence for several known MYP loci, and identified two additional potential loci at chromosome 6q13–16.1 and chromosome 5q35.1–35.2 for myopia. These results will benefit the efforts toward determining genes for myopic refractive error.
The authors that the number of activating and inhibitory KIR genes varies between individuals and plays a role in the regulation of immune mechanisms that determine HIV-1 control.
A genome-wide screen for large structural variants showed that a copy number variant (CNV) in the region encoding killer cell immunoglobulin-like receptors (KIR) associates with HIV-1 control as measured by plasma viral load at set point in individuals of European ancestry. This CNV encompasses the KIR3DL1-KIR3DS1 locus, encoding receptors that interact with specific HLA-Bw4 molecules to regulate the activation of lymphocyte subsets including natural killer (NK) cells. We quantified the number of copies of KIR3DS1 and KIR3DL1 in a large HIV-1 positive cohort, and showed that an increase in KIR3DS1 count associates with a lower viral set point if its putative ligand is present (p = 0.00028), as does an increase in KIR3DL1 count in the presence of KIR3DS1 and appropriate ligands for both receptors (p = 0.0015). We further provide functional data that demonstrate that NK cells from individuals with multiple copies of KIR3DL1, in the presence of KIR3DS1 and the appropriate ligands, inhibit HIV-1 replication more robustly, and associated with a significant expansion in the frequency of KIR3DS1+, but not KIR3DL1+, NK cells in their peripheral blood. Our results suggest that the relative amounts of these activating and inhibitory KIR play a role in regulating the peripheral expansion of highly antiviral KIR3DS1+ NK cells, which may determine differences in HIV-1 control following infection.
There is marked intrinsic variation in the extent to which individuals are able to control HIV-1. We have identified a genetic copy number variable region (CNV) in humans that plays a significant role in the control of HIV-1. This CNV is located in the genomic region that encodes the killer cell immunoglobulin-like receptors (KIRs) and specifically affects the KIR3DS1 and KIR3DL1 genes, encoding two KIRs that interact with human leukocyte antigen B (HLA-B) ligands. KIRs are expressed on the surface of natural killer (NK) cells, which serve as important players in the innate immune response, and are involved in the recognition of infected and malignant cells through a loss or alteration in “self” ligands. We use both genetic association and functional evidence to show a strong interaction between KIR3DL1 and KIR3DS1, indicating that increasing gene counts for KIR3DL1 confer increasing levels of protection against HIV-1, but only in the presence of at least one copy of KIR3DS1. This effect was associated with a dramatic increase in the abundance of KIR3DS1+ NK cells in the peripheral blood, and strongly associated with a more robust capacity of peripheral NK cells to suppress HIV-1 replication in vitro. This work provides one of the few examples of an association between a relatively common CNV and a human complex trait.
Improving the synthesis rate of desired metabolites in metabolic systems is one of the main tasks in metabolic engineering. In the last decade, metabolic engineering approaches based on the mathematical optimization have been used extensively for the analysis and manipulation of metabolic networks. Experimental evidence shows that mutants reflect resilience phenomena against gene alterations. Although researchers have published many studies on the design of metabolic systems based on kinetic models and optimization strategies, almost no studies discuss the multi-objective optimization problem for enzyme manipulations in metabolic networks considering resilience phenomenon.
This study proposes a generalized fuzzy multi-objective optimization approach to formulate the enzyme intervention problem for metabolic networks considering resilience phenomena and cell viability. This approach is a general framework that can be applied to any metabolic networks to investigate the influence of resilience phenomena on gene intervention strategies and maximum target synthesis rates. This study evaluates the performance of the proposed approach by applying it to two metabolic systems: S. cerevisiae and E. coli. Results show that the maximum synthesis rates of target products by genetic interventions are always over-estimated in metabolic networks that do not consider the resilience effects.
Considering the resilience phenomena in metabolic networks can improve the predictions of gene intervention and maximum synthesis rates in metabolic engineering. The proposed generalized fuzzy multi-objective optimization approach has the potential to be a good and practical framework in the design of metabolic networks.
Disturbances in podocytes are typically associated with marked proteinuria, a hallmark of diabetic nephropathy. This study was conducted to investigate modulation of Notch-1 signaling in high glucose (HG)-stressed human podocytes and in a diabetic animal model.
RESEARCH DESIGN AND METHODS
Expression of the Notch signaling components was examined in HG-treated podocytes, human embryonic kidney cells (HEK293), and kidneys from diabetic animals by RT-qPCR, Western blot analysis, and immunohistochemical staining. The association between the Notch signaling, VEGF expression, and podocyte integrity was evaluated.
Notch-1 signaling was significantly activated in HG-cultured human podocytes and HEK293 cells and kidneys from diabetic animals. HG also augmented VEGF expression, decreasing nephrin expression and podocyte number—a critical event for the development of proteinuria in diabetic nephropathy. After use of pharmacological modulators or specific shRNA knockdown strategies, inhibition of Notch-1 signaling significantly abrogated VEGF activation and nephrin repression in HG-stressed cells and ameliorated proteinuria in the diabetic kidney.
Our findings suggest that upregulation of Notch-1 signaling in HG-treated renal podocytes induces VEGF expression and subsequent nephrin repression and apoptosis. Modulation of Notch-1 signaling may hold promise as a novel therapeutic strategy for the treatment of diabetic nephropathy.
Cervical cancer screening is ideally suited for the development of biomarkers due to the ease of tissue acquisition and the well-established histological transitions. Furthermore, cell and biologic fluid obtained from cervix samples undergo specific molecular changes that can be profiled. However, the ideal manner and techniques for preparing cervical samples remains to be determined. To address this critical issue a patient screening protein and nucleic acid collection protocol was established. RNAlater was used to collect the samples followed by proteomic methods to identify proteins that were differentially expressed in normal cervical epithelial versus cervical cancer cells. Three hundred ninety spots were identified via two-dimensional difference gel electrophoresis (2-D DIGE) that were expressed at either higher or lower levels (>3-fold) in cervical cancer samples. These proteomic results were compared to genes in a cDNA microarray analysis of microdissected neoplastic cervical specimens to identify overlapping patterns of expression. The most frequent pathways represented by the combined dataset were: cell cycle: G2/M DNA damage checkpoint regulation; aryl hydrocarbon receptor signaling; p53 signaling; cell cycle: G1/S checkpoint regulation; and the endoplasmic reticulum stress pathway. HNRPA2B1 was identified as a biomarker candidate with increased expression in cancer compared to normal cervix and validated by Western blot.
2-D DIGE; biomarkers; cervical cancer; cDNA microarray; RNAlater
In designing genome-wide association (GWA) studies it is important to calculate statistical power. General statistical power calculation procedures for quantitative measures often require information concerning summary statistics of distributions such as mean and variance. However, with genetic studies, the effect size of quantitative traits is traditionally expressed as heritability, a quantity defined as the amount of phenotypic variation in the population that can be ascribed to the genetic variants among individuals. Heritability is hard to transform into summary statistics. Therefore, general power calculation procedures cannot be used directly in GWA studies. The development of appropriate statistical methods and a user-friendly software package to address this problem would be welcomed.
This paper presents GWAPower, a statistical software package of power calculation designed for GWA studies with quantitative traits, where genetic effect is defined as heritability. Based on several popular one-degree-of-freedom genetic models, this method avoids the need to specify the non-centrality parameter of the F-distribution under the alternative hypothesis. Therefore, it can use heritability information directly without approximation. In GWAPower, the power calculation can be easily adjusted for adding covariates and linkage disequilibrium information. An example is provided to illustrate GWAPower, followed by discussions.
GWAPower is a user-friendly free software package for calculating statistical power based on heritability in GWA studies with quantitative traits. The software is freely available at: http://dl.dropbox.com/u/10502931/GWAPower.zip
The title compound, C22H28N8Si, has crystallographic 2 symmetry with the Si atom located on a twofold rotation axis. The tetrazole ring is oriented at a dihedral angle of 5.32 (18)° with respect to the benzene ring. A C—H⋯π interaction occurs between adjacent molecules in the crystal structure.
It is well established in E. coli and Vibrio cholerae that strains harboring mutations in the ferric uptake regulator gene (fur) are unable to utilize tricarboxylic acid (TCA) compounds, due to the down-regulation of key TCA cycle enzymes, such as AcnA and SdhABCD. This down-regulation is mediated by a Fur-regulated small regulatory RNA named RyhB. It is unclear in the γ-proteobacterium S. oneidensis whether TCA is also regulated by Fur and RyhB.
In the present study, we showed that a fur deletion mutant of S. oneidensis could utilize TCA compounds. Consistently, expression of the TCA cycle genes acnA and sdhA was not down-regulated in the mutant. To explore this observation further, we identified a ryhB gene in Shewanella species and experimentally demonstrated the gene expression. Further experiments suggested that RyhB was up-regulated in fur mutant, but that AcnA and SdhA were not controlled by RyhB.
These cumulative results delineate an important difference of the Fur-RyhB regulatory cycle between S. oneidensis and other γ-proteobacteria. This work represents a step forward for understanding the unique regulation in S. oneidensis.
Mathematical modeling has been applied to the study and analysis of complex
biological systems for a long time. Some processes in biological systems, such as
the gene expression and feedback control in signal transduction networks, involve
a time delay. These systems are represented as delay differential equation (DDE)
models. Numerical sensitivity analysis of a DDE model by the direct method
requires the solutions of model and sensitivity equations with time-delays. The
major effort is the computation of Jacobian matrix when computing the solution of
sensitivity equations. The computation of partial derivatives of complex equations
either by the analytic method or by symbolic manipulation is time consuming,
inconvenient, and prone to introduce human errors. To address this problem, an
automatic approach to obtain the derivatives of complex functions efficiently and
accurately is necessary.
We have proposed an efficient algorithm with an adaptive step size control to
compute the solution and dynamic sensitivities of biological systems described by
ordinal differential equations (ODEs). The adaptive direct-decoupled algorithm is
extended to solve the solution and dynamic sensitivities of time-delay systems
describing by DDEs. To save the human effort and avoid the human errors in the
computation of partial derivatives, an automatic differentiation technique is
embedded in the extended algorithm to evaluate the Jacobian matrix. The extended
algorithm is implemented and applied to two realistic models with time-delays: the
cardiovascular control system and the TNF-α signal transduction
network. The results show that the extended algorithm is a good tool for dynamic
sensitivity analysis on DDE models with less user intervention.
By comparing with direct-coupled methods in theory, the extended algorithm is
efficient, accurate, and easy to use for end users without programming background
to do dynamic sensitivity analysis on complex biological systems with
There is great interindividual variability in HIV-1 viral setpoint after seroconversion, some of which is known to be due to genetic differences among infected individuals. Here, our focus is on determining, genome-wide, the contribution of variable gene expression to viral control, and to relate it to genomic DNA polymorphism. RNA was extracted from purified CD4+ T-cells from 137 HIV-1 seroconverters, 16 elite controllers, and 3 healthy blood donors. Expression levels of more than 48,000 mRNA transcripts were assessed by the Human-6 v3 Expression BeadChips (Illumina). Genome-wide SNP data was generated from genomic DNA using the HumanHap550 Genotyping BeadChip (Illumina). We observed two distinct profiles with 260 genes differentially expressed depending on HIV-1 viral load. There was significant upregulation of expression of interferon stimulated genes with increasing viral load, including genes of the intrinsic antiretroviral defense. Upon successful antiretroviral treatment, the transcriptome profile of previously viremic individuals reverted to a pattern comparable to that of elite controllers and of uninfected individuals. Genome-wide evaluation of cis-acting SNPs identified genetic variants modulating expression of 190 genes. Those were compared to the genes whose expression was found associated with viral load: expression of one interferon stimulated gene, OAS1, was found to be regulated by a SNP (rs3177979, p = 4.9E-12); however, we could not detect an independent association of the SNP with viral setpoint. Thus, this study represents an attempt to integrate genome-wide SNP signals with genome-wide expression profiles in the search for biological correlates of HIV-1 control. It underscores the paradox of the association between increasing levels of viral load and greater expression of antiviral defense pathways. It also shows that elite controllers do not have a fully distinctive mRNA expression pattern in CD4+ T cells. Overall, changes in global RNA expression reflect responses to viral replication rather than a mechanism that might explain viral control.
There has been recent progress in understanding the genetic factors that modulate susceptibility to HIV-1 infection. Genetic variation explains to a certain extent differences in disease progression among individuals. Less is known regarding the contribution of differences in gene expression to viral control. The present study evaluated, genome-wide, gene expression levels in CD4+ T cell, the main target of HIV-1. Thereafter, it searched for genetic variants that would modify gene expression. Specific expression profiles associated with high levels of viremia—in particular, the upregulation of genes of the antiviral defense. In contrast, no expression profile associated with effective viral control. Multiple genetic variants modulated gene expression in CD4+ T cells; however, none had a strong influence on viral control. This integrated genome-wide assessment suggests that viral replication drives gene expression rather than expression pointing to mechanisms of viral control.
To extend the understanding of host genetic determinants of HIV-1 control, we performed a genome-wide association study in a cohort of 2,554 infected Caucasian subjects. The study was powered to detect common genetic variants explaining down to 1.3% of the variability in viral load at set point. We provide overwhelming confirmation of three associations previously reported in a genome-wide study and show further independent effects of both common and rare variants in the Major Histocompatibility Complex region (MHC). We also examined the polymorphisms reported in previous candidate gene studies and fail to support a role for any variant outside of the MHC or the chemokine receptor cluster on chromosome 3. In addition, we evaluated functional variants, copy-number polymorphisms, epistatic interactions, and biological pathways. This study thus represents a comprehensive assessment of common human genetic variation in HIV-1 control in Caucasians.
The ability to spontaneously control HIV-1 upon infection is highly variable between individuals. To evaluate the contribution of variation in human genes to differences in plasma viral load and in disease progression rates, we performed a genome-wide association study in >2,500 HIV–infected individuals. This study achieved two goals: it completed the analysis of common variation influencing viral control, and it re-assessed the majority of previously reported genetic associations. We show that genetic variants located near the HLA-B and HLA-C genes are the strongest determinants of viral control, and that other independent associations exist in the same region of chromosome 6, the Major Histocompatibility Complex, known to contain a large number of genes involved in immune defense. We could not replicate most of the previously published associations with HIV candidate genes in this large, well-characterized cohort. Overall, common human genetic variation, together with demographic variables, explains up to 22% of the variability in viral load in the Caucasian population.
Network Component Analysis (NCA) is a network structure-driven framework for deducing regulatory signal dynamics. In contrast to principal component analysis, which can be employed to select the high-variance genes, NCA makes use of the connectivity structure from transcriptional regulatory networks to infer dynamics of transcription factor activities. Using the budding yeast Saccharomyces cerevisiae as a model system, we aim to deduce regulatory actions of cytokinesis-related genes, using precise spatial proximity (midbody) and/or temporal synchronicity (cytokinesis) to avoid full-scale computation from genome-wide databases.
NCA was applied to infer regulatory actions of transcription factor activity from microarray data and partial transcription factor-gene connectivity information for cytokinesis-related genes, which were a subset of genome-wide datasets. No literature has so far discussed the inferred results through NCA are independent of the scale of the gene expression dataset. To avoid full-scale computation from genome-wide databases, four cytokinesis-related gene cases were selected for NCA by running computational analysis over the transcription factor database to confirm the approach being scale-free. The inferred dynamics of transcription factor activity through NCA were independent of the scale of the data matrix selected from the four cytokinesis-related gene sets. Moreover, the inferred regulatory actions were nearly identical to published observations for the selected cytokinesis-related genes in the budding yeast; namely, Mcm1, Ndd1, and Fkh2, which form a transcription factor complex to control expression of the CLB2 cluster (i.e. BUD4, CHS2, IQG1, and CDC5).
In this study, using S. cerevisiae as a model system, NCA was successfully applied to infer similar regulatory actions of transcription factor activities from two various microarray databases and several partial transcription factor-gene connectivity datasets for selected cytokinesis-related genes independent of data sizes. The regulated action for four selected cytokinesis-related genes (BUD4, CHS2, IQG1, and CDC5) belongs to the M-phase or M/G1 phase, consistent with the empirical observations that in S. cerevisiae, the Mcm1-Ndd1-Fkh2 transcription factor complex can regulate expression of the cytokinesis-related genes BUD4, CHS2, IQG1, and CDC5. Since Bud4, Iqg1, and Cdc5 are highly conserved between human and yeast, results obtained from NCA for cytokinesis in the budding yeast can lead to a suggestion that human cells should have the transcription regulator(s) as the budding yeast Mcm1-Ndd1-Fkh2 transcription factor complex in controlling occurrence of cytokinesis.
Determining the parameters of a mathematical model from quantitative measurements is the main bottleneck of modelling biological systems. Parameter values can be estimated from steady-state data or from dynamic data. The nature of suitable data for these two types of estimation is rather different. For instance, estimations of parameter values in pathway models, such as kinetic orders, rate constants, flux control coefficients or elasticities, from steady-state data are generally based on experiments that measure how a biochemical system responds to small perturbations around the steady state. In contrast, parameter estimation from dynamic data requires time series measurements for all dependent variables. Almost no literature has so far discussed the combined use of both steady-state and transient data for estimating parameter values of biochemical systems.
In this study we introduce a constrained optimization method for estimating parameter values of biochemical pathway models using steady-state information and transient measurements. The constraints are derived from the flux connectivity relationships of the system at the steady state. Two case studies demonstrate the estimation results with and without flux connectivity constraints. The unconstrained optimal estimates from dynamic data may fit the experiments well, but they do not necessarily maintain the connectivity relationships. As a consequence, individual fluxes may be misrepresented, which may cause problems in later extrapolations. By contrast, the constrained estimation accounting for flux connectivity information reduces this misrepresentation and thereby yields improved model parameters.
The method combines transient metabolic profiles and steady-state information and leads to the formulation of an inverse parameter estimation task as a constrained optimization problem. Parameter estimation and model selection are simultaneously carried out on the constrained optimization problem and yield realistic model parameters that are more likely to hold up in extrapolations with the model.
Protein-protein interactions (PPIs) are critical to every aspect of biological processes. Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration. Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge. Even though a number of software tools are available to facilitate PPI network analysis, an integrated tool is crucial to alleviate the burden on querying across multiple web servers and software tools.
We have constructed an integrated web service, POINeT, to simplify the process of PPI searching, analysis, and visualization. POINeT merges PPI and tissue-specific expression data from multiple resources. The tissue-specific PPIs and the numbers of research papers supporting the PPIs can be filtered with user-adjustable threshold values and are dynamically updated in the viewer. The network constructed in POINeT can be readily analyzed with, for example, the built-in centrality calculation module and an integrated network viewer. Nodes in global networks can also be ranked and filtered using various network analysis formulas, i.e., centralities. To prioritize the sub-network, we developed a ranking filtered method (S3) to uncover potential novel mediators in the midbody network. Several examples are provided to illustrate the functionality of POINeT. The network constructed from four schizophrenia risk markers suggests that EXOC4 might be a novel marker for this disease. Finally, a liver-specific PPI network has been filtered with adult and fetal liver expression profiles.
The functionalities provided by POINeT are highly improved compared to previous version of POINT. POINeT enables the identification and ranking of potential novel genes involved in a sub-network. Combining with tissue-specific gene expression profiles, PPIs specific to selected tissues can be revealed. The straightforward interface of POINeT makes PPI search and analysis just a few clicks away. The modular design permits further functional enhancement without hampering the simplicity. POINeT is available at .
There is considerable variability in the susceptibility of smokers to develop chronic obstructive pulmonary disease (COPD). The only known genetic risk factor is severe deficiency of α1-antitrypsin, which is present in 1–2% of individuals with COPD. We conducted a genome-wide association study (GWAS) in a homogenous case-control cohort from Bergen, Norway (823 COPD cases and 810 smoking controls) and evaluated the top 100 single nucleotide polymorphisms (SNPs) in the family-based International COPD Genetics Network (ICGN; 1891 Caucasian individuals from 606 pedigrees) study. The polymorphisms that showed replication were further evaluated in 389 subjects from the US National Emphysema Treatment Trial (NETT) and 472 controls from the Normative Aging Study (NAS) and then in a fourth cohort of 949 individuals from 127 extended pedigrees from the Boston Early-Onset COPD population. Logistic regression models with adjustments of covariates were used to analyze the case-control populations. Family-based association analyses were conducted for a diagnosis of COPD and lung function in the family populations. Two SNPs at the α-nicotinic acetylcholine receptor (CHRNA 3/5) locus were identified in the genome-wide association study. They showed unambiguous replication in the ICGN family-based analysis and in the NETT case-control analysis with combined p-values of 1.48×10−10, (rs8034191) and 5.74×10−10 (rs1051730). Furthermore, these SNPs were significantly associated with lung function in both the ICGN and Boston Early-Onset COPD populations. The C allele of the rs8034191 SNP was estimated to have a population attributable risk for COPD of 12.2%. The association of hedgehog interacting protein (HHIP) locus on chromosome 4 was also consistently replicated, but did not reach genome-wide significance levels. Genome-wide significant association of the HHIP locus with lung function was identified in the Framingham Heart study (Wilk et al., companion article in this issue of PLoS Genetics; doi:10.1371/journal.pgen.1000429). The CHRNA 3/5 and the HHIP loci make a significant contribution to the risk of COPD. CHRNA3/5 is the same locus that has been implicated in the risk of lung cancer.
There is considerable variability in the susceptibility of smokers to develop chronic obstructive pulmonary disease (COPD), which is a heritable multi-factorial trait. Identifying the genetic determinants of COPD risk will have tremendous public health importance. This study describes the first genome-wide association study (GWAS) in COPD. We conducted a GWAS in a homogenous case-control cohort from Norway and evaluated the top 100 single nucleotide polymorphisms in the family-based International COPD Genetics Network. The polymorphisms that showed replication were further evaluated in subjects from the US National Emphysema Treatment Trial and controls from the Normative Aging Study and then in a fourth cohort of extended pedigrees from the Boston Early-Onset COPD population. Two polymorphisms in the α-nicotinic acetylcholine receptor 3/5 locus on chromosome 15 showed unambiguous evidence of association with COPD. This locus has previously been implicated in both smoking behavior and risk of lung cancer, suggesting the possibility of multiple functional polymorphisms in the region or a single polymorphism with wide phenotypic consequences. The hedgehog interacting protein (HHIP) locus on chromosome 4, which is associated with COPD, is also a significant risk locus for COPD.