The effect of HLA-DR on susceptibility to rheumatoid arthritis is influenced by the associated lymphotoxin α-tumor necrosis factor haplotype

Objective. HLA-DRB1, a major genetic determinant of susceptibility to rheumatoid arthritis (RA), is located within 1,000 kb of the gene encoding tumor necrosis factor (TNF). Because certain HLA-DRB1*04 subtypes increase susceptibility to RA, investigation of the role of the TNF gene is complicated by linkage disequilibrium (LD) between TNF and DRB1 alleles. By adequately controlling for this LD, we aimed to investigate the presence of additional major histocompatibility complex (MHC) susceptibility genes. Methods. We identified 274 HLA-DRB1*04-positive cases of RA and 271 HLA-DRB1*04-positive population controls. Each subject was typed for 6 single-nucleotide polymorphisms within a 4.5-kb region encompassing TNF and lymphotoxin a (LTA). LTA-TNF haplotypes in these unrelated individuals were determined using a combination of family data and the PHASE software program. Results. Significant differences in LTA-TNF haplotype frequencies were observed between different subtypes of HLA-DRB1*04. The LTA-TNF haplotypes observed were very restricted, with only 4 haplotypes constituting 81% of all haplotypes present. Among individuals carrying DRB1*0401, the LTA-TNF 2 haplotype was significantly underrepresented in cases compared with controls (odds ratio 0.5 [95% confidence interval 0.3-0.8], P = 0.007), while in those with DRB1*0404, the opposite effect was observed (P = 0.007). Conclusion. These findings suggest that the MHC contains genetic elements outside the LTA-TNF region that modify the effect of HLA-DRB1 on susceptibility to RA.

Genetic variation in tumour necrosis factor and lymphotoxin is not associated with endometriosis in an Australian sample

BACKGROUND Tumour necrosis factor (TNF) is a pleiotropic cytokine with a wide range of immunoregulatory effects. Variation in the promoter region of TNF and the neighbouring lymphotoxin alpha (LTA) gene might be associated with endometriosis. METHODS We examined the association between endometriosis and common single-nucleotide polymorphisms (SNPs) or haplotypes in the TNF/LTA region in an Australian sample by analysing 26 SNPs in 958 endometriosis cases and 959 unrelated controls. We selected functional SNPs in the coding and the promoter region of the TNF gene and HapMap tagging SNPs and typed them on a Sequenom MassARRAY platform. A key SNP (rs1800630) in the promoter region typed in previous studies did not give reliable results. Therefore, we also examined a statistically identical (r(2) = 1) SNP (siSNP) (rs2844482), identified using the web based program ssSNPer. RESULTS Genotype completion rate was 99.5% for SNPs spanning a region of 15.5 kb across the TNF/LTA locus. There was no evidence for association between endometriosis and TNF/LTA SNPs or SNP haplotypes in our case-control study. CONCLUSIONS Our data suggest both TNF and LTA genes are not major susceptibility genes for endometriosis.

Dissection of class III major histocompatibility complex haplotypes associated with rheumatoid arthritis

Objective. We have previously identified a single-nucleotide polymorphism (SNP) haplotype involving the lymphotoxin α (LTA) and tumor necrosis factor (TNF) loci (termed haplotype LTA-TNF2) on chromosome 6 that shows differential association with rheumatoid arthritis (RA) on HLA-DRB1*0404 and *0401 haplotypes, suggesting the presence of additional non-HLA-DRB1 RA susceptibility genes on these haplotypes. To refine this association, we performed a case-control association study using both SNPs and microsatellite markers in haplotypes matched either for HLA-DRB1*0404 or for HLA-DRB1*0401. Methods. Fourteen SNPs lying between HLA-DRB1 and LTA were genotyped in 87 DRB1*04-positive families. High-density microsatellite typing was performed using 24 markers spanning 2,500 kb centered around the TNF gene in 305 DRB1*0401 or *0404 cases and 400 DRB1*0401 or *0404 controls. Single-marker, 2-marker, and 3-marker minihaplotypes were constructed and their frequencies compared between the DRB1*0401 and DRB1*0404 matched case and control haplotypes. Results. Marked preservation of major histocompatibility complex haplotypes was seen, with chromosomes carrying LTA-TNF2 and either DRB1*0401 or DRB1*0404 both carrying an identical SNP haplotype across the 1-Mb region between TNF and HLA-DRB1. Using microsatellite markers, we observed two 3-marker minihaplotypes that were significantly overrepresented in the DRB1*0404 case haplotypes (P = 0.00024 and P = 0.00097). Conclusion. The presence of a single extended SNP haplotype between LTA-TNF2 and both DRB1*0401 and DRB1*0404 is evidence against this region harboring the genetic effects in linkage disequillbrium with LTA-TNF2. Two RA-associated haplotypes on the background of DRB1*0404 were identified in a 126-kb region surrounding and centromeric to the TNF locus.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

Partial agonists of the [alpha]3[beta]4[ast] neuronal nicotinic acetylcholine receptor reduce ethanol consumption and seeking in rats

Alcohol use disorders (AUDs) impact millions of individuals and there remain few effective treatment strategies. Despite evidence that neuronal nicotinic acetylcholine receptors (nAChRs) have a role in AUDs, it has not been established which subtypes of the nAChR are involved. Recent human genetic association studies have implicated the gene cluster CHRNA3-CHRNA5-CHRNB4 encoding the α3, α5, and β4 subunits of the nAChR in susceptibility to develop nicotine and alcohol dependence; however, their role in ethanol-mediated behaviors is unknown due to the lack of suitable and selective research tools. To determine the role of the α3, and β4 subunits of the nAChR in ethanol self-administration, we developed and characterized high-affinity partial agonists at α3β4 nAChRs, CP-601932, and PF-4575180. Both CP-601932 and PF-4575180 selectively decrease ethanol but not sucrose consumption and operant self-administration following long-term exposure. We show that the functional potencies of CP-601932 and PF-4575180 at α3β4 nAChRs correlate with their unbound rat brain concentrations, suggesting that the effects on ethanol self-administration are mediated via interaction with α3β4 nAChRs. Also varenicline, an approved smoking cessation aid previously shown to decrease ethanol consumption and seeking in rats and mice, reduces ethanol intake at unbound brain concentrations that allow functional interactions with α3β4 nAChRs. Furthermore, the selective α4β2(*) nAChR antagonist, DHβE, did not reduce ethanol intake. Together, these data provide further support for the human genetic association studies, implicating CHRNA3 and CHRNB4 genes in ethanol-mediated behaviors. CP-601932 has been shown to be safe in humans and may represent a potential novel treatment for AUDs.