A nonparametric regression-based linkage scan of rheumatoid factor-IgM using sib-pair squared sums and differences
Parametric linkage methods for quantitative trait locus mapping require explicit specification of the probability model of the quantitative trait and hence can lead to misleading linkage inferences when the model assumptions are not valid. Ghosh and Majumder developed a nonparametric regression method based on kernel-smoothing for linkage mapping of quantitative trait locus using squared differences in trait values of independent sib pairs, which is relatively more robust than parametric methods with respect to violations in distributional assumptions. In this study, we modify the above mentioned nonparametric regression method by considering local linear polynomials instead of the Nadaraya-Watson estimator and squared sums of sib-pair trait values in addition to squared differences to perform a genome-wide scan of rheumatoid factor-IgM levels on sib pairs in the Genetic Analysis Workshop 15 simulated data set. We obtain significant evidence of linkage very close to the quantitative trait locus controlling for RF-IgM. We find that the simultaneous use of squared differences and squared sums increases the power to detect linkage compared to using only squared differences. However, because of all the sib pairs are selected for rheumatoid arthritis, there is reduced variance of RF-IgM values, and empirical power to detect linkage is not very high. We also compare the performance of our method with two linear regression approaches: the classical Haseman-Elston method using squared sib-pair trait differences and its extension proposed by Elston et al. using mean-corrected sib-pair cross-products. We find that the proposed nonparametric method yields more power than the linear regression approaches.

title: A quantile-based method for association mapping of quantitative phenotypes: an application to rheumatoid arthritis phenotypes
abstract: Genetic association of population-based quantitative trait data has traditionally been analyzed using analysis of variance (ANOVA). However, violations of certain statistical assumptions may lead to false-positive association results. In this study, we have explored model-free alternatives to ANOVA using correlations between allele frequencies in the different quantile intervals of the quantitative trait and the quantile values. We performed genome-wide association scans on anti-cyclic citrullinated peptide and rheumatoid factor-immunoglobulin M, two quantitative traits correlated with rheumatoid arthritis, using the data provided in Genetic Analysis Workshop 16. Both the quantitative traits exhibited significant evidence of association on Chromosome 6, although not in the human leukocyte antigen region which is known to harbor a major gene predisposing to rheumatoid arthritis. We found that while a majority of the significant findings using the asymptotic thresholds of ANOVA was not validated using permutations, a relatively higher proportion of the significant findings using the asymptotic cut-offs of the correlation statistic were validated using permutations.

title: Linkage mapping of total cholesterol level in a young cohort via nonparametric regression
abstract: BackgroundCompared to model-based approaches, nonparametric methods for quantitative trait loci mapping are more robust to deviations in distributional assumptions. In this study, we modify a nonparametric regression method and the "contrast function"- based regression method to analyze total cholesterol level in the younger cohort (the offspring generation) of the Genetic Analysis Workshop 13 simulated data set.ResultsWe obtained significant evidence of linkage near four of the six non-sex-specific genes in at least 30% of the replicates.ConclusionsThe proposed nonparametric method seems to be a powerful robust alternative to distribution-based methods.

title: A two-stage variable-stringency semiparametric method for mapping quantitative-trait loci with the use of genomewide-scan data on sib pairs.
abstract: Genomewide scans for mapping loci have proved to be extremely powerful and popular. We present a semiparametric method of mapping a quantitative-trait locus (QTL) or QTLs with the use of sib-pair data generated from a two-stage genomic scan. In a two-stage genomic scan, either the entire genome or a large portion of the genome is saturated with low-density markers at the first stage. At the second stage, the intervals that are identified as probable locations of the trait loci, by means of analysis of data from the first stage, are then saturated with higher-density markers. These data are then analyzed for fine mapping of the loci. Our statistical strategy for analysis of data from the first stage is a low-stringency method based on the rank correlation of squared trait-difference values of the sib pairs and the estimated identity-by-descent scores at the marker loci. We suggest the use of a low-stringency method at the first stage, to save on computational time and to avoid missing any marker interval that may contain the trait loci. For analysis of data from the second stage, we have developed a high-stringency nonparametric-regression approach, using the kernel-smoothing technique. Through extensive simulations, we show that this approach is more powerful than is a currently used method for mapping QTLs by use of sib pairs, particularly in the presence of dominance and epistatic effects at the trait loci.

title: Identifying rare variants from exome scans: the GAW17 experience
abstract: Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the workshop.

title: Integrating sibship data for mapping quantitative trait loci.
abstract: Sibship methods have been shown to be more powerful than traditional sib-pair methods in mapping quantative trait loci. We propose a statistical procedure which integrates data on sibships into a so-called 'contrast function', a natural extension of the classical squared sib-pair trait difference proposed by Haseman & Elston (1972). We also develop a combined mean and contrast function which provides more information on linkage compared to the contrast function. Our method is extended to multiple, epistatically interacting trait loci. Monte-Carlo simulations are included to compare the efficiencies of the proposed procedures with some currently used methods. An application of our proposed method is presented using data on alcohol dependence.

title: Essential role of tuberous sclerosis genes TSC1 and TSC2 in NF-kappaB activation and cell survival.
abstract: The TSC1-TSC2 complex has recently been implicated in cell survival responses. We observed that NF-kappaB signaling is attenuated in TSC1- and TSC2-deficient MEFs concomitant with reduced survival following DNA damage or TNFalpha stimulation. Reconstitution of TSC2 expression in TSC2(-/-) MEFs rescued survival in an NF-kappaB activity-dependent manner. Furthermore, in TSC2(-/-) MEFs, the rapamycin-mediated inhibition of deregulated mTOR activity restored NF-kappaB activation and survival. This rapamycin-mediated effect was reversed by inhibition of NF-kappaB transcriptional activation or by inhibition of ERK1/2 MAP kinase or PI-3K pathways, which lie on signaling cascades that lead to NF-kappaB activation. These results provide evidence for a crosstalk between the TSC/Rheb/mTOR pathway and the NF-kappaB induction pathways and indicate that NF-kappaB functions as an important survival factor that regulates TSC2-dependent cell survival.

title: Glycogen content & structure & some enzymes of glycogen metabolism in human foetal organs.
abstract: The glycogen content, and its structure and the enzymes involved in glycogenolysis in human foetal organs were studied at different periods of gestation. Of all the tissues studied glycogen content was found to be the highest in cardiac muscle. Very little glycogen was present in the foetal liver at 9-12 wk of gestation, this increased progressively to nearly 2 per cent at 24 wk. Glycogen content of placenta was lower than that of skeletal muscle and liver. The level of glycogen in adipose tissue, placenta and cerebrum was not high enough to play any role in glucose homeostasis of the foetus. Human foetal liver and skeletal muscle glycogen showed the normal branched structure while the liver glycogen was found to be unusually stable. Glycogen phosphorylase activity in the foetal liver and muscle was found to be low, i.e., about a fifth and a fourth of adult liver and muscle activity respectively. The stability of foetal liver glycogen and phosphorolytic activity in the liver and muscle indicate negligible glycogenolysis during foetal development. Glucose-6-phosphatase activity in foetal liver was undetectable below 12 wk of gestation, the activity increasing progressively up to 24 wk.

title: Application of L1-Norm Regularization to Epicardial Potential Solution of the Inverse Electrocardiography Problem
abstract: The electrocardiographic inverse problem of computing epicardial potentials from multi-electrode body-surface ECG measurements, is an ill-posed problem. Tikhonov regularization is commonly employed, which imposes penalty on the L2-norm of the potentials (zero-order) or their derivatives. Previous work has indicated superior results using L2-norm of the normal derivative of the solution (a first order regularization). However, L2-norm penalty function can cause considerable smoothing of the solution. Here, we use the L1-norm of the normal derivative of the potential as a penalty function. L1-norm solutions were compared to zero-order and first-order L2-norm Tikhonov solutions and to measured ‘gold standards’ in previous experiments with isolated canine hearts. Solutions with L1-norm penalty function (average relative error [RE] = 0.36) were more accurate than L2-norm (average RE = 0.62). In addition, the L1-norm method localized epicardial pacing sites with better accuracy (3.8 ± 1.5 mm) compared to L2-norm (9.2 ± 2.6 mm) during pacing in five pediatric patients with congenital heart disease. In a pediatric patient with Wolff–Parkinson–White syndrome, the L1-norm method also detected and localized two distinct areas of early activation around the mitral valve annulus, indicating the presence of two left-sided pathways which were not distinguished using L2 regularization.

title: Cholesteryl ester hydrolase in human monocyte/macrophage: cloning, sequencing, and expression of full-length cDNA.
abstract: The sensitive technique of RT-PCR was used to identify cholesteryl ester hydrolase (CEH) expressed in human macrophages. This enzyme is thought to regulate the availability of intracellular free cholesterol for efflux. The expected 667-bp product was obtained starting with RNA from human peripheral blood and THP-1 monocytes and macrophages. The cDNA for human macrophage CEH was then cloned by PCR-based screening of a lambda-gt11 cDNA library. The full-length cDNA was sequenced and found to exhibit 76% homology (at the nucleotide and conceptually translated protein level) to hepatic CEH, an enzyme shown to be involved in hepatic cholesterol homeostasis and regulated by cholesterol at the transcription level via sterol response elements in the proximal promoter. Identification of the conserved catalytic triad (Ser(221, His(468), and Glu354)) and the SEDCLY motif places human macrophage CEH in the family of carboxylesterases. A greater than 20-fold increase in CEH activity was observed when COS-1 and COS-7 cells were transiently transfected with an eukaryotic expression vector, pcDNA3.1/V5/His-TOPO, containing the cDNA for human macrophage CEH. Using this full-length cDNA as a probe, a 2.2-kb transcript was identified by Northern blot analysis of total RNA from human peripheral blood and THP -1 macrophages. Overexpression of human macrophage CEH resulted in an impairment of upregulation of low-density lipoprotein (LDL) receptor mRNA in Chinese hamster ovary (CHO-K1) cells grown in cholesterol-deficient environment. These data identify the human macrophage CEH, demonstrate its expression in human peripheral blood macrophage and human macrophage cell line, THP-1, and suggest its role in the intracellular cholesteryl ester metabolism.

title: Comparison of electrical thresholds for evoking movements from sensori-motor areas of the cat cerebral cortex and its relation to motor training
abstract: Motor maps and electrical thresholds for evoking movements from motor areas of the cerebral cortex were evaluated in normal cats by using intracortical microstimulation techniques. Stainless steel chambers were implanted over craniotomies in adult cats trained to perform reaching and retrieval movements with their forelimbs. Prehensile motor training was continued and movement performance monitored for about 6–10 weeks during which the cortex was progressively explored with sharp tungsten electrodes inserted into cortical gyri (anterior and posterior sigmoid, and coronal) and the banks of sulci (cruciate, presylvian and coronal). Twice weekly, under light general anaesthesia, 3–4 tracks were made in either hemisphere till about 50 tracks were made in each hemisphere. Mean thresholds for evoking forelimb movements from different cytoarchitectonic areas (4γ, 4δ, 6aγ and 3a) were compared and no consistent or significant differences were observed between the different areas. In the animals (4/6) which used either forelimb to perform the tasks, there were no consistent differences in the mean thresholds for evoking forelimb movements from the two hemispheres. However, in 2 animals, which used their right forelimbs predominantly or exclusively to perform all the tasks, mean thresholds for evoking forelimb movements was significantly higher in areas 4γ and 6aγ of the left hemisphere (compared to the right); no consistent differences in the mean thresholds for evoking hindlimb or facial movements were observed between the two hemispheres. These findings suggest that ICMS thresholds for evoking forelimb movements may be similar in different sensorimotor areas of the cat cerebral cortex, and these thresholds could be influenced by motor training.