Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases

<p>Abstract</p> <p>Background</p> <p>Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates using a small number of observations. Missing trait and/or marker values prevent one from directly applying the classical model selection criteria such as Akaike's information criterion (AIC) and Bayesian information criterion (BIC).</p> <p>Results</p> <p>We propose a two-step Bayesian variable selection method which deals with the sparse parameter space and the small sample size issues. The regression coefficient priors are flexible enough to incorporate the characteristic of "large <it>p </it>small <it>n</it>" data. Specifically, sparseness and possible asymmetry of the significant coefficients are dealt with by developing a Gibbs sampling algorithm to stochastically search through low-dimensional subspaces for significant variables. The superior performance of the approach is demonstrated via simulation study. We also applied it to real QTL mapping datasets.</p> <p>Conclusion</p> <p>The two-step procedure coupled with Bayesian classification offers flexibility in modeling "large p small n" data, especially for the sparse and asymmetric parameter space. This approach can be extended to other settings characterized by high dimension and low sample size.</p

Mapping quantitative trait loci in line cross with repeat records

<p>Abstract</p> <p>Background</p> <p>Phenotypes with repeat records from one individual or multiple individuals were often encountered in practices of mapping QTL in linecross. The current genetic mapping method for a trait with repeat records is adopted by simply replacing the phenotype by the average value of the repeat records. This simple treatment has not sufficiently utilized the information from the replication and ignored the impacts of the permanent environmental effects on the accuracy of the estimated QTL.</p> <p>Results</p> <p>We propose to map QTL by using the repeatability model to directly analyze the repeat records rather than simply analyze the mean phenotype, improving the efficiency of QTL detecting because of adequately utilizing the information from data and allowing for the permanent environmental effects. A maximum likelihood method implemented via the expectation-maximization (EM) algorithm is applied to perform the parameter estimation of the repeatability model. The superiority of the mapping method based on the repeatability model over simple analysis using the mean phenotype was demonstrated by a series of simulations.</p> <p>Conclusion</p> <p>Our results suggest that the proposed method can serve as a powerful alternative to existing methods. By mean of the repeatability model, utilizing the repeat records on individual may improve the efficiency of QTL detecting in line cross.</p

The role of the fat mass and obesity associated gene (FTO) in breast cancer risk

<p>Abstract</p> <p>Background</p> <p>Obesity has been shown to increase breast cancer risk. <it>FTO </it>is a novel gene which has been identified through genome wide association studies (GWAS) to be related to obesity. Our objective was to evaluate tissue expression of FTO in breast and the role of FTO SNPs in predicting breast cancer risk.</p> <p>Methods</p> <p>We performed a case-control study of 354 breast cancer cases and 364 controls. This study was conducted at Northwestern University. We examined the role of single nucleotide polymorphisms (SNPs) of intron 1 of <it>FTO </it>in breast cancer risk. We genotyped cases and controls for four SNPs: rs7206790, rs8047395, rs9939609 and rs1477196. We also evaluated tissue expression of FTO in normal and malignant breast tissue.</p> <p>Results</p> <p>We found that all SNPs were significantly associated with breast cancer risk with rs1477196 showing the strongest association. We showed that FTO is expressed both in normal and malignant breast tissue. We found that <it>FTO </it>genotypes provided powerful classifiers to predict breast cancer risk and a model with epistatic interactions further improved the prediction accuracy with a receiver operating characteristic (ROC) curves of 0.68.</p> <p>Conclusion</p> <p>In conclusion we have shown a significant expression of FTO in malignant and normal breast tissue and that <it>FTO </it>SNPs in intron 1 are significantly associated with breast cancer risk. Furthermore, these <it>FTO </it>SNPs are powerful classifiers in predicting breast cancer risk.</p

Predicting Unobserved Phenotypes for Complex Traits from Whole-Genome SNP Data

Genome-wide association studies (GWAS) for quantitative traits and disease in humans and other species have shown that there are many loci that contribute to the observed resemblance between relatives. GWAS to date have mostly focussed on discovery of genes or regulatory regions habouring causative polymorphisms, using single SNP analyses and setting stringent type-I error rates. Genome-wide marker data can also be used to predict genetic values and therefore predict phenotypes. Here, we propose a Bayesian method that utilises all marker data simultaneously to predict phenotypes. We apply the method to three traits: coat colour, %CD8 cells, and mean cell haemoglobin, measured in a heterogeneous stock mouse population. We find that a model that contains both additive and dominance effects, estimated from genome-wide marker data, is successful in predicting unobserved phenotypes and is significantly better than a prediction based upon the phenotypes of close relatives. Correlations between predicted and actual phenotypes were in the range of 0.4 to 0.9 when half of the number of families was used to estimate effects and the other half for prediction. Posterior probabilities of SNPs being associated with coat colour were high for regions that are known to contain loci for this trait. The prediction of phenotypes using large samples, high-density SNP data, and appropriate statistical methodology is feasible and can be applied in human medicine, forensics, or artificial selection programs

Convergent Evidence from Mouse and Human Studies Suggests the Involvement of Zinc Finger Protein 326 Gene in Antidepressant Treatment Response

OBJECTIVES: The forced swim test (FST) is a commonly used model to predict antidepressant efficacy. Uncovering the genetic basis of the model may unravel the mechanism of antidepressant treatment. METHODS: FVB/NJ (FVB) and C57BL/6J (B6) were first identified as the response and non-response strains to fluoxetine (a serotonin-specific reuptake inhibitor antidepressant) treatment in the mouse FST. Simple-interval (SIM) and composite-interval (CIM) mappings were applied to map the quantitative trait loci (QTLs) of the anti-immobility effect of fluoxetine in FST (FST(FLX)) in 865 male B6×FVB-F2 mice. The brain mRNA expressions of the gene with the maximum QTL-linkage signal for FST(FLX) after the FST were compared between B6 and FVB mice and also compared between fluoxetine and saline treatment. The association of the variants in the human homologue of the mouse FST(FLX)-QTL gene with major depressive disorder (MDD) and antidepressant response were investigated in 1080 human subjects (MDD/control = 582/498). RESULTS: One linkage signal for FST(FLX)-QTL was detected at an intronic SNP (rs6215396) of the mouse Zfp326 gene (maximal CIM-LOD = 9.36). The Zfp326 mRNA expression in the FVB thalamus was significantly down-regulated by fluoxetine in the FST, and the higher FVB-to-B6 Zfp326 mRNA expressions in the frontal cortex, striatum and hypothalamus diminished after fluoxetine treatment. Two coding-synonymous SNPs (rs2816881 and rs10922744) in the human homologue of Zfp326, ZNF326, were significantly associated with the 8-week antidepressant treatment response in the MDD patients (Bonferroni-corrected p = 0.004-0.028). CONCLUSIONS: The findings suggest the involvement of the Zfp326 and ZNF326 genes in antidepressant treatment response

Mitochondrial Uncoupling Protein-2 (UCP2) Mediates Leptin Protection Against MPP+ Toxicity in Neuronal Cells

Mitochondrial dysfunction is involved in the pathogenesis of neurodegenerative diseases, including Parkinson’s disease (PD). Uncoupling proteins (UCPs) delink ATP production from biofuel oxidation in mitochondria to reduce oxidative stress. UCP2 is expressed in brain, and has neuroprotective effects under various toxic insults. We observed induction of UCP2 expression by leptin in neuronal cultures, and hypothesize that leptin may preserve neuronal survival via UCP2. We showed that leptin preserved cell survival in neuronal SH-SY5Y cells against MPP+ toxicity (widely used in experimental Parkinsonian models) by maintaining ATP levels and mitochondrial membrane potential (MMP); these effects were accompanied by increased UCP2 expression. Leptin had no effect in modulating reactive oxygen species levels. Stable knockdown of UCP2 expression reduced ATP levels, and abolished leptin protection against MPP+-induced mitochondrial depolarization, ATP deficiency, and cell death, indicating that UCP2 is critical in mediating these neuroprotective effects of leptin against MPP+ toxicity. Interestingly, UCP2 knockdown increased UCP4 expression, but not of UCP5. Our findings show that leptin preserves cell survival by maintaining MMP and ATP levels mediated through UCP2 in MPP+-induced toxicity

Magnetic hyperthermia controlled drug release in the GI tract : solving the problem of detection

Drug delivery to the gastrointestinal (GI) tract is highly challenging due to the harsh environments any drug- delivery vehicle must experience before it releases it’s drug payload. Effective targeted drug delivery systems often rely on external stimuli to effect release, therefore knowing the exact location of the capsule and when to apply an external stimulus is paramount. We present a drug delivery system for the GI tract based on coating standard gelatin drug capsules with a model eicosane- superparamagnetic iron oxide nanoparticle composite coating, which is activated using magnetic hyperthermia as an on-demand release mechanism to heat and melt the coating. We also show that the capsules can be readily detected via rapid X-ray computed tomography (CT) and magnetic resonance imaging (MRI), vital for progressing such a system towards clinical applications. This also offers the opportunity to image the dispersion of the drug payload post release. These imaging techniques also influenced capsule content and design and the delivered dosage form. The ability to easily change design demonstrates the versatility of this system, a vital advantage for modern, patient-specific medicine

Efficacy of praziquantel and artemisinin derivatives for the treatment and prevention of human schistosomiasis: a systematic review and meta-analysis

<p>Abstract</p> <p>Background</p> <p>Praziquantel has been used as first-line drug for chemotherapy of schistosomiasis since 1984. Besides praziquantel, artemether and artesunate have also been used for the control of this infectious disease since late 1990s. In this article, we conducted a systematic review and meta-analysis to evaluate the antischistosomal efficacy of different medication strategies including monotherapy or combination therapies of these drugs.</p> <p>Results</p> <p>A number of 52 trials from 38 articles published in peer-reviewed journals before July 2011 were selected for analysis after searching the following literature databases: the Cochrane Library, PubMed/Medline, ISI Web of Science, Chinese Biomedicine Literature Database, and China National Knowledge Infrastructure. Our meta-analyses showed that a dosage of 30-60 mg/kg praziquantel compared with placebo produced a protection rate of about 76% (95% CI: 67%-83%) for treating human schistosomiasis, which varied from 70% to 76% with no significant differences among the subspecies <it>S. haematobium</it>, <it>S. japonicum </it>or <it>S. mansoni</it>. Protection rates were higher when praziquantel doses were elevated, as concluded from the nRCTs results: the protection rate of praziquantel at 40 mg/kg was 52% (95% CI: 49%-55%), and it increased to 91% (95% CI: 88%-92%) when the dosages were elevated to 60/80/100 mg/kg divided two or more doses. Multiple doses of artemether or artesunate over 1- or 2-week intervals resulted in protection rates of 65% to 97% for preventing schistosomiasis, and increased doses and shorter medication intervals improved their efficacies. Praziquantel and artemisinin derivatives (artemether or artesunate) in combination resulted in a higher protection rate of 84% (95% CI: 64%-91%) than praziquantel monotherapy for treatment. praziquantel and artesunate in combination had a great protection rate of 96% (95% CI: 78%-99%) for preventing schistosomes infection.</p> <p>Conclusions</p> <p>According to the results, praziquantel remains effective in schistosomiasis treatment, and multiple doses would improve its efficacy; meanwhile, praziquantel is also a good drug for preventing acute schistosomiasis morbidity. It's better to use multiple doses of artemether or artesunate with 1- or 2-week intervals for prevention against schistosome infection. Praziquantel and artemether or artesunate in combination perform better in treatment than praziquantel monotherapy, and they are especially suitable for treating the patients with repeated exposure to infected water.</p

Heterotic Trait Locus (HTL) Mapping Identifies Intra-Locus Interactions That Underlie Reproductive Hybrid Vigor in Sorghum bicolor

Identifying intra-locus interactions underlying heterotic variation among whole-genome hybrids is a key to understanding mechanisms of heterosis and exploiting it for crop and livestock improvement. In this study, we present the development and first use of the heterotic trait locus (HTL) mapping approach to associate specific intra-locus interactions with an overdominant heterotic mode of inheritance in a diallel population using Sorghum bicolor as the model. This method combines the advantages of ample genetic diversity and the possibility of studying non-additive inheritance. Furthermore, this design enables dissecting the latter to identify specific intra-locus interactions. We identified three HTLs (3.5% of loci tested) with synergistic intra-locus effects on overdominant grain yield heterosis in 2 years of field trials. These loci account for 19.0% of the heterotic variation, including a significant interaction found between two of them. Moreover, analysis of one of these loci (hDPW4.1) in a consecutive F2 population confirmed a significant 21% increase in grain yield of heterozygous vs. homozygous plants in this locus. Notably, two of the three HTLs for grain yield are in synteny with previously reported overdominant quantitative trait loci for grain yield in maize. A mechanism for the reproductive heterosis found in this study is suggested, in which grain yield increase is achieved by releasing the compensatory tradeoffs between biomass and reproductive output, and between seed number and weight. These results highlight the power of analyzing a diverse set of inbreds and their hybrids for unraveling hitherto unknown allelic interactions mediating heterosis