Robust and Powerful Tests for Rare Variants Using Fisher's Method to Combine Evidence of Association From Two or More Complementary Tests

Many association tests have been proposed for rare variants, but the choice of a powerful test is uncertain when there is limited information on the underlying genetic model. Proposed methods use either linear statistics, which are powerful when most variants are causal and have the same direction of effect, or quadratic statistics, which are more powerful in other scenarios. To achieve robustness, it is natural to combine the evidence of association from two or more complementary tests. To this end, we consider the minimum‐p and Fisher's methods of combining P‐values from linear and quadratic statistics. Extensive simulation studies show that both methods are robust across models with varying proportions of causal, deleterious, and protective rare variants, allele frequencies, and effect sizes. When the majority (>75%) of the causal effects are in the same direction (deleterious or protective), Fisher's method consistently outperforms the minimum‐p and the individual linear and quadratic tests, as well as the optimal sequence kernel association test, SKAT‐O. When the individual test has moderate power, Fisher's test has improved power for 90% of the ～5000 models considered, with >20% relative efficiency gain for 40% of the models. The maximum absolute power loss is 8% for the remaining 10% of the models. An application to the GAW17 quantitative trait Q2 data based on sequence data of the 1000 Genomes Project shows that, compared with linear and quadratic tests, Fisher's test has comparable power for all 13 functional genes and provides the best power for more than half of them.     

Central IGF-1 protects against features of cognitive and sensorimotor decline with aging in male mice

GeroScience - Disruptions in growth hormone/insulin-like growth factor-1 (GH/IGF-1) signaling have been linked to improved longevity in mice and humans. Nevertheless, while IGF-1 levels are...     

Timing and route of exposure affects crystal formation in melamine and cyanuric exposed male and female rats: Gavage vs. feeding

Effects of the dosing matrix and timing on the onset of renal crystal formation were evaluated in male and non-pregnant female rats (Fisher 344) exposed to both melamine (MEL) and cyanuric acid (CYA) for 28 days. Rats were fed ground feed containing 60 ppm MEL and 60 ppm CYA, (5 mg/kg bw/day equivalent), or exposed via oral gavage to carboxymethylcellulose containing 5 mg/kg bw MEL followed by 5 mg/kg bw CYA either consecutively (<1 min apart) or delayed 45 min after MEL. Staggered gavage exposure to MEL/CYA caused extensive renal crystal formation as compared to when the two compounds were administered consecutively or in feed. Treatment related effects included reduced weight gain, feed consumption, and testicular weight and increased kidney weight, water consumption and urine output. Animals from the staggered MEL/CYA gavage exposure group became ill and were removed after 9 days of exposure. Approximately 1 week after the initiation of exposure microscopic urinalysis revealed MEL/CYA crystals in both groups of gavaged animals but not in the MEL/CYA feed treatment groups. Urinary crystals were smaller (10 μm) in animals consecutively gavaged. In contrast the urinary crystals were larger (20–40 μm) and frequently clumped in the animals in the staggered gavage group.     

Assessment of beta particle flux from surface contamination as a relative indicator for radionuclide distribution on external surfaces of a multistory building in Pripyat

Several issues should be considered when assessing the feasibility of remediation following the detonation of a radiological dispersion device (e.g., dirty bomb) or improvised nuclear device in a large city. These issues include the levels and characteristics of the radioactive contamination, the availability of resources required for decontamination, and the planned future use of the city's structures and buildings. Presently, little is known about the distribution, redistribution, and migration of radionuclides in an urban environment. However, Pripyat, a city substantially contaminated by the Chernobyl Nuclear Power Plant accident in April 1986, may provide some answers. The main objective of this study was to determine the radionuclide distribution on a Pripyat multistory building that had not been decontaminated and, therefore, could reflect the initial fallout and its further natural redistribution on external surfaces over 23 y. The seven-story building selected was surveyed from the ground floor to the roof on horizontal and vertical surfaces along seven ground-to-roof transections. Some results from this study indicate that the upper floors of the building had higher contamination levels than the lower floors. Consequently, the authors recommend that thorough decontamination should be considered for all the floors of tall buildings (not just lower floors).     

Breakpoint graphs and ancestral genome reconstructions

Recently completed whole-genome sequencing projects marked the transition from gene-based phylogenetic studies to phylogenomics analysis of entire genomes. We developed an algorithm MGRA for reconstructing ancestral genomes and used it to study the rearrangement history of seven mammalian genomes: human, chimpanzee, macaque, mouse, rat, dog, and opossum. MGRA relies on the notion of the multiple breakpoint graphs to overcome some limitations of the existing approaches to ancestral genome reconstructions. MGRA also generates the rearrangement-based characters guiding the phylogenetic tree reconstruction when the phylogeny is unknown.The first attempts to reconstruct the genomic architecture of ancestral mammals predated the era of genomic sequencing and were based on cytogenetics approaches (Wienberg and Stanyon 1997). The rearrangement-based phylogenomic studies were pioneered by Sankoff and colleagues (Sankoff et al. 1992; Blanchette et al. 1997; Sankoff and Blanchette 1998) and were based on analyzing the breakpoint distances. Moret et al. (2001) further optimized this approach and developed a popular GRAPPA software for rearrangement analysis. MGR, another genome rearrangement tool (Bourque and Pevzner 2002), uses genomic distances instead of breakpoint distances for ancestral reconstructions. Since genomic distances lead to more accurate ancestral reconstructions (Moret et al. 2002; Tang and Moret 2003), GRAPPA has been modified for genomic distances as well. While MGR has been used in several phylogenomic studies (Bourque et al. 2005; Murphy et al. 2005; Bulazel et al. 2007; Pontius et al. 2007; Xia et al. 2007; Cardone et al. 2008; Deuve et al. 2008), both MGR and GRAPPA have limited ability to distinguish reliable from unreliable rearrangements and to address the “weak associations” problem in ancestral reconstructions (Bourque et al. 2004, 2005, 2006; Froenicke et al. 2006).Recently, Ma et al. (2006) made an important step toward reliable reconstruction of the ancestral genomes. In contrast to MGR and GRAPPA (which analyze both reliable and unreliable rearrangements), they have chosen to focus on the reliable breakpoint reconstruction in the ancestral genomes and to avoid assignments in the case of weak associations (complex breakpoints). This proved to be a valuable approach since, as it turned out, most breakpoints in the ancestral mammalian genomes can be reliably reconstructed. However, there are some limitations (discussed in Rocchi et al. 2006) that this approach has to overcome to scale for large sets of genomes. First, while the Ma et al. (2006) inferCARs algorithm assumes that the phylogeny is known, it remains a subject of enduring debates even in the case of the primate–rodent–carnivore split (which is assumed to be resolved in Ma et al. 2006). With the increase in the number of species, the reliability of the phylogeny will become even a bigger concern, thus raising the question of devising an approach that does not assume a fixed phylogeny but instead uses rearrangements as new characters for constructing phylogenetic trees (see Chaisson et al. 2006). While MGR does not assume a fixed phylogeny, its heuristically derived weak associations are less reliable. The challenge then is to integrate the reliability of inferCARs with the flexibility of MGR. Another avenue to improve inferCARs algorithms is to find out how to deal with complex breakpoints that create gaps in reconstructions.Note that the Ma et al. (2006) approach focuses on the reliable ancestor reconstruction rather than on the specific rearrangements that happened in the course of evolution. These are related but different problems that both can benefit from incorporating into a single computational framework. Indeed, Ma et al. (2006) consider individual breakpoints and do not distinguish between particular types of rearrangements that generated a breakpoint of interest. In reality, the reversals and translocations operate on pairs of dependent breakpoints rather than individual breakpoints. Some rearrangements (and synteny associations) cannot be inferred from the analysis of single breakpoints but become tractable via analyzing the breakpoint graph.² As a result, while MGR constructs provably optimal scenarios in the absence of breakpoint reuse, it is not clear whether the same result holds for inferCARs.Recently, Zhao and Bourque (2007, 2009) developed the EMRAE algorithm, which reconstructs both reliable rearrangements and ancestors, thus addressing the shortcomings of both MGR (difficulty in distinguishing between reliable and putative rearrangement events) and inferCARs (ancestor reconstruction only). However, EMRAE (in contrast to MGR) does not attempt to reconstruct the phylogenetic tree and is limited to unichromosomal genomes. Below we address some limitations of MGR, EMRAE, and inferCARs by developing the Multiple Genome Rearrangements and Ancestors (MGRA) algorithm (available from http://www.cs.ucsd.edu/users/ppevzner/software.html). In particular: (1) MGRA constructs provably optimal scenarios even when there is some breakpoint reuse and when other tools do not guarantee optimality. (2) MGRA is suitable for ancestral reconstructions of multi-chromosomal genomes (in contrast to EMRAE). (3) MGRA is conceptually simpler and orders of magnitude faster than MGR. (4) MGRA is not limited to reconstructing ancestral genomes in the case of known phylogeny (like inferCARs and EMRAE). Instead, it can guide the rearrangement-based reconstruction of phylogenetic trees. (5) MGRA does not require prior information about the approximate lengths of the branches of the phylogenetic trees (in contrast to inferCARs).To evaluate the performance of MGRA, we compared ancestral reconstructions generated by MGRA and inferCARs. Despite the fact that MGRA and inferCARs are very different algorithms, their reconstructions turned out to be remarkably similar (98.5% of synteny associations are identical). We further analyzed some differences between MGRA, inferCARs, and the cytogenetics approach.     

A Comprehensive Analysis of Nuclear-Encoded Mitochondrial Genes in Schizophrenia

Background

The genetic risk factors of schizophrenia (SCZ), a severe psychiatric disorder, are not yet fully understood. Multiple lines of evidence suggest that mitochondrial dysfunction may play a role in SCZ, but comprehensive association studies are lacking. We hypothesized that variants in nuclear-encoded mitochondrial genes influence susceptibility to SCZ.

Prospective serum metabolomic profiling of lethal prostate cancer

Impaired metabolism may play an important role in the pathogenesis of lethal prostate cancer, yet there is a paucity of evidence regarding the association. We conducted a large prospective serum metabolomic analysis of lethal prostate cancer in 523 cases and 523 matched controls nested within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. Median time from baseline fasting serum collection to prostate cancer death was 18 years (maximum 30 years). We identified 860 known biochemicals through an ultrahigh-performance LC–MS/MS platform. Conditional logistic regression models estimated odds ratios (OR) and 95% confidence intervals of risk associated with 1-standard deviation (s.d.) increases in log-metabolite signals. We identified 34 metabolites associated with lethal prostate cancer with a false discovery rate (FDR) < 0.15. Notably, higher serum thioproline, and thioproline combined with two other cysteine-related amino acids and redox metabolites, cystine and cysteine, were associated with reduced risk (1-s.d. OR = 0.75 and 0.71, respectively; p ≤ 8.2 × 10⁻⁵). By contrast, the dipeptide leucylglycine (OR = 1.36, p = 8.2 × 10⁻⁵), and three gamma-glutamyl amino acids (OR = 1.28–1.30, p ≤ 4.6 × 10⁻⁴) were associated with increased risk of lethal prostate cancer. Cases with metastatic disease at diagnosis (n = 179) showed elevated risk for several lipids, including especially the ketone body 3-hydroxybutyrate (BHBA), acyl carnitines, and dicarboxylic fatty acids (1.37 ≤ OR ≤ 1.49, FDR < 0.15). These findings provide a prospective metabolomic profile of lethal prostate cancer characterized by altered biochemicals in the redox, dipeptide, pyrimidine, and gamma-glutamyl amino acid pathways, whereas ketone bodies and fatty acids were associated specifically with metastatic disease.