Forward-time simulation of realistic samples for genome-wide association studies

<p>Abstract</p> <p>Background</p> <p>Forward-time simulations have unique advantages in power and flexibility for the simulation of genetic samples of complex human diseases because they can closely mimic the evolution of human populations carrying these diseases. However, a number of methodological and computational constraints have prevented the power of this simulation method from being fully explored in existing forward-time simulation methods.</p> <p>Results</p> <p>Using a general-purpose forward-time population genetics simulation environment, we developed a forward-time simulation method that can be used to simulate realistic samples for genome-wide association studies. We examined the properties of this simulation method by comparing simulated samples with real data and demonstrated its wide applicability using four examples, including a simulation of case-control samples with a disease caused by multiple interacting genetic and environmental factors, a simulation of trio families affected by a disease-predisposing allele that had been subjected to either slow or rapid selective sweep, and a simulation of a structured population resulting from recent population admixture.</p> <p>Conclusions</p> <p>Our algorithm simulates populations that closely resemble the complex structure of the human genome, while allows the introduction of signals of natural selection. Because of its flexibility to generate different types of samples with arbitrary disease or quantitative trait models, this simulation method can simulate realistic samples to evaluate the performance of a wide variety of statistical gene mapping methods for genome-wide association studies.</p

An Evolutionary Framework for Association Testing in Resequencing Studies

Sequencing technologies are becoming cheap enough to apply to large numbers of study participants and promise to provide new insights into human phenotypes by bringing to light rare and previously unknown genetic variants. We develop a new framework for the analysis of sequence data that incorporates all of the major features of previously proposed approaches, including those focused on allele counts and allele burden, but is both more general and more powerful. We harness population genetic theory to provide prior information on effect sizes and to create a pooling strategy for information from rare variants. Our method, EMMPAT (Evolutionary Mixed Model for Pooled Association Testing), generates a single test per gene (substantially reducing multiple testing concerns), facilitates graphical summaries, and improves the interpretation of results by allowing calculation of attributable variance. Simulations show that, relative to previously used approaches, our method increases the power to detect genes that affect phenotype when natural selection has kept alleles with large effect sizes rare. We demonstrate our approach on a population-based re-sequencing study of association between serum triglycerides and variation in ANGPTL4

Differential Effects of Pravastatin and Simvastatin on the Growth of Tumor Cells from Different Organ Sites

3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) inhibitors, commonly known as statins, may possess cancer preventive and therapeutic properties. Statins are effective suppressors of cholesterol synthesis with a well-established risk-benefit ratio in cardiovascular disease prevention. Mechanistically, targeting HMGCR activity primarily influences cholesterol biosynthesis and prenylation of signaling proteins. Pravastatin is a hydrophilic statin that is selectively taken up by a sodium-independent organic anion transporter protein-1B1 (OATP1B1) exclusively expressed in liver. Simvastatin is a hydrophobic statin that enters cells by other mechanisms. Poorly-differentiated and well-differentiated cancer cell lines were selected from various tissues and examined for their response to these two statins. Simvastatin inhibited the growth of most tumor cell lines more effectively than pravastatin in a dose dependent manner. Poorly-differentiated cancer cells were generally more responsive to simvastatin than well-differentiated cancer cells, and the levels of HMGCR expression did not consistently correlate with response to statin treatment. Pravastatin had a significant effect on normal hepatocytes due to facilitated uptake and a lesser effect on prostate PC3 and colon Caco-2 cancer cells since the OATP1B1 mRNA and protein were only found in the normal liver and hepatocytes. The inhibition of cell growth was accompanied by distinct alterations in mitochondrial networks and dramatic changes in cellular morphology related to cofilin regulation and loss of p-caveolin. Both statins, hydrophilic pravastatin and hypdrophobic simvastatin caused redistribution of OATP1B1 and HMGCR to perinuclear sites. In conclusion, the specific chemical properties of different classes of statins dictate mechanistic properties which may be relevant when evaluating biological responses to statins

Cytotoxic and Pathogenic Properties of Klebsiella oxytoca Isolated from Laboratory Animals

Klebsiella oxytoca is an opportunistic pathogen implicated in various clinical diseases in animals and humans. Studies suggest that in humans K. oxytoca exerts its pathogenicity in part through a cytotoxin. However, cytotoxin production in animal isolates of K. oxytoca and its pathogenic properties have not been characterized. Furthermore, neither the identity of the toxin nor a complete repertoire of genes involved in K. oxytoca pathogenesis have been fully elucidated. Here, we showed that several animal isolates of K. oxytoca, including the clinical isolates, produced secreted products in bacterial culture supernatant that display cytotoxicity on HEp-2 and HeLa cells, indicating the ability to produce cytotoxin. Cytotoxin production appears to be regulated by the environment, and soy based product was found to have a strong toxin induction property. The toxin was identified, by liquid chromatography-mass spectrometry and NMR spectroscopy, as low molecular weight heat labile benzodiazepine, tilivalline, previously shown to cause cytotoxicity in several cell lines, including mouse L1210 leukemic cells. Genome sequencing and analyses of a cytotoxin positive K. oxytoca strain isolated from an abscess of a mouse, identified genes previously shown to promote pathogenesis in other enteric bacterial pathogens including ecotin, several genes encoding for type IV and type VI secretion systems, and proteins that show sequence similarity to known bacterial toxins including cholera toxin. To our knowledge, these results demonstrate for the first time, that animal isolates of K. oxytoca, produces a cytotoxin, and that cytotoxin production is under strict environmental regulation. We also confirmed tilivalline as the cytotoxin present in animal K. oxytoca strains. These findings, along with the discovery of a repertoire of genes with virulence potential, provide important insights into the pathogenesis of K. oxytoca. As a novel diagnostic tool, tilivalline may serve as a biomarker for K oxytoca-induced cytotoxicity in humans and animals through detection in various samples from food to diseased samples using LC-MS/MS. Induction of K. oxytoca cytotoxin by consumption of soy may be in part involved in the pathogenesis of gastrointestinal disease

Joint effects of known type 2 diabetes susceptibility loci in genome-wide association study of Singapore Chinese: The Singapore Chinese health study

Background: Genome-wide association studies (GWAS) have identified genetic factors in type 2 diabetes (T2D), mostly among individuals of European ancestry. We tested whether previously identified T2D-associated single nucleotide polymorphisms (SNPs) replicate and whether SNPs in regions near known T2D SNPs were associated with T2D within the Singapore Chinese Health Study. Methods: 2338 cases and 2339 T2D controls from the Singapore Chinese Health Study were genotyped for 507,509 SNPs. Imputation extended the genotyped SNPs to 7,514,461 with high estimated certainty (r2>0.8). Replication of known index SNP associations in T2D was attempted. Risk scores were computed as the sum of index risk alleles. SNPs in regions ±100 kb around each index were tested for associations with T2D in conditional fine-mapping analysis. Results: Of 69 index SNPs, 20 were genotyped directly and genotypes at 35 others were well imputed. Among the 55 SNPs with data, disease associations were replicated (at p<0.05) for 15 SNPs, while 32 more were directionally consistent with previous reports. Risk score was a significant predictor with a 2.03 fold higher risk CI (1.69-2.44) of T2D comparing the highest to lowest quintile of risk allele burden (p = 5.72×10-14). Two improved SNPs around index rs10923931 and 5 new candidate SNPs around indices rs10965250 and rs1111875 passed simple Bonferroni corrections for significance in conditional analysis. Nonetheless, only a small fraction (2.3% on the disease liability scale) of T2D burden in Singapore is explained by these SNPs. Conclusions: While diabetes risk in Singapore Chinese involves genetic variants, most disease risk remains unexplained. Further genetic work is ongoing in the Singapore Chinese population to identify unique common variants not already seen in earlier studies. However rapid increases in T2D risk have occurred in recent decades in this population, indicating that dynamic environmental influences and possibly gene by environment interactions complicate the genetic architecture of this disease. © 2014 Chen et al

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function : a report from the COGENT consortium

CORRIGENDUM Molecular Psychiatry (2017) 22, 1651–1652 http://www.nature.com/articles/mp2017197.pdfThe complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (similar to 8M single-nucleotide polymorphisms (SNP) with minor allele frequency >= 1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (PPeer reviewe