The detection of earnings manipulation: the three‐phase cutting plane algorithm using mathematical programming

The primary goal of this study was to propose an algorithm using mathematical programming to detect earnings management practices. In order to evaluate the ability of this proposed algorithm, the traditional statistical models are used as a benchmark vis‐à‐vis their time series counterparts. As emerging techniques in the area of mathematical programming yield better results, application of suitable models is expected to result in highly performed forecasts. The motivation behind this paper is to develop an algorithm which will succeed in detecting companies that appeal to financial manipulation. The methodology is based on cutting plane formulation using mathematical programming. A sample of 126 Turkish manufacturing firms described over 10 financial ratios and indexes are used for detecting factors associated with false financial statements. The results indicate that the proposed three‐phase cutting plane algorithm outperforms the traditional statistical techniques which are widely used for false financial statement detections. Furthermore, the results indicate that the investigation of financial information can be helpful towards the identification of false financial statements and highlight the importance of financial ratios/indexes such as Days' Sales in Receivables Index (DSRI), Gross Margin Index (GMI), Working Capital Accruals to Total Assets (TATA) and Days to Inventory Index (DINV). Copyright © 2009 John Wiley & Sons, Ltd.     

Network modeling links breast cancer susceptibility and centrosome dysfunction

Many cancer-associated genes remain to be identified to clarify the underlying molecular mechanisms of cancer susceptibility and progression. Better understanding is also required of how mutations in cancer genes affect their products in the context of complex cellular networks. Here we have used a network modeling strategy to identify genes potentially associated with higher risk of breast cancer. Starting with four known genes encoding tumor suppressors of breast cancer, we combined gene expression profiling with functional genomic and proteomic (or 'omic') data from various species to generate a network containing 118 genes linked by 866 potential functional associations. This network shows higher connectivity than expected by chance, suggesting that its components function in biologically related pathways. One of the components of the network is HMMR, encoding a centrosome subunit, for which we demonstrate previously unknown functional associations with the breast cancer-associated gene BRCA1. Two case-control studies of incident breast cancer indicate that the HMMR locus is associated with higher risk of breast cancer in humans. Our network modeling strategy should be useful for the discovery of additional cancer-associated genes.     

Human Genome Variation 2006: emerging views on structural variation and large-scale SNP analysis

The eighth annual Human Genome Variation Meeting was held in September 2006 in the Hong Kong Special Administrative Region, China. The meeting highlighted recent advances in characterization of genetic variation, including genome-wide association studies and structural variation.     

Multiple apical plasma membrane constituents are associated with susceptibility to meconium ileus in individuals with cystic fibrosis

Variants associated with meconium ileus in cystic fibrosis were identified in 3,763 affected individuals by genome-wide association study (GWAS). Five SNPs at two loci near SLC6A14 at Xq23-24 (minimum P = 1.28 × 10(-12) at rs3788766) and SLC26A9 at 1q32.1 (minimum P = 9.88 × 10(-9) at rs4077468) accounted for ~5% of phenotypic variability and were replicated in an independent sample of affected individuals (n = 2,372; P = 0.001 and 0.0001, respectively). By incorporating the knowledge that disease-causing mutations in CFTR alter electrolyte and fluid flux across surface epithelium into a hypothesis-driven GWAS (GWAS-HD), we identified associations with the same SNPs in SLC6A14 and SLC26A9 and established evidence for the involvement of SNPs in a third solute carrier gene, SLC9A3. In addition, GWAS-HD provided evidence of association between meconium ileus and multiple genes encoding constituents of the apical plasma membrane where CFTR resides (P = 0.0002; testing of 155 apical membrane genes jointly and in replication, P = 0.022). These findings suggest that modulating activities of apical membrane constituents could complement current therapeutic paradigms for cystic fibrosis.     

A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance

Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and β-cell dysfunction but have contributed little to the understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways might be uncovered by accounting for differences in body mass index (BMI) and potential interactions between BMI and genetic variants. We applied a joint meta-analysis approach to test associations with fasting insulin and glucose on a genome-wide scale. We present six previously unknown loci associated with fasting insulin at P < 5 × 10(-8) in combined discovery and follow-up analyses of 52 studies comprising up to 96,496 non-diabetic individuals. Risk variants were associated with higher triglyceride and lower high-density lipoprotein (HDL) cholesterol levels, suggesting a role for these loci in insulin resistance pathways. The discovery of these loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.     

Resequencing of positional candidates identifies low frequency IL23R coding variants protecting against inflammatory bowel disease

Genome-wide association studies (GWAS) have identified dozens of risk loci for many complex disorders, including Crohn's disease. However, common disease-associated SNPs explain at most ～20% of the genetic variance for Crohn's disease. Several factors may account for this unexplained heritability, including rare risk variants not adequately tagged thus far in GWAS. That rare susceptibility variants indeed contribute to variation in multifactorial phenotypes has been demonstrated for colorectal cancer, plasma high-density lipoprotein cholesterol levels, blood pressure, type 1 diabetes, hypertriglyceridemia and, in the case of Crohn's disease, for NOD2 (refs. 14,15). Here we describe the use of high-throughput resequencing of DNA pools to search for rare coding variants influencing susceptibility to Crohn's disease in 63 GWAS-identified positional candidate genes. We identify low frequency coding variants conferring protection against inflammatory bowel disease in IL23R, but we conclude that rare coding variants in positional candidates do not make a large contribution to inherited predisposition to Crohn's disease.     

Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease

Several risk factors for Crohn's disease have been identified in recent genome-wide association studies. To advance gene discovery further, we combined data from three studies on Crohn's disease (a total of 3,230 cases and 4,829 controls) and carried out replication in 3,664 independent cases with a mixture of population-based and family-based controls. The results strongly confirm 11 previously reported loci and provide genome-wide significant evidence for 21 additional loci, including the regions containing STAT3, JAK2, ICOSLG, CDKAL1 and ITLN1. The expanded molecular understanding of the basis of this disease offers promise for informed therapeutic development.     

Identification of ten loci associated with height highlights new biological pathways in human growth

Height is a classic polygenic trait, reflecting the combined influence of multiple as-yet-undiscovered genetic factors. We carried out a meta-analysis of genome-wide association study data of height from 15,821 individuals at 2.2 million SNPs, and followed up the strongest findings in >10,000 subjects. Ten newly identified and two previously reported loci were strongly associated with variation in height (P values from 4 x 10(-7) to 8 x 10(-22)). Together, these 12 loci account for approximately 2% of the population variation in height. Individuals with < or =8 height-increasing alleles and > or =16 height-increasing alleles differ in height by approximately 3.5 cm. The newly identified loci, along with several additional loci with strongly suggestive associations, encompass both strong biological candidates and unexpected genes, and highlight several pathways (let-7 targets, chromatin remodeling proteins and Hedgehog signaling) as important regulators of human stature. These results expand the picture of the biological regulation of human height and of the genetic architecture of this classical complex trait.     

Crystal structure and biochemical characterization of the transmembrane PAP2 type phosphatidylglycerol phosphate phosphatase from <Emphasis Type="Italic">Bacillus subtilis</Emphasis>

Type 2 phosphatidic acid phosphatases (PAP2s) can be either soluble or integral membrane enzymes. In bacteria, integral membrane PAP2s play major roles in the metabolisms of glycerophospholipids, undecaprenyl-phosphate (C₅₅-P) lipid carrier and lipopolysaccharides. By in vivo functional experiments and biochemical characterization we show that the membrane PAP2 coded by the Bacillus subtilis yodM gene is the principal phosphatidylglycerol phosphate (PGP) phosphatase of B. subtilis. We also confirm that this enzyme, renamed bsPgpB, has a weaker activity on C₅₅-PP. Moreover, we solved the crystal structure of bsPgpB at 2.25 Å resolution, with tungstate (a phosphate analog) in the active site. The structure reveals two lipid chains in the active site vicinity, allowing for PGP substrate modeling and molecular dynamic simulation. Site-directed mutagenesis confirmed the residues important for substrate specificity, providing a basis for predicting the lipids preferentially dephosphorylated by membrane PAP2s.