Estimating the Total Number of Susceptibility Variants Underlying Complex Diseases from Genome-Wide Association Studies

Recently genome-wide association studies (GWAS) have identified numerous susceptibility variants for complex diseases. In this study we proposed several approaches to estimate the total number of variants underlying these diseases. We assume that the variance explained by genetic markers (Vg) follow an exponential distribution, which is justified by previous studies on theories of adaptation. Our aim is to fit the observed distribution of Vg from GWAS to its theoretical distribution. The number of variants is obtained by the heritability divided by the estimated mean of the exponential distribution. In practice, due to limited sample sizes, there is insufficient power to detect variants with small effects. Therefore the power was taken into account in fitting. Besides considering the most significant variants, we also tried to relax the significance threshold, allowing more markers to be fitted. The effects of false positive variants were removed by considering the local false discovery rates. In addition, we developed an alternative approach by directly fitting the z-statistics from GWAS to its theoretical distribution. In all cases, the “winner's curse” effect was corrected analytically. Confidence intervals were also derived. Simulations were performed to compare and verify the performance of different estimators (which incorporates various means of winner's curse correction) and the coverage of the proposed analytic confidence intervals. Our methodology only requires summary statistics and is able to handle both binary and continuous traits. Finally we applied the methods to a few real disease examples (lipid traits, type 2 diabetes and Crohn's disease) and estimated that hundreds to nearly a thousand variants underlie these traits

A Unifying Framework for Evaluating the Predictive Power of Genetic Variants Based on the Level of Heritability Explained

An increasing number of genetic variants have been identified for many complex diseases. However, it is controversial whether risk prediction based on genomic profiles will be useful clinically. Appropriate statistical measures to evaluate the performance of genetic risk prediction models are required. Previous studies have mainly focused on the use of the area under the receiver operating characteristic (ROC) curve, or AUC, to judge the predictive value of genetic tests. However, AUC has its limitations and should be complemented by other measures. In this study, we develop a novel unifying statistical framework that connects a large variety of predictive indices together. We showed that, given the overall disease probability and the level of variance in total liability (or heritability) explained by the genetic variants, we can estimate analytically a large variety of prediction metrics, for example the AUC, the mean risk difference between cases and non-cases, the net reclassification improvement (ability to reclassify people into high- and low-risk categories), the proportion of cases explained by a specific percentile of population at the highest risk, the variance of predicted risks, and the risk at any percentile. We also demonstrate how to construct graphs to visualize the performance of risk models, such as the ROC curve, the density of risks, and the predictiveness curve (disease risk plotted against risk percentile). The results from simulations match very well with our theoretical estimates. Finally we apply the methodology to nine complex diseases, evaluating the predictive power of genetic tests based on known susceptibility variants for each trait

Robust Association Tests Under Different Genetic Models, Allowing for Binary or Quantitative Traits and Covariates

The association of genetic variants with outcomes is usually assessed under an additive model, for example by the trend test. However, misspecification of the genetic model will lead to a reduction in power. More robust tests for association might therefore be preferred. A useful approach is to consider the maximum of the three test statistics under additive, dominant and recessive models (MAX3). The p-value however has to be adjusted to maintain the type I error rate. Previous studies and software on robust association tests have focused on binary traits without covariates. In this study we developed an analytic approach to robust association tests using MAX3, allowing for quantitative or binary traits as well as covariates. The p-values from our theoretical calculations match very well with those from a bootstrap resampling procedure. The methodology is implemented in the R package RobustSNP which is able to handle both small-scale studies and GWAS. The package and documentation are available at http://sites.google.com/site/honcheongso/software/robustsnp

Laboratory layered latte

Inducing thermal gradients in fluid systems with initial, well-defined density gradients results in the formation of distinct layered patterns, such as those observed in the ocean due to double-diffusive convection. In contrast, layered composite fluids are sometimes observed in confined systems of rather chaotic initial states, for example, lattes formed by pouring espresso into a glass of warm milk. Here, we report controlled experiments injecting a fluid into a miscible phase and show that, above a critical injection velocity, layering emerges over a time scale of minutes. We identify critical conditions to produce the layering, and relate the results quantitatively to double-diffusive convection. Based on this understanding, we show how to employ this single-step process to produce layered structures in soft materials, where the local elastic properties vary step-wise along the length of the material

Cerebellar-dependent delay eyeblink conditioning in adolescents with Specific Language Impairment

Cerebellar impairments have been hypothesized as part of the pathogenesis of Specific Language Impairment (SLI), although direct evidence of cerebellar involvement is sparse. Eyeblink Conditioning (EBC) is a learning task with well documented cerebellar pathways. This is the first study of EBC in affected adolescents and controls. 16 adolescent controls, 15 adolescents with SLI, and 12 adult controls participated in a delay EBC task. Affected children had low general language performance, grammatical deficits but no speech impairments. The affected group did not differ from the control adolescent or control adult group, showing intact cerebellar functioning on the EBC task. This study did not support cerebellar impairment at the level of basic learning pathways as part of the pathogenesis of SLI. Outcomes do not rule out cerebellar influences on speech impairment, or possible other forms of cerebellar functioning as contributing to SLI

Species composition, larval habitats, seasonal occurrence and distribution of potential malaria vectors and associated species of Anopheles (Diptera: Culicidae) from the Republic of Korea

<p>Abstract</p> <p>Background</p> <p>Larval mosquito habitats of potential malaria vectors and related species of <it>Anopheles </it>from three provinces (Gyeonggi, Gyeongsangbuk, Chungcheongbuk Provinces) of the Republic of Korea were surveyed in 2007. This study aimed to determine the species composition, seasonal occurrence and distributions of <it>Anopheles </it>mosquitoes. Satellite derived normalized difference vegetation index data (NDVI) was also used to study the seasonal abundance patterns of <it>Anopheles </it>mosquitoes.</p> <p>Methods</p> <p>Mosquito larvae from various habitats were collected using a standard larval dipper or a white plastic larval tray, placed in plastic bags, and were preserved in 100% ethyl alcohol for species identification by PCR and DNA sequencing. The habitats in the monthly larval surveys included artificial containers, ground depressions, irrigation ditches, drainage ditches, ground pools, ponds, rice paddies, stream margins, inlets and pools, swamps, and uncultivated fields. All field-collected specimens were identified to species, and relationships among habitats and locations based on species composition were determined using cluster statistical analysis.</p> <p>Results</p> <p>In about 10,000 specimens collected, eight species of <it>Anopheles </it>belonging to three groups were identified: Hyrcanus Group - <it>Anopheles sinensis</it>, <it>Anopheles kleini</it>, <it>Anopheles belenrae</it>, <it>Anopheles pullus</it>, <it>Anopheles lesteri</it>, <it>Anopheles sineroides</it>; Barbirostris Group - <it>Anopheles koreicus</it>; and Lindesayi Group - <it>Anopheles lindesayi japonicus</it>. Only <it>An. sinensis </it>was collected from all habitats groups, while <it>An. kleini, An. pullus </it>and <it>An. sineroides </it>were sampled from all, except artificial containers. The highest number of <it>Anopheles </it>larvae was found in the rice paddies (34.8%), followed by irrigation ditches (23.4%), ponds (17.0%), and stream margins, inlets and pools (12.0%). <it>Anopheles sinensis </it>was the dominant species, followed by <it>An. kleini, An. pullus </it>and <it>An. sineroides</it>. The monthly abundance data of the <it>Anopheles </it>species from three locations (Munsan, Jinbo and Hayang) were compared against NDVI and NDVI anomalies.</p> <p>Conclusion</p> <p>The species composition of <it>Anopheles </it>larvae varied in different habitats at various locations. <it>Anopheles </it>populations fluctuated with the seasonal dynamics of vegetation for 2007. Multi-year data of mosquito collections are required to provide a better characterization of the abundance of these insects from year to year, which can potentially provide predictive capability of their population density based on remotely sensed ecological measurements.</p

A Genome-Wide Linkage and Association Scan Reveals Novel Loci for Hypertension and Blood Pressure Traits

Hypertension is caused by the interaction of environmental and genetic factors. The condition which is very common, with about 18% of the adult Hong Kong Chinese population and over 50% of older individuals affected, is responsible for considerable morbidity and mortality. To identify genes influencing hypertension and blood pressure, we conducted a combined linkage and association study using over 500,000 single nucleotide polymorphisms (SNPs) genotyped in 328 individuals comprising 111 hypertensive probands and their siblings. Using a family-based association test, we found an association with SNPs on chromosome 5q31.1 (rs6596140; P<9×10−8) for hypertension. One candidate gene, PDC, was replicated, with rs3817586 on 1q31.1 attaining P = 2.5×10−4 and 2.9×10−5 in the within-family tests for DBP and MAP, respectively. We also identified regions of significant linkage for systolic and diastolic blood pressure on chromosomes 2q22 and 5p13, respectively. Further family-based association analysis of the linkage peak on chromosome 5 yielded a significant association (rs1605685, P<7×10−5) for DBP. This is the first combined linkage and association study of hypertension and its related quantitative traits with Chinese ancestry. The associations reported here account for the action of common variants whereas the discovery of linkage regions may point to novel targets for rare variant screening

Identification of IGF1, SLC4A4, WWOX, and SFMBT1 as Hypertension Susceptibility Genes in Han Chinese with a Genome-Wide Gene-Based Association Study

Hypertension is a complex disorder with high prevalence rates all over the world. We conducted the first genome-wide gene-based association scan for hypertension in a Han Chinese population. By analyzing genome-wide single-nucleotide-polymorphism data of 400 matched pairs of young-onset hypertensive patients and normotensive controls genotyped with the Illumina HumanHap550-Duo BeadChip, 100 susceptibility genes for hypertension were identified and also validated with permutation tests. Seventeen of the 100 genes exhibited differential allelic and expression distributions between patient and control groups. These genes provided a good molecular signature for classifying hypertensive patients and normotensive controls. Among the 17 genes, IGF1, SLC4A4, WWOX, and SFMBT1 were not only identified by our gene-based association scan and gene expression analysis but were also replicated by a gene-based association analysis of the Hong Kong Hypertension Study. Moreover, cis-acting expression quantitative trait loci associated with the differentially expressed genes were found and linked to hypertension. IGF1, which encodes insulin-like growth factor 1, is associated with cardiovascular disorders, metabolic syndrome, decreased body weight/size, and changes of insulin levels in mice. SLC4A4, which encodes the electrogenic sodium bicarbonate cotransporter 1, is associated with decreased body weight/size and abnormal ion homeostasis in mice. WWOX, which encodes the WW domain-containing protein, is related to hypoglycemia and hyperphosphatemia. SFMBT1, which encodes the scm-like with four MBT domains protein 1, is a novel hypertension gene. GRB14, TMEM56 and KIAA1797 exhibited highly significant differential allelic and expressed distributions between hypertensive patients and normotensive controls. GRB14 was also found relevant to blood pressure in a previous genetic association study in East Asian populations. TMEM56 and KIAA1797 may be specific to Taiwanese populations, because they were not validated by the two replication studies. Identification of these genes enriches the collection of hypertension susceptibility genes, thereby shedding light on the etiology of hypertension in Han Chinese populations