Leveraging Polygenic Functional Enrichment to Improve GWAS Power.

Functional genomics data has the potential to increase GWAS power by identifying SNPs that have a higher prior probability of association. Here, we introduce a method that leverages polygenic functional enrichment to incorporate coding, conserved, regulatory, and LD-related genomic annotations into association analyses. We show via simulations with real genotypes that the method, functionally informed novel discovery of risk loci (FINDOR), correctly controls the false-positive rate at null loci and attains a 9%-38% increase in the number of independent associations detected at causal loci, depending on trait polygenicity and sample size. We applied FINDOR to 27 independent complex traits and diseases from the interim UK Biobank release (average N = 130K). Averaged across traits, we attained a 13% increase in genome-wide significant loci detected (including a 20% increase for disease traits) compared to unweighted raw p values that do not use functional data. We replicated the additional loci in independent UK Biobank and non-UK Biobank data, yielding a highly statistically significant replication slope (0.66-0.69) in each case. Finally, we applied FINDOR to the full UK Biobank release (average N = 416K), attaining smaller relative improvements (consistent with simulations) but larger absolute improvements, detecting an additional 583 GWAS loci. In conclusion, leveraging functional enrichment using our method robustly increases GWAS power.

Targeting Akt/NF-κB/p53 Pathway and Apoptosis Inducing Potential of 1,2-Benzenedicarboxylic Acid, Bis (2-Methyl Propyl) Ester Isolated from Onosma bracteata Wall. against Human Osteosarcoma (MG-63) Cells.

Onosma bracteata Wall. is an important medicinal and immunity-enhancing herbs. This plant is commonly used in the preparation of traditional Ayurvedic drugs to treat numerous diseases. Inspired by the medicinal properties of this plant, the present study aimed to investigate the antiproliferative potential and the primary molecular mechanisms of the apoptotic induction against human osteosarcoma (MG-63) cells. Among all the fractions isolated from O. bracteata, ethyl acetate fraction (Obea) showed good antioxidant activity in superoxide radical scavenging assay and lipid peroxidation assay with an EC50 value of 95.12 and 80.67 µg/mL, respectively. Silica gel column chromatography of ethyl acetate (Obea) fraction of O. bracteata yielded a pure compound, which was characterized by NMR, FTIR, and HR-MS analysis and was identified as 1,2-benzene dicarboxylic acid, bis (2-methyl propyl) ester (BDCe fraction). BDCe fraction was evaluated for the antiproliferative potential against human osteosarcoma MG-63, human neuroblastoma IMR-32, and human lung carcinoma A549 cell lines by MTT assay and exhibited GI50 values of 37.53 µM, 56.05 µM, and 47.12 µM, respectively. In MG-63 cells, the BDCe fraction increased the level of ROS and simultaneously decreased the mitochondria membrane potential (MMP) potential by arresting cells at the G0/G1 phase, suggesting the initiation of apoptosis. Western blotting analysis revealed the upregulation of p53, caspase3, and caspase9 while the expressions of p-NF-κB, p-Akt and Bcl-xl were decreased. RT-qPCR studies also showed upregulation in the expression of p53 and caspase3 and downregulation in the expression of CDK2, Bcl-2 and Cyclin E genes. Molecular docking analysis displayed the interaction between BDCe fraction with p53 (-151.13 kcal/mol) and CDK1 (-133.96 kcal/mol). The results of the present work suggest that the BDCe fraction has chemopreventive properties against osteosarcoma (MG-63) cells through the induction of cell cycle arrest and apoptosis via Akt/NF-κB/p53 pathways. This study contributes to the understanding of the utilization of BDCe fraction in osteosarcoma treatment.

Functional Architectures of Local and Distal Regulation of Gene Expression in Multiple Human Tissues.

Genetic variants that modulate gene expression levels play an important role in the etiology of human diseases and complex traits. Although large-scale eQTL mapping studies routinely identify many local eQTLs, the molecular mechanisms by which genetic variants regulate expression remain unclear, particularly for distal eQTLs, which these studies are not well powered to detect. Here, we leveraged all variants (not just those that pass stringent significance thresholds) to analyze the functional architecture of local and distal regulation of gene expression in 15 human tissues by employing an extension of stratified LD-score regression that produces robust results in simulations. The top enriched functional categories in local regulation of peripheral-blood gene expression included coding regions (11.41×), conserved regions (4.67×), and four histone marks (p < 5 × 10-5 for all enrichments); local enrichments were similar across the 15 tissues. We also observed substantial enrichments for distal regulation of peripheral-blood gene expression: coding regions (4.47×), conserved regions (4.51×), and two histone marks (p < 3 × 10-7 for all enrichments). Analyses of the genetic correlation of gene expression across tissues confirmed that local regulation of gene expression is largely shared across tissues but that distal regulation is highly tissue specific. Our results elucidate the functional components of the genetic architecture of local and distal regulation of gene expression.

Correction to: Synthesis, spectroscopic characterization and in vitro anticancer activity of new platinum(II) complexes with some thione ligands in the presence of triethylphosphine.

Due to an unfortunate turn of events, the main affiliation of Dr. Saleh Altuwaijri was omitted from the above mentioned three articles. The complete affiliations are published below and should be treated as definitive.

Fast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia.

Searching for genetic variants with unusual differentiation between subpopulations is an established approach for identifying signals of natural selection. However, existing methods generally require discrete subpopulations. We introduce a method that infers selection using principal components (PCs) by identifying variants whose differentiation along top PCs is significantly greater than the null distribution of genetic drift. To enable the application of this method to large datasets, we developed the FastPCA software, which employs recent advances in random matrix theory to accurately approximate top PCs while reducing time and memory cost from quadratic to linear in the number of individuals, a computational improvement of many orders of magnitude. We apply FastPCA to a cohort of 54,734 European Americans, identifying 5 distinct subpopulations spanning the top 4 PCs. Using the PC-based test for natural selection, we replicate previously known selected loci and identify three new genome-wide significant signals of selection, including selection in Europeans at ADH1B. The coding variant rs1229984(∗)T has previously been associated to a decreased risk of alcoholism and shown to be under selection in East Asians; we show that it is a rare example of independent evolution on two continents. We also detect selection signals at IGFBP3 and IGH, which have also previously been associated to human disease.

Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores.

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

Genome-wide scan of 29,141 African Americans finds no evidence of directional selection since admixture.

The extent of recent selection in admixed populations is currently an unresolved question. We scanned the genomes of 29,141 African Americans and failed to find any genome-wide-significant deviations in local ancestry, indicating no evidence of selection influencing ancestry after admixture. A recent analysis of data from 1,890 African Americans reported that there was evidence of selection in African Americans after their ancestors left Africa, both before and after admixture. Selection after admixture was reported on the basis of deviations in local ancestry, and selection before admixture was reported on the basis of allele-frequency differences between African Americans and African populations. The local-ancestry deviations reported by the previous study did not replicate in our very large sample, and we show that such deviations were expected purely by chance, given the number of hypotheses tested. We further show that the previous study's conclusion of selection in African Americans before admixture is also subject to doubt. This is because the FST statistics they used were inflated and because true signals of unusual allele-frequency differences between African Americans and African populations would be best explained by selection that occurred in Africa prior to migration to the Americas.

Synthesis, spectroscopic characterization and in vitro anticancer activity of new platinum(II) complexes with some thione ligands in the presence of triethylphosphine.

Seven new platinum(II) complexes (1-7) of triethylphosphine (Et3P) and thiones (L) with general formula, cis-[Pt(Et3P)2(L)2]Cl2 were prepared and characterized by elemental analysis, FTIR and NMR (1H, 13C & 31P) measurements. The analytical and spectroscopic data suggested the formation of the desired complexes. The complexes were tested for in vitro cytotoxicity against four cell lines: Hela (human cervical adenocarcinoma), MCF-7 (human breast carcinoma), A549 (human lung carcinoma), and HTC15 (human colon carcinoma). The anticancer activity values of compounds 1-6 are much better than cisplatin and carboplatin as indicated by their IC50 values.

Estimating and interpreting FST: the impact of rare variants.

In a pair of seminal papers, Sewall Wright and Gustave Malécot introduced FST as a measure of structure in natural populations. In the decades that followed, a number of papers provided differing definitions, estimation methods, and interpretations beyond Wright's. While this diversity in methods has enabled many studies in genetics, it has also introduced confusion regarding how to estimate FST from available data. Considering this confusion, wide variation in published estimates of FST for pairs of HapMap populations is a cause for concern. These estimates changed-in some cases more than twofold-when comparing estimates from genotyping arrays to those from sequence data. Indeed, changes in FST from sequencing data might be expected due to population genetic factors affecting rare variants. While rare variants do influence the result, we show that this is largely through differences in estimation methods. Correcting for this yields estimates of FST that are much more concordant between sequence and genotype data. These differences relate to three specific issues: (1) estimating FST for a single SNP, (2) combining estimates of FST across multiple SNPs, and (3) selecting the set of SNPs used in the computation. Changes in each of these aspects of estimation may result in FST estimates that are highly divergent from one another. Here, we clarify these issues and propose solutions.

Using extended genealogy to estimate components of heritability for 23 quantitative and dichotomous traits.

Important knowledge about the determinants of complex human phenotypes can be obtained from the estimation of heritability, the fraction of phenotypic variation in a population that is determined by genetic factors. Here, we make use of extensive phenotype data in Iceland, long-range phased genotypes, and a population-wide genealogical database to examine the heritability of 11 quantitative and 12 dichotomous phenotypes in a sample of 38,167 individuals. Most previous estimates of heritability are derived from family-based approaches such as twin studies, which may be biased upwards by epistatic interactions or shared environment. Our estimates of heritability, based on both closely and distantly related pairs of individuals, are significantly lower than those from previous studies. We examine phenotypic correlations across a range of relationships, from siblings to first cousins, and find that the excess phenotypic correlation in these related individuals is predominantly due to shared environment as opposed to dominance or epistasis. We also develop a new method to jointly estimate narrow-sense heritability and the heritability explained by genotyped SNPs. Unlike existing methods, this approach permits the use of information from both closely and distantly related pairs of individuals, thereby reducing the variance of estimates of heritability explained by genotyped SNPs while preventing upward bias. Our results show that common SNPs explain a larger proportion of the heritability than previously thought, with SNPs present on Illumina 300K genotyping arrays explaining more than half of the heritability for the 23 phenotypes examined in this study. Much of the remaining heritability is likely to be due to rare alleles that are not captured by standard genotyping arrays.

Quantifying missing heritability at known GWAS loci.

Recent work has shown that much of the missing heritability of complex traits can be resolved by estimates of heritability explained by all genotyped SNPs. However, it is currently unknown how much heritability is missing due to poor tagging or additional causal variants at known GWAS loci. Here, we use variance components to quantify the heritability explained by all SNPs at known GWAS loci in nine diseases from WTCCC1 and WTCCC2. After accounting for expectation, we observed all SNPs at known GWAS loci to explain 1.29 x more heritability than GWAS-associated SNPs on average (P=3.3 x 10⁻5). For some diseases, this increase was individually significant: 2.07 x for Multiple Sclerosis (MS) (P=6.5 x 10⁻9) and 1.48 x for Crohn's Disease (CD) (P = 1.3 x 10⁻³); all analyses of autoimmune diseases excluded the well-studied MHC region. Additionally, we found that GWAS loci from other related traits also explained significant heritability. The union of all autoimmune disease loci explained 7.15 x more MS heritability than known MS SNPs (P < 1.0 x 10⁻¹6 and 2.20 x more CD heritability than known CD SNPs (P = 6.1 x 10⁻9), with an analogous increase for all autoimmune diseases analyzed. We also observed significant increases in an analysis of > 20,000 Rheumatoid Arthritis (RA) samples typed on ImmunoChip, with 2.37 x more heritability from all SNPs at GWAS loci (P = 2.3 x 10⁻6) and 5.33 x more heritability from all autoimmune disease loci (P < 1 x 10⁻¹6 compared to known RA SNPs (including those identified in this cohort). Our methods adjust for LD between SNPs, which can bias standard estimates of heritability from SNPs even if all causal variants are typed. By comparing adjusted estimates, we hypothesize that the genome-wide distribution of causal variants is enriched for low-frequency alleles, but that causal variants at known GWAS loci are skewed towards common alleles. These findings have important ramifications for fine-mapping study design and our understanding of complex disease architecture.

SR-2P vaginal microbicide gel provides protection against herpes simplex virus 2 when administered as a combined prophylactic and postexposure therapeutic.

Previously, we demonstrated that a single prophylactic dose of SR-2P, a novel dual-component microbicide gel comprising acyclovir and tenofovir, led to a modest increase in mouse survival following a lethal challenge of herpes simplex virus 2 (HSV-2). Here, we show that a dose of SR-2P administered 24 h prior to infection provides some protection against the virus, but to a lesser degree than SR-2P administered either once a day for 2 days or 1 h prior to infection. None of the prophylactic doses blocked infection by the virus, and all resulted in 80 to 100% lethality. However, given that a prophylactic dose still provided a significant reduction in overall clinical score, reduced rate of body weight loss, and increased median survival of the mice, we examined whether a repetitive dose regimen (postinfection) in addition to the prophylactic dose could prevent death and reduce the levels of virus in mice. Nearly all (9 of 10 in each group) of the mice that received SR-2P for 2 days prior to infection or that received SR-2P 1 h prior to infection and were administered SR-2P once a day for 10 days after infection showed no clinical symptoms of infection and no viral loads in vaginal swabs and survived for 28 days postinfection. Conversely, mice receiving no treatment or an identical vehicle treatment demonstrated advanced clinical signs and did not survive past day 9 postinfection. We conclude that SR-2P is an effective anti-HSV-2 agent in mice.

Fast and accurate imputation of summary statistics enhances evidence of functional enrichment.

MOTIVATION: Imputation using external reference panels (e.g. 1000 Genomes) is a widely used approach for increasing power in genome-wide association studies and meta-analysis. Existing hidden Markov models (HMM)-based imputation approaches require individual-level genotypes. Here, we develop a new method for Gaussian imputation from summary association statistics, a type of data that is becoming widely available. RESULTS: In simulations using 1000 Genomes (1000G) data, this method recovers 84% (54%) of the effective sample size for common (>5%) and low-frequency (1-5%) variants [increasing to 87% (60%) when summary linkage disequilibrium information is available from target samples] versus the gold standard of 89% (67%) for HMM-based imputation, which cannot be applied to summary statistics. Our approach accounts for the limited sample size of the reference panel, a crucial step to eliminate false-positive associations, and it is computationally very fast. As an empirical demonstration, we apply our method to seven case-control phenotypes from the Wellcome Trust Case Control Consortium (WTCCC) data and a study of height in the British 1958 birth cohort (1958BC). Gaussian imputation from summary statistics recovers 95% (105%) of the effective sample size (as quantified by the ratio of [Formula: see text] association statistics) compared with HMM-based imputation from individual-level genotypes at the 227 (176) published single nucleotide polymorphisms (SNPs) in the WTCCC (1958BC height) data. In addition, for publicly available summary statistics from large meta-analyses of four lipid traits, we publicly release imputed summary statistics at 1000G SNPs, which could not have been obtained using previously published methods, and demonstrate their accuracy by masking subsets of the data. We show that 1000G imputation using our approach increases the magnitude and statistical evidence of enrichment at genic versus non-genic loci for these traits, as compared with an analysis without 1000G imputation. Thus, imputation of summary statistics will be a valuable tool in future functional enrichment analyses. AVAILABILITY AND IMPLEMENTATION: Publicly available software package available at http://bogdan.bioinformatics.ucla.edu/software/. CONTACT: bpasaniuc@mednet.ucla.edu or aprice@hsph.harvard.edu SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.

Genome-wide comparison of African-ancestry populations from CARe and other cohorts reveals signals of natural selection.

The study of recent natural selection in human populations has important applications to human history and medicine. Positive natural selection drives the increase in beneficial alleles and plays a role in explaining diversity across human populations. By discovering traits subject to positive selection, we can better understand the population level response to environmental pressures including infectious disease. Our study examines unusual population differentiation between three large data sets to detect natural selection. The populations examined, African Americans, Nigerians, and Gambians, are genetically close to one another (F(ST) < 0.01 for all pairs), allowing us to detect selection even with moderate changes in allele frequency. We also develop a tree-based method to pinpoint the population in which selection occurred, incorporating information across populations. Our genome-wide significant results corroborate loci previously reported to be under selection in Africans including HBB and CD36. At the HLA locus on chromosome 6, results suggest the existence of multiple, independent targets of population-specific selective pressure. In addition, we report a genome-wide significant (p = 1.36 × 10(-11)) signal of selection in the prostate stem cell antigen (PSCA) gene. The most significantly differentiated marker in our analysis, rs2920283, is highly differentiated in both Africa and East Asia and has prior genome-wide significant associations to bladder and gastric cancers.

Primary tuberculosis of the breast manifested as abscess: a rare case report.

Primary breast tuberculosis is a rare entity. We are reporting a case of primary breast tuberculosis, which presented as breast abscess. On histopathology, it was diagnosed as breast tuberculosis. Aspiration cytology was not done due breast abscess. Patient was put on anti-tubercular drugs. In follow up, after 3 months patient condition was improved.

The role of the medical emergency team in end-of-life care: a multicenter, prospective, observational study.

OBJECTIVE: To investigate the role of medical emergency teams in end-of-life care planning. DESIGN: One month prospective audit of medical emergency team calls. SETTING: Seven university-affiliated hospitals in Australia, Canada, and Sweden. PATIENTS: Five hundred eighteen patients who received a medical emergency team call over 1 month. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: There were 652 medical emergency team calls in 518 patients, with multiple calls in 99 (19.1%) patients. There were 161 (31.1%) patients with limitations of medical therapy during the study period. The limitation of medical therapy was instituted in 105 (20.3%) and 56 (10.8%) patients before and after the medical emergency team call, respectively. In 78 patients who died with a limitation of medical therapy in place, the last medical emergency team review was on the day of death in 29.5% of patients, and within 2 days in another 28.2%.Compared with patients who did not have a limitation of medical therapy, those with a limitation of medical therapy were older (80 vs. 66 yrs; p < .001), less likely to be male (44.1% vs. 55.7%; p = .014), more likely to be medical admissions (70.8% vs. 51.3%; p < .001), and less likely to be admitted from home (74.5% vs. 92.2%, p < .001). In addition, those with a limitation of medical therapy were less likely to be discharged home (22.4% vs. 63.6%; p < .001) and more likely to die in hospital (48.4% vs. 12.3%; p < .001). There was a trend for increased likelihood of calls associated with limitations of medical therapy to occur out of hours (51.0% vs. 43.8%, p = .089). CONCLUSIONS: Issues around end-of-life care and limitations of medical therapy arose in approximately one-third of calls, suggesting a mismatch between patient needs for end-of-life care and resources at participating hospitals. These calls frequently occur in elderly medical patients and out of hours. Many such patients do not return home, and half die in hospital. There is a need for improved advanced care planning in our hospitals, and to confirm our findings in other organizations.

A covering method for detecting genetic associations between rare variants and common phenotypes.

Genome wide association (GWA) studies, which test for association between common genetic markers and a disease phenotype, have shown varying degrees of success. While many factors could potentially confound GWA studies, we focus on the possibility that multiple, rare variants (RVs) may act in concert to influence disease etiology. Here, we describe an algorithm for RV analysis, RareCover. The algorithm combines a disparate collection of RVs with low effect and modest penetrance. Further, it does not require the rare variants be adjacent in location. Extensive simulations over a range of assumed penetrance and population attributable risk (PAR) values illustrate the power of our approach over other published methods, including the collapsing and weighted-collapsing strategies. To showcase the method, we apply RareCover to re-sequencing data from a cohort of 289 individuals at the extremes of Body Mass Index distribution (NCT00263042). Individual samples were re-sequenced at two genes, FAAH and MGLL, known to be involved in endocannabinoid metabolism (187Kbp for 148 obese and 150 controls). The RareCover analysis identifies exactly one significantly associated region in each gene, each about 5 Kbp in the upstream regulatory regions. The data suggests that the RVs help disrupt the expression of the two genes, leading to lowered metabolism of the corresponding cannabinoids. Overall, our results point to the power of including RVs in measuring genetic associations.

Neuroprotective effects of hydro-alcoholic extract of Eclipta alba against 1-methyl-4-phenylpyridinium-induced in vitro and in vivo models of Parkinson's disease.

Pathogenesis of Parkinson's disease (PD) specifically involves the degeneration of dopaminergic neurons in the substantia nigra region, which mainly begun with the overwhelmed oxidative stress and neuroinflammation. Considering the antioxidant and other pharmacological properties, Eclipta alba needs to be exploited for its possible neuroprotective efficacy against PD and other neurological disorders. Therefore, the current study was conducted to exemplify the remedial effects of hydro-alcoholic extract of E. alba (EA-MEx) against MPP+-elicited in vitro and in vivo PD models. SH-SY5Y, a neuroblastoma cell culture and male Wistar rats were used to impersonate the hallmarks of PD. Qualitative and quantitative analyses of EA-MEx revealed the presence of quercetin, ellagic acid, catechin, kaempferol, and epicatechin at varying concentrations. EA-MEx was found to deliver considerable protection against MPP+-induced oxidative damages in SH-SY5Y cells. Furthermore, in vivo study also supported the neuroprotective efficacy of EA-MEx, with significant mitigation of behavioral deficits induced by intrastriatal injection of MPP+. Furthermore, the disturbed levels of cellular antioxidant machinery have been significantly improved with the pre-treatment of EA-MEx. Mechanistically, the expression of α-synuclein, tyrosine hydroxylase, and mortalin were also found to be improved with the prior treatment of EA-MEx. Hence, the study suggests Eclipta alba as a suitable candidate for the development of better neuropathological therapeutics.

Remote FEV1 Monitoring in Asthma Patients: A Pilot Study.

Forced expiratory volume in one second (FEV1 ) is a critical parameter for the assessment of lung function for both clinical care and research in patients with asthma. While asthma is defined by variable airflow obstruction, FEV1 is typically assessed during clinic visits. Mobile spirometry (mSpirometry) allows more frequent measurements of FEV1 , resulting in a more continuous assessment of lung function over time and its variability. Twelve patients with moderate asthma were recruited in a single-center study and were instructed to perform pulmonary function tests at home twice daily for 28 days and weekly in the clinic. Daily and mean subject compliances were summarized. The agreement between clinic and mobile FEV1 was assessed using correlation and Bland-Altman analyses. The test-retest reliability for clinic and mSpirometry was assessed by interclass correlation coefficient (ICC). Simulation was conducted to explore if mSpirometry could improve statistical power over clinic counterparts. The mean subject compliance with mSpirometry was 70% for twice-daily and 85% for at least once-daily. The mSpirometry FEV1 were highly correlated and agreed with clinic ones from the same morning (r = 0.993) and the same afternoon (r = 0.988) with smaller mean difference for the afternoon (0.0019 L) than morning (0.0126 L) measurements. The test-retest reliability of mobile (ICC = 0.932) and clinic (ICC = 0.942) spirometry were comparable. Our simulation analysis indicated greater power using dense mSpirometry than sparse clinic measurements. Overall, we have demonstrated good compliance for repeated at-home mSpirometry, high agreement and comparable test-retest reliability with clinic counterparts, greater statistical power, suggesting a potential for use in asthma clinical research.