Detection of multiple perturbations in multi-omics biological networks.

Cellular mechanism-of-action is of fundamental concern in many biological studies. It is of particular interest for identifying the cause of disease and learning the way in which treatments act against disease. However, pinpointing such mechanisms is difficult, due to the fact that small perturbations to the cell can have wide-ranging downstream effects. Given a snapshot of cellular activity, it can be challenging to tell where a disturbance originated. The presence of an ever-greater variety of high-throughput biological data offers an opportunity to examine cellular behavior from multiple angles, but also presents the statistical challenge of how to effectively analyze data from multiple sources. In this setting, we propose a method for mechanism-of-action inference by extending network filtering to multi-attribute data. We first estimate a joint Gaussian graphical model across multiple data types using penalized regression and filter for network effects. We then apply a set of likelihood ratio tests to identify the most likely site of the original perturbation. In addition, we propose a conditional testing procedure to allow for detection of multiple perturbations. We demonstrate this methodology on paired gene expression and methylation data from The Cancer Genome Atlas (TCGA).

Correction: Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

[This corrects the article DOI: 10.1371/journal.pgen.1006528.].

Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

The genetics of hemoglobin A2 regulation in sickle cell anemia.

Hemoglobin A2 , a tetramer of α- and δ-globin chains, comprises less than 3% of total hemoglobin in normal adults. In northern Europeans, single nucleotide polymorphisms (SNPs) in the HBS1L-MYB locus on chromosome 6q and the HBB cluster on chromosome 11p were associated with HbA2 levels. We examined the genetic basis of HbA2 variability in sickle cell anemia using genome-wide association studies. HbA2 levels were associated with SNPs in the HBS1L-MYB interval and SNPs in BCL11A. These effects are mediated by the association of these loci with γ-globin gene expression and fetal hemoglobin (HbF) levels. The association of polymorphisms downstream of the ß-globin gene (HBB) cluster on chromosome 11 with HbA2 was not mediated by HbF. In sickle cell anemia, levels of HbA2 appear to be modulated by trans-acting genes that affect HBG expression and perhaps also elements within the ß-globin gene cluster. HbA2 is expressed pancellularly and can inhibit HbS polymerization. It remains to be seen if genetic regulators of HbA2 can be exploited for therapeutic purposes.

Usefulness of postmarket studies to evaluate long-term safety of coronary eluting stents (from the ENDEAVOR and PROTECT Programs).

Differences in enrollment criteria and protocol requirements are believed to affect patient representation and outcomes from premarket and postmarket surveillance (PMS) trials. These differences have not been assessed in studies evaluating coronary stenting. We aimed to assess differences in clinical profile and long-term outcomes in patients enrolled into premarket versus PMS trials assessing the Endeavor zotarolimus-eluting stent (E-ZES). We pooled patient-level data for 2,132 and 4,357 E-ZES-treated subjects enrolled into the ENDEAVOR program (premarket) and Patient Related OuTcomes with Endeavor versus Cypher stenting Trial (PMS), respectively. Follow-up data were available through 3 years. Baseline characteristics and outcomes of patients enrolled in the 2 groups were compared. Propensity score-adjusted Cox proportional hazards models were used to assess the effect of differences in baseline characteristics. We also adjusted for protocol-mandated repeat angiography to account for differences in follow-up requirements. Despite significant differences in baseline characteristics, the unadjusted 3-year rates of major adverse cardiac events, major adverse cardiac and cerebrovascular events, and target vessel failure were similar (premarket vs PMS: 11.9% vs 12.7%, p = 0.369; 12.7% vs 13.9%, p = 0.191; and 13.8% vs 13.4%, p = 0.667, respectively). However, PMS trials had significantly higher rates of myocardial infarctions (p = 0.005) and definite or probable stent thrombosis (p = 0.016). After propensity score adjustment, myocardial infarction rates remained significantly different (hazard ratio 0.53, 95% confidence interval 0.30 to 0.91). To conclude, premarket and PMS trials assessing E-ZES implantation enrolled different patients. PMS trials were shown to be essential for the detection of safety signals.

Sickle cell disease in Saudi Arabia: the phenotype in adults with the Arab-Indian haplotype is not benign.

Sickle cell disease (SCD) in Saudi patients from the Eastern Province is associated with the Arab-Indian (AI) HBB (ß-globin gene) haplotype. The phenotype of AI SCD in children was described as benign and was attributed to their high fetal haemoglobin (HbF). We conducted a hospital-based study to assess the pattern of SCD complications in adults. A total of 104 patients with average age of 27 years were enrolled. Ninety-six per cent of these patients reported history of painful crisis; 47% had at least one episode of acute chest syndrome, however, only 15% had two or more episodes; symptomatic osteonecrosis was reported in 18%; priapism in 17%; overt stroke in 6%; none had leg ulcers. The majority of patients had persistent splenomegaly and 66% had gallstones. Half of the patients co-inherited α-thalassaemia and about one-third had glucose-6-phosphate dehydrogenase deficiency. Higher HbF correlated with higher rate of splenic sequestration but not with other phenotypes. The phenotype of adult patients with AI SCD is not benign despite their relatively high HbF level. This is probably due to the continued decline in HbF level in adults and the heterocellular and variable distribution of HbF amongst F-cells.

Genome-wide association of body fat distribution in African ancestry populations suggests new loci.

Central obesity, measured by waist circumference (WC) or waist-hip ratio (WHR), is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS) of fat distribution among those of predominantly African ancestry (AA). We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1). Overall, 25 SNPs with single genomic control (GC)-corrected p-values<5.0 × 10(-6) were followed-up (stage 2) in AA with WC and with WHR. Additionally, we interrogated genomic regions of previously identified European ancestry (EA) WHR loci among AA. In joint analysis of association results including both Stage 1 and 2 cohorts, 2 SNPs demonstrated association, rs2075064 at LHX2, p = 2.24×10(-8) for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48×10(-8) for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5 × 10(-8); RREB1: p = 5.7 × 10(-8)). Six of fourteen previously reported loci for waist in EA populations were significant (p<0.05 divided by the number of independent SNPs within the region) in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN). Further, we observed associations with metabolic traits: rs13389219 at GRB14 associated with HDL-cholesterol, triglycerides, and fasting insulin, and rs13060013 at ADAMTS9 with HDL-cholesterol and fasting insulin. Finally, we observed nominal evidence for sexual dimorphism, with stronger results in AA women at the GRB14 locus (p for interaction = 0.02). In conclusion, we identified two suggestive loci associated with fat distribution in AA populations in addition to confirming 6 loci previously identified in populations of EA. These findings reinforce the concept that there are fat distribution loci that are independent of generalized adiposity.

Interlaboratory study on differential analysis of protein glycosylation by mass spectrometry: the ABRF glycoprotein research multi-institutional study 2012.

One of the principal goals of glycoprotein research is to correlate glycan structure and function. Such correlation is necessary in order for one to understand the mechanisms whereby glycoprotein structure elaborates the functions of myriad proteins. The accurate comparison of glycoforms and quantification of glycosites are essential steps in this direction. Mass spectrometry has emerged as a powerful analytical technique in the field of glycoprotein characterization. Its sensitivity, high dynamic range, and mass accuracy provide both quantitative and sequence/structural information. As part of the 2012 ABRF Glycoprotein Research Group study, we explored the use of mass spectrometry and ancillary methodologies to characterize the glycoforms of two sources of human prostate specific antigen (PSA). PSA is used as a tumor marker for prostate cancer, with increasing blood levels used to distinguish between normal and cancer states. The glycans on PSA are believed to be biantennary N-linked, and it has been observed that prostate cancer tissues and cell lines contain more antennae than their benign counterparts. Thus, the ability to quantify differences in glycosylation associated with cancer has the potential to positively impact the use of PSA as a biomarker. We studied standard peptide-based proteomics/glycomics methodologies, including LC-MS/MS for peptide/glycopeptide sequencing and label-free approaches for differential quantification. We performed an interlaboratory study to determine the ability of different laboratories to correctly characterize the differences between glycoforms from two different sources using mass spectrometry methods. We used clustering analysis and ancillary statistical data treatment on the data sets submitted by participating laboratories to obtain a consensus of the glycoforms and abundances. The results demonstrate the relative strengths and weaknesses of top-down glycoproteomics, bottom-up glycoproteomics, and glycomics methods.