Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics

There is a growing attention toward personalized medicine. This is led by a fundamental shift from the ‘one size fits all’ paradigm for treatment of patients with conditions or predisposition to diseases, to one that embraces novel approaches, such as tailored target therapies, to achieve the best possible outcomes. Driven by these, several national and international genome projects have been initiated to reap the benefits of personalized medicine. Exome and targeted sequencing provide a balance between cost and benefit, in contrast to whole genome sequencing (WGS). Whole exome sequencing (WES) targets approximately 3% of the whole genome, which is the basis for protein-coding genes. Nonetheless, it has the characteristics of big data in large deployment. Herein, the application of WES and its relevance in advancing personalized medicine is reviewed. WES is mapped to Big Data “10 Vs” and the resulting challenges discussed. Application of existing biological databases and bioinformatics tools to address the bottleneck in data processing and analysis are presented, including the need for new generation big data analytics for the multi-omics challenges of personalized medicine. This includes the incorporation of artificial intelligence (AI) in the clinical utility landscape of genomic information, and future consideration to create a new frontier toward advancing the field of personalized medicine

Observation of an Excited Bc+ State

Using pp collision data corresponding to an integrated luminosity of 8.5 fb-1 recorded by the LHCb experiment at center-of-mass energies of s=7, 8, and 13 TeV, the observation of an excited Bc+ state in the Bc+π+π- invariant-mass spectrum is reported. The observed peak has a mass of 6841.2±0.6(stat)±0.1(syst)±0.8(Bc+) MeV/c2, where the last uncertainty is due to the limited knowledge of the Bc+ mass. It is consistent with expectations of the Bc∗(2S31)+ state reconstructed without the low-energy photon from the Bc∗(1S31)+→Bc+γ decay following Bc∗(2S31)+→Bc∗(1S31)+π+π-. A second state is seen with a global (local) statistical significance of 2.2σ (3.2σ) and a mass of 6872.1±1.3(stat)±0.1(syst)±0.8(Bc+) MeV/c2, and is consistent with the Bc(2S10)+ state. These mass measurements are the most precise to date

The gut microbiota: a major player in the toxicity of environmental pollutants?

Exposure to environmental chemicals has been linked to various health disorders, including obesity, type 2 diabetes, cancer and dysregulation of the immune and reproductive systems, whereas the gastrointestinal microbiota critically contributes to a variety of host metabolic and immune functions. We aimed to evaluate the bidirectional relationship between gut bacteria and environmental pollutants and to assess the toxicological relevance of the bacteria–xenobiotic interplay for the host. We examined studies using isolated bacteria, faecal or caecal suspensions—germ-free or antibiotic-treated animals—as well as animals reassociated with a microbiota exposed to environmental chemicals. The literature indicates that gut microbes have an extensive capacity to metabolise environmental chemicals that can be classified in five core enzymatic families (azoreductases, nitroreductases, β-glucuronidases, sulfatases and β-lyases) unequivocally involved in the metabolism of >30 environmental contaminants. There is clear evidence that bacteria-dependent metabolism of pollutants modulates the toxicity for the host. Conversely, environmental contaminants from various chemical families have been shown to alter the composition and/or the metabolic activity of the gastrointestinal bacteria, which may be an important factor contributing to shape an individual’s microbiotype. The physiological consequences of these alterations have not been studied in details but pollutant-induced alterations of the gut bacteria are likely to contribute to their toxicity. In conclusion, there is a body of evidence suggesting that gut microbiota are a major, yet underestimated element that must be considered to fully evaluate the toxicity of environmental contaminants

Cause of Death and Predictors of All-Cause Mortality in Anticoagulated Patients With Nonvalvular Atrial Fibrillation : Data From ROCKET AF

M. Kaste on työryhmän ROCKET AF Steering Comm jäsen.Background-Atrial fibrillation is associated with higher mortality. Identification of causes of death and contemporary risk factors for all-cause mortality may guide interventions. Methods and Results-In the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) study, patients with nonvalvular atrial fibrillation were randomized to rivaroxaban or dose-adjusted warfarin. Cox proportional hazards regression with backward elimination identified factors at randomization that were independently associated with all-cause mortality in the 14 171 participants in the intention-to-treat population. The median age was 73 years, and the mean CHADS(2) score was 3.5. Over 1.9 years of median follow-up, 1214 (8.6%) patients died. Kaplan-Meier mortality rates were 4.2% at 1 year and 8.9% at 2 years. The majority of classified deaths (1081) were cardiovascular (72%), whereas only 6% were nonhemorrhagic stroke or systemic embolism. No significant difference in all-cause mortality was observed between the rivaroxaban and warfarin arms (P=0.15). Heart failure (hazard ratio 1.51, 95% CI 1.33-1.70, P= 75 years (hazard ratio 1.69, 95% CI 1.51-1.90, P Conclusions-In a large population of patients anticoagulated for nonvalvular atrial fibrillation, approximate to 7 in 10 deaths were cardiovascular, whereasPeer reviewe

Observation of CP Violation in Charm Decays

A search for charge-parity (CP) violation in D-0 -> K-K+ and D-0 -> pi(-)pi(+) decays is reported, using pp collision data corresponding to an integrated luminosity of 5.9 fb(-1) collected at a center-of-mass energy of 13 TeV with the LHCb detector. The flavor of the charm meson is inferred from the charge of the pion in D* (2010)(+) -> D-0 pi(+) decays or from the charge of the muon in (B) over bar -> D-0 mu(-)(nu) over bar X-mu decays. The difference between the CP asymmetries in D-0 -> K-K+ and D-0 -> pi(-)pi(+) decays is measured to be Delta A(CP) = [-18.2 +/- 3.2(stat) +/- 0.9(syst)] x 10(-4) for pi-tagged and Delta A(CP) = [-9 +/- 8(stat) +/- 5(syst)] x 10(-4) for mu-tagged D-0 mesons. Combining these with previous LHCb results leads to Delta A(CP) = (-15.4 +/- 2.9) x 10(-4), where the uncertainty includes both statistical and systematic contributions. The measured value differs from zero by more than 5 standard deviations. This is the first observation of CP violation in the decay of charm hadrons

Observation of an Excited Bc⁺ state

Using p p collision data corresponding to an integrated luminosity of 8.5     fb − 1 recorded by the LHCb experiment at center-of-mass energies of √ s = 7 , 8, and 13 TeV, the observation of an excited B + c state in the B + c π + π − invariant-mass spectrum is reported. The observed peak has a mass of 6841.2 ± 0.6 ( stat ) ± 0.1 ( syst ) ± 0.8 ( B + c )     MeV / c 2 , where the last uncertainty is due to the limited knowledge of the B + c mass. It is consistent with expectations of the B ∗ c ( 2 3 S 1 ) + state reconstructed without the low-energy photon from the B ∗ c ( 1 3 S 1 ) + → B + c γ decay following B ∗ c ( 2 3 S 1 ) + → B ∗ c ( 1 3 S 1 ) + π + π − . A second state is seen with a global (local) statistical significance of 2.2 σ ( 3.2 σ ) and a mass of 6872.1 ± 1.3 ( stat ) ± 0.1 ( syst ) ± 0.8 ( B + c )     MeV / c 2 , and is consistent with the B c ( 2 1 S 0 ) + state. These mass measurements are the most precise to date

Observation of a narrow pentaquark state, P-c(4312)(+), and of the two-peak structure of the P-c(4450)(+)

A narrow pentaquark state, P-c(4312)(+), decaying to J/psi p, is discovered with a statistical significance of 7.3 sigma in a data sample of Lambda(0)(b) -> J/psi pK(-) decays, which is an order of magnitude larger than that previously analyzed by the LHCb Collaboration. The P-c(4450)(+) pentaquark structure formerly reported by LHCb is confirmed and observed to consist of two narrow overlapping peaks, P-c(4440)(+) and P-c(4457)(+), where the statistical significance of this two-peak interpretation is 5.4 sigma. The proximity of the Sigma(+)(c)(D) over bar (0) and Sigma(+)(c)(D) over bar (*0) thresholds to the observed narrow peaks suggests that they play an important role in the dynamics of these states

Common variants in P2RY11 are associated with narcolepsy.

Growing evidence supports the hypothesis that narcolepsy with cataplexy is an autoimmune disease. We here report genome-wide association analyses for narcolepsy with replication and fine mapping across three ethnic groups (3,406 individuals of European ancestry, 2,414 Asians and 302 African Americans). We identify a SNP in the 3' untranslated region of P2RY11, the purinergic receptor subtype P2Y₁₁ gene, which is associated with narcolepsy (rs2305795, combined P = 6.1 × 10⁻¹⁰, odds ratio = 1.28, 95% CI 1.19-1.39, n = 5689). The disease-associated allele is correlated with reduced expression of P2RY11 in CD8(+) T lymphocytes (339% reduced, P = 0.003) and natural killer (NK) cells (P = 0.031), but not in other peripheral blood mononuclear cell types. The low expression variant is also associated with reduced P2RY11-mediated resistance to ATP-induced cell death in T lymphocytes (P = 0.0007) and natural killer cells (P = 0.001). These results identify P2RY11 as an important regulator of immune-cell survival, with possible implications in narcolepsy and other autoimmune diseases.journal articleresearch support, n.i.h., extramuralresearch support, non-u.s. gov'tresearch support, u.s. gov't, p.h.s.2011 Jan2010 12 19importedErratum in : Nat Genet. 2011 Oct;43(10):1040

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery