Enhanced interpretation of newborn screening results without analyte cutoff values

A collaboration among 157 newborn screening programs in 47 countries has lead to the creation of a database of 705,333 discrete analyte concentrations from 11,462 cases affected with 57 metabolic disorders, and from 631 heterozygotes for 12 conditions. This evidence was first applied to establish disease ranges for amino acids and acylcarnitines, and clinically validate 114 cutoff target ranges. Objective: To improve quality and performance with an evidence-based approach, multivariate pattern recognition software has been developed to aid in the interpretation of complex analyte profiles. The software generates tools that convert multiple clinically significant results into a single numerical score based on overlap between normal and disease ranges, penetration within the disease range, differences between specific conditions, and weighted correction factors. Design: Eighty-five on-line tools target either a single condition or the differential diagnosis between two or more conditions. Scores are expressed as a numerical value and as the percentile rank among all cases with the condition chosen as primary target, and are compared to interpretation guidelines. Tools are updated automatically after any new data submission (2009- 2011: 5.2 new cases added per day on average). Main outcome measures: Retrospective evaluation of past cases suggest that these tools could have avoided at least half of 277 false positive outcomes caused by carrier status for fatty acid oxidation disorders, and could have prevented 88% of false negative events caused by cutoff 7 values set inappropriately. In Minnesota, their prospective application has been a major contributing factor to the sustained achievement of a false positive rate below 0.1% and a positive predictive value above 60%. Conclusions: Application of this computational approach to raw data could make cutoff values for single analytes effectively obsolete. This paradigm is not limited to newborn screening and is applicable to the interpretation of diverse multi-analyte profiles utilized in laboratory medicine. Abstract wor

Observation of the decay B-s(0) -> (D)over-bar(0)phi

First observation of the decay B-s(0) -> (D) over bar (0)phi is reported using pp collision data, corresponding to an integrated luminosity of 1.0 fb(-1), collected by the LHCb experiment at a centre-of-mass energy of 7 TeV. The significance of the signal is 6.5 standard deviations. The branching fraction is measured relative to that of the decay B-S(0) -> (D) over bar (0)phi to be beta B-S(0) -> (D) over bar (0)phi/beta B-S(0) -> (D) over bar (0)(K) over bar*(0) = 0.069 +/- 0.013 (stat) +/- 0.007 (syst). The first measurement of the ratio of branching fractions for the decays beta B-S(0) -> (D) over bar (0)(K) over bar*(0) and beta B-S(0) -> (D) over bar (0)(K) over bar*(0) is found to be beta B-S(0) -> (D) over bar (0)(K) over bar*(0/)beta B-S(0) -> (D) over bar (0)(K) over bar*(0=7.8) +/- 0.7(stat) +/- 0.3 (syst) +/- 0.6 (f(s)/f(d)) where the last uncertainty is due to the ratio of the B(s)(0)and B-0 fragmentation fractions

Model-independent search for CP violation in D-0 > K-K+pi(-)pi(+) and D-0 -> pi(-)pi(+)pi(+)pi(-) decays

A search for CP violation in the phase-space structures of 130 and 15 decays to the final states K-K+pi(-)pi(+) and pi(-)pi(+)pi(+)pi(-) is presented. The search is carried out with a data set corresponding to an integrated luminosity of 1.0 fb(-1) collected in 2011 by the LHCb experiment in pp collisions at a centre-of-mass energy of 7 TeV. For the K-K+pi(-)pi(+) final state, the four-body phase space is divided into 32 bins, each bin with approximately 1800 decays. The p-value under the hypothesis of no CP violation is 9.1%, and in no bin is a CP asymmetry greater than 6.5% observed. The phase space of the pi(-)pi(+)pi(+)pi(-). final state is partitioned into 128 bins, each bin with approximately 2500 decays. The p-value under the hypothesis of no CP violation is 41%, and in no bin is a CP asymmetry greater than 5.5% observed. All results are consistent with the hypothesis of no CP violation at the current sensitivity

Toward Male Individualization with Rapidly Mutating Y-Chromosomal Short Tandem Repeats

Relevant for various areas of human genetics, Y-chromosomal short tandem repeats (Y-STRs) are com- monly used for testing close paternal relationships among individuals and populations, and for male lineage iden- tification. However, even the widely used 17-loci Yfiler set cannot resolve individuals and populations completely. Here, 52 centers generated quality-controlled data of 13 rapidly mutating (RM) Y-STRs in 14,644 related and unrelated males from 111 worldwide populations. Strik- ingly, >99% of the 12,272 unrelated males were com- pletely individualized. Haplotype diversity was extremely high (global: 0.9999985, regional: 0.99836\u20130.9999988). Haplotype sharing between populations was almost ab- sent except for six (0.05%) of the 12,156 haplotypes. Haplotype sharing within populations was generally rare (0.8% nonunique haplotypes), significantly lower in ur- ban (0.9%) than rural (2.1%) and highest in endogamous groups (14.3%). Analysis of molecular variance revealed 99.98% of variation within populations, 0.018% among populations within groups, and 0.002% among groups. Of the 2,372 newly and 156 previously typed male relative pairs,29% were differentiated including 27% of the 2,378 father\u2013son pairs. Relative to Yfiler, haplotype diversity was increased in 86% of the populations tested and over- all male relative differentiation was raised by 23.5%. Our study demonstrates the value of RM Y-STRs in identifying and separating unrelated and related males and provides a reference database

Genome-wide meta-analysis of over 29,000 people with epilepsy reveals 26 loci and subtype-specific genetic architecture

AbstractEpilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here, we report a trans-ethnic GWAS including 29,944 cases, stratified into three broad- and seven sub-types of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants substantially close the missing heritability gap for GGE. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analysis of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current anti-seizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment