Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Polygenic Risk Modelling for Prediction of Epithelial Ovarian Cancer Risk

Funder: Funding details are provided in the Supplementary MaterialAbstractPolygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally-efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestry; 7,669 women of East Asian ancestry; 1,072 women of African ancestry, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestry. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38(95%CI:1.28–1.48,AUC:0.588) per unit standard deviation, in women of European ancestry; 1.14(95%CI:1.08–1.19,AUC:0.538) in women of East Asian ancestry; 1.38(95%CI:1.21-1.58,AUC:0.593) in women of African ancestry; hazard ratios of 1.37(95%CI:1.30–1.44,AUC:0.592) in BRCA1 pathogenic variant carriers and 1.51(95%CI:1.36-1.67,AUC:0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.</jats:p

An intronic variant in TBX4 in a single family with variable and severe pulmonary manifestations.

A male infant presented at term with neonatal respiratory failure and pulmonary hypertension. His respiratory symptoms improved initially, but he exhibited a biphasic clinical course, re-presenting at 15 months of age with tachypnea, interstitial lung disease, and progressive pulmonary hypertension. We identified an intronic TBX4 gene variant in close proximity to the canonical donor splice site of exon 3 (hg 19; chr17:59543302; c.401 + 3 A > T), also carried by his father who had a typical TBX4-associated skeletal phenotype and mild pulmonary hypertension, and by his deceased sister who died shortly after birth of acinar dysplasia. Analysis of patient-derived cells demonstrated a significant reduction in TBX4 expression resulting from this intronic variant. Our study illustrates the variable expressivity in cardiopulmonary phenotype conferred by TBX4 mutation and the utility of genetic diagnostics in enabling accurate identification and classification of more subtly affected family members

Role of active metabolites in the use of opioids

The opioid class of drugs, a large group, is mainly used for the treatment of acute and chronic persistent pain. All are eliminated from the body via metabolism involving principally CYP3A4 and the highly polymorphic CYP2D6, which markedly affects the drug's function, and by conjugation reactions mainly by UGT2B7. In many cases, the resultant metabolites have the same pharmacological activity as the parent opioid; however in many cases, plasma metabolite concentrations are too low to make a meaningful contribution to the overall clinical effects of the parent drug. These metabolites are invariably more water soluble and require renal clearance as an important overall elimination pathway. Such metabolites have the potential to accumulate in the elderly and in those with declining renal function with resultant accumulation to a much greater extent than the parent opioid. The best known example is the accumulation of morphine-6-glucuronide from morphine. Some opioids have active metabolites but at different target sites. These are norpethidine, a neurotoxic agent, and nordextropropoxyphene, a cardiotoxic agent. Clinicians need to be aware that many opioids have active metabolites that will become therapeutically important, for example in cases of altered pathology, drug interactions and genetic polymorphisms of drug-metabolizing enzymes. Thus, dose individualisation and the avoidance of adverse effects of opioids due to the accumulation of active metabolites or lack of formation of active metabolites are important considerations when opioids are used.Janet K. Coller, Lona L. Christrup, Andrew A. Somogy

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, &quot;select and shrink for summary statistics&quot; (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.N