Personalized sequencing and the future of medicine: discovery, diagnosis and defeat of disease

DNA as a perfect quantum computer based on the quantum physics principles

DNA is a complex multi-resolution molecule whose theoretical study is a challenge. Its intrinsic multiscale nature requires chemistry and quantum physics to understand the structure and quantum informatics to explain its operation as a perfect quantum computer. Here, we present theoretical results of DNA that allow a better description of its structure and the operation process in the transmission, coding, and decoding of genetic information. Aromaticity is explained by the oscillatory resonant quantum state of correlated electron and hole pairs due to the quantized molecular vibrational energy acting as an attractive force. The correlated pairs form a supercurrent in the nitrogenous bases in a single band π -molecular orbital ( π -MO). The MO wave function ( Φ ) is assumed to be the linear combination of the n constituent atomic orbitals. The central Hydrogen bond between Adenine (A) and Thymine (T) or Guanine (G) and Cytosine (C) functions like an ideal Josephson Junction. The approach of a Josephson Effect between two superconductors is correctly described, as well as the condensation of the nitrogenous bases to obtain the two entangled quantum states that form the qubit. Combining the quantum state of the composite system with the classical information, RNA polymerase teleports one of the four Bell states. DNA is a perfect quantum computer.

Integrative bioinformatics and experimental validation of hub genetic markers in acne vulgaris: Toward personalized diagnostic and therapeutic strategies

BACKGROUND

Acne vulgaris is a widespread chronic inflammatory dermatological condition. The precise molecular and genetic mechanisms of its pathogenesis remain incompletely understood. This research synthesizes existing databases, targeting a comprehensive exploration of core genetic markers.

METHODS

Gene expression datasets (GSE6475, GSE108110, and GSE53795) were retrieved from the GEO. Differentially expressed genes (DEGs) were identified using the limma package. Enrichment analyses were conducted using GSVA for pathway assessment and clusterProfiler for GO and KEGG analyses. PPI networks and immune cell infiltration were analyzed using the STRING database and ssGSEA, respectively. We investigated the correlation between hub gene biomarkers and immune cell infiltration using Spearman's rank analysis. ROC curve analysis validated the hub genes' diagnostic accuracy. miRNet, TarBase v8.0, and ChEA3 identified miRNA/transcription factor-gene interactions, while DrugBank delineated drug-gene interactions. Experiments utilized HaCaT cells stimulated with Propionibacterium acnes, treated with retinoic acid and methotrexate, and evaluated using RT-qPCR, ELISA, western blot, lentiviral transduction, CCK-8, wound-healing, and transwell assays.

RESULTS

There were 104 genes with consistent differences across the three datasets of paired acne and normal skin. Functional analyses emphasized the significant enrichment of these DEGs in immune-related pathways. PPI network analysis pinpointed hub genes PTPRC, CXCL8, ITGB2, and MMP9 as central players in acne pathogenesis. Elevated levels of specific immune cell infiltration in acne lesions corroborated the inflammatory nature of the disease. ROC curve analysis identified the acne diagnostic potential of four hub genes. Key miRNAs, particularly hsa-mir-124-3p, and central transcription factors like TFEC were noted as significant regulators. In vitro validation using HaCaT cells confirmed the upregulation of hub genes following Propionibacterium acnes exposure, while CXCL8 knockdown reduced pro-inflammatory cytokines, cell proliferation, and migration. DrugBank insights led to the exploration of retinoic acid and methotrexate, both of which mitigated gene expression upsurge and inflammatory mediator secretion.

CONCLUSION

This comprehensive study elucidated pivotal genes associated with acne pathogenesis, notably PTPRC, CXCL8, ITGB2, and MMP9. The findings underscore potential biomarkers, therapeutic targets, and the therapeutic potential of agents like retinoic acid and methotrexate. The congruence between bioinformatics and experimental validations suggests promising avenues for personalized acne treatments.

Cellular and molecular mechanisms of skin wound healing

Wound healing is a complex process that involves the coordinated actions of many different tissues and cell lineages. It requires tight orchestration of cell migration, proliferation, matrix deposition and remodelling, alongside inflammation and angiogenesis. Whereas small skin wounds heal in days, larger injuries resulting from trauma, acute illness or major surgery can take several weeks to heal, generally leaving behind a fibrotic scar that can impact tissue function. Development of therapeutics to prevent scarring and successfully repair chronic wounds requires a fuller knowledge of the cellular and molecular mechanisms driving wound healing. In this Review, we discuss the current understanding of the different phases of wound healing, from clot formation through re-epithelialization, angiogenesis and subsequent scar deposition. We highlight the contribution of different cell types to skin repair, with emphasis on how both innate and adaptive immune cells in the wound inflammatory response influence classically studied wound cell lineages, including keratinocytes, fibroblasts and endothelial cells, but also some of the less-studied cell lineages such as adipocytes, melanocytes and cutaneous nerves. Finally, we discuss newer approaches and research directions that have the potential to further our understanding of the mechanisms underpinning tissue repair.

A Zebrafish-Based Platform for High-Throughput Epilepsy Modeling and Drug Screening in F0

The zebrafish model has emerged as a reference tool for phenotypic drug screening. An increasing number of molecules have been brought from bench to bedside thanks to zebrafish-based assays over the last decade. The high homology between the zebrafish and the human genomes facilitates the generation of zebrafish lines carrying loss-of-function mutations in disease-relevant genes; nonetheless, even using this alternative model, the establishment of isogenic mutant lines requires a long generation time and an elevated number of animals. In this study, we developed a zebrafish-based high-throughput platform for the generation of F0 knock-out (KO) models and the screening of neuroactive compounds. We show that the simultaneous inactivation of a reporter gene (tyrosinase) and a second gene of interest allows the phenotypic selection of F0 somatic mutants (crispants) carrying the highest rates of mutations in both loci. As a proof of principle, we targeted genes associated with neurodevelopmental disorders and we efficiently generated de facto F0 mutants in seven genes involved in childhood epilepsy. We employed a high-throughput multiparametric behavioral analysis to characterize the response of these KO models to an epileptogenic stimulus, making it possible to employ kinematic parameters to identify seizure-like events. The combination of these co-injection, screening and phenotyping methods allowed us to generate crispants recapitulating epilepsy features and to test the efficacy of compounds already during the first days post fertilization. Since the strategy can be applied to a wide range of indications, this study paves the ground for high-throughput drug discovery and promotes the use of zebrafish in personalized medicine and neurotoxicity assessment.

An Integrative Pancreatic Cancer Risk Prediction Model in the UK Biobank

Pancreatic cancer (PaCa) is a lethal cancer with an increasing incidence, highlighting the need for early prevention strategies. There is a lack of a comprehensive PaCa predictive model derived from large prospective cohorts. Therefore, we have developed an integrated PaCa risk prediction model for PaCa using data from the UK Biobank, incorporating lifestyle-related, genetic-related, and medical history-related variables for application in healthcare settings. We used a machine learning-based random forest approach and a traditional multivariable logistic regression method to develop a PaCa predictive model for different purposes. Additionally, we employed dynamic nomograms to visualize the probability of PaCa risk in the prediction model. The top five influential features in the random forest model were age, PRS, pancreatitis, DM, and smoking. The significant risk variables in the logistic regression model included male gender (OR = 1.17), age (OR = 1.10), non-O blood type (OR = 1.29), higher polygenic score (PRS) (Q5 vs. Q1, OR = 2.03), smoking (OR = 1.82), alcohol consumption (OR = 1.27), pancreatitis (OR = 3.99), diabetes (DM) (OR = 2.57), and gallbladder-related disease (OR = 2.07). The area under the receiver operating curve (AUC) of the logistic regression model is 0.78. Internal validation and calibration performed well in both models. Our integrative PaCa risk prediction model with the PRS effectively stratifies individuals at future risk of PaCa, aiding targeted prevention efforts and supporting community-based cancer prevention initiatives.

Revolutionizing Medical Microbiology: How Molecular and Genomic Approaches Are Changing Diagnostic Techniques

Molecular and genomic approaches have revolutionized medical microbiology by offering faster and more accurate diagnostic techniques for infectious diseases. Traditional methods, which include culturing microbes and biochemical testing, are time-consuming and may not detect antibiotic-resistant strains. In contrast, molecular and genomic methods, including polymerase chain reaction (PCR)-based techniques and whole-genome sequencing, provide rapid and precise detection of pathogens, early-stage diseases, and antibiotic-resistant strains. These approaches have advantages such as high sensitivity and specificity, the potential for targeted therapies, and personalized medicine. However, implementing molecular and genomic techniques faces challenges related to cost, equipment, expertise, and data analysis. Ethical and legal considerations regarding patient privacy and genetic data usage also arise. Nonetheless, the future of medical microbiology lies in the widespread adoption of molecular and genomic approaches, which can lead to improved patient outcomes and the identification of antibiotic-resistant strains. Continued advancements, education, and exploration of ethical implications are necessary to fully harness the potential of molecular and genomic techniques in medical microbiology.

Nucleic Acid Based Testing (NABing): A Game Changer Technology for Public Health

Timely and accurate detection of the causal agent of a disease is crucial to restrict suffering and save lives. Mere symptoms are often not enough to detect the root cause of the disease. Better diagnostics applied for screening at a population level and sensitive detection assays remain the crucial component of disease surveillance which may include clinical, plant, and environmental samples, including wastewater. The recent advances in genome sequencing, nucleic acid amplification, and detection methods have revolutionized nucleic acid-based testing (NABing) and screening assays. A typical NABing assay consists of three modules: isolation of the nucleic acid from the collected sample, identification of the target sequence, and final reading the target with the help of a signal, which may be in the form of color, fluorescence, etc. Here, we review current NABing assays covering the different aspects of all three modules. We also describe the frequently used target amplification or signal amplification procedures along with the variety of applications of this fast-evolving technology and challenges in implementation of NABing in the context of disease management especially in low-resource settings.

Polygenic risk scores and risk stratification in deep vein thrombosis

INTRODUCTION

Deep vein thrombosis (DVT) is a complex disease, where 60 % of risk is due to genetic factors, such as the Factor V Leiden (FVL) variant. DVT is either asymptomatic or manifests with unspecific symptoms and, if left untreated, DVT leads to severe complications. The impact is dramatic and currently, there is still a research gap in DVT prevention. We characterized the genetic contribution and stratified individuals based on genetic makeup to evaluate if it favorably impacts risk prediction.

METHODS

In the UK Biobank (UKB), we performed gene-based association tests using exome sequencing data, as well as a genome-wide association study. We also constructed polygenic risk scores (PRS) in a subset of the cohort (Number of cases = 8231; Number of controls = 276,360) and calculated the impact on the prediction capacity of the PRS in a non-overlapping part of the cohort (Number of cases = 4342; Number of controls = 142,822). We generated additional PRSs that excluded the known causative variants.

RESULTS

We discovered and replicated a novel common variant (rs11604583) near the region where are located the TRIM51 and LRRC55 genes and identified a novel rare variant (rs187725533) located near the CREB3L1 gene, associated with 2.5-fold higher risk of DVT. In one of the PRS models constructed, the top decile of risk is associated with 3.4-fold increased risk, an effect that is 2.3-fold when excluding FVL carriers. In the top PRS decile, the cumulative risk of DVT at the age of 80 years is 10 % for FVL carriers, contraposed to 5 % for non-carriers. The population attributable fractions of having a high polygenic risk on the rate of DVT was estimated to be around 20 % in our cohort.

CONCLUSION

Individuals with a high polygenic risk of DVT, and not only carriers of well-studied variants such as FVL, may benefit from prevention strategies.

Functionalized electrodes embedded in nanopores: read-out enhancement?

In this review, functionalized nanogaps embedded in nanopores are discussed in view of their high biosensitivity in detecting biomolecules, their length, type, and sequence. Specific focus is given on nanoelectrodes functionalized with tiny nanometer-sized diamond-like particles offering vast functionalization possibilities for gold junction electrodes. This choice of the functionalization, in turn, offers nucleotide-specific binding possibilities improving the detection signals arising from such functionalized electrodes potentially embedded in a nanopore. The review sheds light onto the use and enhancement of the tunnelling recognition in functionalized nanogaps towards sensing DNA nucleotides and mutation detection, providing important input for a practical realization.

Genomic medicine in Africa: a need for molecular genetics and pharmacogenomics experts

The large-scale implementation of genomic medicine in Africa has not been actualized. This overview describes how routine molecular genetics and advanced protein engineering/structural biotechnology could accelerate the implementation of genomic medicine. By using data-mining and analysis approaches, we analyzed relevant information obtained from public genomic databases on pharmacogenomics biomarkers and reviewed published studies to discuss the ideas. The results showed that only 68 very important pharmacogenes currently exist, while 867 drug label annotations, 201 curated functional pathways, and 746 annotated drugs have been catalogued on the largest pharmacogenomics database (PharmGKB). Only about 5009 variants of the reported ∼25,000 have been clinically annotated. Predominantly, the genetic variants were derived from 43 genes that contribute to 2318 clinically relevant variations in 57 diseases. Majority (∼60%) of the clinically relevant genetic variations in the pharmacogenes are missense variants (1390). The enrichment analysis showed that 15 pharmacogenes are connected biologically and are involved in the metabolism of cardiovascular and cancer drugs. The review of studies showed that cardiovascular diseases are the most frequent non-communicable diseases responsible for approximately 13% of all deaths in Africa. Also, warfarin pharmacogenomics is the most studied drug on the continent, while CYP2D6, CYP2C9, DPD, and TPMT are the most investigated pharmacogenes with allele activities indicated in African and considered to be intermediate metaboliser for DPD and TPMT (8.4% and 11%). In summary, we highlighted a framework for implementing genomic medicine starting from the available resources on ground.

Development of a Simultaneous Liquid Chromatography-Tandem Mass Spectrometry Analytical Method for Urinary Endogenous Substrates and Metabolites for Predicting Cytochrome P450 3A4 Activity

CYP3A4, which contributes to the metabolism of more than 30% of clinically used drugs, exhibits high variation in its activity; therefore, predicting CYP3A4 activity before drug treatment is vital for determining the optimal dosage for each patient. We aimed to develop and validate an LC-tandem mass spectrometry (LC-MS/MS) method that simultaneously measures the levels of CYP3A4 activity-related predictive biomarkers (6β-hydroxycortisol (6β-OHC), cortisol (C), 1β-hydroxydeoxycholic acid (1β-OHDCA), and deoxycholic acid (DCA)). Chromatographic separation was achieved using a YMC-Triart C18 column and a gradient flow of the mobile phase comprising deionized water/25% ammonia solution (100 : 0.1, v/v) and methanol/acetonitrile/25% ammonia solution (50 : 50 : 0.1, v/v/v). Selective reaction monitoring in the negative-ion mode was used for MS/MS, and run times of 33 min were used. All analytes showed high linearity in the range of 3-3000 ng/mL. Additionally, their concentrations in urine samples derived from volunteers were analyzed via treatment with deconjugation enzymes, ignoring inter-individual differences in the variation of other enzymatic activities. Our method satisfied the analytical validation criteria under clinical conditions. Moreover, the concentrations of each analyte were quantified within the range of calibration curves for all urine samples. The conjugated forms of each analyte were hydrolyzed to accurately examine CYP3A4 activity. Non-invasive urine sampling employed herein is an effective alternative to invasive plasma sampling. The analytically validated simultaneous quantification method developed in this study can be used to predict CYP3A4 activity in precision medicine and investigate the potential clinical applications of CYP3A4 biomarkers (6β-OHC/C and 1β-OHDCA/DCA ratios).

Starring Role of Biomarkers and Anticancer Agents as a Major Driver in Precision Medicine of Cancer Therapy

Precision medicine is the most modern contemporary medicine approach today, based on great amount of data on people's health, individual characteristics, and life circumstances, and employs the most effective ways to prevent and cure diseases. Precision medicine in cancer is the most precise and viable treatment for every cancer patient based on the disease's genetic profile. Precision medicine changes the standard one size fits all medication model, which focuses on average responses to care. Consolidating modern methodologies for streamlining and checking anticancer drugs can have long-term effects on understanding the results. Precision medicine can help explicit anticancer treatments using various drugs and even in discovery, thus becoming the paradigm of future cancer medicine. Cancer biomarkers are significant in precision medicine, and findings of different biomarkers make this field more promising and challenging. Naturally, genetic instability and the collection of extra changes in malignant growth cells are ways cancer cells adapt and survive in a hostile environment, for example, one made by these treatment modalities. Precision medicine centers on recognizing the best treatment for individual patients, dependent on their malignant growth and genetic characterization. This new era of genomics progressively referred to as precision medicine, has ignited a new episode in the relationship between genomics and anticancer drug development.

Adversarial reinforcement learning for dynamic treatment regimes

Treatment recommendation, as a critical task of delivering effective interventions according to patient state and expected outcome, plays a vital role in precision medicine and healthcare management. As a well-suited tactic to learn optimal policies of recommender systems, reinforcement learning is promising to address the challenge of treatment recommendation. However, existing solutions mostly require frequent interactions between treatment recommender systems and clinical environment, which are expensive, time-consuming, and even infeasible in clinical practice. In this study, we present a novel model-based offline reinforcement learning approach to optimize a treatment policy by utilizing patient treatment trajectories in Electronic Health Records (EHRs). Specifically, a patient treatment trajectory simulator is firstly constructed based on the ground-truth trajectories in EHRs. Thereafter, the constructed simulator is utilized to model the online interactions between the treatment recommender system and clinical environment. In this way, the counterfactual trajectories can be generated. To alleviate the bias deriving from the ground-truth and the counterfactual trajectories, an adversarial network is incorporated into the proposed model, such that a large space of treatment actions can be explored with the scaled rewards. The proposed model is evaluated on a simulated dataset and a real-world dataset. The experimental results demonstrate that the proposed model is superior to other methods, giving rise to a new solution for dynamic treatment regimes and beyond.

Whole Exome Sequencing Study Identifies Novel Rare Risk Variants for Habitual Coffee Consumption Involved in Olfactory Receptor and Hyperphagia

Habitual coffee consumption is an addictive behavior with unknown genetic variations and has raised public health issues about its potential health-related outcomes. We performed exome-wide association studies to identify rare risk variants contributing to habitual coffee consumption utilizing the newly released UK Biobank exome dataset (n = 200,643). A total of 34,761 qualifying variants were imported into SKAT to conduct gene-based burden and robust tests with minor allele frequency <0.01, adjusting the polygenic risk scores (PRS) of coffee intake to exclude the effect of common coffee-related polygenic risk. The gene-based burden and robust test of the exonic variants found seven exome-wide significant associations, such as OR2G2 (PSKAT = 1.88 × 10−9, PSKAT-Robust = 2.91 × 10−17), VEZT1 (PSKAT = 3.72 × 10−7, PSKAT-Robust = 1.41 × 10−7), and IRGC (PSKAT = 2.92 × 10−5, PSKAT-Robust = 1.07 × 10−7). These candidate genes were verified in the GWAS summary data of coffee intake, such as rs12737801 (p = 0.002) in OR2G2, and rs34439296 (p = 0.008) in IRGC. This study could help to extend genetic insights into the pathogenesis of coffee addiction, and may point to molecular mechanisms underlying health effects of habitual coffee consumption.

Ultra-sensitive monitoring of leukemia patients using superRCA mutation detection assays

Rare tumor-specific mutations in patient samples serve as excellent markers to monitor the course of malignant disease and responses to therapy in clinical routine, and improved assay techniques are needed for broad adoption. We describe herein a highly sensitive and selective molecule amplification technology - superRCA assays - for rapid and highly specific detection of DNA sequence variants present at very low frequencies in DNA samples. Using a standard flow cytometer we demonstrate precise, ultra-sensitive detection of single-nucleotide mutant sequences from malignant cells against up to a 100,000-fold excess of DNA from normal cells in either bone marrow or peripheral blood, to follow the course of patients treated for acute myeloid leukemia (AML). We also demonstrate that sequence variants located in a high-GC region may be sensitively detected, and we illustrate the potential of the technology for early detection of disease recurrence as a basis for prompt change of therapy.

The Landscape of Actionable Genomic Alterations by Next-Generation Sequencing in Tumor Tissue Versus Circulating Tumor DNA in Chinese Patients With Non-Small Cell Lung Cancer

Background

Circulating tumor DNA (ctDNA) sequence analysis shows great potential in the management of non-small cell lung cancer (NSCLC) and the prediction of drug sensitivity or resistance in many cancers. Here, we drew and compared the somatic mutational profile using ctDNA and tumor tissue sequence analysis in lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), and assess its potential clinical value.

Methods

In this study, 221 tumor tissues and 174 plasma samples from NSCLC patients were analyzed by hybridization capture-based next-generation sequencing (NGS) panel including 95 cancer-associated genes. Tumor response assessments were applied to 137 patients with advanced-stage (III and IV) NSCLC who first received targeted agents.

Results

Twenty significantly mutated genes were identified such as TP53, EGFR, RB1, KRAS, PIK3CA, CD3EAP, CTNNB1, ERBB2, APC, BRAF, TERT, FBXW7, and HRAS. Among them, TP53 was the most frequently mutated gene and had a higher mutation probability in male (p = 0.00124) and smoking (p < 0.0001) patients. A total of 48.35% (191/395) of NSCLC patients possessed at least one actionable alteration according to the OncoKB database. Although the sensitivity of genomic profiling from ctDNA was lower than that from tumor tissue DNA, the mutational landscape of target genes from ctDNA is similar to that from tumor tissue DNA, which led to 61.22% (30/49) of mutational concordance in NSCLC. Additionally, the mutational concordance between tissue DNA and ctDNA in LUAD differs from that in LUSC, which is 63.83% versus 46.67%, indicating that NSCLC subtypes influence the specificity of mutation detection in plasma-derived ctDNA. Lastly, patients with EGFR and TP53 co-alterations showed similar responses to Gefitinib and Icotinib, and the co-occurring TP53 mutation was most likely to be a poor prognostic factor for patients receiving Gefitinib, indicating that the distributions and types of TP53 mutations may contribute to the efficacy and prognosis of molecular targeted therapy.

Conclusions

As a promising alternative for tumor genomic profiling, ctDNA analysis is more credible in LUAD than in LUSC. Genomic subtyping has strong potential in prognostication and therapeutic decision-making for NSCLC patients, which indicated the necessity for the utility of target NGS in guiding clinical management.

Surveillance in Next-Generation Personalized Healthcare: Science and Ethics of Data Analytics in Healthcare

Advances in science and technology have allowed for incredible improvements in healthcare. Additionally, the digital revolution in healthcare provides new ways of collecting and storing large volumes of patient data, referred to as big healthcare data. As a result, healthcare providers are now able to use data to gain a deeper understanding of how to treat an individual in what is referred to as personalized healthcare. Regardless, there are several ethical challenges associated with big healthcare data that affect how personalized healthcare is delivered. To highlight these issues, this article will review the role of big data in personalized healthcare while also discussing the ethical challenges associated with it. The article will also discuss public health surveillance, its implications, and the challenges associated with collecting participants' information. The article will proceed by highlighting next generation technologies, including robotics and 3D printing. The article will conclude by providing recommendations on how patient privacy can be protected in next-generation personalized healthcare.

The Polygenic and Monogenic Basis of Paediatric Fractures

PURPOSE OF REVIEW

Fractures are frequently encountered in paediatric practice. Although recurrent fractures in children usually unveil a monogenic syndrome, paediatric fracture risk could be shaped by the individual genetic background influencing the acquisition of bone mineral density, and therefore, the skeletal fragility as shown in adults. Here, we examine paediatric fractures from the perspective of monogenic and complex trait genetics.

RECENT FINDINGS

Large-scale genome-wide studies in children have identified ~44 genetic loci associated with fracture or bone traits whereas ~35 monogenic diseases characterized by paediatric fractures have been described. Genetic variation can predispose to paediatric fractures through monogenic risk variants with a large effect and polygenic risk involving many variants of small effects. Studying genetic factors influencing peak bone attainment might help in identifying individuals at higher risk of developing early-onset osteoporosis and discovering drug targets to be used as bone restorative pharmacotherapies to prevent, or even reverse, bone loss later in life.

Privacy considerations for sharing genomics data

An increasing amount of attention has been geared towards understanding the privacy risks that arise from sharing genomic data of human origin. Most of these efforts have focused on issues in the context of genomic sequence data, but the popularity of techniques for collecting other types of genome-related data has prompted researchers to investigate privacy concerns in a broader genomic context. In this review, we give an overview of different types of genome-associated data, their individual ways of revealing sensitive information, the motivation to share them as well as established and upcoming methods to minimize information leakage. We further discuss the concise threats that are being posed, who is at risk, and how the risk level compares to potential benefits, all while addressing the topic in the context of modern technology, methodology, and information sharing culture. Additionally, we will discuss the current legal situation regarding the sharing of genomic data in a selection of countries, evaluating the scope of their applicability as well as their limitations. We will finalize this review by evaluating the development that is required in the scientific field in the near future in order to improve and develop privacy-preserving data sharing techniques for the genomic context.

Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine

Over the last decades, transcriptome profiling emerged as one of the most powerful approaches in oncology, providing prognostic and predictive utility for cancer management. The development of novel technologies, such as revolutionary next-generation sequencing, enables the identification of cancer biomarkers, gene signatures, and their aberrant expression affecting oncogenesis, as well as the discovery of molecular targets for anticancer therapies. Transcriptomics contribute to a change in the holistic understanding of cancer, from histopathological and organic to molecular classifications, opening a more personalized perspective for tumor diagnostics and therapy. The further advancement on transcriptome profiling may allow standardization and cost reduction of its analysis, which will be the next step for transcriptomics to become a canon of contemporary cancer medicine.

Human Organic Anion Transporting Polypeptide 1B3 Applied as an MRI-Based Reporter Gene

Objective

Recent innovations in biology are boosting gene and cell therapy, but monitoring the response to these treatments is difficult. The purpose of this study was to find an MRI-reporter gene that can be used to monitor gene or cell therapy and that can be delivered without a viral vector, as viral vector delivery methods can result in long-term complications.

Materials and Methods

CMV promoter-human organic anion transporting polypeptide 1B3 (CMV-hOATP1B3) cDNA or CMV-blank DNA (control) was transfected into HEK293 cells using Lipofectamine. OATP1B3 expression was confirmed by western blotting and confocal microscopy. In vitro cell phantoms were made using transfected HEK293 cells cultured in various concentrations of gadoxetic acid for 24 hours, and images of the phantoms were made with a 9.4T micro-MRI. In vivo xenograft tumors were made by implanting HEK293 cells transfected with CMV-hOATP1B3 (n = 4) or CMV-blank (n = 4) in 8-week-old male nude mice, and MRI was performed before and after intravenous injection of gadoxetic acid (1.2 µL/g).

Results

Western blot and confocal microscopy after immunofluorescence staining revealed that only CMV-hOATP1B3-transfected HEK293 cells produced abundant OATP1B3, which localized at the cell membrane. OATP1B3 expression levels remained high through the 25th subculture cycle, but decreased substantially by the 50th subculture cycle. MRI of cell phantoms showed that only the CMV-hOATP1B3-transfected cells produced a significant contrast enhancement effect. In vivo MRI of xenograft tumors revealed that only CMV-hOATP1B3-transfected HEK293 tumors demonstrated a T1 contrast effect, which lasted for at least 5 hours.

Conclusion

The human endogenous OATP1B3 gene can be non-virally delivered into cells to induce transient OATP1B3 expression, leading to gadoxetic acid-mediated enhancement on MRI. These results indicate that hOATP1B3 can serve as an MRI-reporter gene while minimizing the risk of long-term complications.

Individuals with common diseases but with a low polygenic risk score could be prioritized for rare variant screening

PURPOSE

Identifying rare genetic causes of common diseases can improve diagnostic and treatment strategies, but incurs high costs. We tested whether individuals with common disease and low polygenic risk score (PRS) for that disease generated from less expensive genome-wide genotyping data are more likely to carry rare pathogenic variants.

METHODS

We identified patients with one of five common complex diseases among 44,550 individuals who underwent exome sequencing in the UK Biobank. We derived PRS for these five diseases, and identified pathogenic rare variant heterozygotes. We tested whether individuals with disease and low PRS were more likely to carry rare pathogenic variants.

RESULTS

While rare pathogenic variants conferred, at most, 5.18-fold (95% confidence interval [CI]: 2.32-10.13) increased odds of disease, a standard deviation increase in PRS, at most, increased the odds of disease by 5.25-fold (95% CI: 5.06-5.45). Among diseased patients, a standard deviation decrease in the PRS was associated with, at most, 2.82-fold (95% CI: 1.14-7.46) increased odds of identifying rare variant heterozygotes.

CONCLUSION

Rare pathogenic variants were more prevalent among affected patients with a low PRS. Therefore, prioritizing individuals for sequencing who have disease but low PRS may increase the yield of sequencing studies to identify rare variant heterozygotes.

The Biomarker and Therapeutic Potential of Circular Rnas in Schizophrenia

Circular RNAs (circRNAs) are endogenous, single-stranded, most frequently non-coding RNA (ncRNA) molecules that play a significant role in gene expression regulation. Circular RNAs can affect microRNA functionality, interact with RNA-binding proteins (RBPs), translate proteins by themselves, and directly or indirectly modulate gene expression during different cellular processes. The affected expression of circRNAs, as well as their targets, can trigger a cascade of events in the genetic regulatory network causing pathological conditions. Recent studies have shown that altered circular RNA expression patterns could be used as biomarkers in psychiatric diseases, including schizophrenia (SZ); moreover, circular RNAs together with other cell molecules could provide new insight into mechanisms of this disorder. In this review, we focus on the role of circular RNAs in the pathogenesis of SZ and analyze their biomarker and therapeutic potential in this disorder.

A molecular dynamics approach on the Y393C variant of protein disulfide isomerase A1

Human protein disulfide isomerase A1 (PDIA1) shows both catalytic (i.e., oxidoreductase) and non-catalytic (i.e., chaperone) activities and plays a crucial role in the oxidative folding of proteins within the endoplasmic reticulum. PDIA1 dysregulation is a common trait in numerous pathophysiological conditions, including neurodegenerative disorders and cancerous diseases. The 1178A>G mutation of the human PDIA1-encoding gene is a non-synonymous single nucleotide polymorphism detected in patients with Cole-Carpenter syndrome type 1 (CSS1), a particularly rare bone disease. In vitro studies showed that the encoded variant (PDIA1 Y393C) exhibits limited oxidoreductase activity. To gain knowledge on the structure-function relationship, we undertook a molecular dynamics (MD) approach to examine the structural stability of PDIA1 Y393C. Results showed that significant conformational changes are the structural consequence of the amino acid substitution Tyr>Cys at position 393 of the PDIA1 protein. This structure-based study provides further knowledge about the molecular origin of CCS1.

Treatment and relapse in breast cancer show significant correlations to noninvasive testing using urinary and plasma DNA

Aim: Circulating tumor DNA is promising for routine monitoring of breast cancer. Noninvasive testing allows regular probing using plasma and urine samples. Methods: Peripheral blood and simultaneous urine collection from patients were quantified. Concordance between methods were made. Serial time-point measurements were correlated to disease outcome. Results: Index measurements demonstrate over 90% concordance with biopsy. Receiver operating characteristics curves showed over 0.95 for both plasma and urine results comparing with controls. Patients with lower risk of relapse experienced greater declines in detected DNA levels. Maximal declines were registered at 4.0- and 6.8-fold for plasma and urine results, respectively. Conclusion: Measuring and monitoring DNA levels complement existing testing regimes and provides better risk profiling of patients for possible relapse.

Concordance of Genomic Alterations by Next-Generation Sequencing in Tumor Tissue versus Cell-Free DNA in Stage I-IV Non-Small Cell Lung Cancer

Molecular biomarkers hold promise for personalization of cancer treatment. However, a typical tumor biopsy may be difficult to acquire and may not capture genetic variations within or across tumors. Given these limitations, tumor genotyping using next-generation sequencing of plasma-derived circulating tumor (ct)-DNA has the potential to transform non-small cell lung cancer (NSCLC) management. Importantly, mutations detected in biopsied tissue must also be detected in plasma-derived ctDNA at different disease stages. Using the AVENIO ctDNA Surveillance kit (research use only), mutations in ctDNA from NSCLC subjects were compared with those identified in matched tumor tissue samples, retrospectively. Plasma and tissue samples were collected from 141 treatment-naïve NSCLC subjects (stage I, n = 48; stage II, n = 37; stage III, n = 33; stage IV, n = 23). In plasma samples, the median numbers of variants per subject were 4, 6, 8, and 9 in those with stage I, II, III, and IV disease, respectively. The corresponding values in tissue samples were 5, 5, 6, and 4. The overall tissue-plasma concordance of stage II through IV was 62.2% by AVENIO software call. On multivariate analysis, concordance was positively and significantly associated with tumor size and cancer stage. Next-generation sequencing-based analyses with the AVENIO ctDNA Surveillance kit could be an alternative approach to detecting genetic variations in plasma-derived ctDNA isolated from NSCLC subjects.

MOSClip: multi-omic and survival pathway analysis for the identification of survival associated gene and modules

Survival analyses of gene expression data has been a useful and widely used approach in clinical applications. But, in complex diseases, such as cancer, the identification of survival-associated cell processes - rather than single genes - provides more informative results because the efficacy of survival prediction increases when multiple prognostic features are combined to enlarge the possibility of having druggable targets. Moreover, genome-wide screening in molecular medicine has rapidly grown, providing not only gene expression but also multi-omic measurements such as DNA mutations, methylation, expression, and copy number data. In cancer, virtually all these aberrations can contribute in synergy to pathological processes, and their measurements can improve a patient’s outcome and help in diagnosis and treatment decisions. Here, we present MOSClip, an R package implementing a new topological pathway analysis tool able to integrate multi-omic data and look for survival-associated gene modules. MOSClip tests the survival association of dimensionality-reduced multi-omic data using multivariate models, providing graphical devices for management, browsing and interpretation of results. Using simulated data we evaluated MOSClip performance in terms of false positives and false negatives in different settings, while the TCGA ovarian cancer dataset is used as a case study to highlight MOSClip’s potential.

Alterations in Eukaryotic Elongation Factor complex proteins (EEF1s) in cancer and their implications in epigenetic regulation

AIMS

In the cell, both transcriptional and translational processes are tightly regulated. Cancer is a multifactorial disease characterized by aberrant protein expression. Since epigenetic control mechanisms are also frequently disrupted during carcinogenesis, they have been the center of attention in cancer research within the past decades. EEF1 complex members, which are required for the elongation process in eukaryotes, have recently been implicated in carcinogenesis. This study aims to investigate genetic alterations within EEF1A1, EEF1A2, EEF1B2, EEF1D, EEF1E1 and EEF1G genes and their potential effects on epigenetic regulation mechanisms.

MATERIALS AND METHODS

In this study, we analyzed DNA sequencing and mRNA expression data available on The Cancer Genome Atlas (TCGA) across different cancer types to detect genetic alterations in EEF1 genes and investigated their potential impact on selected epigenetic modulators.

KEY FINDINGS

We found that EEF1 complex proteins were deregulated in several types of cancer. Lower EEF1A1, EEF1B2, EEF1D and EEF1G levels were correlated with poor survival in glioma, while lower EEF1B2, EEF1D and EEF1E1 levels were correlated with better survival in hepatocellular carcinoma. We detected genetic alterations within EEF1 genes in up to 35% of the patients and showed that these alterations resulted in down-regulation of histone modifying enzymes KMT2C, KMT2D, KMT2E, KAT6A and EP300.

SIGNIFICANCE

Here in this study, we showed that EEF1 deregulations might result in differential epigenomic landscapes, which affect the overall transcriptional profile, contributing to carcinogenesis. Identification of these molecular distinctions might be useful in developing targeted drug therapies and personalized medicine.

Worldwide human mitochondrial haplogroup distribution from urban sewage

Community level genetic information can be essential to direct health measures and study demographic tendencies but is subject to considerable ethical and legal challenges. These concerns become less pronounced when analyzing urban sewage samples, which are ab ovo anonymous by their pooled nature. We were able to detect traces of the human mitochondrial DNA (mtDNA) in urban sewage samples and to estimate the distribution of human mtDNA haplogroups. An expectation maximization approach was used to determine mtDNA haplogroup mixture proportions for samples collected at each different geographic location. Our results show reasonable agreement with both previous studies of ancient evolution or migration and current US census data; and are also readily reproducible and highly robust. Our approach presents a promising alternative for sample collection in studies focusing on the ethnic and genetic composition of populations or diseases associated with different mtDNA haplogroups and genotypes.

The influence of a solvent on the electronic transport across diamondoid-functionalized biosensing electrodes

Electrodes embedded in nanopores have the potential to detect the identity of biomolecules, such as DNA. This identification is typically being done through electronic current measurements across the electrodes in a solvent. In this work, using quantum-mechanical calculations, we qualitatively present the influence of this solvent on the current signals. For this, we model electrodes functionalized with a small diamond-like molecule known as diamondoid and place a DNA nucleotide within the electrode gap. The influence of an aqueous solvent is taken explicitly into account through Quantum-Mechanics/Molecular Mechanics (QM/MM) simulations. From these, we could clearly reveal that at the (111) surface of the Au electrode, water molecules form an adlayer-like structure through hydrogen bond networks. From the temporal evolution of the hydrogen bond between a nucleotide and the functionalizing diamondoid, we could extract information on the conductance across the device. In order to evaluate the influence of the solvent, we compare these results with ground-state electronic structure calculations in combination with the non-equilibrium Green's function (NEGF) approach. These allow access to the electronic transport across the electrodes and show a difference in the detection signals with and without the aqueous solution. We analyze the results with respect to the density of states in the device. In the end, we demonstrate that the presence of water does not hinder the detection of a mutation over a healthy DNA nucleotide. We discuss these results in view of sequencing DNA with nanopores.

CRISPR/Cas9 - An evolving biological tool kit for cancer biology and oncology

The development of genetic engineering in the 1970s marked a new frontier in genome-editing technology. Gene-editing technologies have provided a plethora of benefits to the life sciences. The clustered regularly interspaced short palindromic repeats/CRISPR associated protein 9 (CRISPR/ Cas9) system is a versatile technology that provides the ability to add or remove DNA in the genome in a sequence-specific manner. Serious efforts are underway to improve the efficiency of CRISPR/Cas9 targeting and thus reduce off-target effects. Currently, various applications of CRISPR/Cas9 are used in cancer biology and oncology to perform robust site-specific gene editing, thereby becoming more useful for biological and clinical applications. Many variants and applications of CRISPR/Cas9 are being rapidly developed. Experimental approaches that are based on CRISPR technology have created a very promising tool that is inexpensive and simple for developing effective cancer therapeutics. This review discusses diverse applications of CRISPR-based gene-editing tools in oncology and potential future cancer therapies.

Personalized Metabolomics

The human metabolome is the cumulative product of ingested metabolites and those produced by the body and its microbiota. Together these metabolites can dynamically report on the health and disease state of an individual, as well as their response to drug treatments and other external perturbations. Profiling metabolites in human body fluids provides an opportunity to identify biomarkers and stratify patients for personalized treatments but requires the development of high-throughput approaches compatible with large cohort and longitudinal studies. Here we review in detail sample preparation and analytical liquid chromatography-mass spectrometry (LC-MS) methods to measure the broad chemical diversity of metabolites found in human plasma and urine.

Genetic variation in the Estonian population: pharmacogenomics study of adverse drug effects using electronic health records

Pharmacogenomics aims to tailor pharmacological treatment to each individual by considering associations between genetic polymorphisms and adverse drug effects (ADEs). With technological advances, pharmacogenomic research has evolved from candidate gene analyses to genome-wide association studies. Here, we integrate deep whole-genome sequencing (WGS) information with drug prescription and ADE data from Estonian electronic health record (EHR) databases to evaluate genome- and pharmacome-wide associations on an unprecedented scale. We leveraged WGS data of 2240 Estonian Biobank participants and imputed all single-nucleotide variants (SNVs) with allele counts over 2 for 13,986 genotyped participants. Overall, we identified 41 (10 novel) loss-of-function and 567 (134 novel) missense variants in 64 very important pharmacogenes. The majority of the detected variants were very rare with frequencies below 0.05%, and 6 of the novel loss-of-function and 99 of the missense variants were only detected as single alleles (allele count = 1). We also validated documented pharmacogenetic associations and detected new independent variants in known gene-drug pairs. Specifically, we found that CTNNA3 was associated with myositis and myopathies among individuals taking nonsteroidal anti-inflammatory oxicams and replicated this finding in an extended cohort of 706 individuals. These findings illustrate that population-based WGS-coupled EHRs are a useful tool for biomarker discovery.

Aspects of Modern Biobank Activity - Comprehensive Review

Biobanks play an increasing role in contemporary research projects. These units meet all requirements to regard them as a one of the most innovative and up-to-date in the field of biomedical research. They enable conducting wide-scale research by the professional collection of biological specimens and correlated clinical data. Pathology units may be perceived roots of biobanking. The review aims at describing the concept of biobanks, their model of function and scientific potential. It comprises the division of biobanks, sample preservation methods and IT solutions as well as guidelines and recommendations for management of a vast number of biological samples and clinical data. Therefore, appropriate standard operating procedures and protocols are outlined. Constant individualization of diagnostic process and treatment procedures creates the niche for translational units. Thus, the role of biobanks in personalized medicine was also specified. The exceptionality of biobanks poses some new ethical-legal issues which have various solutions, in each legal system, amongst the world. Finally, distribution and activity of European biobanks are mentioned.

Improved molecular karyotyping in glioblastoma

Uneven replication creates artifacts during whole genome amplification (WGA) that confound molecular karyotype assignment in single cells. Here, we present an improved WGA recipe that increased coverage and detection of copy number variants (CNVs) in single cells. We examined serial resections of glioblastoma (GBM) tumor from the same patient and found low-abundance clones containing CNVs in clinically relevant loci that were not observable using bulk DNA sequencing. We discovered extensive genomic variability in this class of tumor and provide a practical approach for investigating somatic mosaicism.

Large-Scale Low-Cost NGS Library Preparation Using a Robust Tn5 Purification and Tagmentation Protocol

Efficient preparation of high-quality sequencing libraries that well represent the biological sample is a key step for using next-generation sequencing in research. Tn5 enables fast, robust, and highly efficient processing of limited input material while scaling to the parallel processing of hundreds of samples. Here, we present a robust Tn5 transposase purification strategy based on an N-terminal His₆-Sumo3 tag. We demonstrate that libraries prepared with our in-house Tn5 are of the same quality as those processed with a commercially available kit (Nextera XT), while they dramatically reduce the cost of large-scale experiments. We introduce improved purification strategies for two versions of the Tn5 enzyme. The first version carries the previously reported point mutations E54K and L372P, and stably produces libraries of constant fragment size distribution, even if the Tn5-to-input molecule ratio varies. The second Tn5 construct carries an additional point mutation (R27S) in the DNA-binding domain. This construct allows for adjustment of the fragment size distribution based on enzyme concentration during tagmentation, a feature that opens new opportunities for use of Tn5 in customized experimental designs. We demonstrate the versatility of our Tn5 enzymes in different experimental settings, including a novel single-cell polyadenylation site mapping protocol as well as ultralow input DNA sequencing.

Pharmacogenetics: An Important Part of Drug Development with A Focus on Its Application

Since the human genome project in 2003, the view of personalized medicine to improve diagnosis and cure diseases at the molecular level became more real. Sequencing the human genome brought some benefits in medicine such as early detection of diseases with a genetic predisposition, treating patients with rare diseases, the design of gene therapy and the understanding of pharmacogenetics in the metabolism of drugs. This review explains the concepts of pharmacogenetics, polymorphisms, mutations, variations, and alleles, and how this information has helped us better understand the metabolism of drugs. Multiple resources are presented to promote reducing the gap between scientists, physicians, and patients in understanding the use and benefits of pharmacogenetics. Some of the most common clinical examples of genetic variants and how pharmacogenetics was used to determine treatment options for patients having these variants were discussed. Finally, we evaluated some of the challenges of implementing pharmacogenetics in a clinical setting and proposed actions to be taken to make pharmacogenetics a standard diagnostic tool in personalized medicine.

Ethical considerations surrounding germline next-generation sequencing of children with cancer

INTRODUCTION

The advent of next-generation sequencing (NGS) has introduced an exciting new era in biomedical research. NGS forms the foundation of current genetic testing approaches, including targeted gene panel testing, as well as more comprehensive whole-exome and whole-genome sequencing. Together, these approaches promise to provide critical insights into the understanding of health and disease. However, with NGS testing come many ethical questions and concerns, particularly when testing involves children. These concerns are especially relevant for children with cancer, where the testing of tumor and germline tissues is increasingly being incorporated into clinical care. Areas covered: In this manuscript, we explore the key ethical considerations related to conducting germline NGS testing in pediatric oncology, focusing on the four main principles of beneficence, non-maleficence, autonomy and justice. Expert commentary: The ethical issues surrounding germline NGS testing are complex and result in part from our limited understanding of the medical relevance of many of the results obtained and poor knowledge of the impacts of testing, both beneficial and detrimental, on patients and their families. In this article we discuss the risks and benefits of germline NGS testing and the arguments for and against such testing in children with cancer.

The side effects of translational omics: overtesting, overdiagnosis, overtreatment

High-throughput technologies such as next-generation genomics, transcriptomics and proteomics are capable of generating massive amounts of data quickly, and at relatively low costs. It is tempting to use this data for various medical applications including preclinical disease detection and for prediction of disease predisposition. Pilot projects, initiated by various research groups and Google, are currently underway, but results with not be available for a few years. We here summarize some possible difficulties with these approaches, by using examples from already tried cancer and other screening programs. Population screening, especially with multiparametric algorithms, will identify at least some false positive parameters and screening programs will identify abnormal results in otherwise healthy individuals. Whole genome sequencing will identify genetic changes of unknown significance and may not predict accurately future disease predisposition if the disease is also influenced by environmental factors. In screening programs, if the disease is rare, the positive predictive value of the test will be low, even if the test has excellent sensitivity and specificity. False positive results may require invasive procedures to delineate. Furthermore, screening programs are not effective if the cancer grows quickly, and will identify indolent forms of the disease with slow-growing tumors. It has also been recently shown that for some cancers, more intensive and radical treatments do not usually lead to better clinical outcomes. We conclude that new omics testing technologies should avoid overdiagnosis and overtreatment and need to be evaluated for overall clinical benefit before introduction to the clinic.

Advances in the Pharmacogenomics of Adverse Drug Reactions

Rapid developments in pharmacogenomics have been noticeable in recent years, and much of this knowledge has improved understanding of adverse drug reactions. This improved knowledge has largely been the result of improved sequencing technologies and falling costs in this area, as well as improved statistical techniques to analyse the data derived from studies. While the genetic reasons behind adverse drug reactions are becoming better understood, translation of this knowledge, particularly in terms of biomarkers that might be clinically applicable at the bedside, has been more difficult. Understanding of the technologies and their application is limited among practising clinicians. The cost of some of the technologies available may also be prohibitive in stretched healthcare economies. As education about the potential for applying pharmacogenomics improves and costs fall, understanding of adverse drug reactions and application of this knowledge in a clinical setting should improve.

Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

Defining the Clinical Value of a Genomic Diagnosis in the Era of Next-Generation Sequencing

As with all fields of medicine, the first step toward medical management of genetic disorders is obtaining an accurate diagnosis, which often requires testing at the molecular level. Unfortunately, given the large number of genetic conditions without a specific intervention, only rarely does a genetic diagnosis alter patient management-which raises the question, what is the added value of obtaining a molecular diagnosis? Given the fast-paced advancement of genomic technologies, this is an important question to address in the context of genome-scale testing. Here, we address the value of establishing a diagnosis using genome-scale testing and highlight the benefits and drawbacks of such testing. We also review and compare recent major studies implementing genome-scale sequencing methods to identify a molecular diagnosis in cohorts manifesting a broad range of Mendelian monogenic disorders. Finally, we discuss potential future applications of genomic sequencing, such as screening for rare conditions.

How Research on Human Progeroid and Antigeroid Syndromes Can Contribute to the Longevity Dividend Initiative

Although translational applications derived from research on basic mechanisms of aging are likely to enhance health spans and life spans for most of us (the longevity dividend), there will remain subsets of individuals with special vulnerabilities. Medical genetics is a discipline that describes such "private" patterns of aging and can reveal underlying mechanisms, many of which support genomic instability as a major mechanism of aging. We review examples of three classes of informative disorders: "segmental progeroid syndromes" (those that appear to accelerate multiple features of aging), "unimodal progeroid syndromes" (those that impact on a single disorder of aging), and "unimodal antigeroid syndromes," variants that provide enhanced protection against specific disorders of aging; we urge our colleagues to expand our meager research efforts on the latter, including ancillary somatic cell genetic approaches.

Navigating pleiotropy in precision medicine: pharmacogenes from trauma to behavioral health

A strong emerging principle in the field of precision medicine is that variation in any one pharmacogene may impact clinical outcome for more than one drug. Variants tested in the acute care setting often have downstream implications for other drugs impacting chronic disease management. A flexible framework is needed as clinicians and scientists move toward deploying automated decision support for gene-based drug dosing in electronic medical records.

Personalized Medicine for Sepsis

Sepsis is a complex syndrome triggered by infection and characterized by systemic deregulation of immune and inflammatory pathways. It is a major cause of death worldwide and results in the widespread use of antibiotics and substantial health care costs. In a vicious circle, sepsis treatment promotes the emergence of highly virulent and resistant pathogens and devastating nosocomial infections. Sepsis is a heterogeneous disease affecting many people worldwide. Because individual patients have different inflammatory responses and unique profiles of immune activation against pathogens, the most effective way to advance the treatment of sepsis is probably through a tailored approach. The advent of high-throughput technologies and the remarkable progress in the field of bioinformatics has allowed the subclassification of many pathological conditions. This has potential to provide better understanding of life-threatening infections in people. The study of host factors, however, needs to be integrated with studies on bacterial signaling in both symbiotic and pathogenic bacteria. Sepsis is certainly the sum of multiple host-microbial interactions and the metagenome should be extensively investigated. Personalized medicine is probably the only strategy able to deconstruct and reassemble our knowledge about sepsis, and its use should allow us to understand and manipulate sepsis as a wide, interconnected phenomenon with myriad variables and peculiarities. In this study, the recent advances in this area, the major challenges that remain, and the reasons why the septic patient should be approached as a superorganism are discussed.

The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease

The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been available for common disease. Here, we have developed a concept-recognition procedure that analyzes the frequencies of HPO disease annotations as identified in over five million PubMed abstracts by employing an iterative procedure to optimize precision and recall of the identified terms. We derived disease models for 3,145 common human diseases comprising a total of 132,006 HPO annotations. The HPO now comprises over 250,000 phenotypic annotations for over 10,000 rare and common diseases and can be used for examining the phenotypic overlap among common diseases that share risk alleles, as well as between Mendelian diseases and common diseases linked by genomic location. The annotations, as well as the HPO itself, are freely available.