Pre-Examination Factors Affecting Molecular Diagnostic Test Results and Interpretation: a Case-Based Approach.

Clin Chim Acta. 2016 Jun 16;

Authors: Payne DA, Baluchova K, Peoc'h KH, van Schaik RH, Chan KC, Maekawa M, Mamotte C, Russomando G, Rousseau F, Ahmad-Nejad P, IFCC Committee for Molecular Diagnostics (C-MD)

Abstract
BACKGROUND: Multiple organizations produce guidance documents that provide opportunities to harmonize quality practices for diagnostic testing. The International Organization for Standardization ISO 15189 standard addresses requirements for quality in management and technical aspects of the clinical laboratory. One technical aspect addresses the complexities of the pre-examination phase prior to diagnostic testing.
METHODS: The Committee for Molecular Diagnostics of the International Federation for Clinical Chemistry and Laboratory Medicine (also known as, IFCC C-MD) conducted a survey of international molecular laboratories and determined ISO 15189 to be the most referenced guidance document. In this review, the IFCC C-MD provides case-based examples illustrating the value of select pre-examination processes as these processes relate to molecular diagnostic testing. Case-based examples in infectious disease, oncology, inherited disease and pharmacogenomics address the utility of: 1) providing information to patients and users, 2) designing requisition forms, 3) obtaining informed consent and 4) maintaining sample integrity prior to testing.
CONCLUSIONS: The pre-examination phase requires extensive and consistent communication between the laboratory, the healthcare provider and the end user. The clinical vignettes presented in this paper illustrate the value of applying select ISO 15189 recommendations for general laboratory to the more specialized area of Molecular Diagnostics.

PMID: 27321365 [PubMed - as supplied by publisher]

Recent advance in the pharmacogenomics of human Solute Carrier Transporters (SLCs) in drug disposition.

Adv Drug Deliv Rev. 2016 Jun 16;

Authors: Zhou F, Zhu L, Wang K, Murray M

Abstract
Drug pharmacokinetics is influenced by the function of metabolising enzymes and influx/efflux transporters. Genetic variability of these genes is known to impact on clinical therapies. Solute carrier transporters (SLCs) are the primary influx transporters responsible for the cellular uptake of drug molecules, which consequently, impact on drug efficacy and toxicity. The Organic anion transporting polypeptides (OATPs), Organic anion transporters (OATs) and Organic cation transporters (OCTs/OCTNs) are the most important SLCs involved in drug disposition. The information regarding the influence of SLC polymorphisms on drug pharmacokinetics is limited and remains a hot topic of pharmaceutical research. This review summarises the recent advance in the pharmacogenomics of SLCs with an emphasis on human OATPs, OATs and OCTs/OCTNs. Our current appreciation of the degree of variability in these transporters may contribute to better understanding the inter-patient variation of therapies and thus, guide the optimisation of clinical treatments.

PMID: 27320645 [PubMed - as supplied by publisher]

FDA drug labeling: rich resources to facilitate precision medicine, drug safety, and regulatory science.

Drug Discov Today. 2016 Jun 15;

Authors: Fang H, Harris SC, Liu Z, Zhou G, Zhang G, Xu J, Rosario L, Howard P, Tong W

Abstract
Here, we provide a concise overview of US Food and Drug Administration (FDA) drug labeling, which details drug products, drug-drug interactions, adverse drug reactions (ADRs), and more. Labeling data have been collected over several decades by the FDA and are an important resource for regulatory research and decision making. However, navigating through these data is challenging. To aid such navigation, the FDALabel database was developed, which contains a set of approximately 80000 labeling data. The full-text searching capability of FDALabel and querying based on any combination of specific sections, document types, market categories, market date, and other labeling information makes it a powerful and attractive tool for a variety of applications. Here, we illustrate the utility of FDALabel using case scenarios in pharmacogenomics biomarkers and ADR studies.

PMID: 27319291 [PubMed - as supplied by publisher]

Mass Spectrometry in Precision Medicine: Phenotypic Measurements Alongside Pharmacogenomics.

Clin Chem. 2016 Jan;62(1):70-6

Authors: Clarke NJ

Abstract
BACKGROUND: Precision medicine is becoming a major topic within the medical community and is gaining traction as a standard approach in many disciplines. This approach typically revolves around the use of a patient's genetic makeup to allow the physician to choose the appropriate course of treatment. In many cases the genetic information directs the drug to be used to treat the patient. In other cases the genetic markers associated with enzyme function may inform dosage recommendations. However there is a second way in which precision medicine can be practiced-that is, by therapeutic drug monitoring (TDM).
CONTENT: A review of the use of mass spectrometry for TDM in the arena of precision medicine is undertaken. Because the measurement of a drug or its metabolites provides the physician with a snapshot of the therapeutic exposure the patient is undergoing, these concentrations can be thought of as an actual phenotype measurement based around the patient's genetics coupled with all of the environmental, pharmacological, and nutritional variables. The outcome of a TDM measurement by mass spectrometry provides the patient's current phenotype vs the potential phenotype imputed by the genetics.
SUMMARY: The use of mass spectrometry can provide an understanding of how a drug is interacting with the patient, and is orthoganol to the information provided by pharmacogenomic assays. Further, the speed and relatively low expense of drug monitoring by mass spectrometry makes it an ideal test for precision medicine patient management.

PMID: 26555454 [PubMed - indexed for MEDLINE]

Safety and Immunogenicity of the Recombinant BCG Vaccine AERAS-422 in Healthy BCG-naïve Adults: A Randomized, Active-controlled, First-in-human Phase 1 Trial.

EBioMedicine. 2016 May;7:278-286

Authors: Hoft DF, Blazevic A, Selimovic A, Turan A, Tennant J, Abate G, Fulkerson J, Zak DE, Walker R, McClain B, Sadoff J, Scott J, Shepherd B, Ishmukhamedov J, Hokey DA, Dheenadhayalan V, Shankar S, Amon L, Navarro G, Podyminogin R, Aderem A, Barker L, Brennan M, Wallis RS, Gershon AA, Gershon MD, Steinberg S

Abstract
BACKGROUND: We report a first-in-human trial evaluating safety and immunogenicity of a recombinant BCG, AERAS-422, over-expressing TB antigens Ag85A, Ag85B, and Rv3407 and expressing mutant perfringolysin.
METHODS: This was a randomized, double-blind, dose-escalation trial in HIV-negative, healthy adult, BCG-naïve volunteers, negative for prior exposure to Mtb, at one US clinical site. Volunteers were randomized 2:1 at each dose level to receive a single intradermal dose of AERAS-422 (>10(5)-<10(6)CFU=low dose, ≥10(6)-<10(7)CFU=high dose) or non-recombinant Tice BCG (1-8×10(5)CFU). Randomization used an independently prepared randomly generated sequence of treatment assignments. The primary and secondary outcomes were safety and immunogenicity, respectively, assessed in all participants through 182days post-vaccination. ClinicalTrials.gov registration number: NCT01340820.
FINDINGS: Between Nov 2010 and Aug 2011, 24 volunteers were enrolled (AERAS-422 high dose, n=8; AERAS-422 low dose, n=8; Tice BCG, n=8); all were included in the safety and immunogenicity analyses. All 24 subjects had at least one adverse event, primarily expected local reactions. High dose AERAS-422 vaccination induced Ag85A- and Ag85B-specific lymphoproliferative responses and marked anti-mycobacterial activity in a whole blood bactericidal activity culture assay (WBA), but was associated with varicella zoster virus (VZV) reactivation in two vaccinees. These volunteers displayed high BCG-specific IFN-γ responses pre- and post-vaccination possibly predisposing them to autocrine/paracrine negative regulation of immune control of latent VZV. A systems biology transcriptomal approach identified positive correlations between post-vaccination T cell expression modules and WBA, and negative correlations between post-vaccination monocyte expression modules and WBA. The expression of one key macrophage marker (F4/80) was constitutively elevated in the two volunteers with zoster.
INTERPRETATION: The unexpected development of VZV in two of eight healthy adult vaccine recipients resulted in discontinuation of AERAS-422 vaccine development. Immunological and transcriptomal data identified correlations with the development of TB immunity and VZV that require further investigation.
FUNDING: Aeras, FDA, Bill and Melinda Gates Foundation.

PMID: 27322481 [PubMed - as supplied by publisher]

Understanding probiotics' role in allergic children: the clue of gut microbiota profiling.

Curr Opin Allergy Clin Immunol. 2015 Oct;15(5):495-503

Authors: Vernocchi P, Del Chierico F, Fiocchi AG, El Hachem M, Dallapiccola B, Rossi P, Putignani L

Abstract
PURPOSE OF REVIEW: To investigate the functional role of gut microbiota in diet-modulated diseases, evaluating probiotic administration effects by systems biology-driven approaches. Understanding the role of host-gut microbial and gut microbe-microbe interactions in either allergic and healthy children may assist in selecting effective and targeted probiotics for personalized therapies.
RECENT FINDINGS: Food allergy shows a significant increase, especially in Western countries where growing epidemiological data indicate prevalence of small family groups, limited rate of infections in childhood compared with low-income countries, high consumption of sterile foods, hence stimulating a poor trigger of the gut immune system. Therefore, new therapeutic strategies to treat food allergy consist of probiotic administration since early life, thus modulating gut microbiota through immune system stimulation at the mucosal level.
SUMMARY: Currently, new insights for probiotic selection should take into consideration both phenotyping and genotyping bacterial features and host-microbial cross-talk at gut level, by employing multicomponent systems biology approaches to unveil gut ecosystem dynamics in terms of bacteria phylotypes and their metabolic activities. Moreover, new food processes need to be considered to assess the actual performance of probiotic strains administered to allergic patients. The advent of high-performance platforms employing genomic- and mass spectrometry-based techniques has opened new perspectives on the gut microbiota field, and may now serve as advanced tool to dynamically investigate the interplay between probiotics and gut microbiota ecology under allergic conditions.

PMID: 26258924 [PubMed - indexed for MEDLINE]

Malaria vaccine clinical trials: what's on the horizon.

Curr Opin Immunol. 2015 Aug;35:98-106

Authors: Moreno A, Joyner C

Abstract
Significant progress toward a malaria vaccine, specifically for Plasmodium falciparum, has been made in the past few years with the completion of numerous clinical trials. Each trial has utilized a unique combination of antigens, delivery platforms, and adjuvants, which has provided the research community with a wealth of critical information to apply towards the development of next generation malaria vaccines. Despite the progress toward a P. falciparum vaccine, P. vivax vaccine research requires more momentum and additional investigations to identify novel vaccine candidates. In this review, recently completed and ongoing malaria vaccine clinical trials as well as vaccine candidates that are in the development pipeline are reviewed. Perspectives for future research using post-genomic mining, nonhuman primate models, and systems biology are also discussed.

PMID: 26172291 [PubMed - indexed for MEDLINE]

Evolutionary trends and functional anatomy of the human expanded autophagy network.

Autophagy. 2015;11(9):1652-67

Authors: Till A, Saito R, Merkurjev D, Liu JJ, Syed GH, Kolnik M, Siddiqui A, Glas M, Scheffler B, Ideker T, Subramani S

Abstract
All eukaryotic cells utilize autophagy for protein and organelle turnover, thus assuring subcellular quality control, homeostasis, and survival. In order to address recent advances in identification of human autophagy associated genes, and to describe autophagy on a system-wide level, we established an autophagy-centered gene interaction network by merging various primary data sets and by retrieving respective interaction data. The resulting network ('AXAN') was analyzed with respect to subnetworks, e.g. the prime gene subnetwork (including the core machinery, signaling pathways and autophagy receptors) and the transcription subnetwork. To describe aspects of evolution within this network, we assessed the presence of protein orthologs across 99 eukaryotic model organisms. We visualized evolutionary trends for prime gene categories and evolutionary tracks for selected AXAN genes. This analysis confirms the eukaryotic origin of autophagy core genes while it points to a diverse evolutionary history of autophagy receptors. Next, we used module identification to describe the functional anatomy of the network at the level of pathway modules. In addition to obvious pathways (e.g., lysosomal degradation, insulin signaling) our data unveil the existence of context-related modules such as Rho GTPase signaling. Last, we used a tripartite, image-based RNAi - screen to test candidate genes predicted to play a role in regulation of autophagy. We verified the Rho GTPase, CDC42, as a novel regulator of autophagy-related signaling. This study emphasizes the applicability of system-wide approaches to gain novel insights into a complex biological process and to describe the human autophagy pathway at a hitherto unprecedented level of detail.

PMID: 26103419 [PubMed - indexed for MEDLINE]

Analysis of Wnt signalling dynamics during colon crypt development in 3D culture.

Sci Rep. 2015;5:11036

Authors: Tan CW, Hirokawa Y, Burgess AW

Abstract
Many systems biology studies lack context-relevant data and as a consequence the predictive capabilities can be limited in developing targeted cancer therapeutics. Production of colon crypt in vitro is ideal for studying colon systems biology. This report presents the first production of, to our knowledge, physiologically-shaped, functional colon crypts in vitro (i.e. single crypts with cells expressing Mucin 2 and Chromogranin A). Time-lapsed monitoring of crypt formation revealed an increased frequency of single-crypt formation in the absence of noggin. Using quantitative 3D immunofluorescence of β-catenin and E-cadherin, spatial-temporal dynamics of these proteins in normal colon crypt cells stimulated with Wnt3A or inhibited by cycloheximide has been measured. Colon adenoma cultures established from APC(min/+) mouse have developmental differences and β-catenin spatial localization compared to normal crypts. Quantitative data describing the effects of signalling pathways and proteins dynamics for both normal and adenomatous colon crypts is now within reach to inform a systems approach to colon crypt biology.

PMID: 26087250 [PubMed - indexed for MEDLINE]

Metabolic Profiling and Phenotyping of Central Nervous System Diseases: Metabolites Bring Insights into Brain Dysfunctions.

J Neuroimmune Pharmacol. 2015 Sep;10(3):402-24

Authors: Dumas ME, Davidovic L

Abstract
Metabolic phenotyping corresponds to the large-scale quantitative and qualitative analysis of the metabolome i.e., the low-molecular weight <1 KDa fraction in biological samples, and provides a key opportunity to advance neurosciences. Proton nuclear magnetic resonance and mass spectrometry are the main analytical platforms used for metabolic profiling, enabling detection and quantitation of a wide range of compounds of particular neuro-pharmacological and physiological relevance, including neurotransmitters, secondary messengers, structural lipids, as well as their precursors, intermediates and degradation products. Metabolic profiling is therefore particularly indicated for the study of central nervous system by probing metabolic and neurochemical profiles of the healthy or diseased brain, in preclinical models or in human samples. In this review, we introduce the analytical and statistical requirements for metabolic profiling. Then, we focus on key studies in the field of metabolic profiling applied to the characterization of animal models and human samples of central nervous system disorders. We highlight the potential of metabolic profiling for pharmacological and physiological evaluation, diagnosis and drug therapy monitoring of patients affected by brain disorders. Finally, we discuss the current challenges in the field, including the development of systems biology and pharmacology strategies improving our understanding of metabolic signatures and mechanisms of central nervous system diseases.

PMID: 25616565 [PubMed - indexed for MEDLINE]

GNormPlus: An Integrative Approach for Tagging Genes, Gene Families, and Protein Domains.

Biomed Res Int. 2015;2015:918710

Authors: Wei CH, Kao HY, Lu Z

Abstract
The automatic recognition of gene names and their associated database identifiers from biomedical text has been widely studied in recent years, as these tasks play an important role in many downstream text-mining applications. Despite significant previous research, only a small number of tools are publicly available and these tools are typically restricted to detecting only mention level gene names or only document level gene identifiers. In this work, we report GNormPlus: an end-to-end and open source system that handles both gene mention and identifier detection. We created a new corpus of 694 PubMed articles to support our development of GNormPlus, containing manual annotations for not only gene names and their identifiers, but also closely related concepts useful for gene name disambiguation, such as gene families and protein domains. GNormPlus integrates several advanced text-mining techniques, including SimConcept for resolving composite gene names. As a result, GNormPlus compares favorably to other state-of-the-art methods when evaluated on two widely used public benchmarking datasets, achieving 86.7% F1-score on the BioCreative II Gene Normalization task dataset and 50.1% F1-score on the BioCreative III Gene Normalization task dataset. The GNormPlus source code and its annotated corpus are freely available, and the results of applying GNormPlus to the entire PubMed are freely accessible through our web-based tool PubTator.

PMID: 26380306 [PubMed - indexed for MEDLINE]

Identification and Progression of Heart Disease Risk Factors in Diabetic Patients from Longitudinal Electronic Health Records.

Biomed Res Int. 2015;2015:636371

Authors: Jonnagaddala J, Liaw ST, Ray P, Kumar M, Dai HJ, Hsu CY

Abstract
Heart disease is the leading cause of death worldwide. Therefore, assessing the risk of its occurrence is a crucial step in predicting serious cardiac events. Identifying heart disease risk factors and tracking their progression is a preliminary step in heart disease risk assessment. A large number of studies have reported the use of risk factor data collected prospectively. Electronic health record systems are a great resource of the required risk factor data. Unfortunately, most of the valuable information on risk factor data is buried in the form of unstructured clinical notes in electronic health records. In this study, we present an information extraction system to extract related information on heart disease risk factors from unstructured clinical notes using a hybrid approach. The hybrid approach employs both machine learning and rule-based clinical text mining techniques. The developed system achieved an overall microaveraged F-score of 0.8302.

PMID: 26380290 [PubMed - indexed for MEDLINE]

Text Mining for Translational Bioinformatics.

Biomed Res Int. 2015;2015:368264

Authors: Dai HJ, Wei CH, Kao HY, Liu RL, Tsai RT, Lu Z

PMID: 26380272 [PubMed - indexed for MEDLINE]

TRRUST: a reference database of human transcriptional regulatory interactions.

Sci Rep. 2015;5:11432

Authors: Han H, Shim H, Shin D, Shim JE, Ko Y, Shin J, Kim H, Cho A, Kim E, Lee T, Kim H, Kim K, Yang S, Bae D, Yun A, Kim S, Kim CY, Cho HJ, Kang B, Shin S, Lee I

Abstract
The reconstruction of transcriptional regulatory networks (TRNs) is a long-standing challenge in human genetics. Numerous computational methods have been developed to infer regulatory interactions between human transcriptional factors (TFs) and target genes from high-throughput data, and their performance evaluation requires gold-standard interactions. Here we present a database of literature-curated human TF-target interactions, TRRUST (transcriptional regulatory relationships unravelled by sentence-based text-mining, http://www.grnpedia.org/trrust), which currently contains 8,015 interactions between 748 TF genes and 1,975 non-TF genes. A sentence-based text-mining approach was employed for efficient manual curation of regulatory interactions from approximately 20 million Medline abstracts. To the best of our knowledge, TRRUST is the largest publicly available database of literature-curated human TF-target interactions to date. TRRUST also has several useful features: i) information about the mode-of-regulation; ii) tests for target modularity of a query TF; iii) tests for TF cooperativity of a query target; iv) inferences about cooperating TFs of a query TF; and v) prioritizing associated pathways and diseases with a query TF. We observed high enrichment of TF-target pairs in TRRUST for top-scored interactions inferred from high-throughput data, which suggests that TRRUST provides a reliable benchmark for the computational reconstruction of human TRNs.

PMID: 26066708 [PubMed - indexed for MEDLINE]

Using Literature-Based Discovery to Explain Adverse Drug Effects.

J Med Syst. 2016 Aug;40(8):185

Authors: Hristovski D, Kastrin A, Dinevski D, Burgun A, Žiberna L, Rindflesch TC

Abstract
We report on our research in using literature-based discovery (LBD) to provide pharmacological and/or pharmacogenomic explanations for reported adverse drug effects. The goal of LBD is to generate novel and potentially useful hypotheses by analyzing the scientific literature and optionally some additional resources. Our assumption is that drugs have effects on some genes or proteins and that these genes or proteins are associated with the observed adverse effects. Therefore, by using LBD we try to find genes or proteins that link the drugs with the reported adverse effects. These genes or proteins can be used to provide insight into the processes causing the adverse effects. Initial results show that our method has the potential to assist in explaining reported adverse drug effects.

PMID: 27318993 [PubMed - as supplied by publisher]

Identification and characterization of sulfated glycoproteins from small cell lung carcinoma cells assisted by management of molecular charges.

Glycoconj J. 2016 Jun 18;

Authors: Toyoda M, Kaji H, Sawaki H, Togayachi A, Angata T, Narimatsu H, Kameyama A

Abstract
Proteins carrying sulfated glycans (i.e., sulfated glycoproteins) are known to be associated with diseases, such as cancer, cystic fibrosis, and osteoarthritis. Sulfated glycoproteins, however, have not been isolated or characterized from complex biological samples due to lack of appropriate tools for their enrichment. Here, we describe a method to identify and characterize sulfated glycoproteins that are involved in chemical modifications to control the molecular charge of the peptides. In this method, acetohydrazidation of carboxyl groups was performed to accentuate the negative charge of the sulfate group, and Girard's T modification of aspartic acid was performed to assist in protein identification by MS tagging. Using this approach, we identified and characterized the sulfated glycoproteins: Golgi membrane protein 1, insulin-like growth factor binding protein-like 1, and amyloid beta precursor-like protein 1 from H2171 cells, a small cell lung carcinoma cell line. These sulfated glycoproteins carry a complex-type N-glycan with a core fucose and 4'-O-sulfated LacdiNAc as the major glycan.

PMID: 27318476 [PubMed - as supplied by publisher]

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network.

J Genet Genomics. 2015 Dec 15;

Authors: Al-Harazi O, Al Insaif S, Al-Ajlan MA, Kaya N, Dzimiri N, Colak D

Abstract
A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field.

PMID: 27318646 [PubMed - as supplied by publisher]

Using Literature-Based Discovery to Explain Adverse Drug Effects.

J Med Syst. 2016 Aug;40(8):185

Authors: Hristovski D, Kastrin A, Dinevski D, Burgun A, Žiberna L, Rindflesch TC

Abstract
We report on our research in using literature-based discovery (LBD) to provide pharmacological and/or pharmacogenomic explanations for reported adverse drug effects. The goal of LBD is to generate novel and potentially useful hypotheses by analyzing the scientific literature and optionally some additional resources. Our assumption is that drugs have effects on some genes or proteins and that these genes or proteins are associated with the observed adverse effects. Therefore, by using LBD we try to find genes or proteins that link the drugs with the reported adverse effects. These genes or proteins can be used to provide insight into the processes causing the adverse effects. Initial results show that our method has the potential to assist in explaining reported adverse drug effects.

PMID: 27318993 [PubMed - as supplied by publisher]

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SETD2 and DNMT3A screen in the Sotos-like syndrome French cohort.

J Med Genet. 2016 Jun 17;

Authors: Tlemsani C, Luscan A, Leulliot N, Bieth E, Afenjar A, Baujat G, Doco-Fenzy M, Goldenberg A, Lacombe D, Lambert L, Odent S, Pasche J, Sigaudy S, Buffet A, Violle-Poirsier C, Briand-Suleau A, Laurendeau I, Chin M, Saugier-Veber P, Vidaud D, Cormier-Daire V, Vidaud M, Pasmant E, Burglen L

Abstract
BACKGROUND: Heterozygous NSD1 mutations were identified in 60%-90% of patients with Sotos syndrome. Recently, mutations of the SETD2 and DNMT3A genes were identified in patients exhibiting only some Sotos syndrome features. Both NSD1 and SETD2 genes encode epigenetic 'writer' proteins that catalyse methylation of histone 3 lysine 36 (H3K36me). The DNMT3A gene encodes an epigenetic 'reader' protein of the H3K36me chromatin mark.
METHODS: We aimed at confirming the implication of DNMT3A and SETD2 mutations in an overgrowth phenotype, through a comprehensive targeted-next generation sequencing (NGS) screening in 210 well-phenotyped index cases with a Sotos-like phenotype and no NSD1 mutation, from a French cohort.
RESULTS: Six unreported heterozygous likely pathogenic variants in DNMT3A were identified in seven patients: two nonsense variants and four de novo missense variants. One de novo unreported heterozygous frameshift variant was identified in SETD2 in one patient. All the four DNMT3A missense variants affected DNMT3A functional domains, suggesting a potential deleterious impact. DNMT3A-mutated index cases shared similar clinical features including overgrowth phenotype characterised by postnatal tall stature (≥+2SD), macrocephaly (≥+2SD), overweight or obesity at older age, intellectual deficiency and minor facial features. The phenotype associated with SETD2 mutations remains to be described more precisely. The p.Arg882Cys missense de novo constitutional DNMT3A variant found in two patients is the most frequent DNMT3A somatic mutation in acute leukaemia.
CONCLUSIONS: Our results illustrate the power of targeted NGS to identify rare disease-causing variants. These observations provided evidence for a unifying mechanism (disruption of apposition and reading of the epigenetic chromatin mark H3K36me) that causes an overgrowth syndrome phenotype. Further studies are needed in order to assess the role of SETD2 and DNMT3A in intellectual deficiency without overgrowth.

PMID: 27317772 [PubMed - as supplied by publisher]