Genome Medicine Journal Impact Factor & Information

Publisher: BioMed Central

Journal description

Current impact factor: 5.34

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 5.338
2013 Impact Factor 4.942
2012 Impact Factor 3.397

Impact factor over time

Impact factor

Additional details

5-year impact 4.35
Cited half-life 3.00
Immediacy index 0.54
Eigenfactor 0.01
Article influence 1.84
ISSN 1756-994X

Publisher details

BioMed Central

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Publisher's version/PDF may be used
    • Eligible UK authors may deposit in OpenDepot
    • Creative Commons Attribution License
    • Copy of License must accompany any deposit.
    • All titles are open access journals
    • 'BioMed Central' is an imprint of 'Springer Verlag (Germany)'
  • Classification
    ​ green

Publications in this journal

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    ABSTRACT: Besides its growing importance in clinical diagnostics and understanding the genetic basis of Mendelian and complex diseases, whole exome sequencing (WES) is a rich source of additional information of potential clinical utility for physicians, patients and their families. We analyzed the frequency and nature of single nucleotide variants (SNVs) considered secondary findings and recessive disease allele carrier status in the exomes of 8554 individuals from a large, randomly sampled cohort study and 2514 patients from a study of presumed Mendelian disease having undergone WES. We used the same sequencing platform and data processing pipeline to analyze all samples and characterized the distributions of reported pathogenic (ClinVar, Human Gene Mutation Database (HGMD)) and predicted deleterious variants in the pre-specified American College of Medical Genetics and Genomics (ACMG) secondary findings and recessive disease genes in different ethnic groups. In the 56 ACMG secondary findings genes, the average number of predicted deleterious variants per individual was 0.74, and the mean number of ClinVar reported pathogenic variants was 0.06. We observed an average of 10 deleterious and 0.78 ClinVar reported pathogenic variants per individual in 1423 autosomal recessive disease genes. By repeatedly sampling pairs of exomes, 0.5 % of the randomly generated couples were at 25 % risk of having an affected offspring for an autosomal recessive disorder based on the ClinVar variants. By investigating reported pathogenic and novel, predicted deleterious variants we estimated the lower and upper limits of the population fraction for which exome sequencing may reveal additional medically relevant information. We suggest that the observed wide range for the lower and upper limits of these frequency numbers will be gradually reduced due to improvement in classification databases and prediction algorithms.
    Genome Medicine 12/2015; 7(1). DOI:10.1186/s13073-015-0171-1
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    ABSTRACT: Fueled by widespread applications of high-throughput next generation sequencing (NGS) technologies and urgent need to counter threats of pathogenic viruses, large-scale studies were conducted recently to investigate virus integration in host genomes (for example, human tumor genomes) that may cause carcinogenesis or other diseases. A limiting factor in these studies, however, is rapid virus evolution and resulting polymorphisms, which prevent reads from aligning readily to commonly used virus reference genomes, and, accordingly, make virus integration sites difficult to detect. Another confounding factor is host genomic instability as a result of virus insertions. To tackle these challenges and improve our capability to identify cryptic virus-host fusions, we present a new approach that detects Virus intEgration sites through iterative Reference SEquence customization (VERSE). To the best of our knowledge, VERSE is the first approach to improve detection through customizing reference genomes. Using 19 human tumors and cancer cell lines as test data, we demonstrated that VERSE substantially enhanced the sensitivity of virus integration site detection. VERSE is implemented in the open source package VirusFinder 2 that is available at Electronic supplementary material The online version of this article (doi:10.1186/s13073-015-0126-6) contains supplementary material, which is available to authorized users.
    Genome Medicine 12/2015; 7(1):2. DOI:10.1186/s13073-015-0126-6
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    ABSTRACT: Regenerative medicine has a three-body problem: alignment of the dynamics of the genome, stem cell and patient. Focusing on the rare inherited fragile skin disorder epidermolysis bullosa, three recent innovative studies have used induced pluripotent stem cells and gene correction, revertant mosaicism or genome editing to advance the prospects of better cell-based therapeutics to restore skin structure and function for epidermolysis bullosa and potentially other inherited diseases.
    Genome Medicine 12/2015; 7(1):15. DOI:10.1186/s13073-015-0141-7
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    ABSTRACT: Editorial summary Three-dimensional organotypic culture models show great promise as a tool for cancer precision medicine, with potential applications for oncogene modeling, gene discovery and chemosensitivity studies.
    Genome Medicine 12/2015; 7(1):32. DOI:10.1186/s13073-015-0158-y
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    ABSTRACT: Neurodevelopmental disorders such as autism and intellectual disability have a sex bias skewed towards boys; however, systematic assessment of this bias is complicated by the presence of significant genetic and phenotypic heterogeneity of these disorders. To assess the extent and characteristics of sex bias, we analyzed the frequency of comorbid features, the magnitude of genetic load, and the existence of family history within 32,155 individuals ascertained clinically for autism or intellectual disability/developmental delay (ID/DD), including a subset of 8,373 individuals carrying rare copy-number variants (CNVs). We find that girls were more likely than boys to show comorbid features within both autism (P = 2.9 × 10(-6), OR = 1.34) and ID/DD (P = 7.2 × 10(-4), OR = 1.08) cohorts. The frequency of comorbid features in ID/DD was higher in boys (1q21.1 deletion, 15q11.2q13.1 duplication) or girls (15q13.3 deletion, 16p11.2 deletion) carrying specific CNVs associated with variable expressivity while such differences were the smallest for syndromic CNVs (Smith-Magenis syndrome, DiGeorge syndrome). The extent of the male sex bias also varied according to the specific comorbid feature, being most extreme for autism with psychiatric comorbidities and least extreme for autism comorbid with epilepsy. The sex ratio was also specific to certain CNVs, from an 8:1 male:female ratio observed among autistic individuals carrying the 22q11.2 duplication to 1.3:1 male:female ratio in those carrying the 16p11.2 deletion. Girls carried a higher burden of large CNVs compared to boys for autism or ID/DD, and this difference diminished when severe comorbidities were considered. Affected boys showed a higher frequency of neuropsychiatric family histories such as autism (P = 0.01) or specific learning disability (P = 0.03), while affected girls showed a higher frequency of developmental family histories such as growth abnormalities (P = 0.02). The sex bias within neurodevelopmental disorders is influenced by the presence of specific comorbidities, specific CNVs, mutational burden, and pre-existing family history of neurodevelopmental phenotypes.
    Genome Medicine 12/2015; 7(1). DOI:10.1186/s13073-015-0216-5
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    ABSTRACT: Recent work has linked specific genetic variation found in human populations to risk for developing neuropsychiatric diseases. How that risk is mediated through molecular-, cellular- and systems-level mechanisms now becomes the central question in this field. Two recent papers studying high-penetrance copy number variation at chromosome 16p11.2 find large changes in brain structure, refining hypotheses about the regions of the brain that are affected and implicating specific neurodevelopmental processes in these changes.
    Genome Medicine 12/2015; 7(1):13. DOI:10.1186/s13073-015-0140-8
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    ABSTRACT: Lymphocyte receptor repertoires are continually shaped throughout the lifetime of an individual in response to environmental and pathogenic exposure. Thus, they may serve as a fingerprint of an individual's ongoing immunological status (e.g., healthy, infected, vaccinated), with far-reaching implications for immunodiagnostics applications. The advent of high-throughput immune repertoire sequencing now enables the interrogation of immune repertoire diversity in an unprecedented and quantitative manner. However, steadily increasing sequencing depth has revealed that immune repertoires vary greatly among individuals in their composition; correspondingly, it has been reported that there are few shared sequences indicative of immunological status ('public clones'). Disconcertingly, this means that the wealth of information gained from repertoire sequencing remains largely unused for determining the current status of immune responses, thereby hampering the implementation of immune-repertoire-based diagnostics. Here, we introduce a bioinformatics repertoire-profiling framework that possesses the advantage of capturing the diversity and distribution of entire immune repertoires, as opposed to singular public clones. The framework relies on Hill-based diversity profiles composed of a continuum of single diversity indices, which enable the quantification of the extent of immunological information contained in immune repertoires. We coupled diversity profiles with unsupervised (hierarchical clustering) and supervised (support vector machine and feature selection) machine learning approaches in order to correlate patients' immunological statuses with their B- and T-cell repertoire data. We could predict with high accuracy (greater than or equal to 80 %) a wide range of immunological statuses such as healthy, transplantation recipient, and lymphoid cancer, suggesting as a proof of principle that diversity profiling can recover a large amount of immunodiagnostic fingerprints from immune repertoire data. Our framework is highly scalable as it easily allowed for the analysis of 1000 simulated immune repertoires; this exceeds the size of published immune repertoire datasets by one to two orders of magnitude. Our framework offers the possibility to advance immune-repertoire-based fingerprinting, which may in the future enable a systems immunogenomics approach for vaccine profiling and the accurate and early detection of disease and infection.
    Genome Medicine 12/2015; 7(1). DOI:10.1186/s13073-015-0169-8
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    ABSTRACT: Cystic fibrosis is the most common genetically determined, life-limiting disorder in populations of European ancestry. The genetic basis of cystic fibrosis is well established to be mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene that codes for an apical membrane chloride channel principally expressed by epithelial cells. Conventional approaches to cystic fibrosis care involve a heavy daily burden of supportive treatments to combat lung infection, help clear airway secretions and maintain nutritional status. In 2012, a new era of precision medicine in cystic fibrosis therapeutics began with the licensing of a small molecule, ivacaftor, which successfully targets the underlying defect and improves CFTR function in a subgroup of patients in a genotype-specific manner. Here, we review the three main targeted approaches that have been adopted to improve CFTR function: potentiators, which recover the function of CFTR at the apical surface of epithelial cells that is disrupted in class III and IV genetic mutations; correctors, which improve intracellular processing of CFTR, increasing surface expression, in class II mutations; and production correctors or read-through agents, which promote transcription of CFTR in class I mutations. The further development of such approaches offers great promise for future therapeutic strategies in cystic fibrosis.
    Genome Medicine 12/2015; 7(1). DOI:10.1186/s13073-015-0223-6
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    ABSTRACT: Variant interpretation is a central challenge in genomic medicine. A recent study demonstrates the power of Bayesian statistical approaches to improve interpretation of variants in the context of specific genes and syndromes. Such Bayesian approaches combine frequency (in the form of observed genetic variation in cases and controls) with biological annotations to determine a probability of pathogenicity. These Bayesian approaches complement other efforts to catalog human variation. See related Research; 10.1186/s13073-014-0120-4
    Genome Medicine 12/2015; 7(1):4. DOI:10.1186/s13073-015-0129-3
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    ABSTRACT: Somatic mutations affecting components of the RNA splicing machinery occur with high frequencies across many tumor types. These mutations give rise to distinct alterations in normal splice site and exon recognition, such as unusual 3' splice site preferences, that likely contribute to tumorigenesis. We analyzed genome-wide patterns of RNA splicing across 805 matched tumor and normal control samples from 16 distinct cancer types to identify signals of abnormal cancer-associated splicing. We found that abnormal RNA splicing, typified by widespread intron retention, is common across cancers even in the absence of mutations directly affecting the RNA splicing machinery. Almost all liquid and solid cancer types exhibited frequent retention of both alternative and constitutive introns relative to control normal tissues. The sole exception was breast cancer, where intron retention typified adjacent normal rather than cancer tissue. Different introns were preferentially retained in specific cancer types, although a small subset of introns enriched for genes encoding RNA splicing and export factors exhibited frequent retention across diverse cancers. The extent of intron retention correlated with the presence of IDH1 and IDH2 mutations in acute myeloid leukemia and across molecular subtypes in breast cancer. Many introns that were preferentially retained in primary cancers were present at high levels in the cytoplasmic mRNA pools of cancer cell lines. Our data indicate that abnormal RNA splicing is a common characteristic of cancers even in the absence of mutational insults to the splicing machinery, and suggest that intron-containing mRNAs contribute to the transcriptional diversity of many cancers.
    Genome Medicine 12/2015; 7(1). DOI:10.1186/s13073-015-0168-9