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Cells Jan 2019As the primary cellular location for respiration and energy production, mitochondria serve in a critical capacity to the cell. Yet, by virtue of this very function of... (Review)
Review
As the primary cellular location for respiration and energy production, mitochondria serve in a critical capacity to the cell. Yet, by virtue of this very function of respiration, mitochondria are subject to constant oxidative stress that can damage one of the unique features of this organelle, its distinct genome. Damage to mitochondrial DNA (mtDNA) and loss of mitochondrial genome integrity is increasingly understood to play a role in the development of both severe early-onset maladies and chronic age-related diseases. In this article, we review the processes by which mtDNA integrity is maintained, with an emphasis on the repair of oxidative DNA lesions, and the cellular consequences of diminished mitochondrial genome stability.
Topics: DNA Damage; DNA Replication; DNA, Mitochondrial; Disease; Health; Humans; Transcription, Genetic
PubMed: 30700008
DOI: 10.3390/cells8020100 -
Science (New York, N.Y.) Feb 2015According to the disease module hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of...
According to the disease module hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of biologically relevant molecular interactions. Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data have sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant coexpression patterns, symptom similarity, and comorbidity, whereas diseases residing in separated network neighborhoods are phenotypically distinct. These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases, even if they do not share primary disease genes.
Topics: Comorbidity; Disease; Genetic Predisposition to Disease; Humans; Information Services; Protein Interaction Maps
PubMed: 25700523
DOI: 10.1126/science.1257601 -
BioMed Research International 2017Microbiota represents the entire microbial community present in the gut host. It serves several functions establishing a mutualistic relation with the host. Latest years... (Review)
Review
Microbiota represents the entire microbial community present in the gut host. It serves several functions establishing a mutualistic relation with the host. Latest years have seen a burst in the number of studies focusing on this topic, in particular on intestinal diseases. In this scenario, Proteobacteria are one of the most abundant phyla, comprising several known human pathogens. This review highlights the latest findings on the role of Proteobacteria not only in intestinal but also in extraintestinal diseases. Indeed, an increasing amount of data identifies Proteobacteria as a possible microbial signature of disease. Several studies demonstrate an increased abundance of members belonging to this phylum in such conditions. Major evidences currently involve metabolic disorders and inflammatory bowel disease. However, more recent studies suggest a role also in lung diseases, such as asthma and chronic obstructive pulmonary disease, but evidences are still scant. Notably, all these conditions are sustained by various degree of inflammation, which thus represents a core aspect of Proteobacteria-related diseases.
Topics: Animals; Bacterial Infections; Disease; Humans; Microbiota; Proteobacteria
PubMed: 29230419
DOI: 10.1155/2017/9351507 -
Physiological Reviews Oct 2014Extensive experimental animal studies and epidemiological observations have shown that environmental influences during early development affect the risk of later... (Review)
Review
Extensive experimental animal studies and epidemiological observations have shown that environmental influences during early development affect the risk of later pathophysiological processes associated with chronic, especially noncommunicable, disease (NCD). This field is recognized as the developmental origins of health and disease (DOHaD). We discuss the extent to which DOHaD represents the result of the physiological processes of developmental plasticity, which may have potential adverse consequences in terms of NCD risk later, or whether it is the manifestation of pathophysiological processes acting in early life but only becoming apparent as disease later. We argue that the evidence suggests the former, through the operation of conditioning processes induced across the normal range of developmental environments, and we summarize current knowledge of the physiological processes involved. The adaptive pathway to later risk accords with current concepts in evolutionary developmental biology, especially those concerning parental effects. Outside the normal range, effects on development can result in nonadaptive processes, and we review their underlying mechanisms and consequences. New concepts concerning the underlying epigenetic and other mechanisms involved in both disruptive and nondisruptive pathways to disease are reviewed, including the evidence for transgenerational passage of risk from both maternal and paternal lines. These concepts have wider implications for understanding the causes and possible prevention of NCDs such as type 2 diabetes and cardiovascular disease, for broader social policy and for the increasing attention paid in public health to the lifecourse approach to NCD prevention.
Topics: Cardiovascular Diseases; Chronic Disease; Disease; Epigenomics; Human Development; Humans; Life Style; Risk Factors; Time Factors
PubMed: 25287859
DOI: 10.1152/physrev.00029.2013 -
Nature Communications Jan 2022With the growing number of genetic association studies, the genotype-phenotype atlas has become increasingly more complex, yet the functional consequences of most...
With the growing number of genetic association studies, the genotype-phenotype atlas has become increasingly more complex, yet the functional consequences of most disease associated alleles is not understood. The measurement of protein level variation in solid tissues and biofluids integrated with genetic variants offers a path to deeper functional insights. Here we present a large-scale proteogenomic study in 5,368 individuals, revealing 4,035 independent associations between genetic variants and 2,091 serum proteins, of which 36% are previously unreported. The majority of both cis- and trans-acting genetic signals are unique for a single protein, although our results also highlight numerous highly pleiotropic genetic effects on protein levels and demonstrate that a protein's genetic association profile reflects certain characteristics of the protein, including its location in protein networks, tissue specificity and intolerance to loss of function mutations. Integrating protein measurements with deep phenotyping of the cohort, we observe substantial enrichment of phenotype associations for serum proteins regulated by established GWAS loci, and offer new insights into the interplay between genetics, serum protein levels and complex disease.
Topics: Aged; Aged, 80 and over; Blood Proteins; Cohort Studies; Disease; Female; Genetic Predisposition to Disease; Genome, Human; Genome-Wide Association Study; Humans; Iceland; Male; Polymorphism, Single Nucleotide; Quantitative Trait Loci
PubMed: 35078996
DOI: 10.1038/s41467-021-27850-z -
International Journal of Molecular... Nov 2021Functional genomics applied in clinical disease diagnosis and prognosis allow the achievement of the progress in all aspects of biology in health and disease [...].
Functional genomics applied in clinical disease diagnosis and prognosis allow the achievement of the progress in all aspects of biology in health and disease [...].
Topics: Disease; Genetic Markers; Genetic Predisposition to Disease; Genomics; Humans; Prognosis; Risk Factors
PubMed: 34884749
DOI: 10.3390/ijms222312944 -
Cell Jun 2018The evidence that most adult-onset common diseases have a polygenic genetic architecture fully consistent with robust biological systems supported by multiple back-up... (Review)
Review
The evidence that most adult-onset common diseases have a polygenic genetic architecture fully consistent with robust biological systems supported by multiple back-up mechanisms is now overwhelming. In this context, we consider the recent "omnigenic" or "core genes" model. A key assumption of the model is that there is a relatively small number of core genes relevant to any disease. While intuitively appealing, this model may underestimate the biological complexity of common disease, and therefore, the goal to discover core genes should not guide experimental design. We consider other implications of polygenicity, concluding that a focus on patient stratification is needed to achieve the goals of precision medicine.
Topics: Disease; Genome-Wide Association Study; Humans; Models, Genetic; Multifactorial Inheritance; Precision Medicine
PubMed: 29906445
DOI: 10.1016/j.cell.2018.05.051 -
Nucleic Acids Research Jul 2021Here we present an update to MutationTaster, our DNA variant effect prediction tool. The new version uses a different prediction model and attains higher accuracy than...
Here we present an update to MutationTaster, our DNA variant effect prediction tool. The new version uses a different prediction model and attains higher accuracy than its predecessor, especially for rare benign variants. In addition, we have integrated many sources of data that only became available after the last release (such as gnomAD and ExAC pLI scores) and changed the splice site prediction model. To more easily assess the relevance of detected known disease mutations to the clinical phenotype of the patient, MutationTaster now provides information on the diseases they cause. Further changes represent a major overhaul of the interfaces to increase user-friendliness whilst many changes under the hood have been designed to accelerate the processing of uploaded VCF files. We also offer an API for the rapid automated query of smaller numbers of variants from within other software. MutationTaster2021 integrates our disease mutation search engine, MutationDistiller, to prioritise variants from VCF files using the patient's clinical phenotype. The novel version is available at https://www.genecascade.org/MutationTaster2021/. This website is free and open to all users and there is no login requirement.
Topics: Disease; Humans; Mutation; Phenotype; RNA Splice Sites; Software; Untranslated Regions
PubMed: 33893808
DOI: 10.1093/nar/gkab266 -
Nucleic Acids Research Jan 2018ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) is a freely available, public archive of human genetic variants and interpretations of their significance to disease,...
ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) is a freely available, public archive of human genetic variants and interpretations of their significance to disease, maintained at the National Institutes of Health. Interpretations of the clinical significance of variants are submitted by clinical testing laboratories, research laboratories, expert panels and other groups. ClinVar aggregates data by variant-disease pairs, and by variant (or set of variants). Data aggregated by variant are accessible on the website, in an improved set of variant call format files and as a new comprehensive XML report. ClinVar recently started accepting submissions that are focused primarily on providing phenotypic information for individuals who have had genetic testing. Submissions may come from clinical providers providing their own interpretation of the variant ('provider interpretation') or from groups such as patient registries that primarily provide phenotypic information from patients ('phenotyping only'). ClinVar continues to make improvements to its search and retrieval functions. Several new fields are now indexed for more precise searching, and filters allow the user to narrow down a large set of search results.
Topics: Databases, Nucleic Acid; Disease; Genetic Variation; Humans; Phenotype
PubMed: 29165669
DOI: 10.1093/nar/gkx1153 -
Briefings in Bioinformatics Jul 2018Gene co-expression networks can be used to associate genes of unknown function with biological processes, to prioritize candidate disease genes or to discern...
Gene co-expression networks can be used to associate genes of unknown function with biological processes, to prioritize candidate disease genes or to discern transcriptional regulatory programmes. With recent advances in transcriptomics and next-generation sequencing, co-expression networks constructed from RNA sequencing data also enable the inference of functions and disease associations for non-coding genes and splice variants. Although gene co-expression networks typically do not provide information about causality, emerging methods for differential co-expression analysis are enabling the identification of regulatory genes underlying various phenotypes. Here, we introduce and guide researchers through a (differential) co-expression analysis. We provide an overview of methods and tools used to create and analyse co-expression networks constructed from gene expression data, and we explain how these can be used to identify genes with a regulatory role in disease. Furthermore, we discuss the integration of other data types with co-expression networks and offer future perspectives of co-expression analysis.
Topics: Computational Biology; Disease; Gene Expression Profiling; Gene Expression Regulation; Gene Regulatory Networks; Genes; Humans; Phenotype
PubMed: 28077403
DOI: 10.1093/bib/bbw139