Genetics, biology and disease

LAMP: disease classification derived from layered assessment on modules and pathways in the human gene network

Background

Classification of diseases based on genetic information is of great significance as the basis for precision medicine, increasing the understanding of disease etiology and revolutionizing personalized medicine. Much effort has been directed at understanding disease associations by constructing disease networks, and classifying patient samples according to gene expression data. Integrating human gene networks overcomes limited coverage of genes. Incorporating pathway information into disease classification procedure addresses the challenge of cellular heterogeneity across patients.

Results

In this work, we propose a disease classification model LAMP, which concentrates on the layered assessment on modules and pathways. Directed human gene interactions are the foundation of constructing the human gene network, where the significant roles of disease and pathway genes are recognized. The fast unfolding algorithm identifies 11 modules in the largest connected component. Then layered networks are introduced to distinguish positions of genes in propagating information from sources to targets. After gene screening, hierarchical clustering and refined process, 1726 diseases from KEGG are classified into 18 categories. Also, it is expounded that diseases with overlapping genes may not belong to the same category in LAMP. Within each category, entropy is applied to measure the compositional complexity, and to evaluate the prospects for combination diagnosis and gene-targeted therapy for diseases.

Conclusion

In this work, by collecting data from BioGRID and KEGG, we develop a disease classification model LAMP, to support people to view diseases from the perspective of commonalities in etiology and pathology. Comprehensive research on existing diseases can help meet the challenges of unknown diseases. The results provide suggestions for combination diagnosis and gene-targeted therapy, which motivates clinicians and researchers to reposition the understanding of diseases and explore diagnosis and therapy strategies.

Solar insolation in springtime influences age of onset of bipolar I disorder

OBJECTIVE

To confirm prior findings that the larger the maximum monthly increase in solar insolation in springtime, the younger the age of onset of bipolar disorder.

METHOD

Data were collected from 5536 patients at 50 sites in 32 countries on six continents. Onset occurred at 456 locations in 57 countries. Variables included solar insolation, birth-cohort, family history, polarity of first episode and country physician density.

RESULTS

There was a significant, inverse association between the maximum monthly increase in solar insolation at the onset location, and the age of onset. This effect was reduced in those without a family history of mood disorders and with a first episode of mania rather than depression. The maximum monthly increase occurred in springtime. The youngest birth-cohort had the youngest age of onset. All prior relationships were confirmed using both the entire sample, and only the youngest birth-cohort (all estimated coefficients P < 0.001).

CONCLUSION

A large increase in springtime solar insolation may impact the onset of bipolar disorder, especially with a family history of mood disorders. Recent societal changes that affect light exposure (LED lighting, mobile devices backlit with LEDs) may influence adaptability to a springtime circadian challenge.

Yeast genetic interaction screen of human genes associated with amyotrophic lateral sclerosis: identification of MAP2K5 kinase as a potential drug target

To understand disease mechanisms, a large-scale analysis of human–yeast genetic interactions was performed. Of 1305 human disease genes assayed, 20 genes exhibited strong toxicity in yeast. Human–yeast genetic interactions were identified by en masse transformation of the human disease genes into a pool of 4653 homozygous diploid yeast deletion mutants with unique barcode sequences, followed by multiplexed barcode sequencing to identify yeast toxicity modifiers. Subsequent network analyses focusing on amyotrophic lateral sclerosis (ALS)-associated genes, such as optineurin (OPTN) and angiogenin (ANG), showed that the human orthologs of the yeast toxicity modifiers of these ALS genes are enriched for several biological processes, such as cell death, lipid metabolism, and molecular transport. When yeast genetic interaction partners held in common between human OPTN and ANG were validated in mammalian cells and zebrafish, MAP2K5 kinase emerged as a potential drug target for ALS therapy. The toxicity modifiers identified in this study may deepen our understanding of the pathogenic mechanisms of ALS and other devastating diseases.

Application of Smart Infrastructure Systems approach to precision medicine

All biological variation is hierarchically organized dynamic network system of genomic components, organelles, cells, tissues, organs, individuals, families, populations and metapopulations. Individuals are axial in this hierarchy, as they represent antecedent, attendant and anticipated aspects of health, disease, evolution and medical care. Humans show individual specific genetic and clinical features such as complexity, cooperation, resilience, robustness, vulnerability, self-organization, latent and emergent behavior during their development, growth and senescence. Accurate collection, measurement, organization and analyses of individual specific data, embedded at all stratified levels of biological, demographic and cultural diversity - the big data - is necessary to make informed decisions on health, disease and longevity; which is a central theme of precision medicine initiative (PMI). This initiative also calls for the development of novel analytical approaches to handle complex multidimensional data. Here we suggest the application of Smart Infrastructure Systems (SIS) approach to accomplish some of the goals set forth by the PMI on the premise that biological systems and the SIS share many common features. The latter has been successfully employed in managing complex networks of non-linear adaptive controls, commonly encountered in smart engineering systems. We highlight their concordance and discuss the utility of the SIS approach in precision medicine programs.

Complement yourself: Transcomplementation rescues partially folded mutant proteins

Cystic Fibrosis (CF) is an autosomal disease associated with malfunction in fluid and electrolyte transport across several mucosal membranes. The most common mutation in CF is an in-frame three-base pair deletion that removes a phenylalanine at position 508 in the first nucleotide-binding domain of the cystic fibrosis conductance regulator (CFTR) chloride channel. This mutation has been studied extensively and leads to biosynthetic arrest of the protein in the endoplasmic reticulum and severely reduced channel activity. This review discusses a novel method of rescuing ΔF508 with transcomplementation, which occurs when smaller fragments of CFTR containing the wild-type nucleotide binding domain are co-expressed with the ΔF508 deletion mutant. Transcomplementation rescues the processing and channel activity of ΔF508 and reduces its rate of degradation in airway epithelial cells. To apply transcomplementation as a therapy would require that the cDNA encoding the truncated CFTR be delivered to cells. We also discuss a gene therapeutic approach based on delivery of a truncated form of CFTR to airway cells using adeno-associated viral vectors.

Arginine exposure alters ectonucleotidase activities and morphology of zebrafish larvae (Danio rerio)

Hyperargininemia is an inborn error of metabolism (IEM) characterized by tissue accumulation of arginine (Arg). Mental retardation and other neurological features are common symptoms in hyperargininemic patients. Considering purinergic signaling has a crucial role from the early stages of development and underlying mechanisms of this disease are poorly established, we investigated the effect of Arg administration on locomotor activity, morphological alterations, and extracellular nucleotide hydrolysis in larvae and adult zebrafish. We showed that 0.1 mM Arg was unable to promote changes in locomotor activity. In addition, 7-day-post-fertilization (dpf) larvae treated with Arg demonstrated a decreased body size. Arg exposure (0.1 mM) promoted an increase in ATP, ADP, and AMP hydrolysis when compared to control group. These findings demonstrated that Arg might affect morphological parameters and ectonucleotidase activities in zebrafish larvae, suggesting that purinergic system is a target for neurotoxic effects induced by Arg.

Impact of sunlight on the age of onset of bipolar disorder

OBJECTIVE

Although bipolar disorder has high heritability, the onset occurs during several decades of life, suggesting that social and environmental factors may have considerable influence on disease onset. This study examined the association between the age of onset and sunlight at the location of onset.

METHOD

Data were obtained from 2414 patients with a diagnosis of bipolar I disorder, according to DSM-IV criteria. Data were collected at 24 sites in 13 countries spanning latitudes 6.3 to 63.4 degrees from the equator, including data from both hemispheres. The age of onset and location of onset were obtained retrospectively, from patient records and/or direct interviews. Solar insolation data, or the amount of electromagnetic energy striking the surface of the earth, were obtained from the NASA Surface Meteorology and Solar Energy (SSE) database for each location of onset.

RESULTS

The larger the maximum monthly increase in solar insolation at the location of onset, the younger the age of onset (coefficient= -4.724, 95% CI: -8.124 to -1.323, p=0.006), controlling for each country's median age. The maximum monthly increase in solar insolation occurred in springtime. No relationships were found between the age of onset and latitude, yearly total solar insolation, and the maximum monthly decrease in solar insolation. The largest maximum monthly increases in solar insolation occurred in diverse environments, including Norway, arid areas in California, and Chile.

CONCLUSION

The large maximum monthly increase in sunlight in springtime may have an important influence on the onset of bipolar disorder.

A pathway-based view of human diseases and disease relationships

It is increasingly evident that human diseases are not isolated from each other. Understanding how different diseases are related to each other based on the underlying biology could provide new insights into disease etiology, classification, and shared biological mechanisms. We have taken a computational approach to studying disease relationships through 1) systematic identification of disease associated genes by literature mining, 2) associating diseases to biological pathways where disease genes are enriched, and 3) linking diseases together based on shared pathways. We identified 4,195 candidate disease associated genes for 1028 diseases. On average, about 50% of disease associated genes of a disease are statistically mapped to pathways. We generated a disease network which consists of 591 diseases and 6,931 disease relationships. We examined properties of this network and provided examples of novel disease relationships which cannot be readily captured through simple literature search or gene overlap analysis. Our results could potentially provide insights into the design of novel, pathway-guided therapeutic interventions for diseases.

Biobanking for epidemiological research and public health

Almost all healthcare systems are currently facing fundamental challenges. New ways of organizing these systems based on novel knowledge and stakeholders' different needs are required to meet these challenges at the appropriate time. In this context, the issue of biobanking has become a specific challenge having major implications for future research and policy strategies as well as for the healthcare systems in general. Medicine is currently undergoing remarkable developments from its morphological and phenotype orientation to a molecular and genotype orientation, promoting the importance of prognosis and prediction. Yet, the discussion about the relevance of integrating genome-based information into biobanks and about the role of genome-based biobanking for epidemiological research and public health is still at the beginning. The following article contributes to this discussion by focusing on the use of genome-based biobanking for epidemiological research, surveillance systems, health policy development, individual health information management and effective health services.

The human disease network

A network of disorders and disease genes linked by known disorder-gene associations offers a platform to explore in a single graph-theoretic framework all known phenotype and disease gene associations, indicating the common genetic origin of many diseases. Genes associated with similar disorders show both higher likelihood of physical interactions between their products and higher expression profiling similarity for their transcripts, supporting the existence of distinct disease-specific functional modules. We find that essential human genes are likely to encode hub proteins and are expressed widely in most tissues. This suggests that disease genes also would play a central role in the human interactome. In contrast, we find that the vast majority of disease genes are nonessential and show no tendency to encode hub proteins, and their expression pattern indicates that they are localized in the functional periphery of the network. A selection-based model explains the observed difference between essential and disease genes and also suggests that diseases caused by somatic mutations should not be peripheral, a prediction we confirm for cancer genes.

Ensuring the appropriate use of genetic tests

Ensuring the correct use of genetic tests is an important challenge for health-policy makers. Many new genetic tests will identify susceptibility to common diseases or adverse drug responses. Some will lead to new prevention opportunities, but others will have minimal clinical value. Statutory regulation alone cannot guarantee appropriate use. Other strategies, including resource allocation and matters related to clinical governance - such as practice-guideline development and health-provider education - are also important.

Genetics in medical practice

Medical genetics has been formally recognized as a medical specialty in the United States only within the past decade. Initially, medical genetics was concerned with relatively rare single gene or chromosomal disorders, but with the sequencing of the human genome, genetics has become the driving force in medical research and is now poised for integration into medical practice. This article offers a perspective on the role of genetics in medical practice and how this role may evolve over the next several years. The author classifies the genetic contribution to medical practice into three categories: monogenic or chromosomal disorders, more common disorders due to a monogenic or single gene mutation, and common multifactorial disorders in which the interaction of multiple genes and the environment contribute to the cause of the condition. The author discusses the positives and the potential pitfalls facing primary care physicians and specialists as they incorporate medical genetics into their practices and points out some of the anticipated changes medical genetics will necessitate, such as an increased medical genetics workforce, including geneticists and genetic counselors. The Human Genome Project has made information of inestimable diagnostic and therapeutic importance available. The medical profession now must rise to both the opportunities and challenges that this wealth of information presents.

Human disease genes

The complete human genome sequence will facilitate the identification of all genes that contribute to disease. We propose that the functional classification of disease genes and their products will reveal general principles of human disease. We have determined functional categories for nearly 1,000 documented disease genes, and found striking correlations between the function of the gene product and features of disease, such as age of onset and mode of inheritance. As knowledge of disease genes grows, including those contributing to complex traits, more sophisticated analyses will be possible; their results will yield a deeper understanding of disease and an enhanced integration of medicine with biology.