New approaches to investigating heterogeneity in complex traits

Schizophrenia in the genetic era: a review from development history, clinical features and genomic research approaches to insights of susceptibility genes

Schizophrenia is a devastating neuropsychiatric disorder affecting 1% of the world population and ranks as one of the disorders providing the most severe burden for society. Schizophrenia etiology remains obscure involving multi-risk factors, such as genetic, environmental, nutritional, and developmental factors. Complex interactions of genetic and environmental factors have been implicated in the etiology of schizophrenia. This review provides an overview of the historical origins, pathophysiological mechanisms, diagnosis, clinical symptoms and corresponding treatment of schizophrenia. In addition, as schizophrenia is a polygenic, genetic disorder caused by the combined action of multiple micro-effective genes, we further detail several approaches, such as candidate gene association study (CGAS) and genome-wide association study (GWAS), which are commonly used in schizophrenia genomics studies. A number of GWASs about schizophrenia have been performed with the hope to identify novel, consistent and influential risk genetic factors. Finally, some schizophrenia susceptibility genes have been identified and reported in recent years and their biological functions are also listed. This review may serve as a summary of past research on schizophrenia genomics and susceptibility genes (NRG1, DISC1, RELN, BDNF, MSI2), which may point the way to future schizophrenia genetics research. In addition, depending on the above discovery of susceptibility genes and their exact function, the development and application of antipsychotic drugs will be promoted in the future.

Biomedical Big Data Technologies, Applications, and Challenges for Precision Medicine: A Review

The explosive growth of biomedical Big Data presents both significant opportunities and challenges in the realm of knowledge discovery and translational applications within precision medicine. Efficient management, analysis, and interpretation of big data can pave the way for groundbreaking advancements in precision medicine. However, the unprecedented strides in the automated collection of large-scale molecular and clinical data have also introduced formidable challenges in terms of data analysis and interpretation, necessitating the development of novel computational approaches. Some potential challenges include the curse of dimensionality, data heterogeneity, missing data, class imbalance, and scalability issues. This overview article focuses on the recent progress and breakthroughs in the application of big data within precision medicine. Key aspects are summarized, including content, data sources, technologies, tools, challenges, and existing gaps. Nine fields-Datawarehouse and data management, electronic medical record, biomedical imaging informatics, Artificial intelligence-aided surgical design and surgery optimization, omics data, health monitoring data, knowledge graph, public health informatics, and security and privacy-are discussed.

Genetic heterogeneity in cardiovascular disease across ancestries: Insights for mechanisms and therapeutic intervention

Cardiovascular diseases (CVDs) are complex in their aetiology, arising due to a combination of genetics, lifestyle and environmental factors. By nature of this complexity, different CVDs vary in their molecular mechanisms, clinical presentation and progression. Although extensive efforts are being made to develop novel therapeutics for CVDs, genetic heterogeneity is often overlooked in the development process. By considering molecular mechanisms at an individual and ancestral level, a richer understanding of the influence of environmental and lifestyle factors can be gained and more refined therapeutic interventions can be developed. It is therefore expedient to understand the molecular and clinical heterogeneity in CVDs that exists across different populations. In this review, we highlight how the mechanisms underlying CVDs vary across diverse population ancestry groups due to genetic heterogeneity. We then discuss how such genetic heterogeneity is being leveraged to inform therapeutic interventions and personalised medicine, highlighting examples across the CVD spectrum. Finally, we present an overview of how polygenic risk scores and Mendelian randomisation can foster more robust insight into disease mechanisms and therapeutic intervention in diverse populations. Fulfilment of the vision of precision medicine requires more exhaustive leveraging of the genetic variability across diverse ancestry populations to improve our understanding of disease onset, progression and response to therapeutic intervention.

Replication study of GWAS risk loci in Greek multiple sclerosis patients

OBJECTIVES

To validate in an ethnically homogeneous Greek multiple sclerosis (MS) cohort, genetic risk factors for the disease, identified through a number of previous multi-ethnic genome-wide association studies (GWAS).

METHODS

A total of 1228 MS cases and 1014 controls were recruited in the study, from 3 MS centers in Greece. We genotyped 35 susceptibility SNPs that emerged from previous GWAS or meta-analyses of GWAS. Allele and genotype single locus regression analysis, adjusted for gender and site, was performed. Permutation testing was applied to all analyses.

RESULTS

Six polymorphisms reached statistical significance (permutation p value < 0.05). In particular, rs2760524 of LOC105371664, near RGS1 (permutation p value 0.001), rs3129889 of HLA-DRA, near HLA-DRB1 (permutation p value < 1.00e-04), rs1738074 of TAGAP (permutation p value 0.007), rs703842 of METTL1/CYP27B1 (permutation p value 0.008), rs9596270 of DLEU1 (permutation p value < 1.00e-04), and rs17445836 of LincRNA, near IRF8 (permutation p value 0.001) were identified as susceptibility risk factors in our group.

CONCLUSION

The current study replicated a number of GWAS susceptibility SNPs, which implies that some similarities between the examined Greek population and the MS genetic architecture of the GWAS populations do exist.

Common gene-network signature of different neurological disorders and their potential implications to neuroAIDS

The neurological complications of AIDS (neuroAIDS) during the infection of human immunodeficiency virus (HIV) are symptomized by non-specific, multifaceted neurological conditions and therefore, defining a specific diagnosis/treatment mechanism(s) for this neuro-complexity at the molecular level remains elusive. Using an in silico based integrated gene network analysis we discovered that HIV infection shares convergent gene networks with each of twelve neurological disorders selected in this study. Importantly, a common gene network was identified among HIV infection, Alzheimer's disease, Parkinson's disease, multiple sclerosis, and age macular degeneration. An mRNA microarray analysis in HIV-infected monocytes showed significant changes in the expression of several genes of this in silico derived common pathway which suggests the possible physiological relevance of this gene-circuit in driving neuroAIDS condition. Further, this unique gene network was compared with another in silico derived novel, convergent gene network which is shared by seven major neurological disorders (Alzheimer's disease, Parkinson's disease, Multiple Sclerosis, Age Macular Degeneration, Amyotrophic Lateral Sclerosis, Vascular Dementia, and Restless Leg Syndrome). These networks differed in their gene circuits; however, in large, they involved innate immunity signaling pathways, which suggests commonalities in the immunological basis of different neuropathogenesis. The common gene circuits reported here can provide a prospective platform to understand how gene-circuits belonging to other neuro-disorders may be convoluted during real-time neuroAIDS condition and it may elucidate the underlying-and so far unknown-genetic overlap between HIV infection and neuroAIDS risk. Also, it may lead to a new paradigm in understanding disease progression, identifying biomarkers, and developing therapies.

Identification of a gene expression signature in peripheral blood of multiple sclerosis patients treated with disease-modifying therapies

Multiple Sclerosis (MS) is an inflammatory disease with neurodegenerative alterations, ultimately progressing to neurological handicap. Therapies are effective in counteracting inflammation but not neurodegeneration. Biomarkers predicting disease course or treatment response are lacking. We investigated whether altered gene and protein expression profiles were detectable in the peripheral blood of 78 relapsing remitting MS (RR-MS) patients treated by disease-modifying therapies. A discovery/validation study on RR-MS responsive to glatiramer acetate identified 8 differentially expressed genes: ITGA2B, ITGB3, CD177, IGJ, IL5RA, MMP8, P2RY12, and S100β. A longitudinal study on glatiramer acetate, Interferon-β, or Fingolimod treated RR-MS patients confirmed that 7 out of 8 genes were downregulated with reference to the different therapies, whereas S100β was always upregulated. Thus, we identified a peripheral gene signature associated with positive response in RR-MS which may also explain drug immunomodulatory effects. The usefulness of this signature as a biomarker needs confirmation on larger series of patients.

Identification of a functional variant in the KIF5A-CYP27B1-METTL1-FAM119B locus associated with multiple sclerosis

Background and aim

Several studies have highlighted the association of the 12q13.3–12q14.1 region with coeliac disease, type 1 diabetes, rheumatoid arthritis and multiple sclerosis (MS); however, the causal variants underlying diseases are still unclear. The authors sought to identify the functional variant of this region associated with MS.

Methods

Tag-single nucleotide polymorphism (SNP) analysis of the associated region encoding 15 genes was performed in 2876 MS patients and 2910 healthy Caucasian controls together with expression regulation analyses.

Results

rs6581155, which tagged 18 variants within a region where 9 genes map, was sufficient to model the association. This SNP was in total linkage disequilibrium (LD) with other polymorphisms that associated with the expression levels of FAM119B, AVIL, TSFM, TSPAN31 and CYP27B1 genes in different expression quantitative trait loci studies. Functional annotations from Encyclopedia of DNA Elements (ENCODE) showed that six out of these rs6581155-tagged-SNPs were located in regions with regulatory potential and only one of them, rs10877013, exhibited allele-dependent (ratio A/G=9.5-fold) and orientation-dependent (forward/reverse=2.7-fold) enhancer activity as determined by luciferase reporter assays. This enhancer is located in a region where a long-range chromatin interaction among the promoters and promoter-enhancer of several genes has been described, possibly affecting their expression simultaneously.

Conclusions

This study determines a functional variant which alters the enhancer activity of a regulatory element in the locus affecting the expression of several genes and explains the association of the 12q13.3–12q14.1 region with MS.

The challenge of implementing genetic tests with clinical utility while avoiding unsound applications

Genetics and genomics have developed fast in the last decade, but have not revolutionized medicine, as some had expected. While translation of research findings to public health applications is lagging behind, direct-to-consumer (DTC) offers of genetic testing have become available, both for monogenic and severe genetic disorders and for genetic variants possibly associated with common complex diseases (susceptibility variants). The European Society of Human Genetics is concerned about the way in which commercial companies are currently introducing genetic tests into the market outside of the scope of the traditional health-care system. There is a sort of a paradox between the lagging implementation in health care of the few genetic tests with proven clinical utility, on the one hand, and the speedy DTC offer of tests, with or without clinical utility. To translate research findings into appropriate clinical applications, assessment of the clinical validity and utility is needed. Many of the parameters needed in assessment frameworks are not available yet. Clinically relevant associations between genetic variants and disease risks have been established, e.g., in oncogenetics and cardiogenetics, and can be used to reflect on the possibilities and obstacles in using the new genetics in public health. In the absence of sufficient information on clinical validity and clinical utility, introduction of genetic tests in common complex disorders is often premature. Priority should be given to settings where clinical utility is proven or likely, to gain additional information concerning diagnosis, prognosis, and disease management. Monitoring and evaluation are essential.

The network properties of myelodysplastic syndromes pathogenesis revealed by an integrative systems biological method

Insight into the molecular mechanism of complex diseases is an important topic in the current bio-medical research. However, different from the single-gene disorders, high heterogeneity of many of the complex diseases prevents scientists from the exact understanding of the etiology. In this study, we used Myelodysplastic Syndromes (MDSs), a heterogeneous family of clonal disorders of hematopoietic stem cells, as a general model to explore the network properties of the heterogeneity of complex diseases. First, static bioinformatics analysis suggests that despite the huge heterogeneity of MDSs, their clinical properties can be explained well by the local properties of MDS-related genes on the human interactome. Then we design a novel systems biological method to explore the pattern of genetic abnormality propagation of a real MDS cohort by integrating flowcytometry, genotyping, gene expression profiling, expression quantitative trait loci (eQTLs) mapping and pathway inference. We constructed a MDS disease gene network which suggests the network basis of the heterogeneity of MDSs. The pipeline we proposed and the implication the results suggest may be helpful in the research of other complex diseases.

Speaking the Language of Genetics: A Primer

Genetic research advances will continue to result in clinical applications for genetics in primary care settings. Fluency with the evolving genetic terminology will enable primary care providers to provide better clinical care to their patients, particularly when helping patients understand genetic concepts. This article will help clinicians use genetic terminology with greater precision.

Polymorphisms in the µ-opioid receptor gene (OPRM1) and the implications for alcohol dependence in humans

Twin and adoption studies have shown that alcohol dependence contains a substantial genetic component. In attempts to identify the genetic factors involved, association studies have linked the opioid system to alcohol dependence, with a main focus on the OPRM1 gene encoding the μ-opioid receptor. Our aim was to conduct a systematic review of the literature on the associations between polymorphisms in OPRM1 and alcohol dependence. We addressed findings of 12 studies that met our inclusion criteria. All studies employed a case–control design and included alcohol dependence as a dependent outcome measure. Our review showed that clinical studies do not unequivocally support an association between polymorphisms in OPRM1 and alcohol dependence. Factors that complicate genetic research on alcohol dependence, such as gene–environment interaction, and genetic and clinical heterogeneity, are discussed.

Association of mu-opioid receptor gene polymorphism A118G with alcohol dependence in a Japanese population

Ethanol is considered to activate the brain reward system by increasing the release of an endogenous opioid receptor ligand, beta-endorphin. The polymorphism A118G in the mu-opioid receptor gene (OPRM1) causes the amino acid change Asn40Asp and has been reported to affect the affinity of the ligand for the receptor. The association of this polymorphism with the vulnerability to alcohol dependence has been studied in many populations, but not yet in Japanese people. In the present study, we compared the frequencies of the polymorphism OPRM1 A118G between patients with alcohol dependence and healthy control subjects living in a Japanese provincial prefecture. We also genotyped a polymorphism, G1510A, in the acetaldehyde dehydrogenase 2 gene (ALDH2), in which the A allele causes poor metabolism of acetaldehyde, a major metabolite of alcohol. Both OPRM1 118G and ALDH2 1510G were significantly associated with alcohol dependence. These results suggest that OPRM1 118G in addition to ALDH2 1510G might be one of the risk factors for alcohol dependence in Japanese people.

Genetics in eating disorders: extending the boundaries of research

OBJECTIVE: To review the recent literature relevant to genetic research in eating disorders and to discuss unique issues which are crucial for the development of a genetic research project in eating disorders in Brazil. METHOD: A computer literature review was conducted in the Medline database between 1984 and may 2005 with the search terms "eating disorders", "anorexia nervosa", "bulimia nervosa", "binge eating disorder", "family", "twin" and "molecular genetic" studies. RESULTS: Current research findings suggest a substantial influence of genetic factors on the liability to anorexia nervosa and bulimia nervosa. Genetic research with admixed populations should take into consideration sample size, density of genotyping and population stratification. Through admixture mapping it is possible to study the genetic structure of admixed human populations to localize genes that underlie ethnic variation in diseases or traits of interest. CONCLUSIONS: The development of a major collaborative genetics initiative of eating disorders in Brazil and South America would represent a realistic possibility of studying the genetics of eating disorders in the context of inter ethnic groups, and also integrate a new perspective on the biological etiology of eating disorders.

Three allele combinations associated with multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is an immune-mediated disease of polygenic etiology. Dissection of its genetic background is a complex problem, because of the combinatorial possibilities of gene-gene interactions. As genotyping methods improve throughput, approaches that can explore multigene interactions appropriately should lead to improved understanding of MS.

METHODS

286 unrelated patients with definite MS and 362 unrelated healthy controls of Russian descent were genotyped at polymorphic loci (including SNPs, repeat polymorphisms, and an insertion/deletion) of the DRB1, TNF, LT, TGFbeta1, CCR5 and CTLA4 genes and TNFa and TNFb microsatellites. Each allele carriership in patients and controls was compared by Fisher's exact test, and disease-associated combinations of alleles in the data set were sought using a Bayesian Markov chain Monte Carlo-based method recently developed by our group.

RESULTS

We identified two previously unknown MS-associated tri-allelic combinations:-509TGFbeta1*C, DRB1*18(3), CTLA4*G and -238TNF*B1,-308TNF*A2, CTLA4*G, which perfectly separate MS cases from controls, at least in the present sample. The previously described DRB1*15(2) allele, the microsatellite TNFa9 allele and the biallelic combination CCR5Delta32, DRB1*04 were also reidentified as MS-associated.

CONCLUSION

These results represent an independent validation of MS association with DRB1*15(2) and TNFa9 in Russians and are the first to find the interplay of three loci in conferring susceptibility to MS. They demonstrate the efficacy of our approach for the identification of complex-disease-associated combinations of alleles.

Genomic profiling of interpopulation diversity guides prioritization of candidate-genes for autoimmunity

Autoimmune diseases seem to have strong genetic attributes, and are affected to some extent by shared susceptibility loci. The latter potentially amount to hundreds of candidate genes (CG), creating the need for a prioritization strategy in genetic association studies. To form such a strategy, 26 autoimmune-related CG were genotyped for a total of 72 single nucleotide polymorphisms (SNPs) in three distinct Israeli ethnic populations: Ashkenazi Jews, Sephardic Jews and Arabs. Four quantitative criteria reflecting population stratification were analyzed: allele frequencies, haplotype frequencies, the Fst statistic for homozygotes distribution and linkage disequilibrium extents. According to the consequent interpopulation genomic diversity profiles, the genes were classified into conserved, intermediate and diversified gene groups. Our results demonstrate a correlation between the biological role of autoimmune-related CG and their interpopulation diversity profiles as classified by the different analyses. Annotation analysis suggests that genes more readily influenced by environmental conditions, such as immunological mediators, are 'population specific'. Conversely, genes showing genetic conservation across all populations are characterized by apoptotic and cleaving functions. We suggest a research strategy by which CG association studies should focus first on likely conserved gene categories, to increase the likelihood of attaining significant results and promote the development of gene-based therapies.