Understanding human diversity

The Contribution of JAK2 46/1 Haplotype in the Predisposition to Myeloproliferative Neoplasms

Haplotype 46/1 (GGCC) consists of a set of genetic variations distributed along chromosome 9p.24.1, which extend from the Janus Kinase 2 gene to Insulin like 4. Marked by four jointly inherited variants (rs3780367, rs10974944, rs12343867, and rs1159782), this haplotype has a strong association with the development of BCR-ABL1-negative myeloproliferative neoplasms (MPNs) because it precedes the acquisition of the JAK2V617F variant, a common genetic alteration in individuals with these hematological malignancies. It is also described as one of the factors that increases the risk of familial MPNs by more than five times, 46/1 is associated with events related to inflammatory dysregulation, splenomegaly, splanchnic vein thrombosis, Budd-Chiari syndrome, increases in RBC count, platelets, leukocytes, hematocrit, and hemoglobin, which are characteristic of MPNs, as well as other findings that are still being elucidated and which are of great interest for the etiopathological understanding of these hematological neoplasms. Considering these factors, the present review aims to describe the main findings and discussions involving the 46/1 haplotype, and highlights the molecular and immunological aspects and their relevance as a tool for clinical practice and investigation of familial cases.

Innate Immunity

The innate immune response system forms an important line of defense by deploying a limited number of receptors specific for conserved microbial components. This deployment generates a rapid inflammatory response, while activating the adaptive immune system. Improvements in our understanding of the innate immune system have allowed us to explore various therapeutic strategies via modulation of the immune response.

THE FUTURE OF MEDICINE, healthcare innovation through precision medicine: policy case study of Qatar

In 2016, the World Innovation Summit for Health (WISH) published its Forum Report on precision medicine "PRECISION MEDICINE - A GLOBAL ACTION PLAN FOR IMPACT". Healthcare is undergoing a transformation, and it is imperative to leverage new technologies to generate new data and support the advent of precision medicine (PM). Recent scientific breakthroughs and technological advancements have improved our disease knowledge and altered diagnosis and treatment approaches resulting in a more precise, predictive, preventative and personalized health care that is customized for the individual patient. Consequently, the big data revolution has provided an opportunity to apply artificial intelligence and machine learning algorithms to mine such a vast data set. Additionally, personalized medicine promises to revolutionize healthcare, with its key goal of providing the right treatment to the right patient at the right time and dose, and thus the potential of improving quality of life and helping to bring down healthcare costs.This policy briefing will look in detail at the issues surrounding continued development, sustained investment, risk factors, testing and approval of innovations for better strategy and faster process. The paper will serve as a policy bridge that is required to enhance a conscious decision among the powers-that-be in Qatar in order to find a way to harmonize multiple strands of activity and responsibility in the health arena. The end goal will be for Qatar to enhance public awareness and engagement and to integrate effectively the incredible advances in research into healthcare systems, for the benefit of all patients.The PM policy briefing provides concrete recommendations on moving forward with PM initiatives in Qatar and internationally. Equally important, integration of PM within a primary care setting, building a coalition of community champions through awareness and advocacy, finally, communicating PM value, patient engagement/empowerment and education/continued professional development programs of the healthcare workforce.Key recommendations for implementation of precision medicine inside and outside Qatar: 1. Create Community Awareness and PM Education Programs 2. Engage and Empower Patients 3. Communicate PM Value 4. Develop appropriate Infrastructure and Information Management Systems 5. Integrate PM into standard Healthcare System and Ensure Access to Care PM is no longer futuristic. It is here. Implementing PM in routine clinical care does require some investment and infrastructure development. Invariably, cost and lack of expertise are cited as barriers to PM implementation. Equally consequential, are the curriculum and professional development of medical care experts.Policymakers need to lead and coordinate effort among stakeholders and consider cultural and faith perspectives to ensure success. It is essential that policymakers integrate PM approaches into national strategies to improve health and health care for all, and to drive towards the future of medicine precision health.

Innate Immunity

The innate immune response system forms an important line of defense by deploying a limited number of receptors specific for conserved microbial components. This deployment generates a rapid inflammatory response, while activating the adaptive immune system. Improvements in our understanding of the innate immune system have allowed us to explore various therapeutic strategies via modulation of the immune response.

Immune diversity sheds light on missing variation in worldwide genetic diversity panels

Defining worldwide human genetic variation is a critical step to reveal how genome plasticity contributes to disease. Yet, there is currently no metric to assess the representativeness and completeness of current and widely used data on genetic variation. We show here that Human Leukocyte Antigen (HLA) genes can serve as such metric as they are both the most polymorphic and the most studied genetic system. As a test case, we investigated the 1,000 Genomes Project panel. Using high-accuracy in silico HLA typing, we find that over 20% of the common HLA variants and over 70% of the rare HLA variants are missing in this reference panel for worldwide genetic variation, due to undersampling and incomplete geographical coverage, in particular in Oceania and West Asia. Because common and rare variants both contribute to disease, this study thus illustrates how HLA diversity can detect and help fix incomplete sampling and hence accelerate efforts to draw a comprehensive overview of the genetic variation that is relevant to health and disease.

The Potential Role of Genetic Markers in Talent Identification and Athlete Assessment in Elite Sport

In elite sporting codes, the identification and promotion of future athletes into specialised talent pathways is heavily reliant upon objective physical, technical, and tactical characteristics, in addition to subjective coach assessments. Despite the availability of a plethora of assessments, the dependence on subjective forms of identification remain commonplace in most sporting codes. More recently, genetic markers, including several single nucleotide polymorphisms (SNPs), have been correlated with enhanced aerobic capacity, strength, and an overall increase in athletic ability. In this review, we discuss the effects of a number of candidate genes on athletic performance, across single-skilled and multifaceted sporting codes, and propose additional markers for the identification of motor skill acquisition and learning. While displaying some inconsistencies, both the ACE and ACTN3 polymorphisms appear to be more prevalent in strength and endurance sporting teams, and have been found to correlate to physical assessments. More recently, a number of polymorphisms reportedly correlating to athlete performance have gained attention, however inconsistent research design and varying sports make it difficult to ascertain the relevance to the wider sporting population. In elucidating the role of genetic markers in athleticism, existing talent identification protocols may significantly improve—and ultimately enable—targeted resourcing in junior talent pathways.

The Ensembl Genome Browser: Strategies for Accessing Eukaryotic Genome Data

The Ensembl Genome Browser provides a wealth of freely available genomic data that can be accessed for many purposes by genetics, genomics, and molecular biology researchers. Herein we present two protocols for exploring different aspects of these data: a phenotype and its associated variants and genes, and a promoter and the epigenetic marks and protein-binding activity associated with it. These workflows illustrate a subset of the data types available through the Ensembl Browser, and can be considered a springboard for further exploration.

An adaptive threshold determination method of feature screening for genomic selection

Background

Although the dimension of the entire genome can be extremely large, only a parsimonious set of influential SNPs are correlated with a particular complex trait and are important to the prediction of the trait. Efficiently and accurately selecting these influential SNPs from millions of candidates is in high demand, but poses challenges. We propose a backward elimination iterative distance correlation (BE-IDC) procedure to select the smallest subset of SNPs that guarantees sufficient prediction accuracy, while also solving the unclear threshold issue for traditional feature screening approaches.

Results

Verified through six simulations, the adaptive threshold estimated by the BE-IDC performed uniformly better than fixed threshold methods that have been used in the current literature. We also applied BE-IDC to an Arabidopsis thaliana genome-wide data. Out of 216,130 SNPs, BE-IDC selected four influential SNPs, and confirmed the same FRIGIDA gene that was reported by two other traditional methods.

Conclusions

BE-IDC accommodates both the prediction accuracy and the computational speed that are highly demanded in the genomic selection.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1617-9) contains supplementary material, which is available to authorized users.

Genetic aspects of athletic performance: the African runners phenomenon

The current dominance of African runners in long-distance running is an intriguing phenomenon that highlights the close relationship between genetics and physical performance. Many factors in the interesting interaction between genotype and phenotype (eg, high cardiorespiratory fitness, higher hemoglobin concentration, good metabolic efficiency, muscle fiber composition, enzyme profile, diet, altitude training, and psychological aspects) have been proposed in the attempt to explain the extraordinary success of these runners. Increasing evidence shows that genetics may be a determining factor in physical and athletic performance. But, could this also be true for African long-distance runners? Based on this question, this brief review proposed the role of genetic factors (mitochondrial deoxyribonucleic acid, the Y chromosome, and the angiotensin-converting enzyme and the alpha-actinin-3 genes) in the amazing athletic performance observed in African runners, especially the Kenyans and Ethiopians, despite their environmental constraints.

The construction of risk prediction models using GWAS data and its application to a type 2 diabetes prospective cohort

Recent genome-wide association studies (GWAS) have identified several novel single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D). Various models using clinical and/or genetic risk factors have been developed for T2D risk prediction. However, analysis considering algorithms for genetic risk factor detection and regression methods for model construction in combination with interactions of risk factors has not been investigated. Here, using genotype data of 7,360 Japanese individuals, we investigated risk prediction models, considering the algorithms, regression methods and interactions. The best model identified was based on a Bayes factor approach and the lasso method. Using nine SNPs and clinical factors, this method achieved an area under a receiver operating characteristic curve (AUC) of 0.8057 on an independent test set. With the addition of a pair of interaction factors, the model was further improved (p-value 0.0011, AUC 0.8085). Application of our model to prospective cohort data showed significantly better outcome in disease-free survival, according to the log-rank trend test comparing Kaplan-Meier survival curves (p--value 2:09 x 10(-11)). While the major contribution was from clinical factors rather than the genetic factors, consideration of genetic risk factors contributed to an observable, though small, increase in predictive ability. This is the first report to apply risk prediction models constructed from GWAS data to a T2D prospective cohort. Our study shows our model to be effective in prospective prediction and has the potential to contribute to practical clinical use in T2D.

Association of ABCB1 genetic polymorphisms with susceptibility to colorectal cancer and therapeutic prognosis

AIM

To evaluate the association of ABCB1 gene polymorphisms with susceptibility to colorectal cancer (CRC) and clinical outcomes of CRC patients with chemotherapy.

PATIENTS & METHODS

A case-control study was performed on the C3435T, C1236T and G2677T/A polymorphisms in the ABCB1 gene in 1028 CRC patients and 1230 controls.

RESULTS

We observed that the ABCB1 C3435T and G2677T/A variants as well as the 3435T-1236T-2677T haplotype significantly increased the risk of CRC. The ABCB1 C3435T CT genotype had a significant effect on the time to recurrence (adjusted hazard ratio [HR; 95% CI]: 0.560 [0.355-0.882]; p = 0.012). Moreover, ABCB1 C1236T variant carriers displayed a longer overall survival after postoperative oxaliplatin-based chemotherapy (adjusted HR [95% CI]: 0.354 [0.182-0.692], 0.646 [0.458-0.910], respectively). In addition, 1236TT-2677TT-3435TT haplotype carriers showed a worse progression-free survival (adjusted HR [95% CI]: 1.477 [1.012-3.802]; p = 0.043) and recurrence-free survival (adjusted HR [95% CI]: 2.183 [1.253-3.802]; p = 0.006).

CONCLUSION

The ABCB1 polymorphisms might be a candidate pharmacogenomic factor to assess susceptibility and prognosis after oxaliplatin-based chemotherapy for CRC patients.

Clinical applications of whole-genome association studies: future applications at the bedside

Until now, performing whole-genome association studies has been an unattainable, but highly desirable, goal for geneticists. With the recent advent of high-throughput genotyping platforms, this goal is now a reality for geneticists today and for clinicians in the not-so-distant future. This review will cover a broad range of topics to provide an overview of this emerging branch of genetics, and will provide references to more specific sources. Specifically, this review will cover the technologies available today and in the near future, the specific types of whole-genome association studies, the benefits and limitations of these studies, the applications to complex disease-gene interactions, diagnostic devices, therapeutics, and finally, we will describe the 5-year perspective and key issues.

BDNF rs6265 polymorphism and drug addiction: a systematic review and meta-analysis

A majority of studies have shown a link between the common functional rs6265 polymorphism of the BDNF gene and susceptibility to drug dependence. However, the pattern of results is inconsistent. To precisely evaluate this association, a systematic review and meta-analysis of previous case–control reports was conducted. Data from 20 studies containing 9419 participants (4665 cases and 4754 controls) conducted between 2004 and 2013 restricted to alcohol, nicotine, heroin, substance and methamphetamine dependency were meta-analyzed. Following quality control of the results, a significant association between C allele and methamphetamine dependence remained in south Asian subjects (p = 0.004). Similar results were detected in south Asian subjects for methamphetamine dependence and in Chinese subjects for heroin dependence under an autosomal codominant genotype model (TT vs CC, p = 0.005 and p = 0.0004, respectively). In conclusion, the rs6265 polymorphism may be a risk factor for methamphetamine dependence in south Asian subjects or for heroin dependence in Chinese subjects.

Race and Ethnicity in the Era of Emerging Pharmacogenomics

Race and ethnicity are terms that are commonly used to categorize subjects in medical research. Advances in genetics and the emerging discipline of pharmacogenomics have brought these terms under scrutiny, with arguments either for the continued use or for the abandonment of these terms generating strong views. As pharmacogenomics research develops, we may find that more accurate and specific descriptions of relevant variation in genes will reduce the value that these imprecise descriptors have in predicting how people will respond to drug therapies.

SNPranker 2.0: a gene-centric data mining tool for diseases associated SNP prioritization in GWAS

Background

The capability of correlating specific genotypes with human diseases is a complex issue in spite of all advantages arisen from high-throughput technologies, such as Genome Wide Association Studies (GWAS). New tools for genetic variants interpretation and for Single Nucleotide Polymorphisms (SNPs) prioritization are actually needed. Given a list of the most relevant SNPs statistically associated to a specific pathology as result of a genotype study, a critical issue is the identification of genes that are effectively related to the disease by re-scoring the importance of the identified genetic variations. Vice versa, given a list of genes, it can be of great importance to predict which SNPs can be involved in the onset of a particular disease, in order to focus the research on their effects.

Results

We propose a new bioinformatics approach to support biological data mining in the analysis and interpretation of SNPs associated to pathologies. This system can be employed to design custom genotyping chips for disease-oriented studies and to re-score GWAS results. The proposed method relies (1) on the data integration of public resources using a gene-centric database design, (2) on the evaluation of a set of static biomolecular annotations, defined as features, and (3) on the SNP scoring function, which computes SNP scores using parameters and weights set by users. We employed a machine learning classifier to set default feature weights and an ontological annotation layer to enable the enrichment of the input gene set. We implemented our method as a web tool called SNPranker 2.0 (http://www.itb.cnr.it/snpranker), improving our first published release of this system. A user-friendly interface allows the input of a list of genes, SNPs or a biological process, and to customize the features set with relative weights. As result, SNPranker 2.0 returns a list of SNPs, localized within input and ontologically enriched genes, combined with their prioritization scores.

Conclusions

Different databases and resources are already available for SNPs annotation, but they do not prioritize or re-score SNPs relying on a-priori biomolecular knowledge. SNPranker 2.0 attempts to fill this gap through a user-friendly integrated web resource. End users, such as researchers in medical genetics and epidemiology, may find in SNPranker 2.0 a new tool for data mining and interpretation able to support SNPs analysis. Possible scenarios are GWAS data re-scoring, SNPs selection for custom genotyping arrays and SNPs/diseases association studies.

Human complex trait genetics: lifting the lid of the genomics toolbox - from pathways to prediction

During the initial stages of the genome revolution human genetics was hugely successful in discovering the underlying genes for monogenic diseases. Over 3,000 monogenic diseases have been discovered with simple patterns of inheritance. The unravelling and identification of the genetic variants underlying complex or multifactorial traits, however, is proving much more elusive. There have been over 1,000 significant variants found for many quantitative and binary traits yet they explain very little of the estimated genetic variance or heritability evident from family analysis. There are many hypotheses as to why this might be the case. This apparent lack of information is holding back the clinical application of genetics and shedding doubt on whether more of the same will reveal where the remainder of the variation lies. Here we explore the current state of play, the types of variants we can detect and how they are currently exploited. Finally we look at the future challenges we must face to persuade the human genome to yield its secrets.

Roles of ABCB1 gene polymorphisms and haplotype in susceptibility to breast carcinoma risk and clinical outcomes

PURPOSE

Genetic variants of ABCB1 gene contributed to cancer susceptibility and interindividual differences in chemotherapy response. Therefore, we investigated the relevance between genetic variations in ABCB1 gene and both risk and clinical outcomes of breast carcinoma.

METHODS

A case-control study was performed on the SNPs C3435T, C1236T and G2677T/A in 1,173 Chinese breast carcinoma patients and 1,244 age- and sex-matched controls. These SNPs were typed by PCR-restriction fragment length polymorphism assays.

RESULTS

We found the following: (1) ABCB1 C3435T, G2677T/A variants and haplotype 3435T-1236T-2677T significantly increased the risk of breast carcinoma [adjusted OR (95 % CI): 1.281 (1.021-1.285), 1.326 (1.182-1.487) and 1.707 (1.498-1.945), respectively]. (2) A significantly enhanced therapeutic response was observed in both C3435T variants and haplotype 3435T-1236T-2677T after neoadjuvant anthracycline-based chemotherapy (n = 148) [adjusted OR (95 % CI): 2.695 (1.172-6.211) and 8.064 (1.085-58.823), respectively]. (3) Cox proportional hazards regression models showed that the hazards ratio (HR) for progression-free survival (PFS) associated with C3435T CC genotype was 1.664 (95 % CI: 1.022-2.708, P = 0.041). Kaplan-Meier curve showed that C3435T CC carriers had a poor prognosis than those with CT/TT carriers after anthracycline-based chemotherapy (P = 0.043, n = 762). Furthermore, ABCB1 C3435T variants showed a significantly prolonged both PFS and overall survival (OS) in patients with triple-negative (ER-/PR-/HER2-) status (P = 0.001 and P = 0.016, respectively; n = 135). In addition, there was a significantly longer OS in patients with HER2-negative status who had G2677T/A variants (P = 0.036, n = 487). However, we did not find statistically significant association between C1236T genotypes and the risk or prognosis of breast carcinoma.

CONCLUSIONS

These results suggest that ABCB1 gene C3435T, G2677T/A variations and haplotype 3435T-1236T-2677T relate to the risk and clinical outcomes of breast carcinoma and may function as candidate molecular markers of anthracycline chemosensitivity in breast carcinoma.

Community engagement about genetic variation research

The aim of this article is to describe the methods and effectiveness of the Public Engagement in Genetic Variation and Haplotype Mapping Issues (PEGV) Project, which engaged a community in policy discussion about genetic variation research. The project implemented a 6-stage community engagement model in New Rochelle, New York. First, researchers recruited community partners. Second, the project team created community oversight. Third, focus groups discussed concerns generated by genetic variation research. Fourth, community dialogue sessions addressed focus group findings and developed policy recommendations. Fifth, a conference was held to present these policy recommendations and to provide a forum for HapMap (haplotype mapping) researchers to dialogue directly with residents. Finally, findings were disseminated via presentations and papers to the participants and to the wider community beyond. The project generated a list of proposed guidelines for genetic variation research that addressed the concerns of New Rochelle residents. Project team members expressed satisfaction with the engagement model overall but expressed concerns about how well community groups were utilized and what segment of the community actually engaged in the project. The PEGV Project represents a model for researchers to engage the general public in policy development about genetic research. There are benefits of such a process beyond the desired genetic research.

Lack of association between synapsin II (SYN2) gene polymorphism and susceptibility epilepsy: a case-control study and meta-analysis

OBJECTIVE

The SYN2 rs3773364 A>G polymorphism has been proposed to be involved in susceptibility to epilepsy, but research results have been inconclusive. The aim of this study was to investigate the association between the SYN2 rs3773364 A>G polymorphism and susceptibility against epilepsy in a case-control study and a meta-analysis.

METHODS

The SYN2 rs3773364 A>G polymorphism was successfully genotyped in 1182 samples (618 epilepsy patients) of Chinese, Indian, and Malay ethnicities. Meta-analysis of the related studies, including this case-control study, was performed under alternative genetic models.

RESULTS

Data from the case-control study indicated no allelic and genotypic association of this locus with susceptibility to epilepsy in the tri-ethnic Malaysian population. Similar finding was obtained by stratified analysis by epilepsy syndrome for idiopathic epilepsy. These results were verified by meta-analysis of the related pooled data.

CONCLUSIONS

Our study indicated that SYN2 rs3773364 A>G polymorphism is not a risk factor for susceptibility to epilepsy.

SAQC: SNP array quality control

BACKGROUND

Genome-wide single-nucleotide polymorphism (SNP) arrays containing hundreds of thousands of SNPs from the human genome have proven useful for studying important human genome questions. Data quality of SNP arrays plays a key role in the accuracy and precision of downstream data analyses. However, good indices for assessing data quality of SNP arrays have not yet been developed.

RESULTS

We developed new quality indices to measure the quality of SNP arrays and/or DNA samples and investigated their statistical properties. The indices quantify a departure of estimated individual-level allele frequencies (AFs) from expected frequencies via standardized distances. The proposed quality indices followed lognormal distributions in several large genomic studies that we empirically evaluated. AF reference data and quality index reference data for different SNP array platforms were established based on samples from various reference populations. Furthermore, a confidence interval method based on the underlying empirical distributions of quality indices was developed to identify poor-quality SNP arrays and/or DNA samples. Analyses of authentic biological data and simulated data show that this new method is sensitive and specific for the detection of poor-quality SNP arrays and/or DNA samples.

CONCLUSIONS

This study introduces new quality indices, establishes references for AFs and quality indices, and develops a detection method for poor-quality SNP arrays and/or DNA samples. We have developed a new computer program that utilizes these methods called SNP Array Quality Control (SAQC). SAQC software is written in R and R-GUI and was developed as a user-friendly tool for the visualization and evaluation of data quality of genome-wide SNP arrays. The program is available online (http://www.stat.sinica.edu.tw/hsinchou/genetics/quality/SAQC.htm).

Simultaneous detection of multiple single-nucleotide polymorphisms by a simple membrane chip

Technologies that screen multiple single-nucleotide polymorphisms (SNPs) could be very valuable in predicting patients' susceptibilities to diseases or responses to therapeutic interventions. In this study, we developed a chip that can accurately detect four SNPs at same time. This chip is cost-effective and user-friendly because it uses a detection protocol analogous to dot blotting and does not require sophisticated instruments. To establish this chip, we designed and blotted onto a nylon membrane SNP-specific oligonucleotide probes for human angiotensinogen, cholesteryl ester transfer protein, and apolipoprotein E. This chip detected the corresponding SNPs harbored within the angiotensinogen, cholesteryl ester transfer protein, and apolipoprotein E sequences from 20 donors. Importantly, the SNPs detected by our chip matched exactly with the direct sequencing results, thereby highlighting the accuracy of this chip. In conclusion, our chip is a robust tool for multiple SNP screening and holds the potential to future refinement in detecting diseases-associating genes in patients.

A Polymorphic Variant of AFAP-110 Enhances cSrc Activity

Enhanced expression and activity of cSrc are associated with ovarian cancer progression. Generally, cSrc does not contain activating mutations; rather, its activity is increased in response to signals that affect a conformational change that releases its autoinhibition. In this report, we analyzed ovarian cancer tissues for the expression of a cSrc-activating protein, AFAP-110. AFAP-110 activates cSrc through a direct interaction that releases it from its autoinhibited conformation. Immunohistochemical analysis revealed a concomitant increase of AFAP-110 and cSrc in ovarian cancer tissues. An analysis of the AFAP-110 coding sequence revealed the presence of a nonsynonymous, single-nucleotide polymorphism that resulted in a change of Ser403 to Cys403. In cells that express enhanced levels of cSrc, AFAP-110(403C) directed the activation of cSrc and the formation of podosomes independently of input signals, in contrast to wild-type AFAP-110. We therefore propose that, under conditions of cSrc overexpression, the polymorphic variant of AFAP-110 promotes cSrc activation. Further, these data indicate amechanismby which an inherited genetic variation could influence ovarian cancer progression and could be used to predict the response to targeted therapy.

Lack of association of PON polymorphisms with sporadic ALS in an Italian population

Paraoxonase (PON) gene polymorphisms have been associated with susceptibility to sporadic amyotrophic lateral sclerosis (ALS). We have investigated the role of the previously associated single nucleotide polymorphisms rs854560, rs662, and rs6954345 in 350 ALS patients and 376 matched controls from Italy. No significant association was observed at genotype and haplotype level. Our data suggest that PON polymorphisms are not involved in ALS pathogenesis in an Italian population.

The role of Toll-like receptor signaling in human immunodeficiencies

Through the last decade, clinical immunology has witnessed a considerable progress in understanding the role of the innate immunity in human host defense, with Toll-like receptors (TLRs) being the most extensively innate immune receptors investigated. Growing literature documents the relevance of TLR signaling pathways to human disease, revealing a small, but expanding, group of new monogenic primary immunodeficiencies, in patients with various infectious diseases, previously considered as of unexplained "idiopathic" origin. Herein, we review these recently described deficiencies. Autosomal recessive IRAK-4 and myeloid differentiation factor 88 deficiencies were reported in 2003 and 2008, respectively, conferring predisposition to pyogenic bacterial infections, and autosomal recessive UNC93B1 and autosomal dominant TLR3 deficiencies were reported in 2006 and 2007, respectively, conferring predisposition to herpes simplex encephalitis. Furthermore, we highlight the published data associating TLR polymorphism with an altered susceptibility to infectious diseases.

Coregulation mapping based on individual phenotypic variation in response to virus infection

Background

Gene coregulation across a population is an important aspect of the considerable variability of the human immune response to virus infection. Methodology to investigate it must rely on a number of ingredients ranging from gene clustering to transcription factor enrichment analysis.

Results

We have developed a methodology to investigate the gene to gene correlations for the expression of 34 genes linked to the immune response of Newcastle Disease Virus (NDV) infected conventional dendritic cells (DCs) from 145 human donors. The levels of gene expression showed a large variation across individuals. We generated a map of gene co-expression using pairwise correlation and multidimensional scaling (MDS). The analysis of these data showed that among the 13 genes left after filtering for statistically significant variations, two clusters are formed. We investigated to what extent the observed correlation patterns can be explained by the sharing of transcription factors (TFs) controlling these genes. Our analysis showed that there was a significant positive correlation between MDS distances and TF sharing across all pairs of genes. We applied enrichment analysis to the TFs having binding sites in the promoter regions of those genes. This analysis, after Gene Ontology filtering, indicated the existence of two clusters of genes (CCL5, IFNA1, IFNA2, IFNB1) and (IKBKE, IL6, IRF7, MX1) that were transcriptionally co-regulated. In order to facilitate the use of our methodology by other researchers, we have also developed an interactive coregulation explorer web-based tool called CorEx. It permits the study of MDS and hierarchical clustering of data combined with TF enrichment analysis. We also offer web services that provide programmatic access to MDS, hierarchical clustering and TF enrichment analysis.

Conclusions

MDS mapping based on correlation in conjunction with TF enrichment analysis represents a useful computational method to generate predictions underlying gene coregulation across a population.

Host factors associated with outcome from primary human immunodeficiency virus-1 infection

PURPOSE OF REVIEW

The early events in human immunodeficiency virus-1 infection are increasingly recognized as critical for the overall evolution of the disease. Viral and host factors interact to establish a point of equilibrium defined by the viral set point. This review highlights new opportunities in the understanding of the genetic and genomic determinants of those early events.

RECENT FINDINGS

The field of human immunodeficiency virus host genetics is shifting from the measure of long-term consequences of infection to the analysis of quantitative biological endpoints of viral control, with particular attention on the earliest events as study phenotypes. The field has also been enriched by a better understanding of the determinant and complex role of human leukocyte antigen and killer cell immunoglobulin-like-receptor variation, and by the completion of the first genome-wide study of determinants of human immunodeficiency virus-1 replication. The genome analysis highlights the central influence of acquired immunity in viral control, and provides an extensive catalogue of novel gene candidates.

SUMMARY

Host genetics and genomic analyses of precise quantitative study phenotypes offer an unprecedented opportunity to dissect critical steps in human immunodeficiency virus-1 pathogenesis.

Innate immunity

Recent years have witnessed an explosion of interest in the innate immune system. Questions about how the innate immune system senses infection and empowers a protective immune response are being answered at the molecular level. These basic science discoveries are being translated into a more complete understanding of the central role innate immunity plays in the pathogenesis of many human infectious and inflammatory diseases. It is particularly exciting that we are already seeing a return on these scientific investments with the emergence of novel therapies to harness the power of the innate immune system. In this review we explore the defining characteristics of the innate immune system, and through more detailed examples, we highlight recent breakthroughs that have advanced our understanding of the role of innate immunity in human health and disease.

Functional annotations improve the predictive score of human disease-related mutations in proteins

Single nucleotide polymorphisms (SNPs) are the simplest and most frequent form of human DNA variation, also valuable as genetic markers of disease susceptibility. The most investigated SNPs are missense mutations resulting in residue substitutions in the protein. Here we propose SNPs&GO, an accurate method that, starting from a protein sequence, can predict whether a mutation is disease related or not by exploiting the protein functional annotation. The scoring efficiency of SNPs&GO is as high as 82%, with a Matthews correlation coefficient equal to 0.63 over a wide set of annotated nonsynonymous mutations in proteins, including 16,330 disease-related and 17,432 neutral polymorphisms. SNPs&GO collects in unique framework information derived from protein sequence, evolutionary information, and function as encoded in the Gene Ontology terms, and outperforms other available predictive methods.

Genetic variability of innate immunity impacts human susceptibility to fungal diseases

Fungi are a major threat in immunocompromised patients. Despite presenting similar degrees of immunosuppression, not all individuals at-risk ultimately develop fungal diseases. The traditional view of immune suppression as a key risk factor for susceptibility to fungal infections needs to be accommodated within new conceptual advances on host immunity and its relationship to fungal disease. The critical role of the immune system emphasizes the contribution of host genetic polymorphisms to fungal disease susceptibility. This review highlights the present knowledge on innate immunity genetics that associates with susceptibility to fungal diseases.

Human genomic diversity, viral genomics and proteomics, as exemplified by human papillomaviruses and H5N1 influenza viruses

The diversity of hosts, pathogens and host-pathogen relationships reflects the influence of selective pressures that fuel diversity through ongoing interactions with other rapidly evolving molecules in the environment. This paper discusses specific examples illustrating the phenomenon of diversity of hosts and pathogens, with special reference to human papillomaviruses and H5NI influenza viruses. We also review the influence of diverse host-pathogen interactions that determine the pathophysiology of infections, and their responses to drugs or vaccines.

An empirical investigation of organizational memetic variation

The potential of a theory based on organizational memes in coevolution with the environment has been postulated, but remains empirically under-developed. This study explores whether understanding organizational memetic variation is empirically possible and, if so, whether it might, with further development, provide managers with early indications of a misalignment between organizational action (operationalized as memetic variation) and strategic intent—the amount of memetic variation needed to stay aligned with the competitive environment. A method for empirically identifying knowledge-based memes in everyday practice is developed. It stems from modern advances in genetics allowing micro-level changes in genes to be linked to macro-environmental dynamics. Using the concept that memetic variation is caused by everyday, uncontrollable uncertainties of interpretation, memetic variation is reduced to seven categorical types. A highly exploratory quasi-experimental design allows a preliminary comparison of a would-be innovative ‘Portfolio Management Committee’ with self-organizing Internet chat-room settings that are representational of open-source innovation. Results are consistent with predictions showing that higher levels of variation are seen in the latter, despite the former’s strategic intent of innovating to stay aligned with a dynamic environment. Further work is needed, however, to test reliability and validity.

Common variant in myocilin gene is associated with high myopia in isolated population of Korcula Island, Croatia

AIM

To study the association between genetic variants in myocilin and collagen type I alpha 1 genes and high myopia in an isolated island population.

METHODS

A total of 944 examinees from the genetic epidemiology study conducted on the island of Korcula, Croatia, were included in the study. We selected 2 short nucleotide polymorphisms (SNP) available in our genome-wide scan set of SNPs that were previously associated with high myopia and used them to replicate previous claims of possible association.

RESULTS

Nineteen cases of high myopia, defined as the refraction of </=-6.00 diopters, were identified and included in the analysis. We showed that rs2075555 in the COL1A1 gene was not associated with high myopia. In contrast, rs2421853 in the myocilin gene was significantly associated in both bivariate (P=0.006) and age- and sex-adjusted analysis (P=0.049).

CONCLUSION

Myocilin seems to be a very strong candidate for explaining some of the pathophysiological pathways leading to the development of both glaucoma and high myopia. As our finding was obtained in a relatively under-powered sample, further research and replication of these results is needed.

Data structures and compression algorithms for genomic sequence data

MOTIVATION

The continuing exponential accumulation of full genome data, including full diploid human genomes, creates new challenges not only for understanding genomic structure, function and evolution, but also for the storage, navigation and privacy of genomic data. Here, we develop data structures and algorithms for the efficient storage of genomic and other sequence data that may also facilitate querying and protecting the data.

RESULTS

The general idea is to encode only the differences between a genome sequence and a reference sequence, using absolute or relative coordinates for the location of the differences. These locations and the corresponding differential variants can be encoded into binary strings using various entropy coding methods, from fixed codes such as Golomb and Elias codes, to variables codes, such as Huffman codes. We demonstrate the approach and various tradeoffs using highly variables human mitochondrial genome sequences as a testbed. With only a partial level of optimization, 3615 genome sequences occupying 56 MB in GenBank are compressed down to only 167 KB, achieving a 345-fold compression rate, using the revised Cambridge Reference Sequence as the reference sequence. Using the consensus sequence as the reference sequence, the data can be stored using only 133 KB, corresponding to a 433-fold level of compression, roughly a 23% improvement. Extensions to nuclear genomes and high-throughput sequencing data are discussed.

AVAILABILITY

Data are publicly available from GenBank, the HapMap web site, and the MITOMAP database. Supplementary materials with additional results, statistics, and software implementations are available from http://mammag.web.uci.edu/bin/view/Mitowiki/ProjectDNACompression.

Identifying gene-specific variations in biomedical text

The influence of genetic variations on diseases or cellular processes is the main focus of many investigations, and results of biomedical studies are often only accessible through scientific publications. Automatic extraction of this information requires recognition of the gene names and the accompanying allelic variant information. In a previous work, the OSIRIS system for the detection of allelic variation in text based on a query expansion approach was communicated. Challenges associated with this system are the relatively low recall for variation mentions and gene name recognition. To tackle this challenge, we integrate the ProMiner system developed for the recognition and normalization of gene and protein names with a conditional random field (CRF)-based recognition of variation terms in biomedical text. Following the newly developed normalization of variation entities, we can link textual entities to Single Nucleotide Polymorphism database (dbSNP) entries. The performance of this novel approach is evaluated, and improved results in comparison to state-of-the-art systems are reported.

Pharmacogenetics of Anti-HIV Drugs

Pharmacogenetics holds promise in HIV treatment because of the complexity and potential toxicity of multidrug therapies that are prescribed for long periods. Thus far, few candidate genes have been examined for a limited number of allelic variants, but a number of confirmed associations have already emerged. A change in paradigm emerges from the availability of the HapMap, the wealth of data on less-common genetic polymorphisms, and new genotyping technology. This review presents a comprehensive analysis of the existing literature on pharmacogenetic determinants of antiretroviral drug exposure, drug toxicity, as well as genetic markers associated with the rate of disease progression. It is expected that larger-scale comprehensive genome approaches will profoundly change the landscape of knowledge in the future.

Multicentre search for genetic susceptibility loci in sporadic epilepsy syndrome and seizure types: a case-control study

BACKGROUND

The Epilepsy Genetics (EPIGEN) Consortium was established to undertake genetic mapping analyses with augmented statistical power to detect variants that influence the development and treatment of common forms of epilepsy.

METHODS

We examined common variations across 279 prime candidate genes in 2717 case and 1118 control samples collected at four independent research centres (in the UK, Ireland, Finland, and Australia). Single nucleotide polymorphism (SNP) and combined set-association analyses were used to examine the contribution of genetic variation in the candidate genes to various forms of epilepsy.

FINDINGS

We did not identify clear, indisputable common genetic risk factors that contribute to selected epilepsy subphenotypes across multiple populations. Nor did we identify risk factors for the general all-epilepsy phenotype. However, set-association analysis on the most significant p values, assessed under permutation, suggested the contribution of numerous SNPs to disease predisposition in an apparent population-specific manner. Variations in the genes KCNAB1, GABRR2, KCNMB4, SYN2, and ALDH5A1 were most notable.

INTERPRETATION

The underlying genetic component to sporadic epilepsy is clearly complex. Results suggest that many SNPs contribute to disease predisposition in an apparently population-specific manner. However, subtle differences in phenotyping across cohorts, combined with a poor understanding of how the underlying genetic component to epilepsy aligns with current phenotypic classifications, might also account for apparent population-specific genetic risk factors. Variations across five genes warrant further study in independent cohorts to clarify the tentative association.

Evolution of man in the light of molecular genetics: a review. Part I. Our evolutionary history and genomics

The discovery in the mid 1970s of efficient methods of DNA sequencing and their subsequent development into more and more rapid procedures followed by sequencing the genomes of many species, including man in 2001, revolutionised the whole of biology. Remarkably, new light could be cast on the evolutionary relations of different species, and the tempo and mode of evolution within a given species, notably man, could quantitatively be illuminated including ongoing evolution possibly involving also the size of the brains. This review is a short summary of the results of the molecular genetic investigations of human evolution including the time and place of the formation of our species, our evolutionary relation to the closest living species relatives as well as extinct forms of the genus Homo. The nature and amount of genetic polymorphism in man is also considered with special emphasis on the causes of this variation, and the role of natural selection in human evolution. A consensus about the mosaic nature of our genome and the rather dynamic structure of our ancestral population is gradually emerging. The modern gene pool has most likely been contributed to several different ancestral demes either before or after the emergence of the anatomically modern human phenotype in the extent that even the nature of the evolutionary lineage leading to the anatomically modern man as a distinct biological species is disputable. Regulation of the function of genes, as well as the evolution of brains will be dealt with in the second part of this review.

Optimization of candidate-gene SNP-genotyping by flexible oligonucleotide microarrays; analyzing variations in immune regulator genes of hay-fever samples

Background

Genetic variants in immune regulator genes have been associated with numerous diseases, including allergies and cancer. Increasing evidence suggests a substantially elevated disease risk in individuals who carry a combination of disease-relevant single nucleotide polymorphisms (SNPs). For the genotyping of immune regulator genes, such as cytokines, chemokines and transcription factors, an oligonucleotide microarray for the analysis of 99 relevant SNPs was established. Since the microarray design was based on a platform that permits flexible in situ oligonucleotide synthesis, a set of optimally performing probes could be defined by a selection approach that combined computational and experimental aspects.

Results

While the in silico process eliminated 9% of the initial probe set, which had been picked purely on the basis of potential association with disease, the subsequent experimental validation excluded more than twice as many. The performance of the optimized microarray was demonstrated in a pilot study. The genotypes of 19 hay-fever patients (aged 40–44) with high IgE levels against inhalant antigens were compared to the results obtained with 19 age- and sex-matched controls. For several variants, allele-frequency differences of more than 10% were identified.

Conclusion

Based on the ability to improve empirically a chip design, the application of candidate-SNP typing represents a viable approach in the context of molecular epidemiological studies.

Maternal psychological reaction to newborn genetic screening for type 1 diabetes

OBJECTIVE

The purpose of this work was to describe levels of maternal anxiety, depressive symptoms, and perceptions of infant vulnerability associated with newborn genetic screening for susceptibility to type 1 diabetes.

PATIENTS AND METHODS

Mothers of infants tested at birth for genetic susceptibility to type 1 diabetes as part of a prospective study investigating potential environmental triggers of autoimmunity were recruited to this study. Three mother-infant cohorts were studied: 38 infants at increased genetic risk, 73 at low risk, and 76 who had not undergone testing. The Vulnerable Baby Scale, Edinburgh Postnatal Depression Scale, and state subscale of the State Trait Anxiety Inventory were administered at the 9-week, 4-month, and 1-year postnatal ages. Genetic-risk notification occurred at the 10-week postnatal age. Mothers whose infants had undergone genetic testing were also asked to subjectively rate how much they thought and worried about their child's genetic test result. Statistical analyses were conducted to test for differences in questionnaire scores among the 3 groups.

RESULTS

No difference among the groups was detected in Vulnerable Baby Scale or Edinburgh Postnatal Depression Scale scores using linear mixed-effects model analysis. Maternal anxiety was paradoxically slightly lower in the increased-risk group shortly after notification of results, but there were no significant differences among the groups by 1 year. Mothers of infants in the high-risk group reported thinking and worrying about their child's test result significantly more than mothers of low-risk infants at both time points after notification of results.

CONCLUSIONS

Newborn genetic screening to identify infants at risk for type 1 diabetes is not associated with elevated levels of maternal anxiety, depressive symptoms, or heightened perceptions of infant vulnerability. However, responses to subjective assessment questions suggest that it is possible that more subtle effects on mothers do occur, and this requires further investigation.

ADME pathway approach for pharmacogenetic studies of anti-HIV therapy

Pharmacogenetics holds promise in HIV treatment because of the complexity and potential toxicity of multidrug therapies that are prescribed for long periods. However, there has been limited success with the current approach where one or few candidate genes are examined for a limited number of allelic variants. A change in paradigm emerges from the availability of the HapMap, the wealth of data on less common genetic polymorphisms, and new genotyping technology. We present a comprehensive review of functional and putative functional variants in genes encoding absorption, distribution, metabolism and excretion (ADME) proteins relevant to HIV therapy. We propose an analytical array based on our review of the literature, web resources and use of bioinformatic analysis. We identified 126 genes with proven or potential role in HIV therapy. Variation in these genes can be characterized by 2428 SNPs (in Caucasians). On average, a gene is covered by 20 SNPs. This review compiles information for future analysis of the role of specific genes/variants in the exposure and response to antiretroviral therapy to generate a ranked list of new genetic variants for future studies.

Prediction of complex traits based on the epistasis of multiple haplotypes

Analysis of epistasis, or gene-gene interactions, is of particular importance for revealing the molecular mechanisms of complex human diseases. Multiple genes, each of which has a moderate effect, might interact and produce a complex phenotypic trait. In this paper, we present a novel method of epistasis analysis, utilizing multiple phase-resolved haplotypes residing in different genomic regions. Prediction models can then be derived from the epistasis to indicate the susceptibility of a person to a dichrotomous phenotypic trait. The simulation results showed that the prediction accuracy of this method is dependent on the penetrance rate of the underlying model. The computation cost, on the other hand, is dependent on the number of genomic regions involved for the complex phenotypic trait.