A HapMap harvest of insights into the genetics of common disease

Finding a place for genomics in health disparities research

The existence of pronounced differences in health outcomes between US populations is a problem of moral significance and public health urgency. Pursuing research on genetic contributors to such disparities, despite striking data on the fundamental role of social factors, has been controversial. Still, advances in genomic science are providing an understanding of disease biology at a level of precision not previously possible. The potential for genomic strategies to help in addressing population-level disparities therefore needs to be carefully evaluated. Using 3 examples from current research, we argue that the best way to maximize the benefits of population-based genomic investigations, and mitigate potential harms, is to direct research away from the identification of genetic causes of disparities and instead focus on applying genomic methodologies to the development of clinical and public health tools with the potential to ameliorate healthcare inequities, direct population-level health interventions or inform public policy. Such a transformation will require close collaboration between transdisciplinary teams and community members as well as a reorientation of current research objectives to better align genomic discovery efforts with public health priorities and well-recognized barriers to fair health care delivery.

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.

Genetics of patent ductus arteriosus susceptibility and treatment

The ductus arteriosus is a vital fetal structure designed to close shortly after birth. Although many physiologic and pharmacologic investigations have characterized the closure of this structure, genetic studies of persistent patency of the ductus arteriosus (patent ductus arteriosus, PDA) are relatively recent. Progress in the identification of specific genes associated with PDA is well behind that of many adult-onset diseases because of several reasons ranging from the lack of large biorepositories for this unique population to the belief that any genetic contribution to PDA is minimal. Viewing the PDA as a complex, developmentally influenced disease with both genetic and environmental risk factors has resulted in initial successes in some genetic studies. We will introduce several genetic approaches, which have been or are currently being applied to the study of PDA, that have been successful in identifying polymorphisms associated with adult diseases. Genetic investigations of PDA will be discussed with respect to heritability, in general, and to specific risk genes. Several animal models that have been used to study PDA-related genes will also be presented. Further advances in discovering genetic variation causing PDA will drive the more rational use of current therapies, and may help identify currently unknown targets for future therapeutic manipulation.

CNVs: harbingers of a rare variant revolution in psychiatric genetics

The genetic bases of neuropsychiatric disorders are beginning to yield to scientific inquiry. Genome-wide studies of copy number variation (CNV) have given rise to a new understanding of disease etiology, bringing rare variants to the forefront. A proportion of risk for schizophrenia, bipolar disorder, and autism can be explained by rare mutations. Such alleles arise by de novo mutation in the individual or in recent ancestry. Alleles can have specific effects on behavioral and neuroanatomical traits; however, expressivity is variable, particularly for neuropsychiatric phenotypes. Knowledge from CNV studies reflects the nature of rare alleles in general and will serve as a guide as we move forward into a new era of whole-genome sequencing.

Hepatocellular carcinoma: towards personalized medicine

Over the past several years, the success of genome-wide association studies (GWAS) and pharmacogenomics has gradually begun to enable personalized medicine in some fields. In the field of liver diseases, host genetic factors are now very useful in clinical practice for predicting treatment outcome and adverse reactions for pegylated interferon plus ribavirin combination therapy against chronic hepatitis C virus (HCV) infection. Recently, three virus-related hepatocellular carcinoma (HCC) GWAS were reported from Asia. One study examined hepatitis B virus-related HCC in China, where hepatitis B is very prevalent, and the other two examined HCV-related HCC in Japan. We identified a common variant in the DEPDC5 locus associated with HCV-related HCC, and another group identified an association involving the MICA locus. In this review, we compare the results of these GWAS and earlier candidate gene studies. Further research is needed to determine the role of these single nucleotide polymorphisms on HCC risk, but identification of these markers could make it possible to assess the magnitude of the risk of cancer based on each patient's genetic background. Consideration of the genetic background of the patients will likely play a role in personalized medicine for HCC, and understanding the mechanism underlying the association could suggest novel promising therapeutic targets in the future.

The molecular basis of chemoradiosensitivity in rectal cancer: implications for personalized therapies

Introduction

Preoperative chemoradiotherapy represents the standard treatment for patients with locally advanced rectal cancer. Unfortunately, the response of individual tumors to multimodal treatment is not uniform and ranges from complete response to complete resistance. This poses a particular problem for patients with a priori resistant tumors because they may be exposed to irradiation and chemotherapy, treatment regimens that are both expensive and at times toxic, without benefit. Accordingly, there is a strong need to establish molecular biomarkers that predict the response of an individual patient’s tumor to multimodal treatment and that indicate treatment-associated toxicities prior to therapy. Such biomarkers may guide clinicians in choosing the best possible treatment for each individual patient. In addition, these biomarkers could be used to identify novel molecular targets and thereby assist in implementing novel strategies to sensitize a priori resistant tumors to multimodal treatment regimens.

Objective

The aim of this review is to summarize recent findings about the molecular basis of treatment resistance and treatment toxicity in patients with rectal cancer. Whole-genome, as well as single-biomarker or multibiomarker, analyses and their potential implications will be highlighted. At the end, we will outline a future vision of rectal cancer treatment in the era of personalized medicine.

Possible counter effect in newborns of 1936A>G (I646V) polymorphism in the AKAP10 gene encoding A-kinase-anchoring protein 10

OBJECTIVE

Cyclic adenosine monophosphate/protein kinase A (PKA) is important in embryonic development. The human AKAP10 gene is polymorphic: 1936A>G results in changes to a PKA-binding domain and increased targeting to mitochondria. Previous studies found G1936 as 'deleterious' in adults, and this study investigates whether this holds true in preterm birth.

STUDY DESIGN

Study group consisted of 80 preterm newborns (PTNs) born before the 38th gestation week. Control group consisted of 123 full-term healthy newborns born after the 37th gestation week with uncomplicated pregnancies. Genomic DNA was extracted from umbilical blood and AKAP10 genotypes were identified by PCR/restriction enzyme.

RESULT

Significant differences in frequencies of 1936A>G genotypes/alleles between both groups were found. PTNs had increased frequency (55%) of AA homozygotes (odds ratio, AA versus AG+GG: 2.63 (95% confidence interval: 1.33 to 5.20), P=0.006) after adjustments: mothers with previous PTNs, smoking, first pregnancy, first delivery and Cesarean section.

CONCLUSION

Results suggest G1936 is preventative factor against preterm birth, in contrast with previously asserted negative effects in adults.

New genetic insights from autoimmune thyroid disease

The autoimmune thyroid diseases (AITDs) (Graves' disease and Hashimoto's thyroiditis) are complex genetic diseases which most likely have more than 20 genes contributing to the clinical phenotypes. To date, the genes known to be contributing fall into two categories: immune regulatory genes (including HLA, CTLA4, PTPN22, CD40, CD25, and FCRL3) and thyroid-specific genes (TG and TSHR). However, none of these genes contribute more than a 4-fold increase in risk of developing one of these diseases, and none of the polymorphisms discovered is essential for disease development. Hence, it appears that a variety of different gene interactions can combine to cause the same clinical disease pattern, but the contributing genes may differ from patient to patient and from population to population. Furthermore, this possible mechanism leaves open the powerful influence of the environment and epigenetic modifications of gene expression. For the clinician, this means that genetic profiling of such patients is unlikely to be fruitful in the near future.

A central role for long non-coding RNA in cancer

Long non-coding RNAs (ncRNAs) have been shown to regulate important biological processes that support normal cellular functions. Aberrant regulation of these essential functions can promote tumor development. In this review, we underscore the importance of the regulatory role played by this distinct class of ncRNAs in cancer-associated pathways that govern mechanisms such as cell growth, invasion, and metastasis. We also highlight the possibility of using these unique RNAs as diagnostic and prognostic biomarkers in malignancies.

Pharmacogenomic characterization of US FDA-approved cytotoxic drugs

AIMS

Individualization of cancer chemotherapy based on the patient's genetic makeup holds promise for reducing side effects and improving efficacy. However, the relative contribution of genetics to drug response is unknown.

MATERIALS & METHODS

In this study, we investigated the cytotoxic effect of 29 commonly prescribed chemotherapeutic agents from diverse drug classes on 125 lymphoblastoid cell lines derived from 14 extended families.

RESULTS

The results of this systematic study highlight the variable role that genetics plays in response to cytotoxic drugs, ranging from a heritability of <0.15 for gemcitabine to >0.60 for epirubicin.

CONCLUSION

Putative quantitative trait loci for cytotoxic response were identified, as well as drug class-specific signatures, which could indicate possible shared genetic mechanisms. In addition to the identification of putative quantitative trait locis, the results of this study inform the prioritization of chemotherapeutic drugs with a sizable genetic response component for future investigation.

DNA repair gene XRCC3 T241M polymorphism and bladder cancer risk in a Chinese population

The X-ray repair cross-complementing group 3 (XRCC3), one of the DNA repair genes, was suggested to play an imperative role in the development of carcinogenesis. The objective of this study was to evaluate the role of the XRCC3 T241M polymorphism in bladder cancer susceptibility in a Chinese population. We genotyped 150 bladder cancer cases and 150 healthy controls who had been frequency matched to cases by age and sex. Genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism analysis. A significant association was found between smoker and bladder cancer [odds ratio (OR)=1.97, 95% confidence interval (CI)=1.24-3.13, p=0.004]. The XRCC3 241MM genotype was more frequent in the bladder cancer group than in the healthy controls group (OR=3.22, 95% CI=1.14-9.11, p=0.03). There were no significant associations between any genotypes and the stage, grade, and histological type of bladder cancer. Our study suggested an increased risk role of XRCC3 241MM genotype in bladder cancer susceptibility in a Chinese population.

Rare and common variants: twenty arguments

Genome-wide association studies have greatly improved our understanding of the genetic basis of disease risk. The fact that they tend not to identify more than a fraction of the specific causal loci has led to divergence of opinion over whether most of the variance is hidden as numerous rare variants of large effect or as common variants of very small effect. Here I review 20 arguments for and against each of these models of the genetic basis of complex traits and conclude that both classes of effect can be readily reconciled.

The mystery of missing heritability: Genetic interactions create phantom heritability

Human genetics has been haunted by the mystery of "missing heritability" of common traits. Although studies have discovered >1,200 variants associated with common diseases and traits, these variants typically appear to explain only a minority of the heritability. The proportion of heritability explained by a set of variants is the ratio of (i) the heritability due to these variants (numerator), estimated directly from their observed effects, to (ii) the total heritability (denominator), inferred indirectly from population data. The prevailing view has been that the explanation for missing heritability lies in the numerator--that is, in as-yet undiscovered variants. While many variants surely remain to be found, we show here that a substantial portion of missing heritability could arise from overestimation of the denominator, creating "phantom heritability." Specifically, (i) estimates of total heritability implicitly assume the trait involves no genetic interactions (epistasis) among loci; (ii) this assumption is not justified, because models with interactions are also consistent with observable data; and (iii) under such models, the total heritability may be much smaller and thus the proportion of heritability explained much larger. For example, 80% of the currently missing heritability for Crohn's disease could be due to genetic interactions, if the disease involves interaction among three pathways. In short, missing heritability need not directly correspond to missing variants, because current estimates of total heritability may be significantly inflated by genetic interactions. Finally, we describe a method for estimating heritability from isolated populations that is not inflated by genetic interactions.

Genetic mapping of quantitative trait loci for disease-related phenotypes

Quantitative variation underlies normal as well as pathological traits, and large part of this variability is under the control of genetic loci. Thanks to a better understanding of the extent and nature of human genetic variability and the subsequent availability of an increasing number of genetic markers, genetic mapping of several such quantitative trait loci, or QTLs, has been accomplished in the past 20 years or so using linkage and association analysis in family-based and population-based studies. Rather than alternative, such methods are complementary as each has optimal power of detecting genetic variants underlying variability of quantitative traits under different scenarios defined by the QTL allele frequencies and magnitude of genetic effects. We describe how to apply such analyses to whole-genome or candidate-gene genetic marker data to correlate genetic variability to quantitative trait variability for the purpose of gene mapping and identification.

Translational bioinformatics in psychoneuroimmunology: methods and applications

Translational bioinformatics plays an indispensable role in transforming psychoneuroimmunology (PNI) into personalized medicine. It provides a powerful method to bridge the gaps between various knowledge domains in PNI and systems biology. Translational bioinformatics methods at various systems levels can facilitate pattern recognition, and expedite and validate the discovery of systemic biomarkers to allow their incorporation into clinical trials and outcome assessments. Analysis of the correlations between genotypes and phenotypes including the behavioral-based profiles will contribute to the transition from the disease-based medicine to human-centered medicine. Translational bioinformatics would also enable the establishment of predictive models for patient responses to diseases, vaccines, and drugs. In PNI research, the development of systems biology models such as those of the neurons would play a critical role. Methods based on data integration, data mining, and knowledge representation are essential elements in building health information systems such as electronic health records and computerized decision support systems. Data integration of genes, pathophysiology, and behaviors are needed for a broad range of PNI studies. Knowledge discovery approaches such as network-based systems biology methods are valuable in studying the cross-talks among pathways in various brain regions involved in disorders such as Alzheimer's disease.

Direct-to-Consumer Genetic Testing

Genetics has fascinated societies since ancient times, and references to traits or behaviors that appear to be shared or different among related individuals have permeated legends, literature, and popular culture. Biomedical advances from the past century, and particularly the discovery of the DNA double helix, the increasing numbers of links that were established between mutations and medical conditions or phenotypes, and technological advances that facilitated the sequencing of the human genome, catalyzed the development of genetic testing. Genetic tests were initially performed in health care facilities, interpreted by health care providers, and included the availability of counseling. Recent years have seen an increased availability of genetic tests that are offered by companies directly to consumers, a phenomenon that became known as direct-to-consumer genetic testing. Tests offered in this setting range from the ones that are also provided in health care establishments to tests known as ‘recreational genomics,’ and consumers directly receive the test results. In addition, testing in this context often does not involve the availability of counseling and, when this is provided, it frequently occurs on-line or over the phone. As a field situated at the interface between biotechnology, biomedical research, and social sciences, direct-to-consumer genetic testing opens multiple challenges that can be appropriately addressed only by developing a complex, inter-disciplinary framework.

Genetic polymorphisms affecting drug metabolism: recent advances and clinical aspects

Though current knowledge of pharmacogenetic factors relevant to drug metabolism is fairly comprehensive and this should facilitate translation to the clinic, there are a number of gaps in knowledge. Recent studies using both conventional and novel approaches have added to our knowledge of pharmacogenetics of drug metabolism. Genome-wide association studies have provided new insights into the major contribution of cytochromes P450 to response to therapeutic agents such as coumarin anticoagulants and clopidogrel as well as to caffeine and nicotine. Recent advances in understanding of factors affecting gene expression, both regulation by transcription factors and by microRNA and epigenetic factors, have added to understanding of variation in expression of genes such as CYP3A4 and CYP2E1. The implementation of testing for pharmacogenetic polymorphisms in prescription of selected anticancer drugs and cardiovascular agents is considered in detail, with current controversies and barriers to implementation of pharmacogenetic testing assessed. Though genotyping for thiopurine methyltransferase is now common prior to prescription of thiopurines, genotyping for other pharmacogenetic polymorphisms prior to drug prescription remains uncommon. However, it seems likely that it will become more widespread as both increased evidence that certain pharmacogenetic tests are valuable and cost-effective and more accessible genotyping methods become available.

Genome-wide association studies: Where we are heading?

We have witnessed tremendous success in genome-wide association studies (GWAS) in recent years. Since the identification of variants in the complement factor H gene on the risk of age-related macular degeneration, GWAS have become ubiquitous in genetic studies and have led to the identification of genetic variants that are associated with a variety of complex human diseases and traits. These discoveries have changed our understanding of the biological architecture of common, complex diseases and have also provided new hypotheses to test. New tools, such as next-generation sequencing, will be an important part of the future of genetics research; however, GWAS studies will continue to play an important role in disease gene discovery. Many traits have yet to be explored by GWAS, especially in minority populations, and large collaborative studies are currently being conducted to maximize the return from existing GWAS data. In addition, GWAS technology continues to improve, increasing genomic coverage for major global populations and decreasing the cost of experiments. Although much of the variance attributable to genetic factors for many important traits is still unexplained, GWAS technology has been instrumental in mapping over a thousand genes to hundreds of traits. More discoveries are made each month and the scale, quality and quantity of current work has a steady trend upward. We briefly review the current key trends in GWAS, which can be summarized with three goals: increase power, increase collaborations and increase populations.

HNF1B polymorphism associated with development of prostate cancer in Korean patients

OBJECTIVE

To identify whether the genetic variations in HNF1B are associated with the development of prostate cancer in Korean patients. Genome-wide association studies have found the HNF1B gene at 17q12 to be a major causal gene for the risk of prostate cancer.

METHODS

We evaluated the association of 47 single nucleotide polymorphisms (SNPs) in the HNF1B gene with prostate cancer risk and clinical characteristics (Gleason score and tumor stage) in Korean men (240 case subjects and 223 control subjects) using unconditional logistic regression analysis.

RESULTS

Of the 47 SNPs, 14 were associated with prostate cancer risk (P = .002-.02); 9 SNPs were associated with a lower risk of prostate cancer (odds ratio 0.67-0.71, P = .005-.05), and 5 SNPs were associated with a greater risk of disease (odds ratio 1.49-1.51, P = .002-.02). In an analysis involving only patients with prostate cancer, 1 SNP (rs11868513) in the HNF1B gene was more frequent in patients with tumors with a greater stage than in those with a lower tumor stage. Two SNPs (rs4430796 and rs2074429) and 1 haplotype (Block3_ht1) were more frequent in patients with Gleason score of ≥7 than in those with Gleason score <6.

CONCLUSION

As in studies from other populations, our findings indicate that HNF1B is also associated with prostate cancer risk in the Korean population.

A comparison of association methods for cytotoxicity mapping in pharmacogenomics

Cytotoxicity assays of immortalized lymphoblastoid cell lines (LCLs) represent a promising new in vitro approach in pharmacogenomics research. However, previous studies employing LCLs in gene mapping have used simple association methods, which may not adequately capture the true differences in non-linear response profiles between genotypes. Two common approaches summarize each dose-response curve with either the IC50 or the slope parameter estimates from a hill slope fit and treat these estimates as the response in a linear model. The current study investigates these two methods, as well as four novel methods, and compares their power to detect differences between the response profiles of genotypes under a variety of different alternatives. The four novel methods include two methods that summarize each dose-response by its area under the curve, one method based off of an analysis of variance (ANOVA) design, and one method that compares hill slope fits for all individuals of each genotype. The power of each method was found to depend not only on the choice of alternative, but also on the choice for the set of dosages used in cytotoxicity measurements. The ANOVA-based method was found to be the most robust across alternatives and dosage sets for power in detecting differences between genotypes.

Giving and withholding of information following genomic screening: challenges identified in a study of primary care physicians in Estonia

The use of predictive genomic information to improve medical care remains a contentious topic. However, it is generally agreed that the potential of genomics to improve medicine relies on medical care providers' ability to effectively communicate and put in context the meaning of test results. As the amount of information available increasingly outstrips providers' ability to offer qualified judgments on what the information means, consumers inevitably will be faced with test results of uncertain significance, as well as difficult questions about what they do or do not wish to know. Results of this survey of 64 primary care doctors in Estonia suggests that it may be inherently difficult for physicians to withhold genetic information obtained by genome scans or sequencing, even when they believe that having that information is not in the best interests of their patient. The descriptive data suggest introducing genomic medicine through primary care physicians, as proposed by the Estonian Genome Center of the University of Tartu, will require further genetics education as well as a carefully developed set of guidelines for determining where, when and how to use test results.

[Systematic review of the Genomewide Association Studies (GWAS) in schizophrenia]

INTRODUCTION

Heritability in schizophrenia can reach up to 80% and the risk in families is 5-10 times higher than in the general population. The large contribution of genetics in this disorder has led to a growing interest in its study.

OBJECTIVES

To review the findings of genetic studies known as Genomewide Association Studies (GWAS) on schizophrenia.

METHOD

Systematic search using Pubmed with the key words GWAS and (psychosis) or (schizophrenia). The following web pages have been reviewed: http://www.szgene.org/largescale.asp and www.genome.gov/gwastudies/.

RESULTS

The GWAS have focused on causal biological aspects, such as the histocompatibility complex, glutamate metabolism, apoptosis and inflammatory processes, and the immune system (TNF-β, TNFR1). Also focused in the search were the genes that modulate the appearance of secondary metabolic and cardiac effects and secondary effects in subjects with schizophrenia and on anti-psychotic treatment. In neurorecognition, over-expression of the MET proto-oncogene (MET) has been associated with a low susceptibility for schizophrenia and a better cognitive performance, as well as a lower susceptibility for the incidence of cancer. Mention is also made of the different genes that mediate in cognitive functioning depending on the anti-psychotic treatment received.

CONCLUSIONS

The main interests of the GWAS during the last few years have been the neurobiological pathways involved in schizophrenia. The discoveries arising from these studies have been limited. This has led to an innovative approach on the aetiological study of the disorder by studying gene-environment interactions.

Replication and cumulative effects of GWAS-identified genetic variations for prostate cancer in Asians: a case-control study in the ChinaPCa consortium

A recent genome-wide association study has identified five new genetic variants for prostate cancer susceptibility in a Japanese population, but it is unknown whether these newly identified variants are associated with prostate cancer risk in other populations, including Chinese men. We genotyped these five variants in a case-control study of 1524 patients diagnosed with prostate cancer and 2169 control subjects from the Chinese Consortium for Prostate Cancer Genetics (ChinaPCa). We found that three of the five genetic variants were associated with prostate cancer risk (P = 4.33 × 10(-8) for rs12653946 at 5p15, 4.43 × 10(-5) for rs339331 at 6q22 and 8.42 × 10(-4) for rs9600079 at 13q22, respectively). A cumulative effect was observed in a dose-dependent manner with increasing numbers of risk variant alleles (P(trend) = 2.58 × 10(-13)), and men with 5-6 risk alleles had a 2-fold higher risk of prostate cancer than men with 0-2 risk alleles (odds ratio = 2.26, 95% confidence interval = 1.78-2.87). Furthermore, rs339331 T allele was significantly associated with RFX6 and GPRC6A higher messenger RNA expression, compared with the C allele. However, none of the variants was associated with clinical stage, Gleason score or family history. These results provide further evidence that the risk loci identified in Japanese men also contribute to prostate cancer susceptibility in Chinese men.

Recent advances in understanding the role of nutrition in human genome evolution

Dietary transitions in human history have been suggested to play important roles in the evolution of mankind. Genetic variations caused by adaptation to diet during human evolution could have important health consequences in current society. The advance of sequencing technologies and the rapid accumulation of genome information provide an unprecedented opportunity to comprehensively characterize genetic variations in human populations and unravel the genetic basis of human evolution. Series of selection detection methods, based on various theoretical models and exploiting different aspects of selection signatures, have been developed. Their applications at the species and population levels have respectively led to the identification of human specific selection events that distinguish human from nonhuman primates and local adaptation events that contribute to human diversity. Scrutiny of candidate genes has revealed paradigms of adaptations to specific nutritional components and genome-wide selection scans have verified the prevalence of diet-related selection events and provided many more candidates awaiting further investigation. Understanding the role of diet in human evolution is fundamental for the development of evidence-based, genome-informed nutritional practices in the era of personal genomics.

Commentary: Children and predictive genomic testing: disease prevention, research protection, and our future

Genetic testing offered by direct-to-consumer companies-herein referred to as "predictive genomic testing"--has come under federal scrutiny. Critics claim testing yields uninterpretable and potentially harmful information. Supporters assert individuals have a right to this information, which could catalyze preventive health actions. Despite contentions that predictive genomic testing is a tool of primary disease prevention, little discussion has focused on its use with children. This partly stems from concerns expressed in existing professional guidelines about the potential for psychological and behavioral harm to children engendered by predictive genetic tests for Mendelian diseases. Conducting research to understand the actual benefits and harms is important for policy development and practice guidance and can be ethically justified within the pediatric regulatory framework of research that offers a prospect of direct benefit. Child health psychologists are well poised to contribute to this research effort, and promote the translation of genomic discoveries to improve pediatric medicine.

Next-generation DNA sequencing-based assay for measuring allelic expression imbalance (AEI) of candidate neuropsychiatric disorder genes in human brain

BACKGROUND

Common genetic variants that regulate gene expression are widely suspected to contribute to the etiology and phenotypic variability of complex diseases. Although high-throughput, microarray-based assays have been developed to measure differences in mRNA expression among independent samples, these assays often lack the sensitivity to detect rare mRNAs and the reproducibility to quantify small changes in mRNA expression. By contrast, PCR-based allelic expression imbalance (AEI) assays, which use a "marker" single nucleotide polymorphism (mSNP) in the mRNA to distinguish expression from pairs of genetic alleles in individual samples, have high sensitivity and accuracy, allowing differences in mRNA expression greater than 1.2-fold to be quantified with high reproducibility. In this paper, we describe the use of an efficient PCR/next-generation DNA sequencing-based assay to analyze allele-specific differences in mRNA expression for candidate neuropsychiatric disorder genes in human brain.

RESULTS

Using our assay, we successfully analyzed AEI for 70 candidate neuropsychiatric disorder genes in 52 independent human brain samples. Among these genes, 62/70 (89%) showed AEI ratios greater than 1 ± 0.2 in at least one sample and 8/70 (11%) showed no AEI. Arranging log2AEI ratios in increasing order from negative-to-positive values revealed highly reproducible distributions of log2AEI ratios that are distinct for each gene/marker SNP combination. Mathematical modeling suggests that these log2AEI distributions can provide important clues concerning the number, location and contributions of cis-acting regulatory variants to mRNA expression.

CONCLUSIONS

We have developed a highly sensitive and reproducible method for quantifying AEI of mRNA expressed in human brain. Importantly, this assay allowed quantification of differential mRNA expression for many candidate disease genes entirely missed in previously published microarray-based studies of mRNA expression in human brain. Given the ability of next-generation sequencing technology to generate large numbers of independent sequencing reads, our method should be suitable for analyzing from 100- to 200-candidate genes in 100 samples in a single experiment. We believe that this is the appropriate scale for investigating variation in mRNA expression for defined sets candidate disorder genes, allowing, for example, comprehensive coverage of genes that function within biological pathways implicated in specific disorders. The combination of AEI measurements and mathematical modeling described in this study can assist in identifying SNPs that correlate with mRNA expression. Alleles of these SNPs (individually or as sets) that accurately predict high- or low-mRNA expression should be useful as markers in genetic association studies aimed at linking candidate genes to specific neuropsychiatric disorders.

Post-genomic update on a classical candidate gene for coronary artery disease: ESR1

BACKGROUND

After age, sex is the most important risk factor for coronary artery disease (CAD). The mechanism through which women are protected from CAD is still largely unknown, but the observed sex difference suggests the involvement of the reproductive steroid hormone signaling system. Genetic association studies of the gene-encoding Estrogen Receptor α (ESR1) have shown conflicting results, although only a limited range of variation in the gene has been investigated.

METHODS AND RESULTS

We exploited information made available by advanced new methods and resources in complex disease genetics to revisit the question of ESR1's role in risk of CAD. We performed a meta-analysis of 14 genome-wide association studies (CARDIoGRAM discovery analysis, N=≈87,000) to search for population-wide and sex-specific associations between CAD risk and common genetic variants throughout the coding, noncoding, and flanking regions of ESR1. In addition to samples from the MIGen (N=≈6000), WTCCC (N=≈7400), and Framingham (N=≈3700) studies, we extended this search to a larger number of common and uncommon variants by imputation into a panel of haplotypes constructed using data from the 1000 Genomes Project. Despite the widespread expression of ERα in vascular tissues, we found no evidence for involvement of common or low-frequency genetic variation throughout the ESR1 gene in modifying risk of CAD, either in the general population or as a function of sex.

CONCLUSIONS

We suggest that future research on the genetic basis of sex-related differences in CAD risk should initially prioritize other genes in the reproductive steroid hormone biosynthesis system.

Genome-wide association studies (GWAS): impact on elucidating the aetiology of diabetes

It has proven to be challenging to isolate the genes underlying the genetic components conferring susceptibility to type 1 and type 2 diabetes. Unlike previous approaches, 'genome-wide association studies' have extensively delivered on the promise of uncovering genetic determinants of complex diseases, with a number of novel disease-associated variants being largely replicated by independent groups. This review provides an overview of these recent breakthroughs in the context of type 1 and type 2 diabetes, and outlines strategies on how these findings will be applied to impact clinical care for these two highly prevalent disorders.

A systems genetics approach provides a bridge from discovered genetic variants to biological pathways in rheumatoid arthritis

Genome-wide association studies (GWAS) have yielded novel genetic loci underlying common diseases. We propose a systems genetics approach to utilize these discoveries for better understanding of the genetic architecture of rheumatoid arthritis (RA). Current evidence of genetic associations with RA was sought through PubMed and the NHGRI GWAS catalog. The associations of 15 single nucleotide polymorphisms and HLA-DRB1 alleles were confirmed in 1,287 cases and 1,500 controls of Japanese subjects. Among these, HLA-DRB1 alleles and eight SNPs showed significant associations and all but one of the variants had the same direction of effect as identified in the previous studies, indicating that the genetic risk factors underlying RA are shared across populations. By receiver operating characteristic curve analysis, the area under the curve (AUC) for the genetic risk score based on the selected variants was 68.4%. For seropositive RA patients only, the AUC improved to 70.9%, indicating good but suboptimal predictive ability. A simulation study shows that more than 200 additional loci with similar effect size as recent GWAS findings or 20 rare variants with intermediate effects are needed to achieve AUC = 80.0%. We performed the random walk with restart (RWR) algorithm to prioritize genes for future mapping studies. The performance of the algorithm was confirmed by leave-one-out cross-validation. The RWR algorithm pointed to ZAP70 in the first rank, in which mutation causes RA-like autoimmune arthritis in mice. By applying the hierarchical clustering method to a subnetwork comprising RA-associated genes and top-ranked genes by the RWR, we found three functional modules relevant to RA etiology: "leukocyte activation and differentiation", "pattern-recognition receptor signaling pathway", and "chemokines and their receptors".These results suggest that the systems genetics approach is useful to find directions of future mapping strategies to illuminate biological pathways.

Thrombotic gene polymorphisms and postoperative outcome after coronary artery bypass graft surgery

Background

Emerging perioperative genomics may influence the direction of risk assessment and surgical strategies in cardiac surgery. The aim of this study was to investigate whether single nucleotide polymorphisms (SNP) affect the clinical presentation and predispose to increased risk for postoperative adverse events in patients undergoing coronary artery bypass grafting surgery (CABG).

Methods

A total of 220 patients undergoing first-time CABG between January 2005 and May 2008 were screened for factor V gene G1691A (FVL), prothrombin/factor II G20210A (PT G20210A), angiotensin I-converting enzyme insertion/deletion (ACE-ins/del) polymorphisms by PCR and Real Time PCR. End points were defined as death, myocardial infarction, stroke, postoperative bleeding, respiratory and renal insufficiency and event-free survival. Patients were compared to assess for any independent association between genotypes for thrombosis and postoperative phenotypes.

Results

Among 220 patients, the prevalence of the heterozygous FVL mutation was 10.9% (n = 24), and 3.6% (n = 8) were heterozygous carriers of the PT G20210A mutation. Genotype distribution of ACE-ins/del was 16.6%, 51.9%, and 31.5% in genotypes I/I, I/D, and D/D, respectively. FVL and PT G20210A mutations were associated with higher prevalence of totally occluded coronary arteries (p < 0.001). Furthermore the risk of left ventricular aneurysm formation was significantly higher in FVL heterozygote group compared to FVL G1691G (p = 0.002). ACE D/D genotype was associated with hypertension (p = 0.004), peripheral vascular disease (p = 0.006), and previous myocardial infarction (p = 0.007).

Conclusions

FVL and PT G20210A genotypes had a higher prevalence of totally occluded vessels potentially as a result of atherothrombotic events. However, none of the genotypes investigated were independently associated with mortality.

CDH13 is associated with working memory performance in attention deficit/hyperactivity disorder

Different analytic strategies, including linkage, association and meta-analysis support a role of CDH13 in the susceptibility to attention deficit/hyperactivity disorder (ADHD). CDH13 codes for cadherin 13 (or H-cadherin), which is a member of a family of calcium-dependent cell-cell adhesion proteins and a regulator of neural cell growth. We tested the association between CDH13 on three executive functioning tasks that are promising endophenotypes of ADHD. An adjusted linear regression analysis was performed in 190 ADHD-affected Dutch probands of the IMAGE project. Three executive functions were examined: inhibition, verbal and visuo-spatial working memory (WM). We tested 2632 single nucleotide polymorphisms (SNPs) within CDH13 and 20 kb up- and downstream of the gene (capturing regulatory sequences). To adjust for multiple testing within the gene, we applied stringent permutation steps. Intronic SNP rs11150556 is associated with performance on the Verbal WM task. No other SNP showed gene-wide significance with any of the analyzed traits, but a 72-kb SNP block located 446 kb upstream of SNP rs111500556 showed suggestive evidence for association (P-value range 1.20E-03 to 1.73E-04) with performance in the same Verbal WM task. This study is the first to examine CDH13 and neurocognitive functioning. The mechanisms underlying the associations between CDH13 and the clinical phenotype of ADHD and verbal WM are still unknown. As such, our study may be viewed as exploratory, with the results presented providing interesting hypotheses for further testing.

Siblings with ischemic stroke study: results of a genome-wide scan for stroke loci

BACKGROUND AND PURPOSE

Ischemic stroke has a strong familial component to risk. The Siblings With Ischemic Stroke Study (SWISS) is a genome-wide, family-based analysis that included use of imputed genotypes. The Siblings With Ischemic Stroke Study was conducted to examine the associations between single-nucleotide polymorphisms (SNPs) and risk of stroke and stroke subtypes within pairs.

METHODS

The Siblings With Ischemic Stroke Study enrolled 312 probands with ischemic stroke from 70 US and Canadian centers. Affected siblings were ascertained by centers and confirmed by central record review; unaffected siblings were ascertained by telephone contact. Ischemic stroke was subtyped according to Trial of Org 10172 in Acute Stroke Treatment criteria. Genotyping was performed with an Illumina 610 quad array (probands) and an Illumina linkage V array (affected siblings). SNPs were imputed by using 1000 Genomes Project data and MACH software. Family-based association analyses were conducted by using the sibling transmission-disequilibrium test.

RESULTS

For all pairs, the correlation of age at stroke within pairs of affected siblings was r=0.83 (95% CI, 0.78-0.86; P<2.2×10(-16)). The correlation did not differ substantially by subtype. The concordance of stroke subtypes among affected pairs was 33.8% (kappa=0.13; P=5.06×10(-4)) and did not differ by age at stroke in the proband. Although no SNP achieved genome-wide significance for risk of ischemic stroke, there was clustering of the most associated SNPs on chromosomes 3p (neuronal nitric oxide synthase) and 6p.

CONCLUSIONS

Stroke subtype and age at stroke in affected sibling pairs exhibit significant clustering. No individual SNP reached genome-wide significance. However, 2 promising candidate loci were identified, including 1 that contains neuronal nitric oxide synthase, although these risk loci warrant further examination in larger sample collections.

Inference of relationships in population data using identity-by-descent and identity-by-state

It is an assumption of large, population-based datasets that samples are annotated accurately whether they correspond to known relationships or unrelated individuals. These annotations are key for a broad range of genetics applications. While many methods are available to assess relatedness that involve estimates of identity-by-descent (IBD) and/or identity-by-state (IBS) allele-sharing proportions, we developed a novel approach that estimates IBD0, 1, and 2 based on observed IBS within windows. When combined with genome-wide IBS information, it provides an intuitive and practical graphical approach with the capacity to analyze datasets with thousands of samples without prior information about relatedness between individuals or haplotypes. We applied the method to a commonly used Human Variation Panel consisting of 400 nominally unrelated individuals. Surprisingly, we identified identical, parent-child, and full-sibling relationships and reconstructed pedigrees. In two instances non-sibling pairs of individuals in these pedigrees had unexpected IBD2 levels, as well as multiple regions of homozygosity, implying inbreeding. This combined method allowed us to distinguish related individuals from those having atypical heterozygosity rates and determine which individuals were outliers with respect to their designated population. Additionally, it becomes increasingly difficult to identify distant relatedness using genome-wide IBS methods alone. However, our IBD method further identified distant relatedness between individuals within populations, supported by the presence of megabase-scale regions lacking IBS0 across individual chromosomes. We benchmarked our approach against the hidden Markov model of a leading software package (PLINK), showing improved calling of distantly related individuals, and we validated it using a known pedigree from a clinical study. The application of this approach could improve genome-wide association, linkage, heterozygosity, and other population genomics studies that rely on SNP genotype data.

High-density microarrays measuring single nucleotide polymorphisms (SNPs) provide information about the genotypes across many loci. SNP genotypes observed for any two individuals can be compared in terms of identity-by-state (IBS), in which two individuals are observed to have 0, 1, or 2 alleles in common at a given locus, across a chromosomal region, or throughout the genome. These alleles may be shared identical-by-descent (IBD) in which 0, 1, or 2 alleles are inherited from a recent common ancestor, or they may be identical by chance because the allele is frequent in the population. The expected proportion of genome sharing between two individuals varies as a function of their genetic relatedness. We introduce a method to estimate IBD that can be used to analyze relatedness in pedigrees or in large-scale population studies with thousands of individuals. This can be combined with observed IBS to distinguish a variety of types of relatedness, providing theoretically justified results that are graphed in a manner that is straightforward to interpret. The methods we introduce are relevant to a variety of SNP applications including linkage and association studies and population genomics studies.

Identification of IL6R and chromosome 11q13.5 as risk loci for asthma

BACKGROUND

We aimed to identify novel genetic variants affecting asthma risk, since these might provide novel insights into molecular mechanisms underlying the disease.

METHODS

We did a genome-wide association study (GWAS) in 2669 physician-diagnosed asthmatics and 4528 controls from Australia. Seven loci were prioritised for replication after combining our results with those from the GABRIEL consortium (n=26,475), and these were tested in an additional 25,358 independent samples from four in-silico cohorts. Quantitative multi-marker scores of genetic load were constructed on the basis of results from the GABRIEL study and tested for association with asthma in our Australian GWAS dataset.

FINDINGS

Two loci were confirmed to associate with asthma risk in the replication cohorts and reached genome-wide significance in the combined analysis of all available studies (n=57,800): rs4129267 (OR 1·09, combined p=2·4×10(-8)) in the interleukin-6 receptor (IL6R) gene and rs7130588 (OR 1·09, p=1·8×10(-8)) on chromosome 11q13.5 near the leucine-rich repeat containing 32 gene (LRRC32, also known as GARP). The 11q13.5 locus was significantly associated with atopic status among asthmatics (OR 1·33, p=7×10(-4)), suggesting that it is a risk factor for allergic but not non-allergic asthma. Multi-marker association results are consistent with a highly polygenic contribution to asthma risk, including loci with weak effects that might be shared with other immune-related diseases, such as NDFIP1, HLA-B, LPP, and BACH2.

INTERPRETATION

The IL6R association further supports the hypothesis that cytokine signalling dysregulation affects asthma risk, and raises the possibility that an IL6R antagonist (tocilizumab) may be effective to treat the disease, perhaps in a genotype-dependent manner. Results for the 11q13.5 locus suggest that it directly increases the risk of allergic sensitisation which, in turn, increases the risk of subsequent development of asthma. Larger or more functionally focused studies are needed to characterise the many loci with modest effects that remain to be identified for asthma.

FUNDING

National Health and Medical Research Council of Australia. A full list of funding sources is provided in the webappendix.

From genes to therapeutic targets for psychiatric disorders - what to expect?

Neuropsychiatric disorders as schizophrenia, autism and mood disorders represent one of the leading causes of disability. The cost of bringing a drug to the market is increasing and becoming more risky. Pharmaceutical investments in neuroscience are decreasing. At the same time we are facing an unprecedented rate of discovery in human genetics. Genes predisposing for common diseases including psychiatric disorders are being identified. The knowledge derived from the identification of genes relevant for psychiatric disorders holds the promise of providing truly innovative therapeutic interventions. The process of approving new psychiatric drugs, is however complex, lengthy and requires a well orchestrated and funded effort of multiple disciplines. In this article a brief overview of the key learning obtained from the conduction genome-wide association studies, thus far, is given in an attempt to provide a realistic view on the potential contribution of human genetics to drug discovery in psychiatry.

Vaccinomics: current findings, challenges and novel approaches for vaccine development

Recent years have witnessed a growing interest in a field of vaccinology that we have named vaccinomics. The overall idea behind vaccinomics is to identify genetic and other mechanisms and pathways that determine immune responses, and thereby provide new candidate vaccine approaches. Considerable data show that host genetic polymorphisms act as important determinants of innate and adaptive immunity to vaccines. This review highlights examples of the role of immunogenetics and immunogenomics in understanding immune responses to vaccination, which are highly variable across the population. The influence of HLA genes, non-HLA, and innate genes in inter-individual variations in immune responses to viral vaccines are examined using population-based gene/SNP association studies. The ability to understand relationships between immune response gene variants and vaccine-specific immunity may assist in designing new vaccines. At the same time, application of state-of-the-art next-generation sequencing technology (and bioinformatics) is desired to provide new genetic information and its relationship to the immune response.

Realizing the promise of population biobanks: a new model for translation

The promise of science lies in expectations of its benefits to societies and is matched by expectations of the realisation of the significant public investment in that science. In this paper, we undertake a methodological analysis of the science of biobanking and a sociological analysis of translational research in relation to biobanking. Part of global and local endeavours to translate raw biomedical evidence into practice, biobanks aim to provide a platform for generating new scientific knowledge to inform development of new policies, systems and interventions to enhance the public's health. Effectively translating scientific knowledge into routine practice, however, involves more than good science. Although biobanks undoubtedly provide a fundamental resource for both clinical and public health practice, their potentiating ontology--that their outputs are perpetually a promise of scientific knowledge generation--renders translation rather less straightforward than drug discovery and treatment implementation. Biobanking science, therefore, provides a perfect counterpoint against which to test the bounds of translational research. We argue that translational research is a contextual and cumulative process: one that is necessarily dynamic and interactive and involves multiple actors. We propose a new multidimensional model of translational research which enables us to imagine a new paradigm: one that takes us from bench to bedside to backyard and beyond, that is, attentive to the social and political context of translational science, and is cognisant of all the players in that process be they researchers, health professionals, policy makers, industry representatives, members of the public or research participants, amongst others.

Understanding the contribution of synonymous mutations to human disease

Synonymous mutations - sometimes called 'silent' mutations - are now widely acknowledged to be able to cause changes in protein expression, conformation and function. The recent increase in knowledge about the association of genetic variants with disease, particularly through genome-wide association studies, has revealed a substantial contribution of synonymous SNPs to human disease risk and other complex traits. Here we review current understanding of the extent to which synonymous mutations influence disease, the various molecular mechanisms that underlie these effects and the implications for future research and biomedical applications.

Design and coverage of high throughput genotyping arrays optimized for individuals of East Asian, African American, and Latino race/ethnicity using imputation and a novel hybrid SNP selection algorithm

Four custom Axiom genotyping arrays were designed for a genome-wide association (GWA) study of 100,000 participants from the Kaiser Permanente Research Program on Genes, Environment and Health. The array optimized for individuals of European race/ethnicity was previously described. Here we detail the development of three additional microarrays optimized for individuals of East Asian, African American, and Latino race/ethnicity. For these arrays, we decreased redundancy of high-performing SNPs to increase SNP capacity. The East Asian array was designed using greedy pairwise SNP selection. However, removing SNPs from the target set based on imputation coverage is more efficient than pairwise tagging. Therefore, we developed a novel hybrid SNP selection method for the African American and Latino arrays utilizing rounds of greedy pairwise SNP selection, followed by removal from the target set of SNPs covered by imputation. The arrays provide excellent genome-wide coverage and are valuable additions for large-scale GWA studies.

Gene- or region-based association study via kernel principal component analysis

Background

In genetic association study, especially in GWAS, gene- or region-based methods have been more popular to detect the association between multiple SNPs and diseases (or traits). Kernel principal component analysis combined with logistic regression test (KPCA-LRT) has been successfully used in classifying gene expression data. Nevertheless, the purpose of association study is to detect the correlation between genetic variations and disease rather than to classify the sample, and the genomic data is categorical rather than numerical. Recently, although the kernel-based logistic regression model in association study has been proposed by projecting the nonlinear original SNPs data into a linear feature space, it is still impacted by multicolinearity between the projections, which may lead to loss of power. We, therefore, proposed a KPCA-LRT model to avoid the multicolinearity.

Results

Simulation results showed that KPCA-LRT was always more powerful than principal component analysis combined with logistic regression test (PCA-LRT) at different sample sizes, different significant levels and different relative risks, especially at the genewide level (1E-5) and lower relative risks (RR = 1.2, 1.3). Application to the four gene regions of rheumatoid arthritis (RA) data from Genetic Analysis Workshop16 (GAW16) indicated that KPCA-LRT had better performance than single-locus test and PCA-LRT.

Conclusions

KPCA-LRT is a valid and powerful gene- or region-based method for the analysis of GWAS data set, especially under lower relative risks and lower significant levels.

Molecular genetics of meningiomas: a systematic review of the current literature and potential basis for future treatment paradigms

Although a majority of meningiomas are benign neoplasms, those occurring at the cranial base may be challenging tumors to treat because of extensive tissue invasion, an inability to achieve gross-total microscopic resection, and local tumor recurrence and/or progression. A more comprehensive understanding of the genetic abnormalities associated with meningioma tumorigenesis, growth, and invasion may provide novel targets for grading assessments and individualizing molecular therapies for skull base meningiomas. The authors performed a review of the current literature to identify genes that have been associated with the formation and/or progression of meningiomas. Mutations in the NF2 gene have been most commonly implicated in the formation of the majority of meningiomas. Inactivation of other tumor suppressor genes, including DAL-1 and various tissue inhibitors of matrix metalloproteinases, upregulation of several oncogenes including c-sis and STAT3, and signaling dysregulation of pathways such as the Wnt pathway, have each been found to play important, and perhaps, complementary roles in meningioma development, progression, and recurrence. Identification of these genetic factors using genome-wide association studies and high-throughput genomics may provide data for future individualized treatment strategies.

Direct-to-consumer personalized genomic testing

Over the past 18 months, there have been notable developments in the direct-to-consumer (DTC) genomic testing arena, in particular with regard to issues surrounding governmental regulation in the USA. While commentaries continue to proliferate on this topic, actual empirical research remains relatively scant. In terms of DTC genomic testing for disease susceptibility, most of the research has centered on uptake, perceptions and attitudes toward testing among health care professionals and consumers. Only a few available studies have examined actual behavioral response among consumers, and we are not aware of any studies that have examined response to DTC genetic testing for ancestry or for drug response. We propose that further research in this area is desperately needed, despite challenges in designing appropriate studies given the rapid pace at which the field is evolving. Ultimately, DTC genomic testing for common markers and conditions is only a precursor to the eventual cost-effectiveness and wide availability of whole genome sequencing of individuals, although it remains unclear whether DTC genomic information will still be attainable. Either way, however, current knowledge needs to be extended and enhanced with respect to the delivery, impact and use of increasingly accurate and comprehensive individualized genomic data.

Genetics of common forms of heart failure

PURPOSE OF REVIEW

Genetic factors contribute to overall heart failure risk, but specific risk alleles are only beginning to be identified. Here, new results from candidate gene and genome-wide polymorphism studies that have delineated associations between polymorphic genes and heart failure are reviewed in the context of their likely clinical translation and implementation.

RECENT FINDINGS

Recent data support and extend consequences of genetically variant β1-adrenergic receptors and G-protein receptor kinase 5 on heart failure. New genome-wide and subgenome-wide studies have identified unexpected genetic modifiers of heart failure risk and outcome, suggesting that determinants of heart failure onset and progression are distinct, and pointing to unexpected genetic interactions in cardiac disease.

SUMMARY

Advances in high-throughput genotyping and resequencing herald a rapid expansion of genomic information in heart failure. With identification of putative heart failure risk alleles, the next step will be prospective clinical trials evaluating the benefits of genotype-directed heart failure management.

Genetic modifiers of non-alcoholic fatty liver disease progression

Non-alcoholic fatty liver disease (NAFLD) is now recognised as the most common cause of liver dysfunction worldwide. However, whilst the majority of individuals who exhibit features of the metabolic syndrome including obesity and insulin resistance will develop steatosis, only a minority progress to steatohepatitis, fibrosis and cirrhosis. Subtle inter-patient genetic variations and environment interact to determine disease phenotype and influence progression. A decade after the sequencing of the human genome, the comprehensive study of genomic variation offers new insights into the modifier genes, pathogenic mechanisms and is beginning to suggest novel therapeutic targets. We review the current status of the field with particular focus on advances from recent genome-wide association studies.

Annotating individual human genomes

Advances in DNA sequencing technologies have made it possible to rapidly, accurately and affordably sequence entire individual human genomes. As impressive as this ability seems, however, it will not likely amount to much if one cannot extract meaningful information from individual sequence data. Annotating variations within individual genomes and providing information about their biological or phenotypic impact will thus be crucially important in moving individual sequencing projects forward, especially in the context of the clinical use of sequence information. In this paper we consider the various ways in which one might annotate individual sequence variations and point out limitations in the available methods for doing so. It is arguable that, in the foreseeable future, DNA sequencing of individual genomes will become routine for clinical, research, forensic, and personal purposes. We therefore also consider directions and areas for further research in annotating genomic variants.

Alzheimer's disease genetics: current knowledge and future challenges

Alzheimer's disease (AD) is highly heritable, but genetically complex. Recently, three large-scale genome-wide association studies have made substantial breakthroughs in disentangling the genetic architecture of the disease. These studies combined include data from over 43 000 independent individuals and provide compelling evidence that variants in four novel susceptibility genes (CLU, PICALM, CR1, BIN1) are associated with disease risk. These findings are tremendously exciting, not only in providing new avenues for exploration, but also highlighting the potential for further gene discovery when larger samples are analysed. Here we discuss progress to date in identifying risk genes for dementia, ways forward and how current findings are refining previous ideas and defining new putative primary disease mechanisms.