deCODE genetics, Inc

Big data in sarcoidosis

PURPOSE OF REVIEW

This review provides an overview of recent advancements in sarcoidosis research, focusing on collaborative networks, phenotype characterization, and molecular studies. It highlights the importance of collaborative efforts, phenotype characterization, and the integration of multilevel molecular data for advancing sarcoidosis research and paving the way toward personalized medicine.

RECENT FINDINGS

Sarcoidosis exhibits heterogeneous clinical manifestations influenced by various factors. Efforts to define sarcoidosis endophenotypes show promise, while technological advancements enable extensive molecular data generation. Collaborative networks and biobanks facilitate large-scale studies, enhancing biomarker discovery and therapeutic protocols.

SUMMARY

Sarcoidosis presents a complex challenge due to its unknown cause and heterogeneous clinical manifestations. Collaborative networks, comprehensive phenotype delineation, and the utilization of cutting-edge technologies are essential for advancing our understanding of sarcoidosis biology and developing personalized medicine approaches. Leveraging large-scale epidemiological resources and biobanks and integrating multilevel molecular data offer promising avenues for unraveling the disease's heterogeneity and improving patient outcomes.

Exploring family communication preferences in hereditary breast and ovarian cancer and Lynch syndrome: a national Canadian survey

BACKGROUND

Individuals affected with cancer predisposition (CPS) syndromes such as BRCA1, BRCA2 or Lynch syndrome (LS) are at an elevated risk of multiple cancers. Identifying high-risk individuals is important if they are to access risk-reducing strategies. Interventions such as risk-reducing salpingo-oophorectomy in carriers of BRCA pathogenic or likely pathogenic (P/LP) variants or regular colonoscopy for carriers of LS P/LP variants are highly effective and reduce mortality. Despite clear evidence that the identification of at-risk relatives has value, the uptake of cascade testing remains at approximately 50%. It is important to understand strategies and barriers to testing to facilitate communication in families identified as haveing a hereditary cancer syndrome, to improve uptake of counselling and testing.

METHOD

A national online survey of both Canadian probands (the first member in a family to have genetic testing and who were variant positive, regardless of a cancer diagnosis) and their at-risk relatives. Respondents were individuals affected with hereditary breast and ovarian cancer (HBOC) and LS. The survey was constructed based on a review of the literature and authors' feedback. Both open and closed-ended questions were used for items on demographic characteristics, risk perception, genetic test results and cancer diagnosis. Items on experiences with hereditary cancer risk communication, communication challenges, preferences and supports required were explored using a 5-point Likert scale.

RESULTS

Responses indicated a high level of acceptance for the proband's direct involvement in family communication with the support of a health care provider (67% among the probands given a family letter and 55-57% among those who were not given a family letter). Respondents without a personal history of cancer were more likely to endorse a health care professional's help with family communication compared to those with a personal history of cancer (p = 0.031). Preferences for family member outreach also varied by education level, annual income, marital status and geographic location. Similarities were noted between the probands and relatives on communication outreach preferences.

CONCLUSION

While the family-mediated approach to communication remains the standard across many cancer genetics programs, participants note that additional support is necessary for dissemination of result information among relatives. Because family dynamics and communication vary widely, alternative options that retain the probands' involvement in family communication but add support from a health care provider should be explored.

Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum

Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (rg=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (rg=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no rg between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.

Genomic approaches to identify and investigate genes associated with atrial fibrillation and heart failure susceptibility

Atrial fibrillation (AF) and heart failure (HF) contribute to about 45% of all cardiovascular disease (CVD) deaths in the USA and around the globe. Due to the complex nature, progression, inherent genetic makeup, and heterogeneity of CVDs, personalized treatments are believed to be critical. To improve the deciphering of CVD mechanisms, we need to deeply investigate well-known and identify novel genes that are responsible for CVD development. With the advancements in sequencing technologies, genomic data have been generated at an unprecedented pace to foster translational research. Correct application of bioinformatics using genomic data holds the potential to reveal the genetic underpinnings of various health conditions. It can help in the identification of causal variants for AF, HF, and other CVDs by moving beyond the one-gene one-disease model through the integration of common and rare variant association, the expressed genome, and characterization of comorbidities and phenotypic traits derived from the clinical information. In this study, we examined and discussed variable genomic approaches investigating genes associated with AF, HF, and other CVDs. We collected, reviewed, and compared high-quality scientific literature published between 2009 and 2022 and accessible through PubMed/NCBI. While selecting relevant literature, we mainly focused on identifying genomic approaches involving the integration of genomic data; analysis of common and rare genetic variants; metadata and phenotypic details; and multi-ethnic studies including individuals from ethnic minorities, and European, Asian, and American ancestries. We found 190 genes associated with AF and 26 genes linked to HF. Seven genes had implications in both AF and HF, which are SYNPO2L, TTN, MTSS1, SCN5A, PITX2, KLHL3, and AGAP5. We listed our conclusion, which include detailed information about genes and SNPs associated with AF and HF.

New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications

Psychiatric genetics has made substantial progress in the last decade, providing new insights into the genetic etiology of psychiatric disorders, and paving the way for precision psychiatry, in which individual genetic profiles may be used to personalize risk assessment and inform clinical decision-making. Long recognized to be heritable, recent evidence shows that psychiatric disorders are influenced by thousands of genetic variants acting together. Most of these variants are commonly occurring, meaning that every individual has a genetic risk to each psychiatric disorder, from low to high. A series of large-scale genetic studies have discovered an increasing number of common and rare genetic variants robustly associated with major psychiatric disorders. The most convincing biological interpretation of the genetic findings implicates altered synaptic function in autism spectrum disorder and schizophrenia. However, the mechanistic understanding is still incomplete. In line with their extensive clinical and epidemiological overlap, psychiatric disorders appear to exist on genetic continua and share a large degree of genetic risk with one another. This provides further support to the notion that current psychiatric diagnoses do not represent distinct pathogenic entities, which may inform ongoing attempts to reconceptualize psychiatric nosology. Psychiatric disorders also share genetic influences with a range of behavioral and somatic traits and diseases, including brain structures, cognitive function, immunological phenotypes and cardiovascular disease, suggesting shared genetic etiology of potential clinical importance. Current polygenic risk score tools, which predict individual genetic susceptibility to illness, do not yet provide clinically actionable information. However, their precision is likely to improve in the coming years, and they may eventually become part of clinical practice, stressing the need to educate clinicians and patients about their potential use and misuse. This review discusses key recent insights from psychiatric genetics and their possible clinical applications, and suggests future directions.

Genomic data integration and user-defined sample-set extraction for population variant analysis

BACKGROUND

Population variant analysis is of great importance for gathering insights into the links between human genotype and phenotype. The 1000 Genomes Project established a valuable reference for human genetic variation; however, the integrative use of the corresponding data with other datasets within existing repositories and pipelines is not fully supported. Particularly, there is a pressing need for flexible and fast selection of population partitions based on their variant and metadata-related characteristics.

RESULTS

Here, we target general germline or somatic mutation data sources for their seamless inclusion within an interoperable-format repository, supporting integration among them and with other genomic data, as well as their integrated use within bioinformatic workflows. In addition, we provide VarSum, a data summarization service working on sub-populations of interest selected using filters on population metadata and/or variant characteristics. The service is developed as an optimized computational framework with an Application Programming Interface (API) that can be called from within any existing computing pipeline or programming script. Provided example use cases of biological interest show the relevance, power and ease of use of the API functionalities.

CONCLUSIONS

The proposed data integration pipeline and data set extraction and summarization API pave the way for solid computational infrastructures that quickly process cumbersome variation data, and allow biologists and bioinformaticians to easily perform scalable analysis on user-defined partitions of large cohorts from increasingly available genetic variation studies. With the current tendency to large (cross)nation-wide sequencing and variation initiatives, we expect an ever growing need for the kind of computational support hereby proposed.

COVID-19: impact on Public Health and hypothesis-driven investigations on genetic susceptibility and severity

COVID-19 is a new complex multisystem disease caused by the novel coronavirus SARS-CoV-2. In slightly over 2 years, it infected nearly 500 million and killed 6 million human beings worldwide, causing an unprecedented coronavirus pandemic. Currently, the international scientific community is engaged in elucidating the molecular mechanisms of the pathophysiology of SARS-CoV-2 infection as a basis of scientific developments for the future control of COVID-19. Global exome and genome analysis efforts work to define the human genetics of protective immunity to SARS-CoV-2 infection. Here, we review the current knowledge regarding the SARS-CoV-2 infection, the implications of COVID-19 to Public Health and discuss genotype to phenotype association approaches that could be exploited through the selection of candidate genes to identify the genetic determinants of severe COVID-19.

The Scientific Impact Derived From the Disciplinary Profiles

The disciplinary profiles of the mean citation rates across 22 research areas were analyzed for 107 countries/territories that published at least 3,000 papers that exceeded the entrance thresholds for the Essential Science Indicators (ESI; Clarivate Analytics) during the period from January 1, 2009 to December 31, 2019. The matrix of pairwise differences between any two profiles was analyzed with a non-metric multidimensional scaling (MDS) algorithm, which recovered a two-dimensional geometric space describing these differences. These two dimensions, Dim1 and Dim2, described 5,671 pairwise differences between countries' disciplinary profiles with a sufficient accuracy (stress = 0.098). A significant correlation (r = 0.81, N = 107, p < 0.0001) was found between Dim1 and the Indicator of a Nation's Scientific Impact (INSI), which was computed as a composite of the average and the top citation rates. The scientific impact ranking of countries derived from the pairwise differences between disciplinary profiles seems to be more accurate and realistic compared with more traditional citation indices.

A polygenic resilience score moderates the genetic risk for schizophrenia

Based on the discovery by the Resilience Project (Chen R. et al. Nat Biotechnol 34:531-538, 2016) of rare variants that confer resistance to Mendelian disease, and protective alleles for some complex diseases, we posited the existence of genetic variants that promote resilience to highly heritable polygenic disorders1,0 such as schizophrenia. Resilience has been traditionally viewed as a psychological construct, although our use of the term resilience refers to a different construct that directly relates to the Resilience Project, namely: heritable variation that promotes resistance to disease by reducing the penetrance of risk loci, wherein resilience and risk loci operate orthogonal to one another. In this study, we established a procedure to identify unaffected individuals with relatively high polygenic risk for schizophrenia, and contrasted them with risk-matched schizophrenia cases to generate the first known "polygenic resilience score" that represents the additive contributions to SZ resistance by variants that are distinct from risk loci. The resilience score was derived from data compiled by the Psychiatric Genomics Consortium, and replicated in three independent samples. This work establishes a generalizable framework for finding resilience variants for any complex, heritable disorder.

Gene-environment interaction with smoking for increased non-muscle-invasive bladder cancer tumor size

Background

Urinary bladder cancer (UBC) is one of few cancers with an established gene-environment interaction (GxE) with smoking. However, it is unknown whether the interaction with tobacco use is present non-muscle invasive bladder cancer (NMIBC) and characteristics of prognostic relevance. We aimed to investigate if smoking status and/or smoking intensity interact with the effect of discovered variants on key NMIBC characteristics of tumor grade, stage, size, and patient age within the Bladder Cancer Prognosis Programme (BCPP) cohort.

Methods

Analyzed sample consisted of 546 NMIBC patients with valid smoking data from the BCPP. In a previous genome-wide association study (GWAS), we have identified 61 single nucleotide polymorphisms (SNPs) potentially associated with the NMIBC characteristics of tumor stage, grade, size, and patient age. In the current analysis, we have tested these SNPs for GxE with smoking.

Results

Out of 61 SNPs, 10 have showed suggestion (statistical significance level of P<0.05) for GxE with NMIBC tumor size rs35225990, rs188958632, rs180910528, rs74603364, rs187040828, rs144383242, rs117587674, rs113705641, rs2937268, and chromosome 14:38247577. All SNPs were located across loci of 1p31.3, 3p26.1, 6q14.1, 14q21.1, and 13q14.13. In addition, two of the tested polymorphisms were suggestive for interaction with smoking intensity (chromosome 14:38247577 and rs2937268).

Conclusions

Our study suggests interaction between genetic variance and smoking behavior for increased NMIBC tumor size at the time of diagnosis. Further replication is required to validate these findings.

Elucidating the role of maternal environmental exposures on offspring health and disease using two-sample Mendelian randomization

BACKGROUND

There is considerable interest in estimating the causal effect of a range of maternal environmental exposures on offspring health-related outcomes. Previous attempts to do this using Mendelian randomization methodologies have been hampered by the paucity of epidemiological cohorts with large numbers of genotyped mother-offspring pairs.

METHODS

We describe a new statistical model that we have created which can be used to estimate the effect of maternal genotypes on offspring outcomes conditional on offspring genotype, using both individual-level and summary-results data, even when the extent of sample overlap is unknown.

RESULTS

We describe how the estimates obtained from our method can subsequently be used in large-scale two-sample Mendelian randomization studies to investigate the causal effect of maternal environmental exposures on offspring outcomes. This includes studies that aim to assess the causal effect of in utero exposures related to fetal growth restriction on future risk of disease in offspring. We illustrate our framework using examples related to offspring birthweight and cardiometabolic disease, although the general principles we espouse are relevant for many other offspring phenotypes.

CONCLUSIONS

We advocate for the establishment of large-scale international genetics consortia that are focused on the identification of maternal genetic effects and committed to the public sharing of genome-wide summary-results data from such efforts. This information will facilitate the application of powerful two-sample Mendelian randomization studies of maternal exposures and offspring outcomes.

Pseudonymization for research data collection: is the juice worth the squeeze?

BACKGROUND

The collection of data and biospecimens which characterize patients and probands in-depth is a core element of modern biomedical research. Relevant data must be considered highly sensitive and it needs to be protected from unauthorized use and re-identification. In this context, laws, regulations, guidelines and best-practices often recommend or mandate pseudonymization, which means that directly identifying data of subjects (e.g. names and addresses) is stored separately from data which is primarily needed for scientific analyses.

DISCUSSION

When (authorized) re-identification of subjects is not an exceptional but a common procedure, e.g. due to longitudinal data collection, implementing pseudonymization can significantly increase the complexity of software solutions. For example, data stored in distributed databases, need to be dynamically combined with each other, which requires additional interfaces for communicating between the various subsystems. This increased complexity may lead to new attack vectors for intruders. Obviously, this is in contrast to the objective of improving data protection. What is lacking is a standardized process of evaluating and reporting risks, threats and countermeasures, which can be used to test whether integrating pseudonymization methods into data collection systems actually improves upon the degree of protection provided by system designs that simply follow common IT security best practices and implement fine-grained role-based access control models. To demonstrate that the methods used to describe systems employing pseudonymized data management are currently heterogeneous and ad-hoc, we examined the extent to which twelve recent studies address each of the six basic security properties defined by the International Organization for Standardization (ISO) standard 27,000. We show inconsistencies across the studies, with most of them failing to mention one or more security properties.

CONCLUSION

We discuss the degree of privacy protection provided by implementing pseudonymization into research data collection processes. We conclude that (1) more research is needed on the interplay of pseudonymity, information security and data protection, (2) problem-specific guidelines for evaluating and reporting risks, threats and countermeasures should be developed and that (3) future work on pseudonymized research data collection should include the results of such structured and integrated analyses.

Genomic and Phenomic Research in the 21st Century

The field of human genomics has changed dramatically over time. Initial genomic studies were predominantly restricted to rare disorders in small families. Over the past decade, researchers changed course from family-based studies and instead focused on common diseases and traits in populations of unrelated individuals. With further advancements in biobanking, computer science, electronic health record (EHR) data, and more affordable high-throughput genomics, we are experiencing a new paradigm in human genomic research. Rapidly changing technologies and resources now make it possible to study thousands of diseases simultaneously at the genomic level. This review will focus on these advancements as scientists begin to incorporate phenome-wide strategies in human genomic research to understand the etiology of human diseases and develop new drugs to treat them.

Toward critical bioethics

This article deals with the question as to what makes bioethics a critical discipline. It considers different senses of criticism and evaluates their strengths and weaknesses. A primary method in bioethics as a philosophical discipline is critical thinking, which implies critical evaluation of concepts, positions, and arguments. It is argued that the type of analytical criticism that restricts its critical role to critical thinking of this type often suffers from other intellectual flaws. Three examples are taken to demonstrate this: premature criticism, uncritical self-understanding of theoretical assumptions, and narrow framing of bioethical issues. Such flaws can lead both to unfair treatment of authors and to uncritical discussion of topics. In this context, the article makes use of Häyry's analysis of different rationalities in bioethical approaches and argues for the need to recognize the importance of communicative rationality for critical bioethics. A radically different critical approach in bioethics, rooted in social theory, focuses on analyses of power relations neglected in mainstream critical thinking. It is argued that, although this kind of criticism provides an important alternative in bioethics, it suffers from other shortcomings that are rooted in a lack of normative dimensions. In order to complement these approaches and counter their shortcomings, there is a need for a bioethics enlightened by critical hermeneutics. Such hermeneutic bioethics is aware of its own assumptions, places the issues in a wide context, and reflects critically on the power relations that stand in the way of understanding them. Moreover, such an approach is dialogical, which provides both a critical exercise of speech and a normative dimension implied in the free exchange of reasons and arguments. This discussion is framed by Hedgecoe's argument that critical bioethics needs four elements: to be empirically rooted, theory challenging, reflexive, and politely skeptical.

A generic solution for web-based management of pseudonymized data

BACKGROUND

Collaborative collection and sharing of data have become a core element of biomedical research. Typical applications are multi-site registries which collect sensitive person-related data prospectively, often together with biospecimens. To secure these sensitive data, national and international data protection laws and regulations demand the separation of identifying data from biomedical data and to introduce pseudonyms. Neither the formulation in laws and regulations nor existing pseudonymization concepts, however, are precise enough to directly provide an implementation guideline. We therefore describe core requirements as well as implementation options for registries and study databases with sensitive biomedical data.

METHODS

We first analyze existing concepts and compile a set of fundamental requirements for pseudonymized data management. Then we derive a system architecture that fulfills these requirements. Next, we provide a comprehensive overview and a comparison of different technical options for an implementation. Finally, we develop a generic software solution for managing pseudonymized data and show its feasibility by describing how we have used it to realize two research networks.

RESULTS

We have found that pseudonymization models are highly heterogeneous, already on a conceptual level. We have compiled a set of requirements from different pseudonymization schemes. We propose an architecture and present an overview of technical options. Based on a selection of technical elements, we suggest a generic solution. It supports the multi-site collection and management of biomedical data. Security measures are multi-tier pseudonymity and physical separation of data over independent backend servers. Integrated views are provided by a web-based user interface. Our approach has been successfully used to implement a national and an international rare disease network.

CONCLUSIONS

We were able to identify a set of core requirements out of several pseudonymization models. Considering various implementation options, we realized a generic solution which was implemented and deployed in research networks. Still, further conceptual work on pseudonymity is needed. Specifically, it remains unclear how exactly data is to be separated into distributed subsets. Moreover, a thorough risk and threat analysis is needed.

What's more general than a whole population?

Statistical inference is commonly said to be inapplicable to complete population studies, such as censuses, due to the absence of sampling variability. Nevertheless, in recent years, studies of whole populations, e.g., all cases of a certain cancer in a given country, have become more common, and often report p values and confidence intervals regardless of such concerns. With reference to the social science literature, the current paper explores the circumstances under which statistical inference can be meaningful for such studies. It concludes that its use implicitly requires a target population which is wider than the whole population studied - for example future cases, or a supranational geographic region - and that the validity of such statistical analysis depends on the generalizability of the whole to the target population.

Scientific citizenship in a democratic society

Using the example of the sociological analysis of biological citizenship and literacy, it is argued that a merely descriptive analysis of these phenomena does not capture their distinctive normative features. While such a description realistically demonstrates how citizens respond to and are shaped by biotechnology and biomedical discourse, it provides no critique of the forces moulding the citizen-consumer. Ideas of active citizenship fuel the search for forms of public engagement in the spirit of deliberative democracy. While these attempts are guided by an important vision of policy making in democratic society, they are beset with several practical difficulties. It is argued that the discussion of deliberative practices has focused too much on direct participation of citizens in various dialogical events and its impact on policy and decision making. This approach ignores other important aspects of deliberative democratic theory, emphasizing public accountability and trustworthiness of democratic institutions.

Public health in the genomic era: will Public Health Genomics contribute to major changes in the prevention of common diseases?

The completion of the Human Genome Project triggered a whole new field of genomic research which is likely to lead to new opportunities for the promotion of population health. As a result, the distinction between genetic and environmental diseases has faded. Presently, genomics and knowledge deriving from systems biology, epigenomics, integrative genomics or genome-environmental interactions give a better insight on the pathophysiology of common diseases. However, it is barely used in the prevention and management of diseases. Together with the boost in the amount of genetic association studies, this demands for appropriate public health actions. The field of Public Health Genomics analyses how genome-based knowledge and technologies can responsibly and effectively be integrated into health services and public policy for the benefit of population health. Environmental exposures interact with the genome to produce health information which may help explain inter-individual differences in health, or disease risk. However today, prospects for concrete applications remain distant. In addition, this information has not been translated into health practice yet. Therefore, evidence-based recommendations are few. The lack of population-based research hampers the evaluation of the impact of genomic applications. Public Health Genomics also evaluates the benefits and risks on a larger scale, including normative, legal, economic and social issues. These new developments are likely to affect all domains of public health and require rethinking the role of genomics in every condition of public health interest. This article aims at providing an introduction to the field of and the ideas behind Public Health Genomics.

Database Research: Public and Private Interests

It is often argued that a major tension in bioethics is between protecting the private interests of individuals on one hand and contributing to the common good on the other. In this article I ask how fitting this description is as regards the interest at stake in relation to the issue of consent to participation in population data collections. I raise some doubts about what I take to be two common positions regarding public and private interests in this context. The first is that restricted individual consent protects private interests at the cost of public interest.

Recent advances in the genetics and genomics of asthma and related traits

PURPOSE OF REVIEW

Asthma is a complex phenotype caused by a combination of genetic and environmental factors that remain poorly understood. The common variants involved in the pathogenesis of asthma have proved difficult to identify by candidate gene association studies. Recently genome-wide association (GWA) studies have been applied to asthma with considerable success.

RECENT FINDINGS

The past 12 months have seen some notable advances in the genetics of asthma including five GWA studies using asthma status as an endpoint, as well as one chronic obstructive pulmonary disease study and five GWA studies of intermediate phenotypes, one each on serum immunoglobulin E (IgE) levels, blood eosinophil counts and three on lung function as measured by spirometry. There have also been several publications on the previously reported asthma locus on 17q21 replicating the association in multiple populations and showing specific association in patients with early tobacco smoke exposure and with early-onset asthma as well as with nonatopic asthma.

SUMMARY

A wealth of genetic data has been generated on asthma since the publication of the first GWA study in 2007 resulting in the identification of a novel asthma locus as well as novel loci for lung function, eosinophil count and IgE levels. In this review we summarize the most pertinent of these advances.

Bioethics in Iceland

Recent bioethics discussion and research in Iceland has been greatly affected by the fact that one of the world’s largest genetics research companies is based there and has been in the forefront of creating a population database resource for its research projects. Consequently, a large part of this article is centered around the bioethical discussion engendered by these projects, but other recent bioethical developments related to issues at the beginning and the end of life will also be discussed.

Neuregulin-1 genotypes and eye movements in schizophrenia

Neuregulin-1 (NRG-1) is a putative susceptibility gene for schizophrenia but the neurocognitive processes that may involve NRG-1 in schizophrenia are unknown. Deficits in antisaccade (AS) and smooth pursuit eye movements (SPEM) are promising endophenotypes, which may be associated with brain dysfunctions underlying the pathophysiology of schizophrenia. The aim of this study was to investigate the associations of NRG-1 genotypes with AS and SPEM in schizophrenia patients and healthy controls. Patients (N = 113) and controls (N = 106) were genotyped for two NRG-1 single nucleotide polymorphisms (SNPs); SNP8NRG222662, a surrogate marker for the originally described Icelandic NRG-1 risk haplotype, and SNP8NRG243177, which has recently been associated with individual differences in brain function. Subjects underwent infrared oculographic assessment of AS and SPEM. The study replicates previous findings of impaired AS and SPEM performance in schizophrenia patients (all P < 0.005; all d = 0.5-1.5). SNP8NRG243177 risk allele carriers had marginally increased variability of AS spatial error (P = 0.050, d = 0.3), but there were no significant genotype effects on other eye movement variables and no significant diagnosis-by-genotype interactions. Generally, risk allele carriers (G allele for SNP8NRG222662 and T allele for SNP8NRG243177) had numerically worse performance than non-carriers on most AS and SPEM variables. The results do not suggest that NRG-1 genotype significantly affects AS and SPEM task performance. However, the power of the sample to identify small effects is limited and the possibility of a type II error must be kept in mind. Larger samples may be needed to reliably investigate such gene effects on oculomotor endophenotypes.

Pharmacogenetics and functional genomics in asthma

Asthma is a complex phenotype caused by a combination of genetic and environmental factors that remain poorly understood. The common variants involved in the pathogenesis of asthma have proved difficult to identify by candidate gene association studies. As a result, few genetic variants influencing clinical response to asthma and allergy medications have been uncovered. Recently, genome-wide association, which is more robust in identifying common predisposition variants, has been applied to disorders such as asthma. As genome-wide associations are hypothesis-free, they raise the possibility of identifying novel biological pathways that could be translated to the future benefit of patients through improved diagnostic and therapeutic measures in the form of personalized medicine. This review addresses both recent advances in the genetics of asthma and their potential in transforming the treatment of the disorder into more individualized care in the near future.

PINK1 mutations and parkinsonism

BACKGROUND

PINK1 loss-of-function causes recessive, early-onset parkinsonism. In Tunisia there is a high rate of consanguineous marriage but PINK1 carrier frequency and disease prevalence have yet to be assessed.

OBJECTIVES

The frequency of PINK1 mutations in familial parkinsonism, community-based patients with idiopathic Parkinson disease (PD) (non-familial PD), and control subjects was determined. Demographic and clinical characteristics of individuals with PINK1 homozygous or heterozygous variants, or without PINK1 mutations, were compared.

METHODS

A total of 92 kindreds (with 208 affected and 340 unaffected subjects), 240 nonfamilial PD, and 368 control participants were recruited from the Institut National de Neurologie, Tunis. Clinical examinations included Hoehn &Yahr, UPDRS, and Epworth scales. PINK1 sequencing and dosage analysis was performed in familial index patients, the variants identified screened in all subjects. Parkin and LRRK2 genes were also examined.

RESULTS

Four PINK1 homozygous mutations, three novel (Q129X, Q129fsX157, G440E, and one previously reported; Q456X), segregate with parkinsonism in 46 individuals in 14 of 92 families (15%). Six of 240 patients with nonfamilial PD were found with either homozygous Q456X or Q129X (2.5%) substitutions. In patients with familial disease, PINK1 homozygotes were younger at disease onset (36 +/- 12 years) than noncarriers (57 +/- 15 years) and more often had an akinetic-rigid presentation at examination and slow progression.

CONCLUSIONS

Segregation of PINK1 mutations with parkinsonism within families, and frequency estimates within population controls, suggested only four PINK1 mutations were pathogenic. Several PINK1 sequence variants are potentially benign and there was no evidence that PINK1 heterozygosity increases susceptibility to idiopathic Parkinson disease.

Strategies and stakeholders: minority recruitment in cancer genetics research

The Cancer Genetics Network (CGN) is one of a growing number of large-scale registries designed to facilitate investigation of genetic and environmental contributions to health and disease. Despite compelling scientific and social justice arguments that recommend diverse participation in biomedical research, members of ethnic minority groups continue to be chronically underrepresented in such projects. The CGN studies reported in this issue used strategies well documented to increase minority participation in research activities, including use of community-targeted materials, addressing community trust concerns, and the adoption of personalized and flexible research protocols. Here, we review the outcome of these efforts to increase minority recruitment to the CGN, and ask what lessons the findings suggest for future minority recruitment initiatives.

Biobanking for epidemiological research and public health

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

Recent development in pharmacogenomics: from candidate genes to genome-wide association studies

Genetic diversity, most notably through single nucleotide polymorphisms and copy-number variation, together with specific environmental exposures, contributes to both disease susceptibility and drug response variability. It has proved difficult to isolate disease genes that confer susceptibility to complex disorders, and as a consequence, even fewer genetic variants that influence clinical drug responsiveness have been uncovered. As such, the candidate gene approach has largely failed to deliver and, although the family-based linkage approach has certain theoretical advantages in dealing with common/complex disorders, progress has been slower than was hoped. More recently, genome-wide association studies have gained increasing popularity, as they enable scientists to robustly associate specific variants with the predisposition for complex disease, such as age-related macular degeneration, Type 2 diabetes, inflammatory bowel disease, obesity, autism and leukemia. This relatively new methodology has stirred new hope for the mapping of genes that regulate drug response related to these conditions. Collectively, these studies support the notion that modern high-throughput single nucleotide polymorphism genotyping technologies, when applied to large and comprehensively phenotyped patient cohorts, will readily reveal the most clinically relevant disease-modifying and drug response genes. This review addresses both recent advances in the genotyping field and highlights from genome-wide association studies, which have conclusively uncovered variants that underlie disease susceptibility and/or variability in drug response in common disorders.

Genome-wide scan for quantitative ACE activity in Taiwan young-onset hypertension study

OBJECTIVES

Angiotensin converting enzyme (ACE) plays major roles in the pathogenesis of cardiovascular diseases (CVD). However, findings on the relations between ACE variants and CVD have not been consistent. The purpose of this study was to map quantitative trait loci (QTL) for serum ACE activity, a heritable endophenotype of cardiovascular diseases (estimated heritability = 0.58).

METHODS

With 1,271 individuals from 373 young-onset (age <or=40) hypertension pedigrees, 479 deCODE microsatellite markers were genotyped.

RESULTS

We identified a previously unknown loci on chromosomes 9 at 149.4 cM (LOD = 3.00) in addition to a strong linkage peak near the ACE structural locus on chromosome 17 at 89.6 cM (LOD = 4.60).

CONCLUSIONS

These results not only indicate that the ACE gene or nearby loci on 17q was among the strongest QTL influencing ACE activity, but also reveal a potential ACE QTL in human genome, pointing to the complexity of ACE regulation.

Screening for Lrrk2 G2019S and clinical comparison of Tunisian and North American Caucasian Parkinson's disease families

Mutations in the leucine-rich repeat kinase-2 gene (LRRK2) are responsible for some forms of familial as well as sporadic Parkinson's disease (PD). The purpose of this study was to examine the frequency of a single pathogenic mutation (6055G > A) in the kinase domain of this gene in United States and Tunisian familial PD and to compare clinical characteristics between patients with and without the mutation. Standardized case report forms were used for clinical and demographic data collection. We investigated the frequency of the most common substitution of LRRK2 (G2019S, 6055G>A) and its impact on epidemiological and phenotypic features. The frequency of mutations in Tunisian families was 42% (38/91) and in U.S. families 2.6% (1/39), with the unique opportunity to compare homozygous (n = 23) and heterozygous (n = 109) Tunisian carriers of G2019S substitutions. Individuals with G2019S substitutions had an older age at onset but few other differences compared with families negative for the substitution. Patients with LRRK2 mutations had typical clinical features of PD. Comparisons between individuals with heterozygous and homozygous LRRK2 mutations suggested that gene dosage was not correlated with phenotypic differences; however, the estimated penetrance was greater in homozygotes across all age groups.

Strategy Considerations in Genome Cohort Construction in Korea

Focusing on complex diseases of public health significance, strategic issues regarding the on-going Korean Genome Cohort were reviewed: target size and diseases, measurements, study design issues, and followup strategy of the cohort. Considering the epidemiologic characteristics of Korean population as well as strengths and drawbacks of current research environment, we tried to tailor the experience of other existing cohorts into proposals for this Korean study. Currently 100,000 individuals have been participating the new Genome Cohort in Korea. Target size of de novo collection is recommended to be set as between 300,000 to 500,000. This target size would allow acceptable power to detect genetic and environmental factors of moderate effect size and possible interactions between them. Family units and/or special subgroups are recommended to parallel main body of adult individuals to increase the overall efficiency of the study. Given that response rate to the conventional re-contact method may not be satisfactory, successful follow-up is the main key to the achievement of the Korean Genome Cohort. Access to the central database such as National Health Insurance data can provide enormous potential for near-complete case detection. Efforts to build consensus amongst scientists from broad fields and stakeholders are crucial to unleash the centralized database as well as to refine the commitment of this national project.

Genomics and public health in the United States: signposts on the translation highway

Successful completion of the Human Genome Project has raised public expectations that research findings will translate quickly into health benefits; however, the gap between biomedical research and clinical and public health application seems wider than ever. Public health scientists now have the opportunity to help create a broad concept of research translation that integrates genomic information into policies, programs and services benefiting the whole population. Important 'signposts' along the translation highway include conducting population-based research in genomics, developing evidence on the clinical and public health value of genomic information, and integrating genomics into health practice.

The genome-enabled electronic medical record

The integration of patient-specific genomic information into the electronic medical record (EMR) will create many opportunities to improve patient care. Key to the successful incorporation of genomic information into the EMR will be the development of laboratory information systems capable of appropriately formatting molecular diagnostic and cytogenetic findings in the EMR. Due to the lack of granular genomics-related content in existing medical vocabularies, the adoption of new standards for describing clinically significant genomic information will be an important step toward recognizing the genome-enabled EMR. Appropriate capture of patient-specific genomic results in the EMR will generate new opportunities to utilize this information in clinical decision support, including automated response to pharmacogenomic-based risks.

In the eye of the storm: Race and genomics in research and practice

The difficulties of operationalizing race in research and practice for social, behavioral, and genetic researchers and practitioners are neither new nor related to recent genetic knowledge. For geneticists, the bases for understanding groups are clines, observed traits that gradually change in frequency between geographic regions without distinct identifiable population boundaries and population histories that carry information about the distribution of genetic variants. For psychologists, race may not exist or be a social and cultural construct associated with fluid social inferences. Because definitions of populations and race can be socially and biologically incongruent, the authors suggest that geneticists and social and behavioral scientists and clinicians attend to external validity issues by operationalizing population and racial categories and avoiding race proxies for other biological, social, and cultural constructs in research designs, data analyses, and clinical practice.

Translation research: from accurate diagnosis to appropriate treatment

This review article focuses on the various aspects of translational research, where research on human subjects can ultimately enhance the diagnosis and treatment of future patients. While we will use specific examples relating to the asbestos related cancer mesothelioma, it should be stressed that the general approach outlined throughout this review is readily applicable to other diseases with an underlying molecular basis. Through the integration of molecular-based technologies, systematic tissue procurement and medical informatics, we now have the ability to identify clinically applicable "genotype"-"phenotype" associations across cohorts of patients that can rapidly be translated into useful diagnostic and treatment strategies. This review will touch on the various steps in the translational pipeline, and highlight some of the most essential elements as well as possible roadblocks that can impact success of the program. Critical issues with regard to Institutional Review Board (IRB) and Health Insurance Portability and Accountability Act (HIPAA) compliance, data standardization, sample procurement, quality control (QC), quality assurance (QA), data analysis, preclinical models and clinical trials are addressed. The various facets of the translational pipeline have been incorporated into a fully integrated computational system, appropriately named Dx2Tx. This system readily allows for the identification of new diagnostic tests, the discovery of biomarkers and drugable targets, and prediction of optimal treatments based upon the underlying molecular basis of the disease.

Pharmacogenetics and drug development: the path to safer and more effective drugs

Pharmacogenetics provides opportunities for informed decision-making along the pharmaceutical pipeline. There is a growing literature of retrospective studies of marketed medicines that describe efficacy or safety on the basis of patient genotypes. These studies emphasize the potential prospective use of genome information to enhance success in finding new medicines. An example of a prospective efficacy pharmacogenetic Phase-IIA proof-of-concept study is described. Inserting a rapidly performed efficacy pharmacogenetic step after initial clinical data are obtained can provide confidence for a commitment to full drug development. The rapid identification of adverse events during and after drug development using genomic mapping tools is also reviewed.

From pharmacogenetics to personalized medicine: a vital need for educating health professionals and the community

The field of pharmacogenetics will soon celebrate its 50th anniversary. Although science has delivered an impressive amount of information in these 50 years, pharmacogenetics has suffered from lack of integration into clinical practice. There are several reasons for this, including the unmet need for education at medical schools and the lack of awareness about the impact of genetic medicine on healthcare in the community. Recently, the FDA announced that it considers pharmacogenomics one of three major opportunities on the critical path to new medical products. This notion by the FDA is filling the regulatory void that existed between drug developers and drug users. However, in order to bring pharmacogenetic testing to the prescription pad successfully, healthcare professionals and policy makers, as well as patients, need to have the necessary background knowledge for making educated treatment decisions. To effectively move pharmacogenetics into everyday medicine, it is therefore imperative for scientists and teachers in the field to take on the challenge of disseminating pharmacogenetic insights to a broader audience.