Returning pleiotropic results from genetic testing to patients and research participants

POIROT: a powerful test for parent-of-origin effects in unrelated samples leveraging multiple phenotypes

MOTIVATION

There is widespread interest in identifying genetic variants that exhibit parent-of-origin effects (POEs) wherein the effect of an allele on phenotype expression depends on its parental origin. POEs can arise from different phenomena including genomic imprinting and have been documented for many complex traits. Traditional tests for POEs require family data to determine parental origins of transmitted alleles. As most genome-wide association studies (GWAS) sample unrelated individuals (where allelic parental origin is unknown), the study of POEs in such datasets requires sophisticated statistical methods that exploit genetic patterns we anticipate observing when POEs exist. We propose a method to improve discovery of POE variants in large-scale GWAS samples that leverages potential pleiotropy among multiple correlated traits often collected in such studies. Our method compares the phenotypic covariance matrix of heterozygotes to homozygotes based on a Robust Omnibus Test. We refer to our method as the Parent of Origin Inference using Robust Omnibus Test (POIROT) of multiple quantitative traits.

RESULTS

Through simulation studies, we compared POIROT to a competing univariate variance-based method which considers separate analysis of each phenotype. We observed POIROT to be well-calibrated with improved power to detect POEs compared to univariate methods. POIROT is robust to non-normality of phenotypes and can adjust for population stratification and other confounders. Finally, we applied POIROT to GWAS data from the UK Biobank using BMI and two cholesterol phenotypes. We identified 338 genome-wide significant loci for follow-up investigation.

AVAILABILITY AND IMPLEMENTATION

The code for this method is available at https://github.com/staylorhead/POIROT-POE.

Psychiatric manifestations of rare variation in medically actionable genes: a PheWAS approach

BACKGROUND

As genomic sequencing moves closer to clinical implementation, there has been an increasing acceptance of returning incidental findings to research participants and patients for mutations in highly penetrant, medically actionable genes. A curated list of genes has been recommended by the American College of Medical Genetics and Genomics (ACMG) for return of incidental findings. However, the pleiotropic effects of these genes are not fully known. Such effects could complicate genetic counseling when returning incidental findings. In particular, there has been no systematic evaluation of psychiatric manifestations associated with rare variation in these genes.

RESULTS

Here, we leveraged a targeted sequence panel and real-world electronic health records from the eMERGE network to assess the burden of rare variation in the ACMG-56 genes and two psychiatric-associated genes (CACNA1C  and TCF4) across common mental health conditions in 15,181 individuals of European descent. As a positive control, we showed that this approach replicated the established association between rare mutations in LDLR and hypercholesterolemia with no visible inflation from population stratification. However, we did not identify any genes significantly enriched with rare deleterious variants that confer risk for common psychiatric disorders after correction for multiple testing. Suggestive associations were observed between depression and rare coding variation in PTEN (P = 1.5 × 10^-4), LDLR (P = 3.6 × 10^-4), and CACNA1S (P = 5.8 × 10^-4). We also observed nominal associations between rare variants in KCNQ1 and substance use disorders (P = 2.4 × 10^-4), and APOB and tobacco use disorder (P = 1.1 × 10^-3).

CONCLUSIONS

Our results do not support an association between psychiatric disorders and incidental findings in medically actionable gene mutations, but power was limited with the available sample sizes. Given the phenotypic and genetic complexity of psychiatric phenotypes, future work will require a much larger sequencing dataset to determine whether incidental findings in these genes have implications for risk of psychopathology.

Identification of variants in pleiotropic genes causing "isolated" premature ovarian insufficiency: implications for medical practice

Next-generation sequencing (NGS) is increasingly being used in a clinical setting for the molecular diagnosis of patients with heterogeneous disorders, such as premature ovarian insufficiency (POI). We performed NGS of ~1000 candidate genes in four unrelated patients with POI. We discovered the genetic cause of "isolated" POI in two cases, both of which had causative variants in surprising genes. In the first case, a homozygous nonsense variant in NBN was causative. Recessive function-altering NBN variants typically cause Nijmegen breakage syndrome characterized by microcephaly, cancer predisposition, and immunodeficiency, none of which are evident in the patient. At a cellular level, we found evidence of chromosomal instability. In the second case, compound heterozygous variants in EIF2B2 were causative. Recessive EIF2B2 function-altering variants usually cause leukoencephalopathy with episodic decline. Subsequent MRI revealed subclinical neurological abnormalities. These cases demonstrate that variants in NBN and EIF2B2, which usually cause severe syndromes, can cause apparently isolated POI, and that (1) NGS can precede clinical diagnosis and guide patient management, (2) NGS can redefine the phenotypic spectrum of syndromes, and (3) NGS may make unanticipated diagnoses that must be sensitively communicated to patients. Although there is rigorous debate about the handling of secondary/incidental findings using NGS, there is little discussion of the management of causative pleiotropic gene variants that have broader implications than that for which genetic studies were sought.

Powerful and robust cross-phenotype association test for case-parent trios

There has been increasing interest in identifying genes within the human genome that influence multiple diverse phenotypes. In the presence of pleiotropy, joint testing of these phenotypes is not only biologically meaningful but also statistically more powerful than univariate analysis of each separate phenotype accounting for multiple testing. Although many cross-phenotype association tests exist, the majority of such methods assume samples composed of unrelated subjects and therefore are not applicable to family-based designs, including the valuable case-parent trio design. In this paper, we describe a robust gene-based association test of multiple phenotypes collected in a case-parent trio study. Our method is based on the kernel distance covariance (KDC) method, where we first construct a similarity matrix for multiple phenotypes and a similarity matrix for genetic variants in a gene; we then test the dependency between the two similarity matrices. The method is applicable to either common variants or rare variants in a gene, and resulting tests from the method are by design robust to confounding due to population stratification. We evaluated our method through simulation studies and observed that the method is substantially more powerful than standard univariate testing of each separate phenotype. We also applied our method to phenotypic and genotypic data collected in case-parent trios as part of the Genetics of Kidneys in Diabetes (GoKinD) study and identified a genome-wide significant gene demonstrating cross-phenotype effects that was not identified using standard univariate approaches.

Improved ethical guidance for the return of results from psychiatric genomics research

There is an emerging consensus that genomic researchers should, at a minimum, offer to return to individual participants clinically valid, medically important and medically actionable genomic findings (for example, pathogenic variants in BRCA1) identified in the course of research. However, this is not a common practice in psychiatric genetics research. Furthermore, psychiatry researchers often generate findings that do not meet all of these criteria, yet there may be ethically compelling arguments to offer selected results. Here, we review the return of results debate in genomics research and propose that, as for genomic studies of other medical conditions, psychiatric genomics researchers should offer findings that meet the minimum criteria stated above. Additionally, if resources allow, psychiatry researchers could consider offering to return pre-specified 'clinically valuable' findings even if not medically actionable-for instance, findings that help corroborate a psychiatric diagnosis, and findings that indicate important health risks. Similarly, we propose offering 'likely clinically valuable' findings, specifically, variants of uncertain significance potentially related to a participant's symptoms. The goal of this Perspective is to initiate a discussion that can help identify optimal ways of managing the return of results from psychiatric genomics research.

Is there evidence that we should screen the general population for Lynch syndrome with genetic testing? A systematic review

BACKGROUND

The emerging dual imperatives of personalized medicine and technologic advances make population screening for preventable conditions resulting from genetic alterations a realistic possibility. Lynch syndrome is a potential screening target due to its prevalence, penetrance, and the availability of well-established, preventive interventions. However, while population screening may lower incidence of preventable conditions, implementation without evidence may lead to unintentional harms. We examined the literature to determine whether evidence exists that screening for Lynch-associated mismatch repair (MMR) gene mutations leads to improved overall survival, cancer-specific survival, or quality of life. Documenting evidence and gaps is critical to implementing genomic approaches in public health and guiding future research.

MATERIALS AND METHODS

Our 2014-2015 systematic review identified studies comparing screening with no screening in the general population, and controlled studies assessing analytic validity of targeted next-generation sequencing, and benefits or harms of interventions or screening. We conducted meta-analyses for the association between early or more frequent colonoscopies and health outcomes.

RESULTS

Twelve studies met our eligibility criteria. No adequate evidence directly addressed the main question or the harms of screening in the general population. Meta-analyses found relative reductions of 68% for colorectal cancer incidence (relative risk: 0.32, 95% confidence interval: 0.23-0.43, three cohort studies, 590 participants) and 78% for all-cause mortality (relative risk: 0.22, 95% confidence interval: 0.09-0.56, three cohort studies, 590 participants) for early or more frequent colonoscopies among family members of people with cancer who also had an associated MMR gene mutation.

CONCLUSION

Inadequate evidence exists examining harms and benefits of population-based screening for Lynch syndrome. Lack of evidence highlights the need for data that directly compare benefits and harms.

Which Results to Return: Subjective Judgments in Selecting Medically Actionable Genes

BACKGROUND

Advances in genomics have led to calls for returning information about medically actionable genes (MAGs) to patients, research subjects, biobank participants, and through screening programs, the general adult population. Which MAGs are returned affects the harms and benefits of every genetic testing endeavor. Despite published recommendations of selection criteria for MAGs to return, scant data exist regarding how decision makers actually apply such criteria.

METHODS

The process and criteria used by researchers when selecting MAGs for a preventive genomic sequencing program targeting the general adult population were examined. The authors observed and audio-recorded the gene selection meetings, and analyzed meeting transcripts, gene scoring sheets, and meeting handouts.

RESULTS

To select MAGs, the committee imported, from a preexisting project, "a semiquantitative metric" that scores genes on five criteria. Numerous subjective judgments and conceptual challenges in defining and applying the five criteria complicated the selection process. Criteria-related challenges also included the limited evidence available about facts fundamental to the scoring decisions and the emergence and application of criteria that were not part of the original metric.

CONCLUSIONS

When identifying MAGs appropriate for screening and return, decision makers must expect and prepare to address such issues as the inevitability of subjective judgments, limited evidence about fundamental decision-making elements, the conceptual complexity of defining criteria, and the emergence of unplanned criteria during the gene selection process.

Pediatric Issues in Return of Results and Incidental Findings: Weighing Autonomy and Best Interests

Nowhere are the ethical issues in genomic research more complex than in pediatrics. Balancing the sometime conflicting autonomy of the parent and the child, and the best interest of the family and the child, brings up many challenging issues. Addressing this balance, especially in the context of the child's developing maturity and comprehension, requires deep analysis and discussion. Issues discussed include the impact of genetic information on the family, parental versus the child's autonomy, the best interests of the child versus the family, potential limitations on the parents' right to know or not know information about their child, and changing role of the developing child in return of research results. Finally, a dynamic model will be proposed that takes into consideration the child's evolving role in consenting and return of results that can be adapted in different national contexts.

Premature Ovarian Insufficiency: New Perspectives on Genetic Cause and Phenotypic Spectrum

Premature ovarian insufficiency (POI) is one form of female infertility, defined by loss of ovarian activity before the age of 40 and characterized by amenorrhea (primary or secondary) with raised gonadotropins and low estradiol. POI affects up to one in 100 females, including one in 1000 before the age of 30. Substantial evidence suggests a genetic basis for POI; however, the majority of cases remain unexplained, indicating that genes likely to be associated with this condition are yet to be discovered. This review discusses the current knowledge of the genetic basis of POI. We highlight genes typically known to cause syndromic POI that can be responsible for isolated POI. The role of mouse models in understanding POI pathogenesis is discussed, and a thorough list of candidate POI genes is provided. Identifying a genetic basis for POI has multiple advantages, such as enabling the identification of presymptomatic family members who can be offered counseling and cryopreservation of eggs before depletion, enabling personalized treatment based on the cause of an individual's condition, and providing better understanding of disease mechanisms that ultimately aid the development of improved treatments.

Ethical considerations in the implementation of nutrigenetics/nutrigenomics

Awareness of ethical issues that may be raised by the implementation of nutrigenetic/nutrigenomic (NGx) testing and personalized nutrition, at an individual or a public health level, is crucial to ensure the latter's sound and effective implementation. NGx tests that are currently offered or developed have different natures and scopes. We provide an example of NGx testing on the MTHFR gene to illustrate the current challenges when it comes to grasp the meaning of the results of such testing. In addition, NGx testing is developed within an evolving landscape of new genomic technologies and occurs at a time when public health policies mainly focus on preventive and predictive healthcare, with an emphasis on increased individual responsibility. The ethical issues raised by such a context and the genetic nature of NGx testing both should be carefully evaluated.

Identification of Genomic Somatic Variants in Cancer: From Discovery to Actionability

The perfect method to discover and validate actionable somatic variants in cancer has not yet been developed, yet significant progress has been made toward this goal. There have been huge increases in the throughput and cost of deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) sequencing technologies that have led to the burgeoning possibility of using sequencing data in clinical settings. Discovery of somatic mutations is relatively simple and has been improved recently due to laboratory methods optimization, bioinformatics algorithms development, and the expansion of various databases of population genomic information. Tiered systems of evidence evaluation are currently being used to classify genomic variants for clinicians to more rapidly and accurately determine actionability of these aberrations. These efforts are complicated by the intricacies of communicating sequencing results to physicians and supporting its biological relevance, emphasizing the need for increasing education of clinicians and administrators, and the ongoing development of ethical standards for dealing with incidental results. This chapter will focus on general aspects of DNA and RNA tumor sequencing technologies, data analysis and interpretation, assessment of biological and clinical relevance of genomic aberrations, ethical aspects of germline sequencing, and how these factors impact cancer personalized care.

Evidence for extensive pleiotropy among pharmacogenes

AIM

We sought to identify potential pleiotropy involving pharmacogenes.

METHODS

We tested 184 functional variants in 34 pharmacogenes for associations using a custom grouping of International Classification and Disease, Ninth Revision billing codes extracted from deidentified electronic health records of 6892 patients.

RESULTS

We replicated several associations including ABCG2 (rs2231142) and gout (p = 1.73 × 10(-7); odds ratio [OR]: 1.73; 95% CI: 1.40-2.12); and SLCO1B1 (rs4149056) and jaundice (p = 2.50 × 10(-4); OR: 1.67; 95% CI: 1.27-2.20).

CONCLUSION

In this systematic screen for phenotypic associations with functional variants, several novel genotype-phenotype combinations also achieved phenome-wide significance, including SLC15A2 rs1143672 and renal osteodystrophy (p = 2.67 × 10(-) (6); OR: 0.61; 95% CI: 0.49-0.75).

Disclosing Pleiotropic Effects During Genetic Risk Assessment for Alzheimer Disease: A Randomized Trial

BACKGROUND

Increasing use of genetic testing raises questions about disclosing secondary findings, including pleiotropic information.

OBJECTIVE

To determine the safety and behavioral effect of disclosing modest associations between apolipoprotein E (APOE) genotype and coronary artery disease (CAD) risk during APOE-based genetic risk assessments for Alzheimer disease (AD).

DESIGN

Randomized, multicenter equivalence clinical trial. (ClinicalTrials.gov: NCT00462917).

SETTING

4 teaching hospitals.

PARTICIPANTS

257 asymptomatic adults were enrolled, 69% of whom had 1 AD-affected first-degree relative.

INTERVENTION

Disclosure of genetic risk information about AD and CAD (AD+CAD) or AD only (AD-only).

MEASUREMENTS

Primary outcomes were Beck Anxiety Inventory (BAI) and Center for Epidemiologic Studies Depression Scale (CES-D) scores at 12 months. Secondary outcomes were all measures at 6 weeks and 6 months and test-related distress and health behavior changes at 12 months.

RESULTS

At 12 months, mean BAI scores were 3.5 in both the AD-only and AD+CAD groups (difference, 0.0 [95% CI, -1.0 to 1.0]), and mean CES-D scores were 6.4 and 7.1 in the AD-only and AD+CAD groups, respectively (difference, 0.7 [CI, -1.0 to 2.4]). Both confidence bounds fell within the equivalence margin of ±5 points. Among carriers of the APOE ε4 allele, distress was lower in the AD+CAD groups (difference, -4.8 [CI, -8.6 to -1.0]) (P = 0.031 for the interaction between group and APOE genotype). Participants in the AD+CAD groups also reported more health behavior changes, regardless of APOE genotype.

LIMITATIONS

Outcomes were self-reported by volunteers without severe anxiety, severe depression, or cognitive problems. Analyses omitted 33 randomly assigned participants.

CONCLUSION

Disclosure of pleiotropic information did not increase anxiety or depression and may have decreased distress among persons at increased risk for 2 conditions. Providing risk modification information about CAD improved health behaviors. Findings highlight the potential benefits of disclosure of secondary genetic findings when options exist for decreasing risk.

PRIMARY FUNDING SOURCE

National Human Genome Research Institute.

Heimler Syndrome Is Caused by Hypomorphic Mutations in the Peroxisome-Biogenesis Genes PEX1 and PEX6

Heimler syndrome (HS) is a rare recessive disorder characterized by sensorineural hearing loss (SNHL), amelogenesis imperfecta, nail abnormalities, and occasional or late-onset retinal pigmentation. We ascertained eight families affected by HS and, by using a whole-exome sequencing approach, identified biallelic mutations in PEX1 or PEX6 in six of them. Loss-of-function mutations in both genes are known causes of a spectrum of autosomal-recessive peroxisome-biogenesis disorders (PBDs), including Zellweger syndrome. PBDs are characterized by leukodystrophy, hypotonia, SNHL, retinopathy, and skeletal, craniofacial, and liver abnormalities. We demonstrate that each HS-affected family has at least one hypomorphic allele that results in extremely mild peroxisomal dysfunction. Although individuals with HS share some subtle clinical features found in PBDs, the diagnosis was not suggested by routine blood and skin fibroblast analyses used to detect PBDs. In conclusion, our findings define HS as a mild PBD, expanding the pleiotropy of mutations in PEX1 and PEX6.

Incidental Findings with Genomic Testing: Implications for Genetic Counseling Practice

This paper summarizes the current controversies surrounding the identification and disclosure of "incidental" or "secondary" findings from genomic sequencing and the implications for genetic counseling practice. The rapid expansion of clinical sequencing has influenced the ascertainment and return of incidental findings, while empiric data to inform best practices are still being generated. Using the North Carolina Clinical Genomic Evaluation by Next Generation Exome Sequencing (NCGENES) research project as an example, we discuss the implications of different models of consent and their impact on patient decisions.

Ethical signposts for clinical geneticists in secondary variant and incidental finding disclosure discussions

While ethical and empirical interest in so-called secondary variants and incidental findings in clinical genetics contexts is growing, critical reflection on the ethical foundations of the various recommendations proposed is thus far largely lacking. We examine and critique the ethical justifications of the three most prominent disclosure positions: briefly, the clinical geneticist decides, a joint decision, and the patient decides. Subsequently, instead of immediately developing a new disclosure option, we explore relevant foundational ethical values and norms, drawing on the normative and empirical ethical literature. Four ethical signposts are thereby developed to help guide disclosure discussions. These are: respectful sharing of the clinician's expertise; transparent communication; epistemic modesty; and respect for the embedded nature of the patient. We conclude by considering the most common current disclosure positions in the light of the four ethical signposts.

Leveraging Epidemiologic and Clinical Collections for Genomic Studies of Complex Traits

BACKGROUND/AIMS

Present-day limited resources demand DNA and phenotyping alternatives to the traditional prospective population-based epidemiologic collections.

METHODS

To accelerate genomic discovery with an emphasis on diverse populations, we--as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study--accessed all non-European American samples (n = 15,863) available in BioVU, the Vanderbilt University biorepository linked to de-identified electronic medical records, for genomic studies as part of the larger Population Architecture using Genomics and Epidemiology (PAGE) I study. Given previous studies have cautioned against the secondary use of clinically collected data compared with epidemiologically collected data, we present here a characterization of EAGLE BioVU, including the billing and diagnostic (ICD-9) code distributions for adult and pediatric patients as well as comparisons made for select health metrics (body mass index, glucose, HbA1c, HDL-C, LDL-C, and triglycerides) with the population-based National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples (NHANES III, n = 7,159; NHANES 1999-2002, n = 7,839).

RESULTS

Overall, the distributions of billing and diagnostic codes suggest this clinical sample is a mixture of healthy and sick patients like that expected for a contemporary American population.

CONCLUSION

Little bias is observed among health metrics, suggesting this clinical collection is suitable for genomic studies along with traditional epidemiologic cohorts.

Compare and contrast: a cross-national study across UK, USA and Greek experts regarding return of incidental findings from clinical sequencing

Return of incidental findings (IFs) from clinical sequencing has become a hotly debated topic over the past year. Efforts are being made by several bodies to provide guidance at both national and international levels; however, no studies comparing attitudes of experts across different countries have been published so far. Our goal was to investigate attitudes towards return of IFs from clinical sequencing across UK, USA and Greek experts. Thirty in-depth interviews were conducted with genetics and genomic experts with different backgrounds. Our study revealed more differences when experts were compared according to their professional background than their country. General principles guiding the decision-making and the feedback process were common across all experts but the details of integrating these tests might vary as different professionals reported different needs and attitudes.

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case.

A Comparison of Disease Burden Between Twins and Control Pairs in Medicare: Quantification of Heredity's Role in Human Health

To quantify heredity's effects on the burden of illness in the Medicare population, this study linked information between participants in a research twin registry to a comprehensive set of Medicare claims. To calculate disease categories, the authors used the Centers for Medicare & Medicaid Services Hierarchical Conditions Categories (HCC) model that was developed to risk adjust Medicare's capitation payments to private health care plans based on the health expenditure risk of their enrollees. Using the Medicare database, 2 sets of unrelated but demographically matched control pairs (MCPs) were generated, one specific for the monozygotic twin population and the second specific for the dizygotic twin population. The concordance and correlation rates of the 70 HCC categories for the 2 twin populations, in comparison to their corresponding MCP, was then calculated using Medicare claims data from 1991 through 2011. When indicated, HCCs for which there was a statistically significant difference between the twin and corresponding MCP control group were analyzed by calculating concordance and correlation rates of the International Classification of Diseases, Ninth Revision codes that compose the HCC. Findings reveal that monozygotic twins share 6.5% more HCC disease categories than their MCP while dizygotic twins share 3.8% more HCC disease categories than their MCP. Atrial fibrillation is a highly heritable disease category, a finding consistent with prior literature describing the heritability of the cardiac arrhythmias. These findings are consistent with qualitative assessments of heredity's role found in previous models of population health, and provide both novel methods and quantitative evidence to support future model development.

Delivery of a clinical genomics service

Over the past five years, next generation sequencing has revolutionised the discovery of genes responsible for rare inherited diseases previously resistant to traditional discovery techniques. This review considers how this new technology is being introduced into clinical practice to aid diagnosis and improve the clinical management of individuals and families affected by rare diseases where access to genetic testing was previously limited. We compare and contrast the different approaches that have been adopted including panel based tests, exome and genome sequencing. We provide insights from our own clinical practice demonstrating the challenges and benefits of this new technology.

Genetic information, non-discrimination, and privacy protections in genetic counseling practice

The passage of the Genetic Information Non Discrimination Act (GINA) was hailed as a pivotal achievement that was expected to calm the fears of both patients and research participants about the potential misuse of genetic information. However, 6 years later, patient and provider awareness of legal protections at both the federal and state level remains discouragingly low, thereby, limiting their potential effectiveness. The increasing demand for genetic testing will expand the number of individuals and families who could benefit from obtaining accurate information about the privacy and anti-discriminatory protections that GINA and other laws extend. In this paper we describe legal protections that are applicable to individuals seeking genetic counseling, review the literature on patient and provider fears of genetic discrimination and examine their awareness and understandings of existing laws, and summarize how genetic counselors currently discuss genetic discrimination. We then present three genetic counseling cases to illustrate issues of genetic discrimination and provide relevant information on applicable legal protections. Genetic counselors have an unprecedented opportunity, as well as the professional responsibility, to disseminate accurate knowledge about existing legal protections to their patients. They can strengthen their effectiveness in this role by achieving a greater knowledge of current protections including being able to identify specific steps that can help protect genetic information.

Pharmacogenomics: Current State-of-the-Art

The completion of the human genome project 10 years ago was met with great optimism for improving drug therapy through personalized medicine approaches, with the anticipation that an era of genotype-guided patient prescribing was imminent. To some extent this has come to pass and a number of key pharmacogenomics markers of inter-individual drug response, for both safety and efficacy, have been identified and subsequently been adopted in clinical practice as pre-treatment genetic tests. However, the universal application of genetics in treatment guidance is still a long way off. This review will highlight important pharmacogenomic discoveries which have been facilitated by the human genome project and other milestone projects such as the International HapMap and 1000 genomes, and by the continued development of genotyping and sequencing technologies, including rapid point of care pre-treatment genetic testing. However, there are still many challenges to implementation for the many other reported biomarkers which continue to languish within the discovery phase. As technology advances over the next 10 years, and the costs fall, the field will see larger genetic data sets, including affordable whole genome sequences, which will, it is hoped, improve patient outcomes through better diagnostic, prognostic and predictive biomarkers.

Jumping on the Train of Personalized Medicine: A Primer for Non- Geneticist Clinicians: Part 3. Clinical Applications in the Personalized Medicine Area

The rapid decline of sequencing costs brings hope that personal genome sequencing will become a common feature of medical practice. This series of three reviews aim to help non-geneticist clinicians to jump into the fast-moving field of personalized genetic medicine. In the first two articles, we covered the fundamental concepts of molecular genetics and the methodologies used in genetic epidemiology. In this third article, we discuss the evolution of personalized medicine and illustrate the most recent success in the fields of Mendelian and complex human diseases. We also address the challenges that currently limit the use of personalized medicine to its full potential.

Biobanks and personalized medicine

We provide a mini-review of how biobanks can support clinical genetics in the era of personalized medicine. We discuss types of biobanks, including disease specific and general biobanks not focused on one disease. We present considerations in setting up a biobank, including consenting and governance, biospecimens, risk factor and related data, informatics, and linkage to electronic health records for phenotyping. We also discuss the uses of biobanks and ongoing considerations, including genotype-driven recruitment, investigations of gene-environment associations, and the re-use of data generated from studies. Finally, we present a brief discussion of some of the unresolved issues, such as return of research results and sustaining biobanks over time. In summary, carefully designed biobanks can provide critical research and infrastructure support for clinical genetics in the era of personalized medicine.