Why personalized medicine will fail if we stay the course

Pharmacogenomics and health disparities, are we helping?

Pharmacogenomics has been at the forefront of precision medicine during the last few decades. Precision medicine carries the potential of improving health outcomes at both the individual as well as population levels. To harness the benefits of its initiatives, careful dissection of existing health disparities as they relate to precision medicine is of paramount importance. Attempting to address the existing disparities at the early stages of design and implementation of these efforts is the only guarantee of a successful just outcome. In this review, we glance at a few determinants of existing health disparities as they intersect with pharmacogenomics research and implementation. In our opinion, highlighting these disparities is imperative for the purpose of researching meaningful solutions. Failing to identify, and hence address, these disparities in the context of the current and future precision medicine initiatives would leave an already strained health system, even more inundated with inequality.

Non-affective psychosis in traditional Andean culture

We report a case of non-affective psychosis with a brief discussion of the phenomenology and its characterization and treatment by traditional Inka healers and eventually by Western-trained psychiatrists. Traditional Inka psychopathology provided empirical support for the transcultural stability of the Kraepelinian dichotomy.

Making Pain Research More Inclusive: Why and How

Current knowledge about mechanisms and interventions for pain has largely been derived from samples that are healthier, wealthier, younger, and more likely to be White than the general population. Failure to conduct inclusive pain research not only restricts generalizability and application of findings, but also hampers the discovery of mechanisms and the development of measures and interventions that are valid across population subgroups. Most of all, inclusive practices are critical to ensure that underrepresented groups derive equitable benefit from pain research. Here, we provide guidance for the pain research community on how to adopt inclusive research practices. We define "inclusion" to encompass a range of identities and characteristics, including racialized group/ethnicity, disability status, gender identity, sexual orientation, and age. We first describe principles relevant to promoting inclusion in pain research, including attention to: 1) stakeholder engagement; 2) structural factors underlying inequities; 3) the limitations of "disparity" research; 4) intersectionality; and 5) universal design. Next, we provide checklists with practical strategies for making studies more inclusive at each stage of the research process. We conclude by calling for system-level changes to ensure that the future of pain research is socially just, scientifically productive, and responsive to the needs of all people. PERSPECTIVE: This paper offers guidance on promoting inclusion of underrepresented groups in pain research. We describe principles relevant to conducting more inclusive research; eg, attention to stakeholder engagement, structural factors, and universal design. We provide checklists with practical strategies for inclusion at each stage of the research process.

Undercutting efforts of precision medicine: roadblocks to minority representation in breast cancer clinical trials

Precision (or personalized) medicine holds great promise in the treatment of breast cancer. The success of personalized medicine is contingent upon inclusivity and representation for minority groups in clinical trials. In this article, we focus on the roadblocks for the African American demographic, including the barriers to access and enrollment in breast oncology trials, the prevailing classification of race and ethnicity, and the need to refine monolithic categorization by employing genetic ancestry mapping tools for a more accurate determination of race or ethnicity.

Developing pathways for community-led research with big data: a content analysis of stakeholder interviews

BACKGROUND

Big data (BD) informs nearly every aspect of our lives and, in health research, is the foundation for basic discovery and its tailored translation into healthcare. Yet, as new data resources and citizen/patient-led science movements offer sites of innovation, segments of the population with the lowest health status are least likely to engage in BD research either as intentional data contributors or as 'citizen/community scientists'. Progress is being made to include a more diverse spectrum of research participants in datasets and to encourage inclusive and collaborative engagement in research through community-based participatory research approaches, citizen/patient-led research pilots and incremental research policy changes. However, additional evidence-based policies are needed at the organisational, community and national levels to strengthen capacity-building and widespread adoption of these approaches to ensure that the translation of research is effectively used to improve health and health equity. The aims of this study are to capture uses of BD ('use cases') from the perspectives of community leaders and to identify needs and barriers for enabling community-led BD science.

METHODS

We conducted a qualitative content analysis of semi-structured key informant interviews with 16 community leaders.

RESULTS

Based on our analysis findings, we developed a BD Engagement Model illustrating the pathways and various forces for and against community engagement in BD research.

CONCLUSIONS

The goal of our Model is to promote concrete, transparent dialogue between communities and researchers about barriers and facilitators of authentic community-engaged BD research. Findings from this study will inform the subsequent phases of a multi-phased project with the ultimate aims of organising fundable frameworks and identifying policy options to support BD projects within community settings.

[Blood metabolome analysis for creating a digital image of a healthy person]

In the frame of the work, data on the implementation of metabolomics tests in medicine have been systematized. Based on the obtained data, a set of protocols was proposed, the sequential realization of which makes it possible to conduct a blood metabolome analysis for medical purposes. Using this analysis and the number of blood samples from healthy volunteers, a prototype of a healthy person's metabolomic image has been developed; it allows visually and digitally to assess the compliance of the human blood metabolome with the norm. At the same time, 99% of the metabolic processes reflected in the blood plasma are estimated. If abnormalities are detected, the metabolomic image allows to get the value of these deviations of metabolic processes in digital terms.

Brazilian cohort and genes encoding for drug-metabolizing enzymes and drug transporters

Background & aim: Genetic variability in drug absorption, distribution, metabolism and excretion (ADME) genes contributes to the high heterogeneity of drug responses. The present study investigated polymorphisms of ADME genes frequencies and compared the findings with populations from other continents, available in the 1000 Genome Project (1 KGP) and the Exome Aggregation Consortium (ExAC) databases. Methodology & results: We conducted a study of 100 patients in Brazil and a total of 2003 SNPs were evaluated by targeted next-generation sequencing in 148 genes, including Phase I enzymes (n = 50), Phase II enzymes (n = 38) and drug transporters (n = 60). Overall, the distribution of minor allele frequency (MAF) suggests that the distribution of 2003 SNPs is similar between Brazilian cohort, 1 KGP and ExAC; however, we found moderate SNP allele-frequency divergence between Brazilian cohort and both 1000 KGP and ExAC. These differences were observed in several relevant genes including CYP3A4, NAT2 and SLCO1B1. Conclusion: We concluded that the Brazilian population needs clinical assessment of drug treatment based on individual genotype rather than ethnicity.

Results and challenges of Cytochrome P450 2D6 (CYP2D6) testing in an ethnically diverse South Florida population

Background

This study focuses on the implementation of CYP2D6 genetic test profiling and the challenges associated with using standard pharmacogenetics panels in a diverse South Florida population.

Methods

A total of 413 participants were recruited to participate in this study through Nicklaus Children's Hospital. Buccal swabs were collected and tested using an extended CYP2D6 panel including 22 alleles. Phenotype, genotype, and allelic frequencies were compared among different racial and ethnic groups.

Results

The majority of participants (75.0%) self‐identified as Hispanics. Four alleles, CYP2D6*4, *17, *41, and *2A, showed a statistically significant difference between White Hispanics and Black Non‐Hispanics. Aggregate frequency of all alleles with decreased function varied between 2.8% and 50.0% in different racial and ethnic groups. Additionally, rare allele combinations were observed in this South Florida cohort.

Conclusions

The heterogeneity among Hispanic groups demonstrated in previous literature and by this study reflects the complexity of ethnicity and suggests that a more granular categorization is needed, one based on ancestry and migration history rather than primary language. Overall, we have determined that there are statistically significant differences in CYP2D6 allele frequencies in the distinct racial and ethnic populations of South Florida, demonstrating a unique genetic makeup within South Florida. However, overall, the frequencies of Poor Metabolizer, Normal Metabolizer, Intermediate Metabolizer, and Ultrarapid Metabolizer did not differ between racial and ethnic groups at a statistically significant level.

A systems-level analysis of drug-target-disease associations for drug repositioning

Drug repositioning is the process of finding new therapeutic uses for existing, approved drugs-a process thathas value when considering the exorbitant costs of novel drug development. Several computational strategies exist as a way to predict these alternative applications. In this study, we used datasets on: (1) human biological drug targets and (2) disease-associated genes and, based on a direct functional interaction between them, searched for potential opportunities for drug repositioning. From the set of 1125 unique drug targets and their 88 490 interactions with disease-associated genes, 30 drug targets were analyzed and (3) discussed in detail for the purpose of this article. The current indications of the drugs thattarget them were validated through the interactions, and new opportunities for repositioning were predicted. Among the set of drugs for potential repositioning werebenzodiazepines for the treatment of autism spectrum disorders; nortriptyline for the treatment of melanoma, glioma and other cancers; and vitamin B6 in prevention of spontaneous abortions and cleft palate birth defects. Special emphasis was also placed on those new potential indications that pertained to orphan diseases-these are diseases whose rarity means that development of novel treatment is not financially viable. This computational drug repositioning approach uses existing information on drugs and drug targets, and insights into the genetic basis of disease, as a means to systematically generate the most probable new uses for the drugs on offer, and in this way harness their true therapeutic power.

Natural selection and local adaptation of blood pressure regulation and their perspectives on precision medicine in hypertension

Prevalence of hypertension (HTN) varies substantially across different populations. HTN is not only common - affecting at least one third of the world's adult population - but is also the most important driver for cardiovascular diseases. Yet up to a third of hypertensive patients are resistant to therapy, contributed by secondary hypertension but more commonly the hitherto inability to precisely predict response to specific antihypertensive agents. Population and individual genomics information could be useful in guiding the selection and predicting the response to treatment - an approach known as precision medicine. However this cannot be achieved without the knowledge of genetic variations that influence blood pressure (BP). A number of evolutionary factors including population demographics and forces of natural selection may be involved. This article explores some ideas on how natural selection influences BP regulation in ethnically and geographically diverse populations that could lead to them being susceptible to HTN. We explore how such evolutionary factors could impact the implementation of precision medicine in HTN. Finally, in order to ensure the success of precision medicine in HTN, we call for more initiatives to understand the genetic architecture within and between diverse populations with ancestry from different parts of the world, and to precisely classify the intermediate phenotypes of HTN.

Leveraging the Learning Health Care Model to Improve Equity in the Age of Genomic Medicine

To fully achieve the goals of a genomics‐enabled learning health care system, purposeful efforts to understand and reduce health disparities and improve equity of care are essential. This paper highlights 3 major challenges facing genomics‐enabled learning health care systems, as they pertain to ancestrally diverse populations: inequality in the utility of genomic medicine; lack of access to pharmacogenomics in clinical care; and inadequate incorporation of social and environmental data into the electronic health care record. We advance a framework that cannot only be used to directly improve care for all within the learning health system but can also be used to focus on the needs to address racial and ethnic health disparities and improve health equity.

Towards personalized medicine of colorectal cancer

Efforts in colorectal cancer (CRC) research aim to improve early detection and treatment for metastatic stages which could translate into better prognosis of this disease. One of the major challenges that hinder these efforts is the heterogeneous nature of CRC and involvement of diverse molecular pathways. New large-scale 'omics' technologies are making it possible to generate, analyze and interpret biological data from molecular determinants of CRC. The developments of sophisticated computational analyses would allow information from different omics platforms to be integrated, thus providing new insights into the biology of CRC. Together, these technological advances and an improved mechanistic understanding might allow CRC to be clinically managed at the level of the individual patient. This review provides an account of the current challenges in CRC management and an insight into how new technologies could allow the development of personalized medicine for CRC.

Sociocultural variation in attitudes toward use of genetic information and participation in genetic research by race in the United States: implications for precision medicine

Background “Precision medicine” (PM) requires researchers to identify actionable genetic risks and for clinicians to interpret genetic testing results to patients. Whether PM will equally benefit all populations or exacerbate existing disparities is uncertain.

Methods We ascertained attitudes toward genetic testing and genetic research by race in the United States using the online Amazon mTurk US workforce (n = 403 White; n = 56 African American (AA)). Generalized linear models were used to test differences in beliefs and preferences by race, adjusting for sociodemographics and prior genetic experience.

Results AA were less likely than White to believe that genetic tests should be promoted or made available. Further, AA were less likely to want genetic testing results or to participate in genetic research.

Conclusions Important dimensions that underlay PM are not universally accepted by all populations. Without clear attention to concerns, AA communities may not equally benefit from the rapidly-emerging trend in PM-centered research and clinical practice.

Genomic Test Results and the Courtroom: The Roles of Experts and Expert Testimony

The rapid advancement from single-gene testing to whole genome sequencing has significantly broadened the type and amount of information available to researchers, physicians, patients, and the public in general. Much debate has ensued about whether genomic test results should be reported to research participants, patients and consumers, and at what stage we can be sure that existing evidence justifies their use in clinical settings. Courts and judges evaluating the utility of these results will not be immune to this uncertainty. As scholars increasingly explore the duty of care standards related to reporting genomic test results, it is timely to provide a framework for understanding how uncertainty about genetic and genomic tests influences evidentiary considerations in the court room. Here, we explore the subtleties and nuances of interpreting genetic data in an environment of substantial discord related to the value that individuals should place on genetic and genomic tests. In conjunction, we discuss the roles courts should play in qualifying experts, expert testimony, and genetic and genomic tests given the intricate and complex nature of genetic and genomic information.

Pharmacogenetics of drug-metabolizing enzymes in US Hispanics

Although the Hispanic population is continuously growing in the United States, they are underrepresented in pharmacogenetic studies. This review addresses the need for compiling available pharmacogenetic data in US Hispanics, discussing the prevalence of clinically relevant polymorphisms in pharmacogenes encoding for drug-metabolizing enzymes. CYP3A5*3 (0.245-0.867) showed the largest frequency in a US Hispanic population. A higher prevalence of CYP2C9*3, CYP2C19*4, and UGT2B7 IVS1+985 A>G was observed in US Hispanic vs. non-Hispanic populations. We found interethnic and intraethnic variability in frequencies of genetic polymorphisms for metabolizing enzymes, which highlights the need to define the ancestries of participants in pharmacogenetic studies. New approaches should be integrated in experimental designs to gain knowledge about the clinical relevance of the unique combination of genetic variants occurring in this admixed population. Ethnic subgroups in the US Hispanic population may harbor variants that might be part of multiple causative loci or in linkage-disequilibrium with functional variants. Pharmacogenetic studies in Hispanics should not be limited to ascertain commonly studied polymorphisms that were originally identified in their parental populations. The success of the Personalized Medicine paradigm will depend on recognizing genetic diversity between and within US Hispanics and the uniqueness of their genetic backgrounds.

Multidisciplinary approach to genomics research in Africa: the AfriCRAN model

This article is an outcome of the African Craniofacial Anomalies Research Network (AfriCRAN) Human Hereditary and Health (H3A) grant planning meeting in 2012 in Lagos, Nigeria. It describes the strengths of a multidisciplinary team approach to solving complex genetic traits in the craniofacial region. It also highlights the different components and argues for the composition of similar teams to fast track the discovery of disease genes, diagnostic tools, improved clinical treatment and ultimately prevention of diseases.

Pharmacogenetics of cancer therapy: breakthroughs from beyond?

‘Pharmacogenetics or Pharmacogenomics’ (PG) is one of the most practiced cancer therapeutic strategies, tailored for individualized patients. Despite its popularity and rapid advancements in the field, many obstacles for cancer therapy PG still need to be overcome. By borrowing scientific systems from other disciplines such as cancer diagnosis, and therapeutic information from the diversity of tumor origins, categories and stages, cancer therapy PG may hopefully be improved. Furthermore, to quickly acquire genetic and pathologic information and seek therapeutic interventions, possible breakthroughs may come from beyond – changing the cancer therapeutic landscapes. The next generations of PG protocols and hospital routines for searching deadly cancer pathogenic pathways versus drug-targeting predictions are of great clinical significance for the future. Yet, progress of cancer therapy PG is entering into a bottleneck stage owing to simple model of relevant techniques and routines. Promoting or even innovating present PG modular is very necessary. This perspective highlights this issue by introducing new initiatives and ideas.

The mathematical limits of genetic prediction for complex chronic disease

BACKGROUND

Attempts at predicting individual risk of disease based on common germline genetic variation have largely been disappointing. The present paper formalises why genetic prediction at the individual level is and will continue to have limited utility given the aetiological architecture of most common complex diseases.

METHODS

Data were simulated on one million populations with 10 000 individuals in each populations with varying prevalences of a genetic risk factor, an interacting environmental factor and the background rate of disease. The determinant risk ratio and risk difference magnitude for the association between a gene variant and disease is a function of the prevalence of the interacting factors that activate the gene, and the background rate of disease.

RESULTS

The risk ratio and total excess cases due to the genetic factor increase as the prevalence of interacting factors increase, and decrease as the background rate of disease increases. Germline genetic variations have high predictive capacity for individual disease only under conditions of high heritability of particular genetic sequences, plausible only under rare variant hypotheses.

CONCLUSIONS

Under a model of common germline genetic variants that interact with other genes and/or environmental factors in order to cause disease, the predictive capacity of common genetic variants is determined by the prevalence of the factors that interact with the variant and the background rate. A focus on estimating genetic associations for the purpose of prediction without explicitly grounding such work in an understanding of modifiable (including environmentally influenced) factors will be limited in its ability to yield important insights about the risk of disease.

Rare functional variants in genome-wide association identified candidate genes for nonsyndromic clefts in the African population

Nonsyndromic clefts of the lip and palate (NSCLP) are complex genetic traits. Together, they are classified as one of the most common birth defects with a prevalence of 1/700 live births. Genome-wide association studies (GWAS) for nonsyndromic cleft lip with or without cleft palate (NSCL[P]) revealed significant association for common single nucleotide polymorphisms near genes involved in craniofacial development i.e., MAFB, PAX7, VAX1, ARHGAP29 (ABCA4 locus), and IRF6. Sequencing of protein coding regions of the NSCL(P) GWAS candidate genes or adjacent genes suggest a role for rare functional variants. Replication studies in the African population did not observe any significant association with the GWAS candidate genes. On the other hand, the role of rare functional variants in GWAS candidate genes has not been evaluated in the African population. We obtained saliva samples from case triads in Nigeria and Ethiopia for Sanger sequencing of the GWAS candidate genes (MAFB, PAX7, VAX1, ARHGAP29, and IRF6) in order to identify rare functional variants. A total of 220 African samples (140 Nigerians and 80 Ethiopians) were sequenced and we found the following new rare variants- p.His165Asn in the MAFB gene, p.Asp428Asn in the PAX7, a splice-site variant that creates a new donor splice-site in PAX7. We also found three previously reported missense variants p.Gly466Ser in PAX7; p.Leu913Ser and Arg955His in ARHGAP29. No de novo mutations were found. Future genome-wide association and sequencing studies should be conducted using samples from Africa in order to identify new molecular genetic factors that contribute to the etiology of NSCLP.

Personalized medicine, availability, and group disparity: an inquiry into how physicians perceive and rate the elements and barriers of personalized medicine

BACKGROUND

The success of personalized medicine depends on factors influencing the availability and implementation of its new tools to individualize clinical care. However, little is known about physicians' views of the availability of personalized medicine across racial/ethnic groups and the relationship between perceived availability and clinical implementation. This study examines physicians' perceptions of key elements/tools and potential barriers to personalized medicine in connection with their perceptions of the availability of the latter across subpopulations.

METHODS

Study subjects consisted of physicians recruited from Cincinnati Children's Hospital Medical Center and UC Health. An electronic survey conducted from September 2012 to November 2012 recruited 104 physicians. Wilcoxon rank sum analysis compared groups.

RESULTS

Physicians were divided about whether personalized medicine contributes to health equality, as 37.4% of them believe that personalized medicine is currently available only for some subpopulations. They also rated the importance of racial/ethnic background almost as high as the importance of genetic information in the delivery of personalized medicine. Actual elements of personalized medicine rated highest include family history, drug-drug interaction alerts in medical records, and biomarker measurements to guide therapy. Costs of gene-based therapies and genetic testing were rated the most significant barriers. The ratings of several elements and barriers were associated with perceived availability of personalized medicine across subpopulations.

CONCLUSION

While physicians hold differing views about the availability and implementation of personalized medicine, they likewise establish complex relationships between race/ethnicity and personalized medicine that may carry serious implications for its clinical success.

Genomic data-sharing: what will be our legacy?

Prior to 1974, the Tuskegee Syphilis experiments, expansive use of the HeLa cells, and other blatant instances of research abuse pervaded the medical research field. Ongoing challenges to informed consent, privacy and data-sharing will influence the stories that research participants today share with future generations. This has significant implications for the advancement of genomic science, and the public's perception of genomic research.

Unique considerations for advancing genomic medicine in African populations

Genomic medicine presents many opportunities for improved health outcomes in the future. African countries, however, face many challenges in harnessing these opportunities for the benefit of African patients. Unique aspects that fuel these challenges include the enormous genetic diversity found in African individuals and communities across the continent; a high burden of infectious diseases and prioritized commitment of scarce public health resources to primary healthcare; limited economic resources for genomic health research and translation; and a history of the one-way transfer of samples, human resources and research translation off the continent. While these challenges are significant, there are opportunities for African countries to harness the economic and health benefits of genomic medicine for people in Africa. An active and supported biotechnology sector can provide an avenue for translating the benefits of African genomic research to African patients and populations.

Engaging the next generation of healthcare professionals in genomics: planning for the future

There is broad agreement that healthcare professionals require fundamental training in genomics to keep pace with scientific advancement. Strong models that promote effective genomic education, however, are lacking. Furthermore, curricula at many institutions are now straining to adapt to the integration of additional material on next-generation sequencing and the bioethical and legal issues that will accompany clinical genomic testing. This article advocates for core competencies focused on job function, which will best prepare providers to be end-users of healthcare information. In addition, it argues in favor of online and blended learning models that incorporate student genotyping and specific training in the ethical, legal and social issues raised by genomic testing.

Understanding symptoms in patients with advanced chronic kidney disease managed without dialysis: use of a short patient-completed assessment tool

BACKGROUND

It is often believed that patients with advanced chronic kidney disease (CKD) stage 4-5 have few symptoms, and that dying with renal disease is relatively symptom-free. But the symptom burden of patients managed conservatively (without dialysis), with potentially high levels of comorbidity and poor functional status, is unknown. This clinical audit evaluated the prevalence and severity of symptoms in conservatively managed CKD stage 4-5 patients.

METHODS

Symptom data was collected from all conservatively managed patients from 2 renal units referred to a new renal palliative care service over a 10-month period between April 2005 and January 2006. Data on symptom prevalence and severity was collected as part of their routine clinical care, using a modified version of the Patient Outcome Scale--symptom module (POSs). This patient-completed instrument identifies the presence and severity of 17 symptoms. Demographic data was also collected, including estimated glomerular filtration rate (eGFR) using the MDRD formula, primary renal diagnosis and comorbidity.

RESULTS

Symptoms were evaluated in 55 patients, with a mean age of 82 years (SD 5.5, range 66-96). eGFR ranged from 3 to 30 ml/min (median 11, mean 12.75). In patients with CKD stage 4-5, managed without dialysis, the symptom burden is high. The most prevalent symptoms reported were weakness (75%), poor mobility (75%), poor appetite (58%), pain (56%), pruritus (56%) and dyspnoea (49%). The total number of symptoms each individual patient experienced ranged from 1 to 14 (median 7, mean 6.8). Symptoms were frequently reported as moderate, severe, or overwhelming; in 54% of patients with poor mobility, 48% with weakness, 30% with itching, 31% with anorexia and 27% with pain. No significant association was demonstrated between the number of symptoms experienced and either severity of renal disease or comorbidity score.

CONCLUSIONS

This structured clinical evaluation demonstrates the extent and severity of symptom burden in conservatively managed patients with CKD stage 4-5, and demonstrates the use of an appropriate clinical tool that can be used to assess the efficacy of treatment.