Phenytoin is an antiepileptic drug with a narrow therapeutic index and large interpatient pharmacokinetic variability, partly due to genetic variation in CYP2C9. Furthermore, the variant allele ...HLA‐B*15:02 is associated with an increased risk of Stevens–Johnson syndrome and toxic epidermal necrolysis in response to phenytoin treatment. We summarize evidence from the published literature supporting these associations and provide therapeutic recommendations for the use of phenytoin based on CYP2C9 and/or HLA‐B genotypes (updates on cpicpgx.org).
Community‐centric approaches to engage underrepresented populations—including community engagement, community‐level consent practices, and capacity development for research—are means to enhance ...diversity in biomedical research populations in a more ethical way. Low diversity is a known problem in biomedical research that presents challenges in translating the benefits of research to the global population. Through long‐term partnerships built on trust and collaboration, communities who would otherwise avoid research may be more willing to participate. When communities are engaged in research as partners and research questions are motivated by community health priorities, research is more meaningful and research methods are more respectful. Conversely, a lack of consultation throughout the research process can further alienate the very communities that these efforts are designed to engage. A number of underserved populations—for example American Indian and Alaska Native peoples—may value the benefits of research to a community equally or more than individual benefits. A community's autonomy must be considered, particularly when that community is not adequately protected by traditional informed consent processes. Opportunities for capacity development to support collaborative partnerships between communities and researchers are required to support engagement and understanding of the research process. Changes to research processes and infrastructure that encourage a higher level of research oversight within the community should be supported. In this paper, we present approaches that may improve diversity and equitable access to research and the delivery of health innovations for people that have historically been left out of biomedical research.
Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256,523 Europeans aged 60 ...years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1 p = 4 × 10
), arthritis (GDF5 p = 4 × 10
), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing.
The varying frequencies of pharmacogenetic alleles among populations have important implications for the impact of these alleles in different populations. Current population grouping methods to ...communicate these patterns are insufficient as they are inconsistent and fail to reflect the global distribution of genetic variability. To facilitate and standardize the reporting of variability in pharmacogenetic allele frequencies, we present seven geographically defined groups: American, Central/South Asian, East Asian, European, Near Eastern, Oceanian, and Sub‐Saharan African, and two admixed groups: African American/Afro‐Caribbean and Latino. These nine groups are defined by global autosomal genetic structure and based on data from large‐scale sequencing initiatives. We recognize that broadly grouping global populations is an oversimplification of human diversity and does not capture complex social and cultural identity. However, these groups meet a key need in pharmacogenetics research by enabling consistent communication of the scale of variability in global allele frequencies and are now used by Pharmacogenomics Knowledgebase (PharmGKB).
Precision public health is a relatively new field that integrates components of precision medicine, such as human genomics research, with public health concepts to help improve population health. ...Despite interest in advancing precision public health initiatives using human genomics research, current and future opportunities in this emerging field remain largely undescribed. To that end, we provide examples of promising opportunities and current applications of genomics research within precision public health and outline future directions within five major domains of public health: biostatistics, environmental health, epidemiology, health policy and health services, and social and behavioral science. To further extend applications of genomics within precision public health research, three key cross-cutting challenges will need to be addressed: developing policies that implement precision public health initiatives at multiple levels, improving data integration and developing more rigorous methodologies, and incorporating initiatives that address health equity. Realizing the potential to better integrate human genomics within precision public health will require transdisciplinary efforts that leverage the strengths of both precision medicine and public health.
To use unsupervised topic modeling to evaluate heterogeneity in sepsis treatment patterns contained within granular data of electronic health records.
A multicenter, retrospective cohort study of 29 ...253 hospitalized adult sepsis patients between 2010 and 2013 in Northern California. We applied an unsupervised machine learning method, Latent Dirichlet Allocation, to the orders, medications, and procedures recorded in the electronic health record within the first 24 hours of each patient's hospitalization to uncover empiric treatment topics across the cohort and to develop computable clinical signatures for each patient based on proportions of these topics. We evaluated how these topics correlated with common sepsis treatment and outcome metrics including inpatient mortality, time to first antibiotic, and fluids given within 24 hours.
Mean age was 70 ± 17 years with hospital mortality of 9.6%. We empirically identified 42 clinically recognizable treatment topics (eg, pneumonia, cellulitis, wound care, shock). Only 43.1% of hospitalizations had a single dominant topic, and a small minority (7.3%) had a single topic comprising at least 80% of their overall clinical signature. Across the entire sepsis cohort, clinical signatures were highly variable.
Heterogeneity in sepsis is a major barrier to improving targeted treatments, yet existing approaches to characterizing clinical heterogeneity are narrowly defined. A machine learning approach captured substantial patient- and population-level heterogeneity in treatment during early sepsis hospitalization.
Using topic modeling based on treatment patterns may enable more precise clinical characterization in sepsis and better understanding of variability in sepsis presentation and outcomes.
Uncovering the root causes of complex diseases requires complex approaches, yet many studies continue to isolate the effects of genetic and social determinants of disease. Epidemiologic efforts that ...under-utilize genetic epidemiology methods and findings may lead to incomplete understanding of disease. Meanwhile, genetic epidemiology studies are often conducted without consideration of social and environmental context, limiting the public health impact of genomic discoveries. This divide endures despite shared goals and increases in interdisciplinary data due to a lack of shared theoretical frameworks and differing language. Here, we demonstrate that bridging epidemiological divides does not require entirely new ways of thinking. Existing social epidemiology frameworks including Ecosocial theory and Fundamental Cause Theory, can both be extended to incorporate principles from genetic epidemiology. We show that genetic epidemiology can strengthen, rather than detract from, efforts to understand the impact of social determinants of health. In addition to presenting theoretical synergies, we offer practical examples of how genetics can improve the public health impact of epidemiology studies across the field. Ultimately, we aim to provide a guiding framework for trainees and established epidemiologists to think about diseases and complex systems and foster more fruitful collaboration between genetic and traditional epidemiological disciplines.
PDF
