Pharmacogenomics of an Australian Indigenous populations

Genomic technologies have enabled an increased understanding of population specific genetic differences and their effect on health and disease. However, there exists an under-representation of indigenous people in medical and clinical research. The objective of this study was to investigate the prevalence and existence of genetic polymorphisms that can affect drug metabolism(Pharmacogenomic variants) in the Aboriginal Tiwi population. We developed a pharmacogenomic analysis pipeline and identified 22 pharmacogenomic variants with 18 clinically actionable guidelines with implications for drug dosing and treatment of conditions including heart disease, diabetes and cancer

Pharmacogenomic analysis of a genetically distinct Indigenous population

Indigenous Australians face a disproportionately severe burden of chronic disease relative to other Australians, with elevated rates of morbidity and mortality. While genomics technologies are slowly gaining momentum in personalised treatments for many, a lack of pharmacogenomic research in Indigenous peoples could delay adoption. Appropriately implementing pharmacogenomics in clinical care necessitates an understanding of the frequencies of pharmacologically relevant genetic variants within Indigenous populations. We analysed whole-genome sequence data from 187 individuals from the Tiwi Islands and characterised the pharmacogenomic landscape of this population. Specifically, we compared variant profiles and allelic distributions of previously described pharmacologically significant genes and variants with other population groups. We identified 22 translationally relevant pharmacogenomic variants and 18 clinically actionable guidelines with implications for drug dosing and treatment of conditions including heart disease, diabetes and cancer. We specifically observed increased poor and intermediate metabolizer phenotypes in the CYP2C9 (PM:19%, IM:44%) and CYP2C19 (PM:18%, IM:44%) genes.</p

RBCeq: A robust and scalable algorithm for accurate genetic blood typing

Background: While blood transfusion is an essential cornerstone of hematological care, patients requiring repetitive transfusion remain at persistent risk of alloimmunization due to the diversity of human blood group polymorphisms. Despite the promise, user friendly methods to accurately identify blood types from next-generation sequencing data are currently lacking. To address this unmet need, we have developed RBCeq, a novel genetic blood typing algorithm to accurately identify 36 blood group systems. Methods: RBCeq can predict complex blood groups such as RH, and ABO that require identification of small indels and copy number variants. RBCeq also reports clinically significant, rare, and novel variants with potential clinical relevance that may lead to the identification of novel blood group alleles. Findings: The RBCeq algorithm demonstrated 99·07% concordance when validated on 402 samples which included 29 antigens with serology and 9 antigens with SNP-array validation in 14 blood group systems and 59 antigens validation on manual predicted phenotype from variant call files. We have also developed a user-friendly web server that generates detailed blood typing reports with advanced visualization (https://www.rbceq.org/). Interpretation: RBCeq will assist blood banks and immunohematology laboratories by overcoming existing methodological limitations like scalability, reproducibility, and accuracy when genotyping and phenotyping in multi-ethnic populations. This Amazon Web Services (AWS) cloud based platform has the potential to reduce pre-transfusion testing time and to increase sample processing throughput, ultimately improving quality of patient care. Funding: This work was supported in part by Advance Queensland Research Fellowship, MRFF Genomics Health Futures Mission (76,757), and the Australian Red Cross LifeBlood. The Australian governments fund the Australian Red Cross Lifeblood for the provision of blood, blood products and services to the Australian community.</p

Combating the COVID-19 pandemic in a resource-constrained setting: insights from initial response in India

The low-and-middle-income country (LMIC) context is volatile, uncertain and resource-constrained. India, an LMIC, has put up a complex response to the COVID-19 pandemic. Using an analytic approach, we have described India’s response to combat the pandemic during the initial months (from 17 January to 20 April 2020). India issued travel advisories and implemented graded international border controls between January and March 2020. By early March, cases started to surge. States scaled up movement restrictions. On 25 March, India went into a nationwide lockdown to ramp up preparedness. The lockdown uncovered contextual vulnerabilities and stimulated countermeasures. India leveraged existing legal frameworks, institutional mechanisms and administrative provisions to respond to the pandemic. Nevertheless, the cross-sectoral impact of the initial combat was intense and is potentially long-lasting. The country could have further benefited from evidence-based policy and planning attuned to local needs and vulnerabilities. Experience from India offers insights to nations, especially LMICs, on the need to have contextualised pandemic response plans