Annals of Human Genetics最新文献

Pharmacogenomics, the use of germline genomic data to guide prescription to improve effective and safer medication, holds promise as a clinical intervention. To date in most health systems, there has been limited uptake of pharmacogenomic testing confined to a few single drug–gene associations. Here, we describe the current reactive model of single gene testing and the potential for this to change to a pre-emptive panel or genome-based approach. For this change to occur, three major challenges need to be addressed—the pharmacogenomic testing approach, the digital and data integration, and service delivery models. We explore some of the potential solutions and how pharmacogenomics can be integrated into routine care at scale for patient benefit.

Pharmacological responses can vary significantly among patients from different ethnogeographic backgrounds. This variability can, at least in part, be attributed to population-specific genetic patterns in genes involved in drug absorption, distribution, metabolism, and excretion, as well as in genes associated with drug-induced toxicity. Identification of such ethnogeographic variability is thus crucial for the optimization of precise population-specific drug treatments. In this review, we summarize the current knowledge about the clinically actionable pharmacogenetic diversity of genes involved in drug metabolism (CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A5, DPYD, TPMT, NUDT15, UGT1A1, and NAT2), drug-induced hypersensitivity reactions (HLA-A and HLA-B), and drug-induced acute hemolytic anemia (G6PD). We highlight risk populations with distinct allele frequencies and discuss implications for the customization of treatment. Subsequently, we discuss key challenges and opportunities in population pharmacogenomics, including the importance of considering distinct allele frequency patterns in indigenous or founder populations, interpreting pharmacogenomic response in admixed populations, addressing the investigation bias of the pharmacogenomic literature, and difficulties in including rare and population-specific variants into drug response predictions. The information provided here underscores the critical role of population pharmacogenomics in refining pharmacological treatment strategies and aspires to provide further guidance to maximize the benefits of precision medicine across populations.

Individuals with familial hypercholesterolaemia (FH) have severely elevated plasma concentrations of low-density lipoprotein cholesterol (LDL-C) from birth and as a consequence have an elevated morbidity and mortality due to the development of coronary heart disease (CHD). Monogenic FH can be caused by carrying a single copy of a pathogenic variant in any of four genes (LDLR/APOB/PCSK9/APOE), which are all involved in the clearance of LDL-C from the blood by the liver. FH is one of the most common inherited disorders, with an estimated prevalence of carriers of around 1/280 individuals in most populations and ancestry groups. However, such variants can be found usually only in 20%–30% of clinically FH subjects, and in the majority of the no-variant individuals, the phenotype is most likely explained by the inheritance of a greater-than-average number of common variants of small effect, with such individuals better given the diagnosis of ‘polygenic hypercholesterolaemia’. Also, in a proportion of no-variant subjects who meet the clinical criteria, the most likely explanation is due to overproduction of Lp(a) which is an LDL-C particle with a bound copy of the ‘little-a’ protein. Here, we review the research that has elucidated the genetic architecture of the FH phenotype and discuss recent studies and future prospects of finding additional genes where variants can cause FH.