Individual responses to medications can vary, in part due to genomic variability (Roden et al., 2011). Pharmacogenomics (PGx) focuses on the use of individuals’ genomic information to guide medication selection and dosing in order to maximize therapeutic benefits and minimize side effects (Sadee and Dai, 2005). Over the past few decades, incorporation and application of PGx information into clinical decisions have been on the rise. So far, the Clinical Pharmacogenetics Implementation Consortium (CPIC) has published 26 clinical guidelines to help clinicians systematically interpret genetic tests to optimize medication therapy (CPIC, 2021). Also, around 15% of the medications approved by the US Food and Drug Administration (FDA) contain PGx-guided recommendations on their respective package inserts (FDA, 2022).

Individuals’ genomic information can differ significantly based on their geo-ancestral origins (Slatkin and Racimo, 2016). In recent years, in response to the US National Institutes of Health “All of Us” initiative (All of Us Research Program et al., 2019), the importance of including diverse populations in PGx studies has been gaining recognition (Mensah et al., 2019; Magavern et al., 2022). A 2009 study concluded that 96% of participants in genome-wide association studies (GWAS) were of European ancestry (Need and Goldstein, 2009). A subsequent 2016 study showed that 80% participants in GWAS were of European ancestry, due to more studies being conducted in East Asian countries such as China and Japan (Popejoy and Fullerton, 2016). As a broad geographical area, East Asia consists of subpopulations with diverse cultural and genomic backgrounds, such that differences in allele frequencies in single nucleotide variations (SNVs) exist among East Asian subpopulations (Lo et al., 2020; Pan and Xu, 2020).

In the US, there is still a paucity of PGx research being conducted in minority East Asian subpopulations. Examples of minority East Asian subpopulations in the US include Hmong, Filipinos, Cambodians, and Vietnamese (United States Census Bureau, 2019). If clinical decisions incorporating PGx are made based on the patient’s general East Asian ethnic category, the potential risks of failing to appreciate unique allele variations within minority Asian subpopulations could result in inappropriate medication recommendations. This underscores the critical need to expand inclusion of diverse populations in PGx research, specifically focusing on underrepresented subpopulations.

In this article, we highlight our accumulated research endeavors that collaborated with Hmong community to identify unique allele frequencies and novel SNV’s within key pharmacogenes. Translating such observations into real-world clinical decision-making tools holds promise for more safe and effective use of medications to achieve improved clinical outcomes.

The Hmong are an East Asian subpopulation that originated in China and migrated into Southeast Asia in the 1800s. After the end of the Vietnam War, over 150,000 people fled Laos for Thailand, where they were re-settled as refugees in multiple countries (Goldfarb, 1982). Now the Hmong diaspora includes the United States, France, Australia, French New Guinea, as well as China, Laos, Thailand, and Vietnam. The most populous states in the US are California, Minnesota, and Wisconsin. In 2019, the population of Hmong in the United States was 326,843 and Minnesota had 94,079 Hmong (United States Census Bureau, 2019).

The Hmong are experiencing a high prevalence of chronic diseases including gout, hypertension and type 2 diabetes, and in some cases higher rates compared to other populations (Culhane-Pera et al., 2009; Wahedduddin et al., 2010; Thao et al., 2015; Lor, 2018; Roman et al., 2021). Research has been conducted to investigate factors contributing to this observation as well as the overall quality of medical care for chronic diseases. Possible factors include general healthcare screening seeking behavior (Barrett et al., 1998), health literacy (Wong et al., 2005), traditional beliefs (Helsel et al., 2005), cultural clashes with the health care system and concerns about taking chronic medications (Culhane-Pera et al., 2003), and environment and lifestyle changes. A recent cross-sectional study explored how migration from Southeast Asia to US with the changes in environment and lifestyle, including diet, could significantly decrease the diversity and function of Hmong gut microbiota, which in turn could contribute to obesity and cardiometabolic disease progression (Vangay et al., 2018). In addition, recent discoveries of relatively unique prevalence of SNVs known to affect medication selection and dosing may be contributing, which represent the prime focus of contemporary PGx research.

Hmong appear to be a genetically unique population, which is supported by multiple studies. Hmong can be differentiated from Thai and Chinese based on only 32 microsatellite genetic markers in contrast with the absence of a clear separation between Thai and Chinese individuals (Listman et al., 2007). Hmong are genetically and linguistically the most distinct ethnic group compared to four other Thai hill tribe populations (Akha, Karen, Lahu, and Lisu), as indicated by a study analyzing 2,445 genome-wide single nucleotide polymorphism markers in the Human Genome Diversity Project (Listman et al., 2011). Additionally, excess rare alleles have been found in the Hmong population that could be explained by accumulated mutations over time or through genetic drift caused by significant losses in the Hmong population due to wars (Listman et al., 2011). Analysis of 537 Hmong-Mien speaking individuals using mitochondrial DNA demonstrated variable ratios of lineages that implied Hmong-Mien populations had more genetic contacts with Northern East Asians compared to Southern East Asians (Wen et al., 2005; Yang et al., 2022). Hmong kinship practices could contribute as well, including clan hospitality (treating people with the same last name as family), clan exogamy (marrying outside one’s clan), ethnic endogamy (marrying within one’s ethnic group) (Lee, 2020), as well as cross-cousin marriage (Culhane-Pera et al., 2003). All of these observations provide a basis for conducting genomic research in this genetically unique population.

Using principles of community-based participatory research (Culhane-Pera et al., 2017b), our research efforts have engaged Hmong to participate in PGx studies in the past 15 years. After exploring cultural concepts of heredity and reactions to genetic research (Culhane-Pera et al., 2017a), PGx studies were conducted in two independent cohorts of Hmong adults (age ≥ 18 years old) in Minnesota. The first cohort enrolled 236 self-identified Hmong (Hmong-PGx cohort) in 2009 (Straka et al., 2010). The second cohort enrolled 198 Hmong (VIP-Hmong cohort) in 2017 (Wen et al., 2020). Collectively, a selection of SNVs within key pharmacogenes were identified to exhibit differential frequencies between Hmong and East Asians, including CYP2C9*3 (18.9% vs. 3%), CYP2C19*2 (42.2% vs. 29%), CYP2C19*3 (0.3% vs. 8.3%), and CYP4F2*3 (6.5% vs. 22.1%) (Wen et al., 2020; Sun et al., 2021). Such differences could have translational impact on medication selection and dosing for Hmong. Based on the CPIC guidelines (CPIC, 2021), compared to other East Asians, Hmong would require alternative therapies for several medications based on their predicted phenotypes. Examples of medications include antithrombotic agents such as warfarin and clopidogrel, and antidepressants such as selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants (TCAs) (Wen et al., 2020).

Other than the apparent differences in allele frequencies of SNVs, unique subpopulations also have novel genetic variants, which appears to be the case for the Hmong related to genetic variants within a key pharmacokinetics (Woodahl et al., 2014) gene: CYP2D6. This highly polymorphic pharmacogene has an impact on several medications including tamoxifen, SSRIs and opioids (CPIC, 2021). Using targeted next-generation sequencing with confirmatory Sanger sequencing, three novel sub-alleles (*10.007, *36.004, and *75.002) were identified (Wen et al., 2022b). This discovery underscores the importance of using novel sequencing techniques to better characterize genomic profiles in subpopulations in addition to reporting allele frequencies in common alleles.

By using available tools such as CPIC guidelines, FDA package inserts or other published PGx-guided dosing algorithms, research has been conducted to further demonstrate the clinical translation and implications of these unique allele frequency distributions discovered in our Hmong cohorts. The following sections describe examples applied to several classes of medications.

Failure to recognize the unique geo-ancestral differences in PGx can have real-world ramifications. The overall minor allele frequency (MAF) of a specific SNV can modulate the translational impact of SNVs on medication selection and dosing. A well-known example relates to the CYP2C9*5, *6, *8, and *11 alleles in warfarin dosing, which are prevalent among African populations and virtually non-existent in non-African populations (Perera et al., 2014). Failure to incorporate these alleles in warfarin PGx dosing algorithms led to inferior performance of such algorithms in patients of African ancestry (Kimmel et al., 2013).

As another example, CYP2C19 poor/intermediate metabolizers of clopidogrel vary substantially among different populations ranging from 58% in East Asians to 28% in Europeans (Lee et al., 2022). This can partially explain the lack of statistical power to ascertain the advantage of implementing PGx-guided approach for P2Y12 inhibitors selection compared to the current clinical practice in large-scale landmark clinical trials that primarily consisted of Europeans such as the POPular Genetics trial (Claassens et al., 2019). Consequently, the thresholds of the MAF for clinical actionable SNVs, which are set primarily based on patients of European ancestry, may mask the real-world frequency of such SNVs in diverse populations and hence impede, or at least, confound the translation and implementation of PGx in clinical settings. Thus, there is a critical need to assess the real-world applicability and clinical usability of current PGx guidelines in geo-ancestrally diverse populations.

Hmong, along with other underrepresented subpopulations (Fohner et al., 2013; Woodahl et al., 2014; Leitch et al., 2022), are eager for clinicians to recognize their uniqueness when considering selection and dosing of medications, rather than being represented by the broader definition of geo-ancestral grouping (Culhane-Pera et al., 2017a; Culhane-Pera et al., 2017b; Holzer et al., 2021). PGx has uncovered some relevant issues, but more PGx research is needed within subpopulations to identify differences in genomic biomarkers that can contribute to personalized medicine. It should be acknowledged that conducting research within underrepresented communities can have particular challenges. We encourage researchers to 1) actively engage with liaisons and leaders from the community to discuss key community needs and how research can assist in addressing such needs; 2) create community-academic research teams to ensure that methods are appropriate and effective for the community; and 3) disseminate the findings back to the community in culturally and linguistically appropriate ways. These approaches can contribute to maximizing benefits that communities can gain from participating in PGx research.

This mini-review highlights the significant and translational impact of variability in PGx in Hmong population, as a geo-ancestral subpopulation, discovered by our collaboration with Hmong community. The current challenges and future opportunities were presented with the goals of expanding diversity in PGx research and reducing health disparities. Finally, it is expected that our approaches to conducting and communicating PGx research in Hmong community can be motivating for other researchers.