Abstract Background/Objectives: Biological factors such as genetics contribute to nutrition-related outcomes, but nutritional epidemiological studies often lack consideration of genetics despite evidence of their functional impacts on health and cognition. Phenylalanine hydroxylase (PAH) genetic variation has been hypothesized to influence health and cognitive outcomes due to evidence of metabolic perturbations in L-phenylalanine to L-tyrosine hydroxylation, including plausible downstream effects on catecholamine neurotransmitters among not only individuals with phenylketonuria (PKU) [homozygotes for PAH mutations] but also PKU carriers [heterozygotes]. Related to these metabolic perturbations, diminished executive functioning has been observed in individuals with PKU, even when treated, but research is lacking exploring this outcome in PKU carriers. The present study aims to detail methods for stratifying populations based on genetic variation, for use in epidemiological precision nutrition research. It further provides an exploratory exemplar of such research through population stratification by PAH genetic variation (i.e., PKU carriers vs. non-carriers), while providing the first descriptive data on executive functioning skills using the validated Executive Skills Questionnaire—Revised (ESQ-R) tool with PAH-genetically stratified groups (PKU carriers and non-carriers). Methods: Participants were ≥18 years of age and PAH heterozygotes (PKU carriers) or non-carriers. Levels of executive functioning were self-reported anonymously online and included the validated Executive Skills Questionnaire—Revised (ESQ-R) tool. Data were analyzed using t-tests, chi-square tests, ANOVAs, and ANCOVAs. Results: Respondents (n = 99, n = 79 carriers and n = 20 non-carriers) consisted of males (22.2%) and females (77.8%), primarily of European ancestry. There were no significant differences between groups (carriers vs. non-carriers) for total scores (mean ± SD ESQ-R score carriers = 17.41 ± 14.01; non-carriers = 14.95 ± 10.00), but carriers scored significantly worse than non-carriers for the ESQ-R item “I have trouble making a plan” in the adjusted model. Conclusions: This study provides a methodological exemplar for exploring genetically stratified subpopulations in epidemiological precision nutrition research. Nutritional epidemiological research has historically failed to consider genetic variation, which can be important for hypothesis generation, population stratification, and interpretation of results, among other factors. It is well known that genetic variation influences metabolic processes, and it has often been observed that the stratification of populations based on genetic variation can lead to striking differences in health responses to diet. For example, Vallée Marcotte et al. were able to clearly discriminate between “responders” and “non-responders” to omega-3 supplementation for triglyceride lowering by stratifying participants based on genetic variation [ 1]. In addition, genetic variation can influence caffeine metabolism and related clinical outcomes. Studies have demonstrated that upon stratifying the population based on CYP1A2 genetic variation (i.e., “fast” vs. “slow” caffeine metabolizers), when caffeine intake exceeds the equivalent of approximately 2–3 cups of coffee per day, “slow metabolizers” of caffeine are at a significantly higher risk of cardiovascular and renal disease compared to “fast metabolizers” [ 2, 3]. Precision nutrition can be defined as dietary recommendations that consider individual profiling, such as metabolomic, genomic, proteomic, and metagenomic data, in order to optimize health status [ 4]. Stratifying populations by genetic variation and other elements of precision nutrition can help improve methodological rigor in nutritional epidemiology; this concept has been highlighted in a recent report from the National Institutes of Health’s workshop on precision nutrition [ 5]. For example, genetic variation influencing metabolism should be used to generate hypotheses, with the aim of helping to improve our understanding of specific population subgroups that may experience unique health risks in response to nutrition interventions [ 6]. Furthermore, stratifying populations based on genetic variations can improve our understanding of discrepant results in epidemiological research. As a further example, some intervention research has found that L-tyrosine (Tyr) supplementation can improve cognitive outcomes (ex. working memory) while others have found no effect [ 7]. However, when researchers stratified participants based on genetic variation, differences in DRD2 genotypes impacted variability in responses to Tyr supplementation [ 8]. While research consistently considers confounding factors such as demographic variables, genetic variation has not commonly been considered as one of these factors. Phenylketonuria (PKU) is the most common genetically inherited metabolic disease [ 10, 11]. The condition is caused by mutations in the phenylalanine hydroxylase (PAH) gene, which encodes the PAH enzyme [ 11]. Mutations in the PAH gene lead to reduced or absent PAH enzymatic activity, significantly impairing the conversion of the amino acid L-phenylalanine (Phe) to Tyr [ 11]. Elevated circulating levels of Phe can arise when PKU is not well controlled, for example, when not following a strict diet low in Phe-containing foods, without pharmaceutical treatment, or when left untreated altogether [ 11]. High Phe levels can lead to neurological damage, intellectual and developmental disabilities, and mental illnesses [ 11]. In addition, excess Phe can competitively inhibit the L-type amino acid transporter 1 (LAT1) at the blood–brain barrier, limiting the transport of all other large neutral amino acids (LNAAs), including Tyr and tryptophan, to the brain and potentially leading to deficiencies in neurotransmitter production [ 12]. PKU treatment is individualized, typically including dietary restriction of protein and aspartame, which contain high amounts of Phe, while supplementing with Phe-free foods and formulas consisting of Tyr and other amino acids [ 13]. Pharmacological treatments include sapropterin, a synthetic co-factor for the PAH enzyme, which is effective in a subset of responsive patients, pegvaliase, an enzyme-substitution therapy, and others [ 14, 15]. Current guidelines recommend maintaining circulating Phe levels ≤ 360 μmol/L in individuals with PKU, as lower circulating Phe levels are associated with higher IQ, a recommendation that is supported by a high certainty of evidence [ 14 PKU follows an autosomal recessive inheritance pattern; thus, biological parents or children of PKU patients are heterozygotes for a single PAH variant. While PKU is a rare genetic condition affecting approximately 1 in 10,000 individuals, a notable 2% of the population (1 in 50) are PAH heterozygotes (i.e., PKU carriers) [ 16]. The higher prevalence of PKU carriers within the population is highly relevant, as evidence suggests that PKU carriers exhibit an intermediate subclinical metabolic phenotype for PKU. For example, Phe-loading trials have demonstrated that carriers of PKU have higher blood levels of Phe and lower levels of Tyr compared to non-carrier controls, which demonstrates reduced capacity for Phe-to-Tyr conversion [ 17, 18, 19, 20, 21]. However, these trials lack the inclusion of clinical outcomes and genetic sequencing, highlighting the need for complementary methods that explore clinical outcomes such as executive functioning [ 17, 18, 19, 20, 21]. Studies using liver biopsies have also supported the reduced metabolic efficiency of the PAH enzymatic pathway in PKU carriers compared to non-carriers [ 22, 23]. Whether these metabolic disruptions translate into clinical outcomes, such as altered cognitive executive functioning, has yet to be thoroughly explored. Currently, PKU carriers are generally considered to be clinically “unaffected.” However, early research has suggested that carriers may exhibit lower IQ and worse cognitive functioning capabilities compared to non-carrier controls [ 24, 25], but these outcomes have yet to be robustly investigated. Executive functioning is a high-order cognitive skillset that refers to the ability to control, organize, and prioritize time and activities [ 26]. It can be sub-categorized into plan management, time management, organization, emotional regulation and behavioral regulation [ 27]. In patients with PKU, impairments in executive functioning are commonly noted; metabolically, these likely stem from disturbances in monoamine neurotransmitters, including deficiencies in serotonin, norepinephrine, and dopamine, which directly relate back to PKU impairments in the PAH metabolic pathway (i.e., reduced endogenous Tyr production) [ 11, 28, 29, 30, 31]. In 2018, a study demonstrated that parents of PKU children (PKU carriers) performed worse on cognitive tasks than non-carriers [ 25]. Specifically, they reported that carriers had worse executive functioning, delayed and immediate memory, and processing speed when compared to non-carrier controls [ 25]. While PKU carriers tend to exhibit disruptions in the production of PAH pathway metabolites, such as Phe and Tyr [ 17, 18, 19, 20, 21], further studies exploring clinical outcomes, including executive functioning in this population, are needed. Descriptive, reference data on executive functioning in this population is also needed. Biological sex is also important to consider in this work, given that it appears to play a role in executive functioning [ 32]. Specifically, structural and functional differences have been observed in the male and female brain, and moreover, males and females have been shown to differ in how they manage household tasks, discipline, and emotional support, which are directly related to executive functioning [ 33, 34 Overall, many factors have been demonstrated to impact executive functioning. One factor being parenthood that generally has a protective effect on levels of executive functioning, and parents’ executive functioning capabilities are also predictors of their children’s executive functioning capabilities [ 35, 36, 37]. Among biological parents of patients affected by PKU (who are also PAH heterozygotes/genetic carriers for PKU), only one small study has explored executive functioning in this population, and the results were intriguing [ 25]. This study compared PKU carrier parents of adult PKU patients (n = 12) to non-carrier controls (n = 14) and observed overall lower executive functioning scores among the parents (carriers) compared to controls. More specifically, carriers scored significantly worse than non-carrier controls on tests related to processing speed and executive functioning, such as set-shifting abilities and inhibitory control [ 25]. Given the abovementioned differences in PAH pathway metabolism among PKU carriers, executive functioning outcomes could be related to higher serum Phe following protein intake, and may be an important outcome to understand among the 1 in 50 individuals who are genetic carriers for PKU [ 16 To provide a strong foundation for future epidemiological precision nutrition research, it is important to develop descriptive data on priority nutrition-related outcomes of interest for specific subsets of the population based on their unique metabolic, genetic and/or health statuses. While genetic sequencing and metabolomic profiling are not typically part of routine clinical care, there is movement towards integrating these multi-omics technologies into practice settings [ 38]. As such, precision nutrition research is needed to inform the use of genetic and metabolic information clinically. Given the metabolic perturbations observed in PKU carriers alongside early evidence of possible impacts on executive functioning (plausibly related to Phe [protein] intake, which is typically high in a standard, non-PKU diet), the present study aims to provide preliminary descriptive data on executive functioning skills among genetic carriers and non-carriers of PKU. This study also aims to detail a methodological exemplar for stratifying populations based on genetic variation, to inform epidemiological precision nutrition research. The exemplar included herein focuses on population stratification by PAH genetic variation and is exploratory at this time; as such, the results should be interpreted with caution. Between-group comparisons intend to provide foundational descriptive data that can help inform future epidemiological precision nutrition studies (e.g., for use in sample size calculations). The comparison explicitly accounts for precision-related factors, such as biological sex, genetic variation, metabolic differences and other variables relevant to precision nutrition. Notably, this is the first study to report on executive functioning skills among PKU carriers using the validated Executive Skills Questionnaire—Revised (ESQ-R) tool [ 19]. This descriptive data can be used to inform future epidemiological precision nutrition research that aims to compare carriers to non-carriers, while inferring effects of carrier status on executive function. 2.1. Study Conceptualization and Hypothesis Generation 2.2. Recruitment and Participants Participants were recruited through advertisements from clinics, organizations, and social media pages related to PKU, metabolic conditions, and/or genomics ( Supplementary Table S1). All participants in the present study were 18 years of age or older and confirmed genetic carriers or non-carriers of PKU. Descriptive characteristics of participants were all self-reported (e.g., self-identified ethnicity, self-reported income, etc.). All participants provided their written informed consent. This study was reviewed and approved by the University of Guelph Research Ethics Board (REB#23-02-009). 2.3. Executive Skills Questionnaire—Revised (ESQ-R) Levels of executive functioning were anonymously self-reported by participants using Qualtrics survey software (XM Platform) and evaluated using the validated ESQ-R tool [ 39]. The ESQ-R comprises 25 questions that are scored on a 4-point Likert scale, indicating: never or rarely [0 points], sometimes [1 point], often [2 points], or very often [3 points]. While the complete ESQ-R can be scored to obtain an indicator of overall executive functioning, the following sub-categories can also be individually calculated and scored to determine different domains of executive functioning capabilities including plan management [score based on 11 questions], time management [score based on 4 questions], organization [score based on 3 questions], emotional regulation [score based on 3 questions] and behavioral regulation [score based on 4 questions]. The ESQ-R provides an estimate of executive function based on participant self-report, rather than direct behavioral assessment. Higher scores are indicative of worse executive functioning skills. 2.4. Data Analysis Data were analyzed using SPSS version 29.0.2 and analyses included descriptive statistics, as well as analysis of variance (ANOVAs), analysis of covariance (ANCOVAs), t-tests, and chi-square/Fisher’s exact tests (for categorical data) to compare outcomes between PAH-genetically stratified groups. In cases where expected counts were 1 question and were removed from the analysis (therefore n = 97). 2. A zero value was imputed for one participant who had a missing value for one question. 3. A zero value was imputed for two participants who had missing values for one question; one participant had missing values for >1 question and was removed from the analysis (therefore n = 98). 4. One participant had missing values for >1 question and was removed from the analysis (therefore n = 98). 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Nutrients. 2026; 18(11):1811. https://doi.org/10.3390/nu18111811 Chicago/Turabian Style Dhawan, Anoushka, Sophia M. Khan, Madison L. Fennell, Clara E. Cho, Jennifer M. Monk, and Justine R. Keathley. 2026. "Exploring Subpopulations for Epidemiological Precision Nutrition Research: The Example of Phenylalanine Hydroxylase (PAH) Genetic Variation" Nutrients 18, no. 11: 1811. https://doi.org/10.3390/nu18111811 APA Style Dhawan, A., Khan, S. M., Fennell, M. L., Cho, C. E., Monk, J. M., & Keathley, J. R. (2026). Exploring Subpopulations for Epidemiological Precision Nutrition Research: The Example of Phenylalanine Hydroxylase (PAH) Genetic Variation. Nutrients, 18(11), 1811. https://doi.org/10.3390/nu18111811 Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here. Article Metrics Article metric data becomes available approximately 24 hours after publication online.
