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. 2025 Apr 22;16(1):26.
doi: 10.1186/s13293-025-00708-5.

Sexual dimorphism in metabolomic and phenotypic spectra of UGT deficiency: findings from the Canadian Longitudinal Study on Aging

Ana Lucia Rivera-Herrera  1   2   3 , Michèle Rouleau  1   2   3 , Mahukpe Narcisse Ulrich Singbo  3 , Tania Cuppens  2   3   4 , Julien Prunier  2   3   4 , Arnaud Droit  2   3   4 , David Simonyan  3 , Chantal Guillemette  5   6   7
Affiliations

Sexual dimorphism in metabolomic and phenotypic spectra of UGT deficiency: findings from the Canadian Longitudinal Study on Aging

Ana Lucia Rivera-Herrera et al. Biol Sex Differ. .

Abstract
in English, German, Spanish

Background: Two of the most frequently deleted genes in the human genome are the UDP-glycosyltransferases UGT2B17 and UGT2B28. They encode metabolic enzymes of the glucuronidation pathway that plays a pivotal role in the maintenance of cellular homeostasis for a variety of small molecule metabolites. These deletions may impact health, yet their effects remain poorly understood. We evaluated the impact of UGT deficiency on the plasma metabolome and examined the association between altered metabolites and health outcomes.

Methods: The metabolomic profiles of 4262 proficient gene carriers were compared with those of 352 UGT2B17-deficient, 97 UGT2B28-deficient, and 20 double-gene-deficient individuals from the Canadian Longitudinal Study on Aging. Significant metabolites found in these comparisons were analyzed for their associations with common diseases.

Results: The unexpectedly broad molecular divergence found in UGT-deficient metabolomes, which affected > 10% of metabolites, implies their significant influence across various metabolite classes-particularly lipids and amino acids - extending beyond their known substrates. The metabolic profiles of UGT2B17-deficient men and UGT2B28-deficient women were most impacted, with UGT2B17 deficiency affecting various metabolites linked to metabolic diseases, arthritis, and osteoporosis. Metabolites impacted by a UGT2B28 deficiency such as amino acids, were linked to metabolic disorders in women.

Conclusion: The findings significantly advance our understanding of the metabolic landscape associated with these frequently deleted genes in the human genome, which may influence susceptibility to various diseases in a sex-specific manner, laying the groundwork for determining their pathological mechanisms and impact on human health.

Divergent metabolomes of deficient glycosyltransferase individuals (UGT KO).Highest impact of UGT deficiency on lipid profiles.Unique metabolic signatures characterize UGT2B17 KO men and UGT2B28 KO women.UGT KO metabolic signatures are linked to a variety of diseases.

The human body constantly produces a variety of small molecules, including steroids, bile acids, fatty acids, and hormones. UDP-glycosyltransferases (UGTs) are a key family of enzymes that help balance these molecules and remove them from the body through a process called glucuronidation. Interestingly, two UGT genes, UGT2B17 and UGT2B28, are often naturally deleted, meaning some people are born without these genes. This gene absence results in a complete deficiency of the associated UGT proteins, potentially disrupting the balance of certain metabolites in the body. To understand how missing UGT2B17 or UGT2B28 affects the body’s full profile of metabolites (known as the circulating metabolome), we compared individuals without one or both of these genes (deletants) to those with both gene copies (references). We found distinct, sex-specific changes in metabolite levels: men lacking UGT2B17 had higher levels of steroids and phospholipids, while women lacking UGT2B28 had lower levels of fatty acids. Additionally, these disrupted metabolite levels were linked to different diseases in a sex-specific way. These insights help clarify how these commonly deleted genes influence metabolism and may lead to disease, opening avenues for future health research.

Keywords: CLSA; Glycosyltransferase; Human gene knockout; Metabolic disorders; Metabolomics.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: This study was approved by the local ethics committee (CHU de Québec – UL #2012 − 362). All participants provided written informed consent upon enrollment into the CLSA. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. Disclaimer: The opinions expressed in this manuscript are those of the authors and do not reflect the views of the Canadian Longitudinal Study on Aging. Additional files: File name: Additional file 1 File format. Pdf. Title of data: Supplementary Figures of Sexual Dimorphism in Metabolomic and Phenotypic Spectra of UGT deficiency: Findings from the Canadian Longitudinal Study on Aging. Description of data: Supplementary Fig. 1: Metabolites quantified in this study and number of metabolites in each super-pathway that were available for analysis. Supplementary Fig. 2: Gene expression by sex for (A) UGT2B17 and (B) UGT2B28 in human tissues. Supplementary Fig. 3: Number of significantly altered metabolites in each UGT KO group relative to the gene-proficient reference group (P < 0.05) by subpathway. Supplementary Fig. 4: Relative abundance of significantly dysregulated metabolites in each KO group. Supplementary Fig. 5: Associations between significantly altered metabolites in UGT2B17 KO and diseases. Supplementary Fig. 6: Associations between significantly altered metabolites in UGT2B17 KO females, UGT2B28 KO males, and diseases. File name: Additional file 2: File format. Excel.xlsx. Title of data: Supplementary tables of Sexual Dimorphism in Metabolomic and Phenotypic Spectra of UGT deficiency: Findings from the Canadian Longitudinal Study on Aging. Description of data: Supplementary Table 1: Detail of the chronic diseases / categories of chronic diseases used in this study. Supplementary Table 2: Fold change of the plasma metabolites measured in KO and reference groups. Supplementary Table 2.1: Significant changes in plasma metabolites for postmenopausal women. Supplementary Table 3: Characteristics of the study groups. Supplementary Table 4: Top 5 most changed metabolites in UGT2B17 KO, UGT2B28 KO and Double KO for overall and sex-based analyses. Supplementary Table 4.1: Top 5 most changed metabolites including unknown and partially characterized metabolites in UGT2B17 KO, UGT2B28 KO and Double KO for overall and sex-based analyses.

Figures

Fig. 1
Fig. 1
UGT deletions significantly impact the metabolic profile of plasma. (A) The study cohort consisted of homozygous reference gene carriers or UGT knockout (KO) individuals (n = 4731) from the genotyped comprehensive CLSA cohort for which metabolomics profiles (n = 1458 metabolites) were assessed. (B) Number of significantly altered metabolites in each UGT KO group relative to the gene-proficient reference group (P < 0.05). Total number of metabolites of lower or higher abundance is given for each UGT KO group. A detailed report on the metabolites affected in each group is available in Supplementary Table 2. C–E. Venn diagrams depicting the number of altered metabolites in the overall and sex-based analyses; (C) UGT2B17 KO, (D) UGT2B28 KO and (E) double KO. F–H. Distribution of altered metabolites within superpathways for each UGT KO group in the overall and sex-based analyses. Results were consistent when limited to postmenopausal women (Supplementary Table 2.1). The numbers above each bar represent the percentage of altered metabolites relative to the total number of metabolites measured in each superpathway
Fig. 2
Fig. 2
Distinct lipid subclasses are affected by each UGT KO. Enrichment analysis was conducted for significantly (P < 0.05) altered lipids in the overall (O), male (M), and female (F) analyses. Results were consistent when limited to postmenopausal women (Supplementary Table 2.1). Bubble sizes are proportional to the enrichment score. BCAA: branched-chain amino acids. Number of metabolites measured in each lipid subclass is provided
Fig. 3
Fig. 3
Lipid subclasses most affected by UGT KO. A. Schematic pathway of cholesterol-derived progestogens and androgens. Steroids that differ significantly in at least one UGT KO group are shown as tile arrays depicting sense of fold change relative to the reference group (blue, lower; red, higher). Most steroids that were measured were sulfate (-S) or glucuronide (-G) conjugates. Each asterisk denotes that the steroid has two sulfate groups. O: overall; M: males; F: females. B. Simplified sphingolipid metabolic pathway and sphingolipids significantly altered in UGT2B17 KO overall analysis. The global sense of the fold change for each sphingolipid subclass is indicated by color (blue, lower; light red, higher). The numbers of measured (center) and altered sphingolipids (parts of the donut) are given for each subclass. DCER, dihydroceramides; DhSM, dihydrosphingomyelins; CER, ceramides; HCER, hexosylceramides; LCER, lactosylceramides; SM, sphingomyelins. C. Phospholipid profiles in UGT2B17 KO and UGT2B28 KO groups relative to reference. LPC, lysophosphatidylcholines; LPE, lysophosphatidylethanolamines; LPI, lysophosphatidylinositol; LPG, lysophosphatidylglycerol; PC, phosphatidylcholine; PE, phosphatidylethanolamine; PI, phosphatidylinositol. *P < 0.05. (D) Fatty acid and (E) acylcarnitine profiles for UGT2B28 KO females relative to the reference group. Fold changes are shown relative to the reference group level set at 1.0 (dashed line). The x axis indicates carbon chain length and includes fatty-acid dicarboxylates (DC), monohydroxy fatty acids or hydroxy acyl carnitines (2OH, 3OH, 16OH), and branched-chain fatty acids (CH3). 3-CMPFP, 3-carboxy-4-methyl-5-pentyl-2-furanpropionate; CAR, carnitine. The terms 22:3* and 22:5* denote omega-6 polyunsaturated fatty acids
Fig. 4
Fig. 4
Non-lipid metabolic pathways that are altered by UGT KO. A. Enrichment analysis of each subclass of metabolites for the overall (O), male (M) and female (F) analyses. Bubble size represents the enrichment score for each UGT KO group. B–D. Relative abundance of significantly altered representative metabolites in each KO group. Results were consistent when limited to postmenopausal women (Supplementary Table 2.1). Boxes represent interquartile range, the median (horizontal bar), and mean (+). Whiskers depict minimum and maximum values. Ref: reference group. *P < 0.05, **P < 0.01, ***P < 0.001
Fig. 5
Fig. 5
Association of UGT2B17 KO divergent metabolites with the most common metabolic diseases and chronic conditions. A. Number of metabolites per subpathway significantly associated with diseases. CVD, cardiovascular diseases. B. Odds ratio (OR) and 95% confidence interval (CI) for the core metabolites commonly associated with obesity, hypertension and diabetes. 3α-diol-G, 5α-androstan-3α,17β-diol-17-glucuronide; 11β-ADT-G, 11β-hydroxyandrosterone glucuronide; PC (P-16:0/18:2), 1-(1-enyl-palmitoyl)-2-linoleoyl-glycerophosphocholine (P-16:0/18:2); 3MG carnitine, 3-methylglutarylcarnitine. Associations were significant (Padj<0.05) in a model adjusted for age, smoking and alcohol consumption. The overall analysis was also adjusted for sex. C. Significant associations (Padj<0.05) between the core metabolites and biomarkers related to obesity, diabetes and hypertension. BMI, body mass index; WC, waist circumference; A1C, hemoglobin A1c; HDL, high-density lipoprotein; TGL, triglycerides; DBP, diastolic blood pressure; SBP, systolic blood pressure
Fig. 6
Fig. 6
Metabolomic profile of UGT2B28 KO is associated with chronic diseases. A. Number of metabolites per subpathway significantly associated with each disease. B–F. Odds ratio (OR) and 95% confidence interval (CI) for metabolites associated with obesity, hypertension, diabetes, cardiovascular diseases and arthritis. 3β-cholestenoate, 3β-hydroxy-5-cholestenoate; Cys-glutathione-SS, cysteine-glutathione disulfide; 2-HPAA, 2-hydroxyphenylacetate; N-lactoyl-Leu, N-lactoyl-leucine; N-lactoyl-Phe, N-lactoyl-phenylalanine; N-lactoyl-Tyr, N-lactoyl-tyrosine. Associations were significant (Padj<0.05) in a model adjusted for age, smoking and alcohol consumption, and for sex for the overall analysis. In UGT2B28 KO females, after adjusting for these covariates as well as menopausal status and history of HRT use, all metabolites associated with obesity, diabetes, and X-23,644 in arthritis remained significant (Padj<0.05)
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