A Genome-wide Association Study Discovers 46 Loci of the Human Metabolome in the Hispanic Community Health Study/Study of Latinos.

Variation in levels of the human metabolome reflect changes in homeostasis, providing a window into health and disease. The genetic impact on circulating metabolites in Hispanics, a population with high cardiometabolic disease burden, is largely unknown. We conducted genome-wide association analyses on 640 circulating metabolites in 3,926 Hispanic Community Health Study/Study of Latinos participants. The estimated heritability for 640 metabolites ranged between 0%-54% with a median at 2.5%. We discovered 46 variant-metabolite pairs (p value < 1.2 × 10-10, minor allele frequency ≥ 1%, proportion of variance explained [PEV] mean = 3.4%, PEVrange = 1%-22%) with generalized effects in two population-based studies and confirmed 301 known locus-metabolite associations. Half of the identified variants with generalized effect were located in genes, including five nonsynonymous variants. We identified co-localization with the expression quantitative trait loci at 105 discovered and 151 known loci-metabolites sets. rs5855544, upstream of SLC51A, was associated with higher levels of three steroid sulfates and co-localized with expression levels of SLC51A in several tissues. Mendelian randomization (MR) analysis identified several metabolites associated with coronary heart disease (CHD) and type 2 diabetes. For example, two variants located in or near CYP4F2 (rs2108622 and rs79400241, respectively), involved in vitamin E metabolism, were associated with the levels of octadecanedioate and vitamin E metabolites (gamma-CEHC and gamma-CEHC glucuronide); MR analysis showed that genetically high levels of these metabolites were associated with lower odds of CHD. Our findings document the genetic architecture of circulating metabolites in an underrepresented Hispanic/Latino community, shedding light on disease etiology.

Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies.

OBJECTIVE: Tryptophan can be catabolised to various metabolites through host kynurenine and microbial indole pathways. We aimed to examine relationships of host and microbial tryptophan metabolites with incident type 2 diabetes (T2D), host genetics, diet and gut microbiota. METHOD: We analysed associations between circulating levels of 11 tryptophan metabolites and incident T2D in 9180 participants of diverse racial/ethnic backgrounds from five cohorts. We examined host genome-wide variants, dietary intake and gut microbiome associated with these metabolites. RESULTS: Tryptophan, four kynurenine-pathway metabolites (kynurenine, kynurenate, xanthurenate and quinolinate) and indolelactate were positively associated with T2D risk, while indolepropionate was inversely associated with T2D risk. We identified multiple host genetic variants, dietary factors, gut bacteria and their potential interplay associated with these T2D-relaetd metabolites. Intakes of fibre-rich foods, but not protein/tryptophan-rich foods, were the dietary factors most strongly associated with tryptophan metabolites. The fibre-indolepropionate association was partially explained by indolepropionate-associated gut bacteria, mostly fibre-using Firmicutes. We identified a novel association between a host functional LCT variant (determining lactase persistence) and serum indolepropionate, which might be related to a host gene-diet interaction on gut Bifidobacterium, a probiotic bacterium significantly associated with indolepropionate independent of other fibre-related bacteria. Higher milk intake was associated with higher levels of gut Bifidobacterium and serum indolepropionate only among genetically lactase non-persistent individuals. CONCLUSION: Higher milk intake among lactase non-persistent individuals, and higher fibre intake were associated with a favourable profile of circulating tryptophan metabolites for T2D, potentially through the host-microbial cross-talk shifting tryptophan metabolism toward gut microbial indolepropionate production.

Exome sequence association study of levels and longitudinal change of cardiovascular risk factor phenotypes in European Americans and African Americans from the Atherosclerosis Risk in Communities Study.

Cardiovascular disease (CVD) is responsible for 31% of all deaths worldwide. Among CVD risk factors are age, race, increased systolic blood pressure (BP), and dyslipidemia. Both BP and blood lipids levels change with age, with a dose-dependent relationship between the cumulative exposure to hyperlipidemia and the risk of CVD. We performed an exome sequence association study using longitudinal data with up to 7805 European Americans (EAs) and 3171 African Americans (AAs) from the Atherosclerosis Risk in Communities (ARIC) study. We assessed associations of common (minor allele frequency > 5%) nonsynonymous and splice-site variants and gene-based sets of rare variants with levels and with longitudinal change of seven CVD risk factor phenotypes (BP traits: systolic BP, diastolic BP, pulse pressure; lipids traits: triglycerides, total cholesterol, high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C]). Furthermore, we investigated the relationship of the identified variants and genes with select CVD endpoints. We identified two novel genes: DCLK3 associated with the change of HDL-C levels in AAs and RAB7L1 associated with the change of LDL-C levels in EAs. RAB7L1 is further associated with an increased risk of heart failure in ARIC EAs. Investigation of the contribution of genetic factors to the longitudinal change of CVD risk factor phenotypes promotes our understanding of the etiology of CVD outcomes, stressing the importance of incorporating the longitudinal structure of the cohort data in future analyses.

Unraveling the functional role of the orphan solute carrier, SLC22A24 in the transport of steroid conjugates through metabolomic and genome-wide association studies.

Variation in steroid hormone levels has wide implications for health and disease. The genes encoding the proteins involved in steroid disposition represent key determinants of interindividual variation in steroid levels and ultimately, their effects. Beginning with metabolomic data from genome-wide association studies (GWAS), we observed that genetic variants in the orphan transporter, SLC22A24 were significantly associated with levels of androsterone glucuronide and etiocholanolone glucuronide (sentinel SNPs p-value <1x10-30). In cells over-expressing human or various mammalian orthologs of SLC22A24, we showed that steroid conjugates and bile acids were substrates of the transporter. Phylogenetic, genomic, and transcriptomic analyses suggested that SLC22A24 has a specialized role in the kidney and appears to function in the reabsorption of organic anions, and in particular, anionic steroids. Phenome-wide analysis showed that functional variants of SLC22A24 are associated with human disease such as cardiovascular diseases and acne, which have been linked to dysregulated steroid metabolism. Collectively, these functional genomic studies reveal a previously uncharacterized protein involved in steroid homeostasis, opening up new possibilities for SLC22A24 as a pharmacological target for regulating steroid levels.

Genome-wide association study of serum metabolites in the African American Study of Kidney Disease and Hypertension.

The genome-wide association study (GWAS) is a powerful means to study genetic determinants of disease traits and generate insights into disease pathophysiology. To date, few GWAS of circulating metabolite levels have been performed in African Americans with chronic kidney disease. Hypothesizing that novel genetic-metabolite associations may be identified in a unique population of African Americans with a lower glomerular filtration rate (GFR), we conducted a GWAS of 652 serum metabolites in 619 participants (mean measured glomerular filtration rate 45 mL/min/1.73m2) in the African American Study of Kidney Disease and Hypertension, a clinical trial of blood pressure lowering and antihypertensive medication in African Americans with chronic kidney disease. We identified 42 significant variant metabolite associations. Twenty associations had been previously identified in published GWAS, and eleven novel associations were replicated in a separate cohort of 818 African Americans with genetic and metabolomic data from the Atherosclerosis Risk in Communities Study. The replicated novel variant-metabolite associations comprised eight metabolites and eleven distinct genomic loci. Nine of the replicated associations represented clear enzyme-metabolite interactions, with high expression in the kidneys as well as the liver. Three loci (ACY1, ACY3, and NAT8) were associated with a common pool of metabolites, acetylated amino acids, but with different individual affinities. Thus, extensive metabolite profiling in an African American population with chronic kidney disease aided identification of novel genome-wide metabolite associations, providing clues about substrate specificity and the key roles of enzymes in modulating systemic levels of metabolites.

Practical Approaches for Whole-Genome Sequence Analysis of Heart- and Blood-Related Traits.

Whole-genome sequencing (WGS) allows for a comprehensive view of the sequence of the human genome. We present and apply integrated methodologic steps for interrogating WGS data to characterize the genetic architecture of 10 heart- and blood-related traits in a sample of 1,860 African Americans. In order to evaluate the contribution of regulatory and non-protein coding regions of the genome, we conducted aggregate tests of rare variation across the entire genomic landscape using a sliding window, complemented by an annotation-based assessment of the genome using predefined regulatory elements and within the first intron of all genes. These tests were performed treating all variants equally as well as with individual variants weighted by a measure of predicted functional consequence. Significant findings were assessed in 1,705 individuals of European ancestry. After these steps, we identified and replicated components of the genomic landscape significantly associated with heart- and blood-related traits. For two traits, lipoprotein(a) levels and neutrophil count, aggregate tests of low-frequency and rare variation were significantly associated across multiple motifs. For a third trait, cardiac troponin T, investigation of regulatory domains identified a locus on chromosome 9. These practical approaches for WGS analysis led to the identification of informative genomic regions and also showed that defined non-coding regions, such as first introns of genes and regulatory domains, are associated with important risk factor phenotypes. This study illustrates the tractable nature of WGS data and outlines an approach for characterizing the genetic architecture of complex traits.

Whole-genome sequencing study of serum peptide levels: the Atherosclerosis Risk in Communities study.

Oligopeptides are important markers of protein metabolism, as they are cleaved from larger polypeptides and proteins. Genetic association studies may help elucidate their origin and function. In 1,552 European Americans and 1,872 African Americans of the Atherosclerosis Risk in Communities study, we performed whole-genome and whole-exome sequencing and measured serum levels of 25 peptides. Common variants (minor allele frequency > 5%) were analysed individually. We grouped low-frequency variants (minor allele frequency ≤ 5%) by a genome-wide sliding window using region-based aggregate tests. Furthermore, low-frequency regulatory variants were grouped by gene, as were functional coding variants. All analyses were performed separately in each ancestry group and then meta-analysed. We identified 22 common variant associations with peptide levels (P-value < 4.2 × 10-10), including 16 novel gene-peptide pairs. Notably, variants in kinin-kallikrein genes KNG1, F12, KLKB1, and ACE were associated with several different peptides. Variants in KLKB1 and ACE were associated with a fragment of complement component 3f. Both common variants and low-frequency coding variants in CPN1 were associated with a fibrinogen cleavage peptide. Four sliding windows were significantly associated with peptide levels (P-value < 4.2 × 10-10). Our results highlight the importance of the kinin-kallikrein system in the regulation of serum peptide levels, strengthen the evidence for a broad link between the kinin-kallikrein and complement systems, and suggest a role of CPN1 in the conversion of fibrinogen to fibrin.

Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations.

Circulating metabolite levels may reflect the state of the human organism in health and disease, however, the genetic architecture of metabolites is not fully understood. We have performed a whole-genome sequencing association analysis of both common and rare variants in up to 11,840 multi-ethnic participants from five studies with up to 1666 circulating metabolites. We have discovered 1985 novel variant-metabolite associations, and validated 761 locus-metabolite associations reported previously. Seventy-nine novel variant-metabolite associations have been replicated, including three genetic loci located on the X chromosome that have demonstrated its involvement in metabolic regulation. Gene-based analysis have provided further support for seven metabolite-replicated loci pairs and their biologically plausible genes. Among those novel replicated variant-metabolite pairs, follow-up analyses have revealed that 26 metabolites have colocalized with 21 tissues, seven metabolite-disease outcome associations have been putatively causal, and 7 metabolites might be regulated by plasma protein levels. Our results have depicted the genetic contribution to circulating metabolite levels, providing additional insights into understanding human disease.

Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups.

We assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare "clumping-and-thresholding" (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals.

A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood.

In a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called "PRSsum", forming the HTN-PRS. The HTN-PRS is associated with both prevalent and incident hypertension at 4-6 years of follow up. This association is further confirmed in age-stratified analysis. In an independent biobank of 40,201 individuals, the HTN-PRS is confirmed to be predictive of increased risk for coronary artery disease, ischemic stroke, type 2 diabetes, and chronic kidney disease.

The Implementation Science for Genomic Health Translation (INSIGHT) Study in Epilepsy: Protocol for a Learning Health Care System.

BACKGROUND: Genomic medicine is poised to improve care for common complex diseases such as epilepsy, but additional clinical informatics and implementation science research is needed for it to become a part of the standard of care. Epilepsy is an exemplary complex neurological disorder for which DNA diagnostics have shown to be advantageous for patient care. OBJECTIVE: We designed the Implementation Science for Genomic Health Translation (INSIGHT) study to leverage the fact that both the clinic and testing laboratory control the development and customization of their respective electronic health records and clinical reporting platforms. Through INSIGHT, we can rapidly prototype and benchmark novel approaches to incorporating clinical genomics into patient care. Of particular interest are clinical decision support tools that take advantage of domain knowledge from clinical genomics and can be rapidly adjusted based on feedback from clinicians. METHODS: Building on previously developed evidence and infrastructure components, our model includes the following: establishment of an intervention-ready genomic knowledge base for patient care, creation of a health informatics platform and linking it to a clinical genomics reporting system, and scaling and evaluation of INSIGHT following established implementation science principles. RESULTS: INSIGHT was approved by the Institutional Review Board at the University of Texas Health Science Center at Houston on May 15, 2020, and is designed as a 2-year proof-of-concept study beginning in December 2021. By design, 120 patients from the Texas Comprehensive Epilepsy Program are to be enrolled to test the INSIGHT workflow. Initial results are expected in the first half of 2023. CONCLUSIONS: INSIGHT's domain-specific, practical but generalizable approach may help catalyze a pathway to accelerate translation of genomic knowledge into impactful interventions in patient care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/25576.

Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals.

Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to ~1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency ≤ 0.01) variant BP associations (P < 5 × 10-8), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were ~8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.

Trans-ethnic association study of blood pressure determinants in over 750,000 individuals.

In this trans-ethnic multi-omic study, we reinterpret the genetic architecture of blood pressure to identify genes, tissues, phenomes and medication contexts of blood pressure homeostasis. We discovered 208 novel common blood pressure SNPs and 53 rare variants in genome-wide association studies of systolic, diastolic and pulse pressure in up to 776,078 participants from the Million Veteran Program (MVP) and collaborating studies, with analysis of the blood pressure clinical phenome in MVP. Our transcriptome-wide association study detected 4,043 blood pressure associations with genetically predicted gene expression of 840 genes in 45 tissues, and mouse renal single-cell RNA sequencing identified upregulated blood pressure genes in kidney tubule cells.

Correction: DeltaNp63alpha-Mediated Induction of Epidermal Growth Factor Receptor Promotes Pancreatic Cancer Cell Growth and Chemoresistance.

[This corrects the article DOI: 10.1371/journal.pone.0026815.].

Sequence-Based Analysis of Lipid-Related Metabolites in a Multiethnic Study.

Small molecule lipid-related metabolites are important components of fatty acid and steroid metabolism-two important contributors to human health. This study investigated the extent to which rare and common genetic variants spanning the human genome influence the lipid-related metabolome. Sequence data from 1552 European-Americans (EA) and 1872 African-Americans (AA) were analyzed to examine the impact of common and rare variants on the levels of 102 circulating lipid-related metabolites measured by a combination of chromatography and mass spectroscopy. We conducted single variant tests [minor allele frequency (MAF) > 5%, statistical significance P-value ≤ 2.45 × 10-10] and tests aggregating rare variants (MAF ≤ 5%) across multiple genomic motifs, such as coding regions and regulatory domains, and sliding windows. Multiethnic meta-analyses detected 53 lipid-related metabolites-locus pairs, which were inspected for evidence of consistent signal between the two ethnic groups. Thirty-eight lipid-related metabolite-genomic region associations were consistent across ethnicities, among which seven were novel. The regions contain genes that are related to metabolite transport (SLC10A1) and metabolism (SCD, FDX1, UGT2B15, and FADS2). Six of the seven novel findings lie in expression quantitative trait loci affecting the expression levels of 14 surrounding genes in multiple tissues. Imputed expression levels of 10 of the affected genes were associated with four corresponding lipid-related traits in at least one tissue. Our findings offer valuable insight into circulating lipid-related metabolite regulation in a multiethnic population.

Remnant-Like Particle Cholesterol, Low-Density Lipoprotein Triglycerides, and Incident Cardiovascular Disease.

BACKGROUND: Hypertriglyceridemia is associated with increased remnant-like particle cholesterol (RLP-C) and triglycerides in low-density lipoprotein (LDL-TG). Recent studies have focused on atherogenicity of RLP-C, with few data on LDL-TG. OBJECTIVES: The aim of this study was to examine associations of RLP-C and LDL-TG with incident cardiovascular disease (CVD) events and genetic variants in the ARIC (Atherosclerosis Risk In Communities) study. METHODS: Fasting plasma RLP-C and LDL-TG levels were measured in 9,334 men and women without prevalent CVD. Participants were followed for incident CVD events (coronary heart disease and ischemic stroke) for up to 16 years. Associations between LDL-TG and RLP-C levels and genetic variants were assessed by whole-exome sequencing using single-variant analysis for common variants and gene-based burden tests for rare variants; both an unbiased and a candidate gene approach were explored. RESULTS: RLP-C and LDL-TG levels were correlated with triglyceride levels (r = 0.85 and r = 0.64, p < 0.0001). In minimally adjusted analyses, RLP-C and LDL-TG were associated with CVD risk, but in models adjusted for traditional risk factors including lipids, only LDL-TG was associated with incident CHD (hazard ratio: 1.28; 95% confidence interval: 1.10 to 1.50) and stroke (hazard ratio: 1.47; 95% confidence interval: 1.13 to 1.92). A common APOE variant, rs7412, had the strongest association with LDL-TG and RLP-C (p < 5 × 10-8). CONCLUSIONS: RLP-C and LDL-TG levels were predictive of CVD and associated with APOE variants. LDL-TG may represent a marker of dysfunctional remnant lipoprotein metabolism associated with increased CVD risk. Further research is needed to determine whether LDL-TG plays a causal role in CVD and may be a target for therapy.

Genetic Variants in SGLT1, Glucose Tolerance, and Cardiometabolic Risk.

BACKGROUND: Loss-of-function mutations in the SGLT1 (sodium/glucose co-transporter-1) gene result in a rare glucose/galactose malabsorption disorder and neonatal death if untreated. In the general population, variants related to intestinal glucose absorption remain uncharacterized. OBJECTIVES: The goal of this study was to identify functional SGLT1 gene variants and characterize their clinical consequences. METHODS: Whole exome sequencing was performed in the ARIC (Atherosclerosis Risk in Communities) study participants enrolled from 4 U.S. communities. The association of functional, nonsynonymous substitutions in SGLT1 with 2-h oral glucose tolerance test results was determined. Variants related to impaired glucose tolerance were studied, and Mendelian randomization analysis of cardiometabolic outcomes was performed. RESULTS: Among 5,687 European-American subjects (mean age 54 ± 6 years; 47% male), those who carried a haplotype of 3 missense mutations (frequency of 6.7%)-Asn51Ser, Ala411Thr, and His615Gln-had lower 2-h glucose and odds of impaired glucose tolerance than noncarriers (ß-coefficient: -8.0; 95% confidence interval [CI]: -12.7 to -3.3; OR: 0.71; 95% CI: 0.59 to 0.86, respectively). The association of the haplotype with oral glucose tolerance test results was consistent in a replication sample of 2,791 African-American subjects (ß = -16.3; 95% CI: -36.6 to 4.1; OR: 0.39; 95% CI: 0.17 to 0.91) and an external European-Finnish population sample of 6,784 subjects (ß = -3.2; 95% CI: -6.4 to -0.02; OR: 0.81; 95% CI: 0.68 to 0.98). Using a Mendelian randomization approach in the index cohort, the estimated 25-year effect of a reduction of 20 mg/dl in 2-h glucose via SGLT1 inhibition would be reduced prevalent obesity (OR: 0.43; 95% CI: 0.23 to 0.63), incident diabetes (hazard ratio [HR]: 0.58; 95% CI: 0.35 to 0.81), heart failure (HR: 0.53; 95% CI: 0.24 to 0.83), and death (HR: 0.66; 95% CI: 0.42 to 0.90). CONCLUSIONS: Functionally damaging missense variants in SGLT1 protect from diet-induced hyperglycemia in multiple populations. Reduced intestinal glucose uptake may protect from long-term cardiometabolic outcomes, providing support for therapies that target SGLT1 function to prevent and treat metabolic conditions.

Whole genome sequence analysis of serum amino acid levels.

BACKGROUND: Blood levels of amino acids are important biomarkers of disease and are influenced by synthesis, protein degradation, and gene-environment interactions. Whole genome sequence analysis of amino acid levels may establish a paradigm for analyzing quantitative risk factors. RESULTS: In a discovery cohort of 1872 African Americans and a replication cohort of 1552 European Americans we sequenced exons and whole genomes and measured serum levels of 70 amino acids. Rare and low-frequency variants (minor allele frequency ≤5%) were analyzed by three types of aggregating motifs defined by gene exons, regulatory regions, or genome-wide sliding windows. Common variants (minor allele frequency >5%) were analyzed individually. Over all four analysis strategies, 14 gene-amino acid associations were identified and replicated. The 14 loci accounted for an average of 1.8% of the variance in amino acid levels, which ranged from 0.4 to 9.7%. Among the identified locus-amino acid pairs, four are novel and six have been reported to underlie known Mendelian conditions. These results suggest that there may be substantial genetic effects on amino acid levels in the general population that may underlie inborn errors of metabolism. We also identify a predicted promoter variant in AGA (the gene that encodes aspartylglucosaminidase) that is significantly associated with asparagine levels, with an effect that is independent of any observed coding variants. CONCLUSIONS: These data provide insights into genetic influences on circulating amino acid levels by integrating -omic technologies in a multi-ethnic population. The results also help establish a paradigm for whole genome sequence analysis of quantitative traits.