Integrating Multi-Omics with environmental data for precision health: A novel analytic framework and case study on prenatal mercury induced childhood fatty liver disease.

BACKGROUND: Precision Health aims to revolutionize disease prevention by leveraging information across multiple omic datasets (multi-omics). However, existing methods generally do not consider personalized environmental risk factors (e.g., environmental pollutants). OBJECTIVE: To develop and apply a precision health framework which combines multiomic integration (including early, intermediate, and late integration, representing sequential stages at which omics layers are combined for modeling) with mediation approaches (including high-dimensional mediation to identify biomarkers, mediation with latent factors to identify pathways, and integrated/quasi-mediation to identify high-risk subpopulations) to identify novel biomarkers of prenatal mercury induced metabolic dysfunction-associated fatty liver disease (MAFLD), elucidate molecular pathways linking prenatal mercury with MAFLD in children, and identify high-risk children based on integrated exposure and multiomics data. METHODS: This prospective cohort study used data from 420 mother-child pairs from the Human Early Life Exposome (HELIX) project. Mercury concentrations were determined in maternal or cord blood from pregnancy. Cytokeratin 18 (CK-18; a MAFLD biomarker) and five omics layers (DNA Methylation, gene transcription, microRNA, proteins, and metabolites) were measured in blood in childhood (age 6-10 years). RESULTS: Each standard deviation increase in prenatal mercury was associated with a 0.11 [95% confidence interval: 0.02-0.21] standard deviation increase in CK-18. High dimensional mediation analysis identified 10 biomarkers linking prenatal mercury and CK-18, including six CpG sites and four transcripts. Mediation with latent factors identified molecular pathways linking mercury and MAFLD, including altered cytokine signaling and hepatic stellate cell activation. Integrated/quasi-mediation identified high risk subgroups of children based on unique combinations of exposure levels, omics profiles (driven by epigenetic markers), and MAFLD. CONCLUSIONS: Prenatal mercury exposure is associated with elevated liver enzymes in childhood, likely through alterations in DNA methylation and gene expression. Our analytic framework can be applied across many different fields and serve as a resource to help guide future precision health investigations.

PFHpA alters lipid metabolism and increases the risk of metabolic dysfunction-associated steatotic liver disease in youth-a translational research framework.

To address the growing epidemic of liver disease, particularly in pediatric populations, it is crucial to identify modifiable risk factors for the development and progression of metabolic dysfunction-associated steatotic liver disease (MASLD). Per- and polyfluoroalkyl substances (PFAS) are persistent ubiquitous chemicals and have emerged as potential risk factors for liver damage. However, their impact on the etiology and severity of MASLD remains largely unexplored in humans. This study aims to bridge the gap between human and in vitro studies to understand how exposure to perfluoroheptanoic acid (PFHpA), one of the emerging PFAS replacements which accumulates in high concentrations in the liver, contributes to MASLD risk and progression. First, we showed that PFHpA plasma concentrations were significantly associated with increased risk of MASLD in obese adolescents. Further, we examined the impact of PFHpA on hepatic metabolism using 3D human liver spheroids and single-cell transcriptomics to identify major hepatic pathways affected by PFHpA. Next, we integrated the in vivo and in vitro multi-omics datasets with a novel statistical approach which identified signatures of proteins and metabolites associated with MASLD development triggered by PFHpA exposure. In addition to characterizing the contribution of PFHpA to MASLD progression, our study provides a novel strategy to identify individuals at high risk of PFHpA-induced MASLD and develop early intervention strategies. Notably, our analysis revealed that the proteomic signature exhibited a stronger correlation between both PFHpA exposure and MASLD risk compared to the metabolomic signature. While establishing a clear connection between PFHpA exposure and MASLD progression in humans, our study delved into the molecular mechanisms through which PFHpA disrupts liver metabolism. Our in vitro findings revealed that PFHpA primarily impacts lipid metabolism, leading to a notable increase of lipid accumulation in human hepatocytes after PFHpA exposure. Among the pathways involved in lipid metabolism in hepatocytes, regulation of lipid metabolism by PPAR-a showed a remarkable activation. Moreover, the translational research framework we developed by integrating human and in vitro data provided us biomarkers to identify individuals at a high risk of MASLD due to PFHpA exposure. Our framework can inform policies on PFAS-induced liver disease and identify potential targets for prevention and treatment strategies.

Early Prostate Cancer Deaths Among Men With Higher vs Lower Genetic Risk.

Importance: Prostate cancer, a leading cause of cancer death among men, urgently requires new prevention strategies, which may involve targeting men with an underlying genetic susceptibility. Objective: To explore differences in risk of early prostate cancer death among men with higher vs lower genetic risk to inform prevention efforts. Design, Setting, and Participants: This cohort study used a combined analysis of genotyped men without prostate cancer at inclusion and with lifestyle data in 2 prospective cohort studies in Sweden and the US, the Malmö Diet and Cancer Study (MDCS) and the Health Professionals Follow-Up Study (HPFS), followed up from 1991 to 2019. Data were analyzed between April 2023 and April 2024. Exposures: Men were categorized according to modifiable lifestyle behaviors and genetic risk. A polygenic risk score above the median or a family history of cancer defined men at higher genetic risk (67% of the study population); the remaining men were categorized as being at lower genetic risk. Main Outcomes and Measures: Prostate cancer death analyzed using time-to-event analysis estimating hazard ratios (HR), absolute risks, and preventable deaths by age. Results: Among the 19 607 men included for analysis, the median (IQR) age at inclusion was 59.0 (53.0-64.7) years (MDCS) and 65.1 (58.0-71.8) years (HPFS). During follow-up, 107 early (by age 75 years) and 337 late (after age 75 years) prostate cancer deaths were observed. Compared with men at lower genetic risk, men at higher genetic risk had increased rates of both early (HR, 3.26; 95% CI, 1.82-5.84) and late (HR, 2.26; 95% CI, 1.70-3.01) prostate cancer death, and higher lifetime risks of prostate cancer death (3.1% vs 1.3% [MDCS] and 2.3% vs 0.6% [HPFS]). Men at higher genetic risk accounted for 94 of 107 early prostate cancer deaths (88%), of which 36% (95% CI, 12%-60%) were estimated to be preventable through adherence to behaviors associated with a healthy lifestyle (not smoking, healthy weight, high physical activity, and a healthy diet). Conclusions and Relevance: In this 20-year follow-up study, men with a genetic predisposition accounted for the vast majority of early prostate cancer deaths, of which one-third were estimated to be preventable. This suggests that men at increased genetic risk should be targeted in prostate cancer prevention strategies.

Transcriptome-wide association analysis identifies candidate susceptibility genes for prostate-specific antigen levels in men without prostate cancer.

Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility for prostate cancer (PCa) screening. Using genome-wide association study (GWAS) summary statistics from 95,768 PCa-free men, we conducted a transcriptome-wide association study (TWAS) to examine impacts of genetically predicted gene expression on PSA. Analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10 × 10-6) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61 × 10-6) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses identified 155 statistically significantly (p < 0.05/22,249 = 2.25 × 10-6) genes. Out of 173 unique PSA-associated genes across analyses, we replicated 151 (87.3%) in a TWAS of 209,318 PCa-free individuals from the Million Veteran Program. Based on conditional analyses, we found 20 genes (11 single tissue, nine cross-tissue) that were associated with PSA levels in the discovery TWAS that were not attributable to a lead variant from a GWAS. Ten of these 20 genes replicated, and two of the replicated genes had colocalization probability of >0.5: CCNA2 and HIST1H2BN. Six of the 20 identified genes are not known to impact PCa risk. Fine-mapping based on whole blood and prostate tissue revealed five protein-coding genes with evidence of causal relationships with PSA levels. Of these five genes, four exhibited evidence of colocalization and one was conditionally independent of previous GWAS findings. These results yield hypotheses that should be further explored to improve understanding of genetic factors underlying PSA levels.

Hierarchical joint analysis of marginal summary statistics-Part II: High-dimensional instrumental analysis of omics data.

Instrumental variable (IV) analysis has been widely applied in epidemiology to infer causal relationships using observational data. Genetic variants can also be viewed as valid IVs in Mendelian randomization and transcriptome-wide association studies. However, most multivariate IV approaches cannot scale to high-throughput experimental data. Here, we leverage the flexibility of our previous work, a hierarchical model that jointly analyzes marginal summary statistics (hJAM), to a scalable framework (SHA-JAM) that can be applied to a large number of intermediates and a large number of correlated genetic variants-situations often encountered in modern experiments leveraging omic technologies. SHA-JAM aims to estimate the conditional effect for high-dimensional risk factors on an outcome by incorporating estimates from association analyses of single-nucleotide polymorphism (SNP)-intermediate or SNP-gene expression as prior information in a hierarchical model. Results from extensive simulation studies demonstrate that SHA-JAM yields a higher area under the receiver operating characteristics curve (AUC), a lower mean-squared error of the estimates, and a much faster computation speed, compared to an existing approach for similar analyses. In two applied examples for prostate cancer, we investigated metabolite and transcriptome associations, respectively, using summary statistics from a GWAS for prostate cancer with more than 140,000 men and high dimensional publicly available summary data for metabolites and transcriptomes.

Genome-wide interaction study of dietary intake of fibre, fruits, and vegetables with risk of colorectal cancer.

BACKGROUND: Consumption of fibre, fruits and vegetables have been linked with lower colorectal cancer (CRC) risk. A genome-wide gene-environment (G × E) analysis was performed to test whether genetic variants modify these associations. METHODS: A pooled sample of 45 studies including up to 69,734 participants (cases: 29,896; controls: 39,838) of European ancestry were included. To identify G × E interactions, we used the traditional 1--degree-of-freedom (DF) G × E test and to improve power a 2-step procedure and a 3DF joint test that investigates the association between a genetic variant and dietary exposure, CRC risk and G × E interaction simultaneously. FINDINGS: The 3-DF joint test revealed two significant loci with p-value <5 × 10-8. Rs4730274 close to the SLC26A3 gene showed an association with fibre (p-value: 2.4 × 10-3) and G × fibre interaction with CRC (OR per quartile of fibre increase = 0.87, 0.80, and 0.75 for CC, TC, and TT genotype, respectively; G × E p-value: 1.8 × 10-7). Rs1620977 in the NEGR1 gene showed an association with fruit intake (p-value: 1.0 × 10-8) and G × fruit interaction with CRC (OR per quartile of fruit increase = 0.75, 0.65, and 0.56 for AA, AG, and GG genotype, respectively; G × E -p-value: 0.029). INTERPRETATION: We identified 2 loci associated with fibre and fruit intake that also modify the association of these dietary factors with CRC risk. Potential mechanisms include chronic inflammatory intestinal disorders, and gut function. However, further studies are needed for mechanistic validation and replication of findings. FUNDING: National Institutes of Health, National Cancer Institute. Full funding details for the individual consortia are provided in acknowledgments.

Two genome-wide interaction loci modify the association of nonsteroidal anti-inflammatory drugs with colorectal cancer.

Regular, long-term aspirin use may act synergistically with genetic variants, particularly those in mechanistically relevant pathways, to confer a protective effect on colorectal cancer (CRC) risk. We leveraged pooled data from 52 clinical trial, cohort, and case-control studies that included 30,806 CRC cases and 41,861 controls of European ancestry to conduct a genome-wide interaction scan between regular aspirin/nonsteroidal anti-inflammatory drug (NSAID) use and imputed genetic variants. After adjusting for multiple comparisons, we identified statistically significant interactions between regular aspirin/NSAID use and variants in 6q24.1 (top hit rs72833769), which has evidence of influencing expression of TBC1D7 (a subunit of the TSC1-TSC2 complex, a key regulator of MTOR activity), and variants in 5p13.1 (top hit rs350047), which is associated with expression of PTGER4 (codes a cell surface receptor directly involved in the mode of action of aspirin). Genetic variants with functional impact may modulate the chemopreventive effect of regular aspirin use, and our study identifies putative previously unidentified targets for additional mechanistic interrogation.

Genetic risk impacts the association of menopausal hormone therapy with colorectal cancer risk.

BACKGROUND: Menopausal hormone therapy (MHT), a common treatment to relieve symptoms of menopause, is associated with a lower risk of colorectal cancer (CRC). To inform CRC risk prediction and MHT risk-benefit assessment, we aimed to evaluate the joint association of a polygenic risk score (PRS) for CRC and MHT on CRC risk. METHODS: We used data from 28,486 postmenopausal women (11,519 cases and 16,967 controls) of European descent. A PRS based on 141 CRC-associated genetic variants was modeled as a categorical variable in quartiles. Multiplicative interaction between PRS and MHT use was evaluated using logistic regression. Additive interaction was measured using the relative excess risk due to interaction (RERI). 30-year cumulative risks of CRC for 50-year-old women according to MHT use and PRS were calculated. RESULTS: The reduction in odds ratios by MHT use was larger in women within the highest quartile of PRS compared to that in women within the lowest quartile of PRS (p-value = 2.7 × 10-8). At the highest quartile of PRS, the 30-year CRC risk was statistically significantly lower for women taking any MHT than for women not taking any MHT, 3.7% (3.3%-4.0%) vs 6.1% (5.7%-6.5%) (difference 2.4%, P-value = 1.83 × 10-14); these differences were also statistically significant but smaller in magnitude in the lowest PRS quartile, 1.6% (1.4%-1.8%) vs 2.2% (1.9%-2.4%) (difference 0.6%, P-value = 1.01 × 10-3), indicating 4 times greater reduction in absolute risk associated with any MHT use in the highest compared to the lowest quartile of genetic CRC risk. CONCLUSIONS: MHT use has a greater impact on the reduction of CRC risk for women at higher genetic risk. These findings have implications for the development of risk prediction models for CRC and potentially for the consideration of genetic information in the risk-benefit assessment of MHT use.

Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes.

Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.

Hierarchical joint analysis of marginal summary statistics-Part I: Multipopulation fine mapping and credible set construction.

Recent advancement in genome-wide association studies (GWAS) comes from not only increasingly larger sample sizes but also the shift in focus towards underrepresented populations. Multipopulation GWAS increase power to detect novel risk variants and improve fine-mapping resolution by leveraging evidence and differences in linkage disequilibrium (LD) from diverse populations. Here, we expand upon our previous approach for single-population fine-mapping through Joint Analysis of Marginal SNP Effects (JAM) to a multipopulation analysis (mJAM). Under the assumption that true causal variants are common across studies, we implement a hierarchical model framework that conditions on multiple SNPs while explicitly incorporating the different LD structures across populations. The mJAM framework can be used to first select index variants using the mJAM likelihood with different feature selection approaches. In addition, we present a novel approach leveraging the ideas of mediation to construct credible sets for these index variants. Construction of such credible sets can be performed given any existing index variants. We illustrate the implementation of the mJAM likelihood through two implementations: mJAM-SuSiE (a Bayesian approach) and mJAM-Forward selection. Through simulation studies based on realistic effect sizes and levels of LD, we demonstrated that mJAM performs well for constructing concise credible sets that include the underlying causal variants. In real data examples taken from the most recent multipopulation prostate cancer GWAS, we showed several practical advantages of mJAM over other existing multipopulation methods.

Changes in plasma concentrations of per- and Polyfluoroalkyl substances after bariatric surgery in adolescents from the Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) study.

Exposure to per- and poly-fluoroalkyl substances (PFAS) is ubiquitous due to their persistence in the environment and in humans. Extreme weight loss has been shown to influence concentrations of circulating persistent organic pollutants (POPs). Using data from the multi-center perspective Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) cohort, we investigated changes in plasma-PFAS in adolescents after bariatric surgery. Adolescents (Mean age = 17.1 years, SD = 1.5 years) undergoing bariatric surgery were enrolled in the Teen-LABS study. Plasma-PFAS were measured at the time of surgery and then 6-, 12-, and 36 months post-surgery. Linear mixed effect models were used to evaluate longitudinal changes in plasma-PFAS after the time of bariatric surgery. This study included 214 adolescents with severe obesity who had available longitudinal measures of plasma-PFAS and underwent bariatric surgery between 2007 and 2012. Underlying effects related to undergoing bariatric surgery were found to be associated with an initial increase or plateau in concentrations of circulating PFAS up to 6 months after surgery followed by a persistent decline in concentrations of 36 months (p < 0.001 for all plasma-PFAS). Bariatric surgery in adolescents was associated with a decline in circulating PFAS concentrations. Initially following bariatric surgery (0-6 months) concentrations were static followed by decline from 6 to 36 months following surgery. This may have large public health implications as PFAS are known to be associated with numerous metabolic related diseases and the significant reduction in circulating PFAS in individuals who have undergone bariatric surgery may be related to the improvement of such metabolic related diseases following bariatric surgery.

Exposure to per- and polyfluoroalkyl substances and high-throughput proteomics in Hispanic youth.

BACKGROUND: Strong epidemiological evidence shows positive associations between exposure to per- and polyfluoroalkyl substances (PFAS) and adverse cardiometabolic outcomes (e.g., diabetes, hypertension, and dyslipidemia). However, the underlying cardiometabolic-relevant biological activities of PFAS in humans remain largely unclear. AIM: We evaluated the associations of PFAS exposure with high-throughput proteomics in Hispanic youth. MATERIAL AND METHODS: We included 312 overweight/obese adolescents from the Study of Latino Adolescents at Risk (SOLAR) between 2001 and 2012, along with 137 young adults from the Metabolic and Asthma Incidence Research (Meta-AIR) between 2014 and 2018. Plasma PFAS (i.e., PFOS, PFOA, PFHxS, PFHpS, PFNA) were quantified using liquid-chromatography high-resolution mass spectrometry. Plasma proteins (n = 334) were measured utilizing the proximity extension assay using an Olink Explore Cardiometabolic Panel I. We conducted linear regression with covariate adjustment to identify PFAS-associated proteins. Ingenuity Pathway Analysis, protein-protein interaction network analysis, and protein annotation were used to investigate alterations in biological functions and protein clusters. RESULTS: Results after adjusting for multiple comparisons showed 13 significant PFAS-associated proteins in SOLAR and six in Meta-AIR, sharing similar functions in inflammation, immunity, and oxidative stress. In SOLAR, PFNA demonstrated significant positive associations with the largest number of proteins, including ACP5, CLEC1A, HMOX1, LRP11, MCAM, SPARCL1, and SSC5D. After considering the mixture effect of PFAS, only SSC5D remained significant. In Meta-AIR, PFAS mixtures showed positive associations with GDF15 and IL6. Exploratory analysis showed similar findings. Specifically, pathway analysis in SOLAR showed PFOA- and PFNA-associated activation of immune-related pathways, and PFNA-associated activation of inflammatory response. In Meta-AIR, PFHxS-associated activation of dendric cell maturation was found. Moreover, PFAS was associated with common protein clusters of immunoregulatory interactions and JAK-STAT signaling in both cohorts. CONCLUSION: PFAS was associated with broad alterations of the proteomic profiles linked to pro-inflammation and immunoregulation. The biological functions of these proteins provide insight into potential molecular mechanisms of PFAS toxicity.

Combining magnetic resonance imaging with a multi-ancestry polygenic risk score to improve identification of clinically significant prostate cancer.

Multi-parametric magnetic resonance imaging (mpMRI) has emerged as an important tool for identifying clinically significant prostate cancer. We examined if the addition of a 400-variant multi-ancestry polygenic risk score (PRS) to mpMRI has the potential to improve identification. Based on data from 24 617 men from the Mass General Brigham Biobank, we identified 1243 men who underwent mpMRI. Men in the top PRS quartile were more likely to have clinically significant prostate cancer (47.1% vs 28.6% in the bottom PRS quartile, adjusted relative proportion 1.72 [95% CI = 1.35 to 2.19]). Both among men with a positive and a negative mpMRI, men in the top PRS quartile had the highest frequency of clinically significant cancer. In a constructed scenario for selecting men to undergo biopsy, use of the PRS lowered the frequency of missed clinically significant cancers from 9.1% to 5.9%. Our study provides initial support for using the PRS to improve identification of potentially lethal prostate cancer.

Exposure to 4,4'-DDE in visceral adipose tissue and weight loss in adolescents from the Teen-LABS cohort.

OBJECTIVE: Dichlorodiphenyldichloroethylene (DDE), an obesogen accumulating in adipose tissue, is released into circulation with weight loss, although its impact is underexplored among adolescents. We tested the association using an integrative translational approach of epidemiological analysis among adolescents with obesity and in vitro measures exploring the impact of DDE on adipogenesis via preadipocytes. METHODS: We included 63 participants from the Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) cohort. We assessed 4,4'-DDE in visceral adipose tissue at surgery and BMI and waist circumference at surgery and 0.5, 1, 3, and 5 years after. We conducted longitudinal analysis to estimate the interaction on weight loss between DDE and time since surgery. In vitro analysis quantified adipogenic differentiation in commercial human preadipocytes exposed to 4,4'-DDE via fluorescent staining and imaging. RESULTS: A dose-response relationship was observed, with the low-exposure group having a greater reduction in BMI during the first year compared to higher-exposure groups and showing smaller regains compared to higher-exposure groups after the first year. In vitro analysis of preadipocytes treated with 4,4'-DDE during adipogenic differentiation for 12 days showed a concentration-dependent increase in lipid accumulation. CONCLUSIONS: DDE could contribute to weight trajectory among adolescents undergoing bariatric surgery, potentially mediated via promoted adipogenesis in preadipocytes.

Identification of Genes with Rare Loss of Function Variants Associated with Aggressive Prostate Cancer and Survival.

BACKGROUND: Prostate cancer (PrCa) is a substantial cause of mortality among men globally. Rare germline mutations in BRCA2 have been validated robustly as increasing risk of aggressive forms with a poorer prognosis; however, evidence remains less definitive for other genes. OBJECTIVE: To detect genes associated with PrCa aggressiveness, through a pooled analysis of rare variant sequencing data from six previously reported studies in the UK Genetic Prostate Cancer Study (UKGPCS). DESIGN, SETTING, AND PARTICIPANTS: We accumulated a cohort of 6805 PrCa cases, in which a set of ten candidate genes had been sequenced in all samples. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We examined the association between rare putative loss of function (pLOF) variants in each gene and aggressive classification (defined as any of death from PrCa, metastatic disease, stage T4, or both stage T3 and Gleason score ≥8). Secondary analyses examined staging phenotypes individually. Cox proportional hazards modelling and Kaplan-Meier survival analyses were used to further examine the relationship between mutation status and survival. RESULTS AND LIMITATIONS: We observed associations between PrCa aggressiveness and pLOF mutations in ATM, BRCA2, MSH2, and NBN (odds ratio = 2.67-18.9). These four genes and MLH1 were additionally associated with one or more secondary analysis phenotype. Carriers of germline mutations in these genes experienced shorter PrCa-specific survival (hazard ratio = 2.15, 95% confidence interval 1.79-2.59, p = 4 × 10-16) than noncarriers. CONCLUSIONS: This study provides further support that rare pLOF variants in specific genes are likely to increase aggressive PrCa risk and may help define the panel of informative genes for screening and treatment considerations. PATIENT SUMMARY: By combining data from several previous studies, we have been able to enhance knowledge regarding genes in which inherited mutations would be expected to increase the risk of more aggressive PrCa. This may, in the future, aid in the identification of men at an elevated risk of dying from PrCa.

Associations of dietary intake and longitudinal measures of per- and polyfluoroalkyl substances (PFAS) in predominantly Hispanic young Adults: A multicohort study.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are pollutants linked to adverse health effects. Diet is an important source of PFAS exposure, yet it is unknown how diet impacts longitudinal PFAS levels. OBJECTIVE: To determine if dietary intake and food sources were associated with changes in blood PFAS concentrations among Hispanic young adults at risk of metabolic diseases. METHODS: Predominantly Hispanic young adults from the Children's Health Study who underwent two visits (CHS; n = 123) and young adults from NHANES 2013-2018 who underwent one visit (n = 604) were included. Dietary data at baseline was collected using two 24-hour dietary recalls to measure individual foods and where foods were prepared/consumed (home/restaurant/fast-food). PFAS were measured in blood at both visits in CHS and cross-sectionally in NHANES. In CHS, multiple linear regression assessed associations of baseline diet with longitudinal PFAS; in NHANES, linear regression was used. RESULTS: In CHS, all PFAS except PFDA decreased across visits (all p < 0.05). In CHS, A 1-serving higher tea intake was associated with 24.8 %, 16.17 %, and 12.6 % higher PFHxS, PFHpS, and PFNA at follow-up, respectively (all p < 0.05). A 1-serving higher pork intake was associated with 13.4 % higher PFOA at follow-up (p < 0.05). Associations were similar in NHANES, including unsweetened tea, hot dogs, and processed meats. For food sources, in CHS each 200-gram increase in home-prepared food was associated with 0.90 % and 1.6 % lower PFOS at baseline and follow-up, respectively, and in NHANES was associated with 0.9 % lower PFDA (all p < 0.05). CONCLUSION: Results suggest that beverage consumption habits and food preparation are associated with differences in PFAS levels in young adults. This highlights the importance of diet in determining PFAS exposure and the necessity of public monitoring of foods and beverages for PFAS contamination.

Circulating microRNA expression and nonalcoholic fatty liver disease in adolescents with severe obesity.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases in children and adolescents. NAFLD ranges in severity from isolated hepatic steatosis to nonalcoholic steatohepatitis (NASH), wherein hepatocellular inflammation and/or fibrosis coexist with steatosis. Circulating microRNA (miRNA) levels have been suggested to be altered in NAFLD, but the extent to which miRNA are related to NAFLD features remains unknown. This analysis tested the hypothesis that plasma miRNAs are significantly associated with histological features of NAFLD in adolescents. AIM: To investigate the relationship between plasma miRNA expression and NAFLD features among adolescents with NAFLD. METHODS: This study included 81 adolescents diagnosed with NAFLD and 54 adolescents without NAFLD from the Teen-Longitudinal Assessment of Bariatric Surgery study. Intra-operative core liver biopsies were collected from participants and used to characterize histological features of NAFLD. Plasma samples were collected during surgery for miRNA profiling. A total of 843 plasma miRNAs were profiled using the HTG EdgeSeq platform. We examined associations of plasma miRNAs and NAFLD features using logistic regression after adjusting for age, sex, race, and other key covariates. Ingenuity Pathways Analysis was used to identify biological functions of miRNAs that were associated with multiple histological features of NAFLD. RESULTS: We identified 16 upregulated plasma miRNAs, including miR-193a-5p and miR-193b-5p, and 22 downregulated plasma miRNAs, including miR-1282 and miR-6734-5p, in adolescents with NAFLD. Moreover, 52, 16, 15, and 9 plasma miRNAs were associated with NASH, fibrosis, ballooning degeneration, and lobular inflammation, respectively. Collectively, 16 miRNAs were associated with two or more histological features of NAFLD. Among those miRNAs, miR-411-5p was downregulated in NASH, ballooning, and fibrosis, while miR-122-5p, miR-1343-5p, miR-193a-5p, miR-193b-5p, and miR-7845-5p were consistently and positively associated with all histological features of NAFLD. Pathway analysis revealed that most common pathways of miRNAs associated with multiple NAFLD features have been associated with tumor progression, while we also identified linkages between miR-122-5p and hepatitis C virus and between miR-199b-5p and chronic hepatitis B. CONCLUSION: Plasma miRNAs were associated with NAFLD features in adolescent with severe obesity. Larger studies with more heterogeneous NAFLD phenotypes are needed to evaluate miRNAs as potential biomarkers of NAFLD.

Proteomic and Metabolomic Signatures of Diet Quality in Young Adults.

The assessment of "omics" signatures may contribute to personalized medicine and precision nutrition. However, the existing literature is still limited in the homogeneity of participants' characteristics and in limited assessments of integrated omics layers. Our objective was to use post-prandial metabolomics and fasting proteomics to identify biological pathways and functions associated with diet quality in a population of primarily Hispanic young adults. We conducted protein and metabolite-wide association studies and functional pathway analyses to assess the relationships between a priori diet indices, Healthy Eating Index-2015 (HEI) and Dietary Approaches to Stop Hypertension (DASH) diets, and proteins (n = 346) and untargeted metabolites (n = 23,173), using data from the MetaAIR study (n = 154, 61% Hispanic). Analyses were performed for each diet quality index separately, adjusting for demographics and BMI. Five proteins (ACY1, ADH4, AGXT, GSTA1, F7) and six metabolites (undecylenic acid, betaine, hyodeoxycholic acid, stearidonic acid, iprovalicarb, pyracarbolid) were associated with both diets (p < 0.05), though none were significant after adjustment for multiple comparisons. Overlapping proteins are involved in lipid and amino acid metabolism and in hemostasis, while overlapping metabolites include amino acid derivatives, bile acids, fatty acids, and pesticides. Enriched biological pathways were involved in macronutrient metabolism, immune function, and oxidative stress. These findings in young Hispanic adults contribute to efforts to develop precision nutrition and medicine for diverse populations.

Excess pancreatic cancer risk due to smoking and modifying effect of quitting smoking: The Multiethnic Cohort Study.

PURPOSE: Risk factors for pancreatic cancer include racial/ethnic disparities and smoking. However, risk trajectories by smoking history and race/ethnicity are unknown. We examined the association of smoking with pancreatic cancer by race/ethnicity to generate age-specific incidence estimates by smoking history. METHODS: We modeled pancreatic cancer incidence by race/ethnicity, age, pack-years, and years-quit using an excess relative risk model for 182,011 Multiethnic Cohort participants. We tested heterogeneity of smoking variables and pancreatic cancer by race/ethnicity and predicted incidence by smoking history. RESULTS: We identified 1,831 incident pancreatic cancer cases over an average 19.3 years of follow-up. Associations of pack-years (p interaction by race/ethnicity = 0.41) and years-quit (p interaction = 0.83) with pancreatic cancer did not differ by race/ethnicity. Fifty pack-years smoked was associated with 91% increased risk (95% CI 54%, 127%) relative to never smokers in the combined sample. Every year quit corresponded to 9% decreased excess risk (95% CI 2%, 15%) from pack-years smoked. Differences in baseline pancreatic cancer risk across racial/ethnic groups (p < 0.001) translated to large differences in risk for smokers at older ages across racial/ethnic groups (65-122 cases per 100,000 at age 70). CONCLUSION: Smoking pack-years were positively associated with elevated pancreatic cancer risk. Predicted risk trajectories showed a high impact of smoking cessation at < 65 years. Although we did not identify significant heterogeneity in the association of pack-years or years quit with pancreatic cancer risk, current smoker risk varied greatly by race/ethnicity in later life due to large differences in baseline risk.

Postprandial Metabolite Profiles and Risk of Prediabetes in Young People: A Longitudinal Multicohort Study.

OBJECTIVE: Prediabetes in young people is an emerging epidemic that disproportionately impacts Hispanic populations. We aimed to develop a metabolite-based prediction model for prediabetes in young people with overweight/obesity at risk for type 2 diabetes. RESEARCH DESIGN AND METHODS: In independent, prospective cohorts of Hispanic youth (discovery; n = 143 without baseline prediabetes) and predominately Hispanic young adults (validation; n = 56 without baseline prediabetes), we assessed prediabetes via 2-h oral glucose tolerance tests. Baseline metabolite levels were measured in plasma from a 2-h postglucose challenge. In the discovery cohort, least absolute shrinkage and selection operator regression with a stability selection procedure was used to identify robust predictive metabolites for prediabetes. Predictive performance was evaluated in the discovery and validation cohorts using logistic regression. RESULTS: Two metabolites (allylphenol sulfate and caprylic acid) were found to predict prediabetes beyond known risk factors, including sex, BMI, age, ethnicity, fasting/2-h glucose, total cholesterol, and triglycerides. In the discovery cohort, the area under the receiver operator characteristic curve (AUC) of the model with metabolites and known risk factors was 0.80 (95% CI 0.72-0.87), which was higher than the risk factor-only model (AUC 0.63 [0.53-0.73]; P = 0.001). When the predictive models developed in the discovery cohort were applied to the replication cohort, the model with metabolites and risk factors predicted prediabetes more accurately (AUC 0.70 [95% CI 40.55-0.86]) than the same model without metabolites (AUC 0.62 [0.46-0.79]). CONCLUSIONS: Metabolite profiles may help improve prediabetes prediction compared with traditional risk factors. Findings suggest that medium-chain fatty acids and phytochemicals are early indicators of prediabetes in high-risk youth.