Identification and validation of CRLF1 and NRG1 as immune-related signatures in hypertrophic scar.

BACKGROUND: Hypertrophic scar (HTS) is a prevalent chronic inflammatory skin disorder characterized by abnormal proliferation and extracellular matrix deposition and the precise mechanisms underlying HTS remain elusive. This study aimed to identify and validate potential immune-related genes associated with hypertrophic scar formation. METHODS: Skin samples from normal (n = 12) and hypertrophic scar tissues (n = 12) were subjected to RNA-seq analysis. Differentially expressed genes (DEGs) and significant modular genes in Weighted gene Co-expression Network Analysis (WGCNA) were identified. Subsequently, functional enrichment analysis was performed on the intersecting genes. Additionally, eight immune-related genes were matched from the ImmPort database. Validation of NRG1 and CRLF1 was carried out using an external cohort (GSE136906). Furthermore, the association between these two genes and immune cells was assessed by Spearman correlation analysis. Finally, RNA was extracted from normal and hypertrophic scar samples, and RT-qPCR, Immunohistochemistry staining and Western Blot were employed to validate the expression of characteristic genes. RESULTS: A total of 940 DEGs were identified between HTS and normal samples, and 288 key module genes were uncovered via WGCNA. Enrichment analysis in key module revealed involvement in many immune-related pathways, such as Th17 cell differentiation, antigen processing and presentation and B cell receptor signaling pathway. The eight immune-related genes (IFI30, NR2F2, NRG1, ESM1, NFATC2, CRLF1, COLEC12 and IL6) were identified by matching from the ImmPort database. Notably, we observed that activated mast cell positively correlated with CRLF1 expression, while CD8 T cells exhibited a positive correlation with NRG1. The expression of NRG1 and CRLF1 was further validated in clinical samples. CONCLUSION: In this study, two key immune-related genes (CRLF1 and NRG1) were identified as characteristic genes associated with HTS. These findings provide valuable insights into the immune-related mechanisms underlying hypertrophic scar formation.

Metabolomic profiles during early childhood and risk of food allergies and asthma in multiethnic children from a prospective birth cohort.

BACKGROUND: There are increasing numbers of metabolomic studies in food allergy (FA) and asthma, which, however, are predominantly limited by cross-sectional designs, small sample size, and being conducted in European populations. OBJECTIVE: We sought to identify metabolites unique to and shared by children with FA and/or asthma in a racially diverse prospective birth cohort, the Boston Birth Cohort. METHODS: Mass spectrometry-based untargeted metabolomic profiling was performed using venous plasma collected in early childhood (n = 811). FA was diagnosed according to clinical symptoms consistent with an acute hypersensitivity reaction at food ingestion and food specific-IgE > 0.35 kU/L. Asthma was defined on the basis of physician diagnosis. Generalized estimating equations were applied to analyze metabolomic associations with FA and asthma, adjusting for potential confounders. RESULTS: During a mean ± standard deviation follow-up of 11.8 ± 5.2 years from birth, 78 children developed FA and 171 developed asthma. Androgenic and pregnenolone steroids were significantly associated with a lower risk of FA, especially for egg allergy. N,N,N-trimethyl-5-aminovalerate (odds ratio [OR] = 0.65, 95% confidence interval [CI] = 0.48-0.87), and 1-oleoyl-2-arachidonoyl-sn-glycero-3-phosphoinositol (OR = 0.77; 95% CI = 0.66-0.90) were inversely associated with FA risk. Orotidine (OR = 4.73; 95% CI = 2.2-10.2) and 4-cholesten-3-one (OR = 0.52; 95% CI = 0.35-0.77) were the top 2 metabolites associated with risk of asthma, although they had no association with FA. In comparison, children with both FA and asthma exhibited an altered metabolomic profile that aligned with that of FA, including altered levels of lipids and steroids. CONCLUSION: In this US multiethnic prospective birth cohort, unique and shared alterations in plasma metabolites during early childhood were associated with risk of developing FA and/or asthma. These findings await further validation.

Analytical challenges in omics research on asthma and allergy: A National Institute of Allergy and Infectious Diseases workshop.

Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes the major points and conclusions from this NIAID workshop. As a group, the investigators underscored the imperatives for rigorous analytic frameworks, integration of different omics data types, cross-disciplinary interaction, strategies for overcoming current limitations, and the overarching goal to improve scientific understanding and care of asthma and allergic diseases.

Discovery and validation of plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance and diabetes progression or regression among Puerto Rican adults.

AIMS/HYPOTHESIS: Many studies have examined the relationship between plasma metabolites and type 2 diabetes progression, but few have explored saliva and multi-fluid metabolites. METHODS: We used LC/MS to measure plasma (n=1051) and saliva (n=635) metabolites among Puerto Rican adults from the San Juan Overweight Adults Longitudinal Study. We used elastic net regression to identify plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting baseline HOMA-IR in a training set (n=509) and validated these scores in a testing set (n=340). We used multivariable Cox proportional hazards models to estimate HRs for the association of baseline metabolomic scores predicting insulin resistance with incident type 2 diabetes (n=54) and prediabetes (characterised by impaired glucose tolerance, impaired fasting glucose and/or high HbA1c) (n=130) at 3 years, along with regression from prediabetes to normoglycaemia (n=122), adjusting for traditional diabetes-related risk factors. RESULTS: Plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance included highly weighted metabolites from fructose, tyrosine, lipid and amino acid metabolism. Each SD increase in the plasma (HR 1.99 [95% CI 1.18, 3.38]; p=0.01) and multi-fluid (1.80 [1.06, 3.07]; p=0.03) metabolomic scores was associated with higher risk of type 2 diabetes. The saliva metabolomic score was associated with incident prediabetes (1.48 [1.17, 1.86]; p=0.001). All three metabolomic scores were significantly associated with lower likelihood of regressing from prediabetes to normoglycaemia in models adjusting for adiposity (HRs 0.72 for plasma, 0.78 for saliva and 0.72 for multi-fluid), but associations were attenuated when adjusting for lipid and glycaemic measures. CONCLUSIONS/INTERPRETATION: The plasma metabolomic score predicting insulin resistance was more strongly associated with incident type 2 diabetes than the saliva metabolomic score. Only the saliva metabolomic score was associated with incident prediabetes.

The metabolic potential of inflammatory and insulinaemic dietary patterns and risk of type 2 diabetes.

AIMS/HYPOTHESIS: Diets with higher inflammatory and insulinaemic potential have been associated with an increased risk of type 2 diabetes. However, it remains unknown whether plasma metabolomic profiles related to proinflammatory/hyperinsulinaemic diets and to inflammatory/insulin biomarkers are associated with type 2 diabetes risk. METHODS: We analysed 6840 participants from the Nurses' Health Study and Health Professionals Follow-up Study to identify the plasma metabolome related to empirical dietary inflammatory pattern (EDIP), empirical dietary index for hyperinsulinemia (EDIH), four circulating inflammatory biomarkers and C-peptide. Dietary intakes were assessed using validated food frequency questionnaires. Plasma metabolomic profiling was conducted by LC-MS/MS. Metabolomic signatures were derived using elastic net regression. Multivariable Cox regression was used to examine associations of the metabolomic profiles with type 2 diabetes risk. RESULTS: We identified 27 metabolites commonly associated with both EDIP and inflammatory biomarker z score and 21 commonly associated with both EDIH and C-peptide. Higher metabolomic dietary inflammatory potential (MDIP), reflecting higher metabolic potential of both an inflammatory dietary pattern and circulating inflammatory biomarkers, was associated with higher type 2 diabetes risk. The HR comparing highest vs lowest quartiles of MDIP was 3.26 (95% CI 2.39, 4.44). We observed a strong positive association with type 2 diabetes risk for the metabolomic signature associated with EDIP-only (HR 3.75; 95% CI 2.71, 5.17) or inflammatory biomarkers-only (HR 4.07; 95% CI 2.91, 5.69). In addition, higher metabolomic dietary index for hyperinsulinaemia (MDIH), reflecting higher metabolic potential of both an insulinaemic dietary pattern and circulating C-peptide, was associated with greater type 2 diabetes risk (HR 3.00; 95% CI 2.22, 4.06); further associations with type 2 diabetes were HR 2.79 (95% CI 2.07, 3.76) for EDIH-only signature and HR 3.89 (95% CI 2.82, 5.35) for C-peptide-only signature. The diet scores were significantly associated with risk, although adjustment for the corresponding metabolomic signature scores attenuated the associations with type 2 diabetes, these remained significant. CONCLUSIONS/INTERPRETATION: The metabolomic signatures reflecting proinflammatory or hyperinsulinaemic diets and related biomarkers were positively associated with type 2 diabetes risk, supporting that these dietary patterns may influence type 2 diabetes risk via the regulation of metabolism.

Type 2 diabetes metabolomics score and risk of progression to type 2 diabetes among women with a history of gestational diabetes mellitus.

BACKGROUND: Several metabolites are individually related to incident type 2 diabetes (T2D) risk. We prospectively evaluated a novel T2D-metabolite pattern with a risk of progression to T2D among high-risk women with a history of gestational diabetes mellitus (GDM). METHODS: The longitudinal Nurses' Health Study II cohort enroled 116,429 women in 1989 and collected blood samples from 1996 to 1999. We profiled plasma metabolites in 175 incident T2D cases and 175 age-matched controls, all with a history of GDM before the blood draw. We derived a metabolomics score from 21 metabolites previously associated with incident T2D in the published literature by scoring according to the participants' quintile (1-5 points) of each metabolite. We modelled the T2D metabolomics score categorically in quartiles and continuously per 1 standard deviation (SD) with the risk of incident T2D using conditional logistic regression models adjusting for body mass index at the blood draw, and other established T2D risk factors. RESULTS: The percentage of women progressing to T2D ranged from 10% in the bottom T2D metabolomics score quartile to 78% in the highest score quartile. Adjusting for established T2D risk factors, women in the highest quartile had more than a 20-fold greater diabetes risk than women in the lowest quartile (odds ratios [OR] = 23.1 [95% CI = 8.6, 62.1]; p for trend<0.001). The continuous T2D metabolomics score was strongly and positively associated with incident T2D (adjusted OR = 2.7 per SD [95% CI = 1.9, 3.7], p < 0.0001). CONCLUSIONS: A pattern of plasma metabolites among high-risk women is associated with a markedly elevated risk of progression to T2D later in life.

Metabolite Profiles of Plant-Based Diets and Cardiometabolic Risk in the Mediators of Atherosclerosis in South Asians Living in America Study.

BACKGROUND: Healthy plant-based diets have been associated with lower risk of type 2 diabetes (T2D). Metabolomics can be leveraged to identify potential pathways through which diet influences disease risk. OBJECTIVES: This study aimed to identify profiles of serum metabolites reflective of plant-based diets of varying quality and examine associations with cardiometabolic risk and T2D. METHODS: We included data from 687 participants of the Mediators of Atherosclerosis in South Asians Living in America (MASALA) cohort. An overall plant-based diet index (PDI), healthy PDI (hPDI), and unhealthy PDI (uPDI) were estimated from food frequency questionnaires. Serum metabolites were assayed using ultraperformance liquid chromatography mass spectrometry. Elastic net regression was used to identify sets of metabolites predictive of each diet index, and metabolite profile scores were calculated as the weighted sum of the selected metabolites. Cross-sectional associations between metabolite profile scores and cardiometabolic measures and prospective associations with incident T2D were evaluated with multivariable-adjusted linear and logistic regressions. RESULTS: Metabolite profiles for PDI, hPDI, and uPDI consisted of n = 51, 55, and 45 metabolites, respectively. Metabolites strongly positively correlated with diet indices included phosphatidylcholine (16:0/18:3) for PDI, phosphatidylethanolamine (20:1/20:4) and pantothenate for hPDI, and lysophosphatidylglycerol (18:2/0:0), proline, and lauric acid for uPDI. Higher metabolite profile scores for PDI and hPDI were associated with lower glycemia and lipids measures, whereas a higher uPDI metabolite score was associated with higher triglycerides and lower low density lipoprotein cholesterol and high density lipoprotein cholesterol. A higher metabolite score for hPDI was additionally associated with lower adiposity measures, higher liver fat attenuation, higher adiponectin, lower odds of overweight (odds ratio [OR]: 0.64; 95% confidence interval [CI]: 0.51, 0.81) and obesity (OR: 0.59; 95% CI: 0.48, 0.74), and lower odds of incident T2D (OR: 0.66; 95% CI: 0.45, 0.97). CONCLUSIONS: Metabolite profiles of different plant-based diets were identified. Metabolite profiles of overall and healthy plant-based diets were associated with favorable cardiometabolic risk profiles.

Associations between cord blood acetaminophen biomarkers and childhood asthma with and without allergic comorbidities.

BACKGROUND: Previous studies have linked prenatal acetaminophen use to increased asthma risk in children. However, none have explored this association while differentiating between asthma cases with and without other allergic conditions or by employing objective biomarkers to assess acetaminophen exposure. OBJECTIVE: To evaluate whether the detection of acetaminophen biomarkers in cord blood is associated with the subgroups of asthma both with and without allergic comorbidities in children. METHODS: Acetaminophen biomarkers, including unchanged acetaminophen and acetaminophen glucuronide, were measured in neonatal cord blood samples from the Boston Birth Cohort. Asthma subgroups were defined on the basis of physician diagnoses of asthma and other allergic conditions (atopic dermatitis and allergic rhinitis). Multinomial regressions were used to evaluate the associations between acetaminophen biomarkers and asthma subgroups, adjusting for multiple confounders, including potential indications for maternal acetaminophen use such as maternal fever. RESULTS: The study included 142 children with asthma and at least 1 other allergic condition, 55 children with asthma but no other allergic condition, and 613 children free of asthma. Detection of acetaminophen in cord blood, reflecting maternal exposure to acetaminophen shortly before delivery, was associated with 3.73 times the odds of developing asthma without allergic comorbidities (95% CI: 1.79-7.80, P = .0004). In contrast, the detection of acetaminophen in cord blood was not associated with an elevated risk of asthma with allergic comorbidities. Analysis of acetaminophen glucuronide yielded consistent results. CONCLUSION: In a prospective birth cohort, cord blood acetaminophen biomarkers were associated with an increased risk of childhood asthma without allergic comorbidities, but were not associated with childhood asthma with allergic comorbidities.

Exploring the association between type 2 diabetes and fecal incontinence in american adults: insights from a large cross-sectional study.

BACKGROUND: The relationship between fecal incontinence (FI) and type 2 diabetes (T2D) has been well recognized, but a comprehensive understanding of this relationship is lacking, taking into account demographic factors and lifestyle variables. METHODS: Using a cross-sectional approach, 13,510 adults aged 20 years and older were identified from the 2005-2010 National Health and Nutrition Examination Survey. Multivariate logistic regression models were used to calculate the adjusted odds ratios (ORs), and further subgroup analyses and propensity score analysis were performed to ensure stable results. RESULTS: Among 13,510 adults, 11.2% had T2D, and 8.8% had FI. We found a strong T2D-FI link (OR: 1.30; 95% CI: 1.09-1.54, P < 0.001), even after adjusting for covariates. Age > 45 was a critical factor, with a stronger T2D-FI association. Sedentary behavior (OR: 1.41; 95% CI: 1.15-1.73) in T2D patients were associated with FI. CONCLUSIONS: Our study highlights the significant T2D-FI link in US adults, especially in older T2D patients. Lifestyle changes may reduce FI risk. More research is needed for causality and mechanisms.

Maternal arsenic exposure modifies associations between arsenic, folate and arsenic metabolism gene variants, and spina bifida risk: A case‒control study in Bangladesh.

BACKGROUND: Spina bifida is a type of neural tube defect (NTD); NTDs are developmental malformations of the spinal cord that result from failure of neural tube closure during embryogenesis and are likely caused by interactions between genetic and environmental factors. Arsenic induces NTDs in animal models, and studies demonstrate that mice with genetic defects related to folate metabolism are more susceptible to arsenic's effects. We sought to determine whether 25 single-nucleotide polymorphisms (SNPs) in genes involved in folate and arsenic metabolism modified the associations between maternal arsenic exposure and risk of spina bifida (a common NTD) among a hospital-based case-control study population in Bangladesh. METHODS: We used data from 262 mothers and 220 infants who participated in a case‒control study at the National Institutes of Neurosciences & Hospital and Dhaka Shishu Hospital in Dhaka, Bangladesh. Neurosurgeons assessed infants using physical examinations, review of imaging, and we collected histories using questionnaires. We assessed arsenic from mothers' toenails using inductively coupled plasma mass spectrometry (ICP-MS), and we genotyped participants using the Illumina Global Screening Array v1.0. We chose candidate genes and SNPs through a review of the literature. We assessed SNP-environment interactions using interaction terms and stratified models, and we assessed gene-environment interactions using interaction sequence/SNP-set kernel association tests (iSKAT). RESULTS: The median toenail arsenic concentration was 0.42 µg/g (interquartile range [IQR]: 0.27-0.86) among mothers of cases and 0.47 µg/g (IQR: 0.30-0.97) among mothers of controls. We found an two SNPs in the infants' AS3MT gene (rs11191454 and rs7085104) and one SNP in mothers' DNMT1 gene (rs2228611) were associated with increased odds of spina bifida in the setting of high arsenic exposure (rs11191454, OR 3.01, 95% CI: 1.28-7.09; rs7085104, OR 2.33, 95% CI: 1.20-4.and rs2228611, OR 2.11, 95% CI: 1.11-4.01), along with significant SNP-arsenic interactions. iSKAT analyses revealed significant interactions between mothers' toenail concentrations and infants' AS3MT and MTR genes (p = 0.02), and mothers' CBS gene (p = 0.05). CONCLUSIONS: Our results support the hypothesis that arsenic increases spina bifida risk via interactions with folate and arsenic metabolic pathways and suggests that individuals in the population who have certain genetic polymorphisms in genes involved with arsenic and folate metabolism may be more susceptible than others to the arsenic teratogenicity.

Arsenic modifies the effect of folic acid in spina bifida prevention, a large hospital-based case-control study in Bangladesh.

BACKGROUND: Spina bifida, a developmental malformation of the spinal cord, is associated with high rates of mortality and disability. Although folic acid-based preventive strategies have been successful in reducing rates of spina bifida, some areas continue to be at higher risk because of chemical exposures. Bangladesh has high arsenic exposures through contaminated drinking water and high rates of spina bifida. This study examines the relationships between mother's arsenic exposure, folic acid, and spina bifida risk in Bangladesh. METHODS: We conducted a hospital-based case-control study at the National Institute of Neurosciences & Hospital (NINS&H) in Dhaka, Bangladesh, between December 2016 and December 2022. Cases were infants under age one year with spina bifida and further classified by a neurosurgeon and imaging. Controls were drawn from children seen at NINS&H and nearby Dhaka Shishu Hospital. Mothers reported folic acid use during pregnancy, and we assessed folate status with serum assays. Arsenic exposure was estimated in drinking water using graphite furnace atomic absorption spectrophotometry (GF-AAS) and in toenails using inductively coupled plasma mass spectrometry (ICP-MS). We used logistic regression to examine the associations between arsenic and spina bifida. We used stratified models to examine the associations between folic acid and spina bifida at different levels of arsenic exposure. RESULTS: We evaluated data from 294 cases of spina bifida and 163 controls. We did not find a main effect of mother's arsenic exposure on spina bifida risk. However, in stratified analyses, folic acid use was associated with lower odds of spina bifida (adjusted odds ratio [OR]: 0.50, 95% confidence interval [CI]: 0.25-1.00, p = 0.05) among women with toenail arsenic concentrations below the median value of 0.46 µg/g, and no association was seen among mothers with toenail arsenic concentrations higher than 0.46 µg/g (adjusted OR: 1.09, 95% CI: 0.52-2.29, p = 0.82). CONCLUSIONS: Mother's arsenic exposure modified the protective association of folic acid with spina bifida. Increased surveillance and additional preventive strategies, such as folic acid fortification and reduction of arsenic, are needed in areas of high arsenic exposure.

The MIND diet, brain transcriptomic alterations, and dementia.

INTRODUCTION: Dietary patterns are associated with dementia risk, but the underlying molecular mechanisms are largely unknown. METHODS: We used RNA sequencing data from post mortem prefrontal cortex tissue and annual cognitive evaluations from 1204 participants in the Religious Orders Study and Memory and Aging Project. We identified a transcriptomic profile correlated with the MIND diet (Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay) among 482 individuals who completed ante mortem food frequency questionnaires; and examined its associations with cognitive health in the remaining 722 participants. RESULTS: We identified a transcriptomic profile, consisting of 50 genes, correlated with the MIND diet score (p = 0.001). Each standard deviation increase in the transcriptomic profile score was associated with a slower annual rate of decline in global cognition (ß = 0.011, p = 0.003) and lower odds of dementia (odds ratio = 0.76, p = 0.0002). Expressions of several genes (including TCIM and IGSF5) appeared to mediate the association between MIND diet and dementia. DISCUSSION: A brain transcriptomic profile for healthy diets revealed novel genes potentially associated with cognitive health. HIGHLIGHTS: Why healthy dietary patterns are associated with lower dementia risk are unknown. We integrated dietary, brain transcriptomic, and cognitive data in older adults. Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay (MIND) diet intake is correlated with a specific brain transcriptomic profile. This brain transcriptomic profile score is associated with better cognitive health. More data are needed to elucidate the causality and functionality of identified genes.

Regulation of vascular remodeling by immune microenvironment after the establishment of autologous arteriovenous fistula in ESRD patients.

Autogenous arteriovenous fistula (AVF) is the preferred dialysis access for receiving hemodialysis treatment in end-stage renal disease patients. After AVF is established, vascular remodeling occurs in order to adapt to hemodynamic changes. Uremia toxins, surgical injury, blood flow changes and other factors can induce inflammatory response, immune microenvironment changes, and play an important role in the maintenance of AVF vascular remodeling. This process involves the infiltration of pro-inflammatory and anti-inflammatory immune cells and the secretion of cytokines. Pro-inflammatory and anti-inflammatory immune cells include neutrophil (NEUT), dendritic cell (DC), T lymphocyte, macrophage (Mφ), etc. This article reviews the latest research progress and focuses on the role of immune microenvironment changes in vascular remodeling of AVF, in order to provide a new theoretical basis for the prevention and treatment of AVF failure.

Gestational DNA methylation age as a marker for fetal development and birth outcomes: findings from the Boston Birth Cohort.

BACKGROUND: Gestational DNA methylation age (GAmAge) has been developed and validated in European ancestry samples. Its applicability to other ethnicities and associations with fetal stress and newborn phenotypes such as inflammation markers are still to be determined. This study aims to examine the applicability of GAmAge developed from cord blood samples of European decedents to a racially diverse birth cohort, and associations with newborn phenotypes. METHODS: GAmAge based on 176 CpGs (Haftorn GAmAge) was calculated for 940 children from a US predominantly urban, low-income, multiethnic birth cohort. Cord blood DNA methylation was profiled by Illumina EPIC array. Newborn phenotypes included anthropometric measurements and, for a subset of newborns (N = 194), twenty-seven cord blood inflammatory markers (sandwich immunoassays). RESULTS: GAmAge had a stronger correlation with GEAA in boys (r = 0.89, 95% confidence interval (CI) [0.87,0.91]) compared with girls (r = 0.83, 95% CI [0.80,0.86]), and was stronger among extremely preterm to very preterm babies (r = 0.91, 95% CI [0.81,0.96]), compared with moderate (r = 0.48, 95% CI [0.34,0.60]) and term babies (r = 0.58, 95% CI [0.53,0.63]). Among White newborns (N = 51), the correlation between GAmAge vs. GEAA was slightly stronger (r = 0.89, 95% CI [0.82,0.94]) compared with Black/African American newborns (N = 668; r = 0.87, 95% CI [0.85,0.89]) or Hispanic (N = 221; r = 0.79, 95% CI [0.74,0.84]). Adjusting for GEAA and sex, GAmAge was associated with anthropometric measurements, cord blood brain-derived neurotrophic factor (BDNF), and monocyte chemoattractant protein-1 (MCP-1) (p < 0.05 for all). CONCLUSIONS: GAmAge estimation is robust across different populations and racial/ethnic subgroups. GAmAge may be utilized as a proxy for GEAA and for assessing fetus development, indicated by inflammatory state and birth outcomes.

Epigenetic Clock at Birth and Childhood Blood Pressure Trajectory: A Prospective Birth Cohort Study.

BACKGROUND: The impact of methylation gestational age (GAmAge; a biomarker of fetal maturity) at birth on childhood blood pressure (BP) trajectories is unknown. METHODS: This cohort study included 500 boys and 440 girls with data on cord blood DNA methylation and BP at 3 to 15 years of age. Systolic BP (SBP) and diastolic BP percentiles were calculated based on clinical guidelines. Time-series K-means clustering identified 4 distinct SBP and diastolic BP percentile trajectories: high-steady, high-decrease, normal-increase, and normal-steady. GAmAge was estimated using an existing pediatric epigenetic clock. Extrinsic age acceleration was calculated as residuals of associations between GAmAge and chronological gestational age. Intrinsic age acceleration was calculated using the same method adjusting for cord blood cell compositions. RESULTS: Extrinsic age acceleration and intrinsic age acceleration were inversely associated with repeated measures of BP percentiles. Significant inverse associations were observed between extrinsic age acceleration and SBP percentiles in boys (ß=-2.02; P=0.02) but not in girls (ß=-0.49; P=0.58). Both extrinsic age acceleration and intrinsic age acceleration were inversely associated with SBP percentiles in girls born preterm (<37 weeks; ßEAA=-2.95; ßIAA=-3.00; P<0.05). Compared with the normal-steady SBP trajectory, significant inverse associations were observed between intrinsic age acceleration and high-steady, high-decrease, and normal-increase SBP trajectories in boys (odds ratio, 0.73-0.81; P<0.03), and significant positive associations were observed for high-decrease and normal-increase SBP trajectories in girls (odds ratio, 1.26-1.38; P<0.01). Significant sex differences were observed (Psex-interaction<2×10-16). CONCLUSIONS: GAmAge acceleration at birth was inversely associated with child BP, and such association was more pronounced in boys than in girls. Our findings may shed new light on the developmental origins of high BP and sex differences in cardiovascular risk.

MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data.

Leveraging data from multiple ancestries can greatly improve fine-mapping power due to differences in linkage disequilibrium and allele frequencies. We propose MultiSuSiE, an extension of the sum of single effects model (SuSiE) to multiple ancestries that allows causal effect sizes to vary across ancestries based on a multivariate normal prior informed by empirical data. We evaluated MultiSuSiE via simulations and analyses of 14 quantitative traits leveraging whole-genome sequencing data in 47k African-ancestry and 94k European-ancestry individuals from All of Us. In simulations, MultiSuSiE applied to Afr47k+Eur47k was well-calibrated and attained higher power than SuSiE applied to Eur94k; interestingly, higher causal variant PIPs in Afr47k compared to Eur47k were entirely explained by differences in the extent of LD quantified by LD 4th moments. Compared to very recently proposed multi-ancestry fine-mapping methods, MultiSuSiE attained higher power and/or much lower computational costs, making the analysis of large-scale All of Us data feasible. In real trait analyses, MultiSuSiE applied to Afr47k+Eur94k identified 579 fine-mapped variants with PIP > 0.5, and MultiSuSiE applied to Afr47k+Eur47k identified 44% more fine-mapped variants with PIP > 0.5 than SuSiE applied to Eur94k. We validated MultiSuSiE results for real traits via functional enrichment of fine-mapped variants. We highlight several examples where MultiSuSiE implicates well-studied or biologically plausible fine-mapped variants that were not implicated by other methods.

Branched-Chain and Aromatic Amino Acids, Type 2 Diabetes, and Cardiometabolic Risk Factors among Puerto Rican Adults.

(1) Background: Branched-chain and aromatic amino acids (BCAAs/AAAs) have been considered as markers of type 2 diabetes (T2D); however, studies on associations between these metabolites and T2D and cardiometabolic traits in Hispanic populations are limited. The aim of this study was to examine the associations between baseline BCAAs (isoleucine, leucine, valine)/AAAs (phenylalanine, tyrosine) and prevalent and incident T2D, as well as baseline and longitudinal (2 year) changes in cardiometabolic traits (measures of glycemia, dyslipidemia, inflammation, and obesity) in two large cohorts of adults of Puerto Rican descent. (2) Methods: We included participants of the Boston Puerto Rican Health Study (BPRHS, n = 670) and San Juan Overweight Adult Longitudinal study (SOALS, n = 999) with available baseline metabolite and covariate data. T2D diagnosis was defined based on American Diabetes Association criteria. Multivariable logistic (for baseline T2D), Poisson (for incident T2D), and linear (for cardiometabolic traits) regression models were used; cohort-specific results were combined in the meta-analysis and adjusted for multiple comparisons. (3) Results: Higher baseline BCAAs were associated with higher odds of prevalent T2D (OR1SD BCAA score = 1.46, 95% CI: 1.34-1.59, p < 0.0001) and higher risk of incident T2D (IRR1SD BCAA score = 1.24, 95% CI: 1.13-1.37, p < 0.0001). In multivariable longitudinal analysis, higher leucine and valine concentrations were associated with 2-year increase in insulin (beta 1SD leucine = 0.37 mcU/mL, 95% CI: 0.11-0.63, p < 0.05; beta 1SD valine = 0.43 mcU/mL, 95% CI: 0.17-0.68, p < 0.01). Tyrosine was a significant predictor of incident T2D (IRR = 1.31, 95% CI: 1.09-1.58, p < 0.05), as well as 2 year increases in HOMA-IR (beta 1SD tyrosine = 0.13, 95% CI: 0.04-0.22, p < 0.05) and insulin concentrations (beta 1SD tyrosine = 0.37 mcU/mL, 95% CI: 0.12-0.61, p < 0.05). (4) Conclusions: Our results confirmed the associations between BCAAs and prevalent and incident T2D, as well as concurrent measures of glycemia, dyslipidemia, and obesity, previously reported in predominantly White and Asian populations. Baseline leucine, valine, and tyrosine were predictors of 2 year increases in insulin, whereas tyrosine was a significant predictor of deteriorating insulin resistance over time. Our study suggests that BCAAs and tyrosine could serve as early markers of future glycemic changes in Puerto Ricans.

Type 2 diabetes and its genetic susceptibility are associated with increased severity and mortality of COVID-19 in UK Biobank.

Type 2 diabetes (T2D) is known as one of the important risk factors for the severity and mortality of COVID-19. Here, we evaluate the impact of T2D and its genetic susceptibility on the severity and mortality of COVID-19, using 459,119 individuals in UK Biobank. Utilizing the polygenic risk scores (PRS) for T2D, we identified a significant association between T2D or T2D PRS, and COVID-19 severity. We further discovered the efficacy of vaccination and the pivotal role of T2D-related genetics in the pathogenesis of severe COVID-19. Moreover, we found that individuals with T2D or those in the high T2D PRS group had a significantly increased mortality rate. We also observed that the mortality rate for SARS-CoV-2-infected patients was approximately 2 to 7 times higher than for those not infected, depending on the time of infection. These findings emphasize the potential of T2D PRS in estimating the severity and mortality of COVID-19.