Gene expression profiling in elderly patients with familial hypercholesterolemia with and without coronary heart disease.

BACKGROUND AND AIMS: Elderly familial hypercholesterolemia (FH) patients are at high risk of coronary heart disease (CHD) due to high cholesterol burden and late onset of effective cholesterol-lowering therapies. A subset of these individuals remains free from any CHD event, indicating the potential presence of protective factors. Identifying possible cardioprotective gene expression profiles could contribute to our understanding of CHD prevention and future preventive treatment. Therefore, this study aimed to investigate gene expression profiles in elderly event-free FH patients. METHODS: Expression of 773 genes was analysed using the Nanostring Metabolic Pathways Panel, in peripheral blood mononuclear cells (PBMCs) from FH patients ≥65 years without CHD (FH event-free, n = 44) and with CHD (FH CHD, n = 39), and from healthy controls ≥70 years (n = 39). RESULTS: None of the genes were differentially expressed between FH patients with and without CHD after adjusting for multiple testing. However, at nominal p < 0.05, we found 36 (5%) differentially expressed genes (DEGs) between the two FH groups, mainly related to lipid metabolism (e.g. higher expression of ABCA1 and ABCG1 in FH event-free) and immune responses (e.g. lower expression of STAT1 and STAT3 in FH event-free). When comparing FH patients to controls, the event-free group had fewer DEGs than the CHD group; 147 (19%) and 219 (28%) DEGs, respectively. CONCLUSIONS: Elderly event-free FH patients displayed a different PBMC gene expression profile compared to FH patients with CHD. Differences in gene expression compared to healthy controls were more pronounced in the CHD group, indicating a less atherogenic gene expression profile in event-free individuals. Overall, identification of cardioprotective factors could lead to future therapeutic targets.

Inflammatory markers and frailty in home-dwelling elderly, a cross-sectional study.

BACKGROUND: Low-grade, chronic inflammation during ageing, ("inflammageing"), is suggested to be involved in the development of frailty in older age. However, studies on the association between frailty, using the frailty index definition, and inflammatory markers are limited. The aim of this study was to investigate the relationship between inflammatory markers and frailty index (FI) in older, home-dwelling adults. METHOD: Home-dwelling men and women aged ≥ 70 years old, living in South-East Norway were recruited and included in a cross-sectional study. The FI used in the current study was developed according to Rockwood's frailty index and included 38 variables, resulting in an FI score between 0 and 1 for each participant. Circulating inflammatory markers (IL-6, CRP, IGF-1, cystatin C, cathepsin S, and glycoprotein Acetyls) were analyzed from non-fasting blood samples using ELISA. Whole-genome PBMC transcriptomics was used to study the association between FI score and inflammation. RESULTS: The study population comprised 403 elderly (52% women), with a median age of 74 years and a mean BMI of 26.2 kg/m2. The mean FI score for the total group was 0.15 (range 0.005-0.56). The group was divided into a frail group (FI score ≥ 0.25) and non-frail group. After adjusting for BMI, age, sex, and smoking in the whole group, IL-6, cathepsin S, cystatin C, and Gp-acetyls remained significant associated to FI score (IL-6: 0.002, 95% CI: 0.001, 0.002, cathepsin S: 6.7e-06, 95% CI 2.44e-06, 0.00001, cystatin C: 0.004, 95% CI: 0.002, 0.006, Gp- Acetyls: 0.09, 95% CI: 0.05, 0.13, p < 0.01 for all), while CRP and IGF-1 were not (0.0003, 95% CI: -00001, 0.0007, p = 0.13, (-1.27e-06), 95% CI: (-0.0003), 0.0003, p = 0.99). There was a significant association between FI score and inflammatory markers, and FI score and monocyte-specific gene expression. CONCLUSIONS: We found an association between FI score and inflammatory markers, and between FI score and monocyte-specific gene expression among elderly subjects above 70 years of age. Whether inflammation is a cause or consequence of frailty and whether the progression of frailty can be attenuated by reducing inflammation remains to be clarified.

Dietary fat quality, plasma atherogenic lipoproteins, and atherosclerotic cardiovascular disease: An overview of the rationale for dietary recommendations for fat intake.

The scientific evidence supporting the current dietary recommendations for fat quality keeps accumulating; however, a paradoxical distrust has taken root among many researchers, clinicians, and in parts of the general public. One explanation for this distrust may relate to an incomplete overview of the totality of the evidence for the link between fat quality as a dietary exposure, and health outcomes such as atherosclerotic cardiovascular disease (ASCVD). Therefore, the main aim of the present narrative review was to provide a comprehensive overview of the rationale for dietary recommendations for fat intake, limiting our discussion to ASCVD as outcome. Herein, we provide a core framework - a causal model - that can help us understand the evidence that has accumulated to date, and that can help us understand new evidence that may become available in the future. The causal model for fat quality and ASCVD is comprised of three key research questions (RQs), each of which determine which scientific methods are most appropriate to use, and thereby which lines of evidence that should feed into the causal model. First, we discuss the link between low-density lipoprotein (LDL) particles and ASCVD (RQ1); we draw especially on evidence from genetic studies, randomized controlled trials (RCTs), epidemiology, and mechanistic studies. Second, we explain the link between dietary fat quality and LDL particles (RQ2); we draw especially on metabolic ward studies, controlled trials (randomized and non-randomized), and mechanistic studies. Third, we explain the link between dietary fat quality, LDL particles, and ASCVD (RQ3); we draw especially on RCTs in animals and humans, epidemiology, population-based changes, and experiments of nature. Additionally, the distrust over dietary recommendations for fat quality may partly relate to an unclear understanding of the scientific method, especially as applied in nutrition research, including the process of developing dietary guidelines. We therefore also aimed to clarify this process. We discuss how we assess causality in nutrition research, and how we progress from scientific evidence to providing dietary recommendations.

Rate-Limiting Enzymes in Cardiometabolic Health and Aging in Humans.

INTRODUCTION: Rate-limiting enzymes (RLEs) are innate slow points in metabolic pathways, and many function in bio-processes related to nutrient sensing. Many RLEs carry causal mutations relevant to inherited metabolic disorders. Because the activity of RLEs in cardiovascular health is poorly characterized, our objective was to assess their involvement in cardiometabolic health and disease and where altered biophysical and biochemical functions can promote disease. METHODS: A dataset of 380 human RLEs was compared to protein and gene datasets for factors likely to contribute to cardiometabolic disease, including proteins showing significant age-related altered expression in blood and genetic loci with variants that associate with common cardiometabolic phenotypes. The biochemical reactions catalyzed by RLEs were evaluated for metabolites enriched in RLE subsets associating with various cardiometabolic phenotypes. Most significance tests were based on Z-score enrichment converted to p values with a normal distribution function. RESULTS: Of 380 RLEs analyzed, 112 function in mitochondria, and 53 are assigned to inherited metabolic disorders. There was a depletion of RLE proteins known as aging biomarkers. At the gene level, RLEs were assessed for common genetic variants that associated with important cardiometabolic traits of LDL-cholesterol or any of the five outcomes pertinent to metabolic syndrome. This revealed several RLEs with links to cardiometabolic traits, from a minimum of 26 for HDL-cholesterol to a maximum of 45 for plasma glucose. Analysis of these GWAS-linked RLEs for enrichment of the molecular constituents of the catalyzed reactions disclosed a number of significant phenotype-metabolite links. These included blood pressure with acetate (p = 2.2 × 10-4) and NADP+ (p = 0.0091), plasma HDL-cholesterol and triglyceride with diacylglycerol (p = 2.6 × 10-5, 6.4 × 10-5, respectively) and diolein (p = 2.2 × 10-6, 5.9 × 10-6), and waist circumference with d-glucosamine-6-phosphate (p = 1.8 × 10-4). CONCLUSION: In the context of cardiometabolic health, aging, and disease, these results highlight key diet-derived metabolites that are central to specific rate-limited processes that are linked to cardiometabolic health. These metabolites include acetate and diacylglycerol, pertinent to blood pressure and triglycerides, respectively, as well as diacylglycerol and HDL-cholesterol.

Associations between PBMC whole genome transcriptome, muscle strength, muscle mass, and physical performance in healthy home-dwelling older women.

Increasing age is accompanied by many changes, including declining functional skeletal muscle health and immune dysfunction. Peripheral blood mononuclear cells (PBMCs) are circulating cells that assemble an immune response, but their whole genome transcriptome has not been studied in the context of age-related muscle health. Consequently, this article explored associations between three muscle variables indicative of functional muscle health - maximum handgrip strength (muscle strength), appendicular skeletal muscle mass index (ASMI, muscle mass), and gait speed (physical performance) - and two groups of bioinformatics-generated PBMC gene expression features (gene expression-estimated leukocyte subset proportions and gene clusters). We analyzed cross-sectional data from 95 home-dwelling healthy women ≥ 70 years, using "cell-type identification by estimating relative subsets of RNA transcripts" (CIBERSORT) to estimate leukocyte subset proportions and "weighted correlation network analysis" (WGCNA) to generate gene clusters. Associations were studied using linear regression models and relevant gene clusters were subjected to gene set enrichment analysis using gene ontology. Gait speed and ASMI associated with CIBERSORT-estimated monocyte proportions (ß = - 0.090, 95% CI = (- 0.146, - 0.034), p-value = 0.002 for gait speed, and ß = - 0.206, 95% CI = (- 0.385, - 0.028), p-value = 0.024 for ASMI), and gait speed associated with CIBERSORT-estimated M2 macrophage proportions (ß = - 0.026, 95% CI = (- 0.043, - 0.008), p-value = 0.004). Furthermore, maximum handgrip strength associated with nine WGCNA gene clusters, enriched in processes related to immune function and skeletal muscle cells (ß in the range - 0.007 to 0.008, p-values < 0.05). These results illustrate interactions between skeletal muscle and the immune system, supporting the notion that age-related functional muscle health and the immune system are closely linked.

Young women with familial hypercholesterolemia have higher LDL-cholesterol burden than men: Novel data using repeated measurements during 12-years follow-up.

Background and aims: The concentration and the duration of exposure to low-density lipoprotein cholesterol (LDL-C) (LDL-C burden) is an important determinant of risk for cardiovascular disease and thresholds has recently been estimated. Individuals with familial hypercholesterolemia (FH) have increased risk of premature cardiovascular disease. The overall aim of the present study was to describe differences in LDL-C level and LDL-C burden in females and males with FH visiting an outpatient lipid clinic from a young age, using multiple LDL-C measurements during a follow-up time of 12 years. First, we aimed to study if the LDL-C concentration and the LDL-C burden is different between females and males at ages 0-10, 10-20, 20-30 and >30 years. Second, we aimed to estimate the subject-specific LDL-C burden at age 19 and 30 years, and the proportion of female and male patients that reach suggested LDL-C thresholds indicating high risk of ASCVD. Methods: Data was retrospectively collected from medical records of 438 subjects (207 girls and 231 boys) with FH, referred to the Lipid Clinic, Oslo University Hospital below the age of 19 years. The LDL-C burden was estimated based on repeated LDL-C measurements over time. Results: Subjects were followed over a period of mean 12.0 (SD 7.0) years, with median 10 years (7-17; 25-75 percentiles, minimum 2), with median 6 (4-9; 25-75 percentiles, minimum 2) available LDL-C measurements, starting at mean age 11 (SD 3.9) years. There was a difference in both LDL-C and LDL-C burden between sexes at different ages. On average, males had lower LDL-C over time, although this difference was less pronounced with age and males also had lower estimated LDL-C burden over time, and this difference was further exacerbated with age. Conclusion: Our study shows that young women with FH have a higher LDL-C burden than their male counterparts, potentially explaining the increased excess CVD risk seen among these. It underscores the importance of careful-follow up and early treatment initiation both prior to and after pregnancies in order to limit statin-free periods.

Associations between dietary intake and glucose tolerance in clinical and metabolomics-based metabotypes.

BACKGROUND: Metabotyping is a novel concept to group metabolically similar individuals. Different metabotypes may respond differently to dietary interventions; hence, metabotyping may become an important future tool in precision nutrition strategies. However, it is not known if metabotyping based on comprehensive omic data provides more useful identification of metabotypes compared to metabotyping based on only a few clinically relevant metabolites. AIM: This study aimed to investigate if associations between habitual dietary intake and glucose tolerance depend on metabotypes identified from standard clinical variables or comprehensive nuclear magnetic resonance (NMR) metabolomics. METHODS: We used cross-sectional data from participants recruited through advertisements aimed at people at risk of type 2 diabetes mellitus (n = 203). Glucose tolerance was assessed with a 2-h oral glucose tolerance test (OGTT), and habitual dietary intake was recorded with a food frequency questionnaire. Lipoprotein subclasses and various metabolites were quantified with NMR spectroscopy, and plasma carotenoids were quantified using high-performance liquid chromatography. We divided participants into favorable and unfavorable clinical metabotypes based on established cutoffs for HbA1c and fasting and 2-h OGTT glucose. Favorable and unfavorable NMR metabotypes were created using k-means clustering of NMR metabolites. RESULTS: While the clinical metabotypes were separated by glycemic variables, the NMR metabotypes were mainly separated by variables related to lipoproteins. A high intake of vegetables was associated with a better glucose tolerance in the unfavorable, but not the favorable clinical metabotype (interaction, p = 0.01). This interaction was confirmed using plasma concentrations of lutein and zeaxanthin, objective biomarkers of vegetable intake. Although non-significantly, the association between glucose tolerance and fiber intake depended on the clinical metabotypes, while the association between glucose tolerance and intake of saturated fatty acids and dietary fat sources depended on the NMR metabotypes. CONCLUSION: Metabotyping may be a useful tool to tailor dietary interventions that will benefit specific groups of individuals. The variables that are used to create metabotypes will affect the association between dietary intake and disease risk.

Maternal prenatal cholesterol levels predict offspring weight trajectories during childhood in the Norwegian Mother, Father and Child Cohort Study.

BACKGROUND: Numerous intrauterine factors may affect the offspring's growth during childhood. We aimed to explore if maternal and paternal prenatal lipid, apolipoprotein (apo)B and apoA1 levels are associated with offspring weight, length, and body mass index from 6 weeks to eight years of age. This has previously been studied to a limited extent. METHODS: This parental negative control study is based on the Norwegian Mother, Father and Child Cohort Study and uses data from the Medical Birth Registry of Norway. We included 713 mothers and fathers with or without self-reported hypercholesterolemia and their offspring. Seven parental metabolites were measured by nuclear magnetic resonance spectroscopy, and offspring weight and length were measured at 12 time points. Data were analyzed by linear spline mixed models, and the results are presented as the interaction between parental metabolite levels and offspring spline (age). RESULTS: Higher maternal total cholesterol (TC) level was associated with a larger increase in offspring body weight up to 8 years of age (0.03 ≤ Pinteraction ≤ 0.04). Paternal TC level was not associated with change in offspring body weight (0.17 ≤ Pinteraction ≤ 0.25). Higher maternal high-density lipoprotein cholesterol (HDL-C) and apoA1 levels were associated with a lower increase in offspring body weight up to 8 years of age (0.001 ≤ Pinteraction ≤ 0.005). Higher paternal HDL-C and apoA1 levels were associated with a lower increase in offspring body weight up to 5 years of age but a larger increase in offspring body weight from 5 to 8 years of age (0.01 ≤ Pinteraction ≤ 0.03). Parental metabolites were not associated with change in offspring height or body mass index up to 8 years of age (0.07 ≤ Pinteraction ≤ 0.99). CONCLUSIONS: Maternal compared to paternal TC, HDL-C, and apoA1 levels were more strongly and consistently associated with offspring body weight during childhood, supporting a direct intrauterine effect.

Metabolic profiling of pregnancies complicated by preeclampsia: A longitudinal study.

INTRODUCTION: Preeclampsia is associated with maternal metabolic disturbances, but longitudinal studies with comprehensive metabolic profiling are lacking. We aimed to determine metabolic profiles across gestation in women who developed preeclampsia compared with women with healthy pregnancies. We also explored the respective effects of body mass index (BMI) and preeclampsia on various metabolic measures. MATERIAL AND METHODS: We measured 91 metabolites by high-throughput nuclear magnetic resonance spectroscopy at four time points (visits) during pregnancy (weeks 14-16, 22-24, 30-32 and 36-38). Samples were taken from a Norwegian pregnancy cohort. We fitted a linear regression model for each metabolic measure to compare women who developed preeclampsia (n = 38) and healthy controls (n = 70). RESULTS: Among women who developed preeclampsia, 92% gave birth after 34 weeks of gestation. Compared to women with healthy pregnancies, women who developed preeclampsia had higher levels of several lipid-related metabolites at visit 1, whereas fewer differences were observed at visit 2. At visit 3, the pattern from visit 1 reappeared. At visit 4 the differences were larger in most subgroups of very-low-density lipoprotein particles, the smallest high-density lipoprotein, total lipids and triglycerides. Total fatty acids were also increased, of which monounsaturated fatty acids and saturated fatty acids showed more pronounced differences. Concentration of glycine tended to be lower in pregnancies with preeclampsia until visit 3, although this was not significant after correction for multiple testing. After adjustment for age, BMI, parity and gestational weight gain, all significant differences were attenuated at visits 1 and 2. The estimates were less affected by adjustment at visits 3 and 4. CONCLUSIONS: In early pregnancy, the metabolic differences between preeclamptic and healthy pregnancies were primarily driven by maternal BMI, probably representing the women's pre-pregnancy metabolic status. In early third trimester, several weeks before clinical manifestation, the differences were less influenced by BMI, indicating preeclampsia-specific changes. Near term, women with preeclampsia developed an atherogenic metabolic profile, including elevated total lipids, very-low-density lipoprotein, triglycerides, and total fatty acids.

Use of statins and other lipid-modifying agents across pregnancy: A nationwide drug utilization study in Norway in 2005-2018.

BACKGROUND AND AIMS: Statins are becoming more widely used among women of reproductive age; however, nationwide data on statin use across pregnancy is scarce. We therefore aimed to describe the drug utilization patterns for statins and other lipid-modifying agents (LMAs) before, during, and after pregnancy, for all pregnancies in Norway from 2005 to 2018. METHODS: We linked individual-level data from four nationwide electronic health care registries in Norway and characterized the prescription fills of statins and other LMAs across pregnancy. We also examined trends in pregnancy-related LMA use, and characterized women using statins and other LMAs on parameters of health status and co-morbidity. RESULTS: In total, 822,071 pregnancies for 503,723 women were included. The number of statin prescription fills decreased rapidly during the first trimester and returned to pre-pregnancy levels about one year postpartum. Pregnancy-related statin use increased from 2005 (approx. 0.11% of all pregnancies) to 2018 (approx. 0.29% of all pregnancies); however, in total, few statin prescriptions were filled within any trimester of pregnancy (n = 331, 0.04% of all pregnancies). Statin use was more common in women with higher age, higher weight, smoking, and comorbidities such as hypertension and diabetes mellitus; also, statin users often had co-medication pertinent to these conditions. CONCLUSIONS: Although statins and other LMAs were increasingly being used around the time of pregnancy among women in Norway, drug use was mostly discontinued during the first trimester. Our results suggest that pregnancy-related statin use should be monitored, and that drug safety analyses for maternal and offspring health outcomes are needed.

Glycated Proteins, Glycine, Acetate, and Monounsaturated Fatty Acids May Act as New Biomarkers to Predict the Progression of Type 2 Diabetes: Secondary Analyses of a Randomized Controlled Trial.

Food protein or food-derived peptides may regulate blood glucose levels; however, studies have shown inconsistent results. The aim of the present study was to characterize subgroups of individuals with increased risk of type 2 diabetes (T2D) and to investigate the cardiometabolic effects of fish protein in the same subgroups. We first divided participants into high insuliniAUC and low insuliniAUC subjects based on their insulin incremental area under the curve (iAUC) levels after a 2 h oral glucose tolerance test (OGTT), and secondly based on whether they had received 5.2 g salmon fish protein or placebo for 8 weeks, in a previously conducted randomized controlled trial (RCT). We then profiled these groups by analyzing plasma metabolomics and peripheral blood mononuclear cell (PBMC) gene expression. Compared to the low insuliniAUC group, the high insuliniAUC group had higher plasma concentrations of monounsaturated fatty acids (MUFAs) and glycated proteins (GlycA) and lower concentrations of glycine and acetate. After intervention with fish protein compared to placebo, however, only acetate was significantly increased in the low insuliniAUC group. In conclusion, we identified metabolic biomarkers known to be associated with T2D; also, intervention with fish protein did not affect cardiometabolic risk markers in subgroups with increased risk of T2D.

What characterizes event-free elderly FH patients? A comprehensive lipoprotein profiling.

BACKGROUND AND AIMS: Familial hypercholesterolemia (FH) is a genetic disorder characterized by lifelong elevated low-density lipoprotein cholesterol (LDL-C) and increased risk of premature coronary heart disease (CHD). Cholesterol-lowering therapy (statins) reduces CHD risk, but have been available only in the last 25 years, thus, elderly FH patients have been exposed to elevated LDL-C levels most of their life. Surprisingly, some of these have never experienced any CHD event, raising the question whether they present CHD resistant characteristics. Identifying possible cardioprotective biomarkers could contribute to future CHD preventive treatment, therefore, we aimed to identify metabolic markers in event-free elderly FH subjects. METHODS AND RESULTS: We used a high-throughput nuclear magnetic resonance (NMR) spectroscopy platform to quantify a large number of metabolites in serum samples from 83 FH patients ≥65 years, and analyze differences between subjects with (n = 39) and without (n = 44) CHD. Mean age was 70 years in both groups (57% and 38% female in the event-free group and CHD group, respectively). The event-free group had significantly higher levels of large and extra-large high-density lipoprotein (HDL) particles, and higher concentration of Apolipoprotein A1 (ApoA1) and cholesterol in HDL and HDL2 particles, compared to the CHD group (p ≤ 0.05 for all). CONCLUSION: CHD resistant elderly FH patients have higher levels of large HDL particles. The mechanisms behind the event-free survival among these patients remain unclear; hence, a deeper understanding of the metabolic profile in event-free elderly FH subjects may lead to development of novel preventive therapies.

Replacing Saturated Fat with Polyunsaturated Fat Modulates Peripheral Blood Mononuclear Cell Gene Expression and Pathways Related to Cardiovascular Disease Risk Using a Whole Transcriptome Approach.

SCOPE: The aim of this study is to explore the molecular mechanisms underlying the effect of replacing dietary saturated fat (SFA) with polyunsaturated fat (PUFA) on cardiovascular disease (CVD) risk using a whole transcriptome approach. METHODS AND RESULTS: Healthy subjects with moderate hypercholesterolemia (n = 115) are randomly assigned to a control diet (C-diet) group or an experimental diet (Ex-diet) group receiving comparable food items with different fatty acid composition for 8 weeks. RNA isolated from peripheral blood mononuclear cells (PBMCs) at baseline and after 8 weeks of intervention is analyzed by microarray technology (n = 95). By use of a linear regression model (n = 92), 14 gene transcripts are differentially altered in the Ex-diet group compared to the C-diet group. These include transcripts related to vascular smooth muscle cell proliferation, low-density lipoprotein receptor folding, and regulation of blood pressure. Furthermore, pathways mainly related to immune response and inflammation, signal transduction, development, and cytoskeleton remodeling, gene expression and protein function, are differentially enriched between the groups. CONCLUSION: Replacing dietary SFA with PUFA for 8 weeks modulates PBMC gene expression and pathways related to CVD risk in healthy subjects with moderate hypercholesterolemia.

Children with familial hypercholesterolemia display changes in LDL and HDL function: A cross-sectional study.

BACKGROUND: The functional status of lipoprotein particles contributes to atherogenesis. The tendency of plasma low-density lipoprotein (LDL) particles to aggregate and the ability of igh-density lipoprotein (HDL) particles to induce and mediate reverse cholesterol transport associate with high and low risk for cardiovascular disease in adult patients, respectively. However, it is unknown whether children with familial hypercholesterolemia (FH) display lipoprotein function alterations. HYPOTHESIS: We hypothesized that FH children had disrupted lipoprotein functions. METHODS: We analyzed LDL aggregation susceptibility and HDL-apoA-I exchange (HAE), and activity of four proteins that regulate lipoprotein metabolism (cholesteryl ester transfer protein, lecithin-cholesterol acyltransferase, phospholipid transfer protein, and paraoxonase-1) in plasma samples derived from children with FH (n = 47) and from normocholesterolemic children (n = 56). Variation in lipoprotein functions was further explored using an nuclear magnetic resonance-based metabolomics profiling approach. RESULTS: LDL aggregation was higher, and HAE was lower in FH children than in normocholesterolemic children. LDL aggregation associated positively with LDL cholesterol (LDL-C) and negatively with triglycerides, and HAE/apoA-I associated negatively with LDL-C. Generally, the metabolomic profile for LDL aggregation was opposite of that of HAE/apoA-I. CONCLUSIONS: FH children displayed increased atherogenicity of LDL and disrupted HDL function. These newly observed functional alterations in LDL and HDL add further understanding of the risk for atherosclerotic cardiovascular disease in FH children.

Novel associations between parental and newborn cord blood metabolic profiles in the Norwegian Mother, Father and Child Cohort Study.

BACKGROUND: More than one third of Norwegian women and men between 20 and 40 years of age have elevated cholesterol concentration. Parental metabolic health around conception or during pregnancy may affect the offspring's cardiovascular disease risk. Lipids are important for fetal development, but the determinants of cord blood lipids have scarcely been studied. We therefore aimed to describe the associations between maternal and paternal peri-pregnancy lipid and metabolic profile and newborn cord blood lipid and metabolic profile. METHODS: This study is based on 710 mother-father-newborn trios from the Norwegian Mother, Father and Child Cohort Study (MoBa) and uses data from the Medical Birth Registry of Norway (MBRN). The sample included in this study consisted of parents with and without self-reported hypercholesterolemia the last 6 months before pregnancy and their partners and newborns. Sixty-four cord blood metabolites detected by nuclear magnetic resonance spectroscopy were analyzed by linear mixed model analyses. The false discovery rate procedure was used to correct for multiple testing. RESULTS: Among mothers with hypercholesterolemia, maternal and newborn plasma high-density lipoprotein cholesterol, apolipoprotein A1, linoleic acid, docosahexaenoic acid, alanine, glutamine, isoleucine, leucine, valine, creatinine, and particle concentration of medium high-density lipoprotein were significantly positively associated (0.001 ≤ q ≤ 0.09). Among mothers without hypercholesterolemia, maternal and newborn linoleic acid, valine, tyrosine, citrate, creatinine, high-density lipoprotein size, and particle concentration of small high-density lipoprotein were significantly positively associated (0.02 ≤ q ≤ 0.08). Among fathers with hypercholesterolemia, paternal and newborn ratio of apolipoprotein B to apolipoprotein A1 were significantly positively associated (q = 0.04). Among fathers without hypercholesterolemia, no significant associations were found between paternal and newborn metabolites. Sex differences were found for many cord blood lipids. CONCLUSIONS: Maternal and paternal metabolites and newborn sex were associated with several cord blood metabolites. This may potentially affect the offspring's long-term cardiovascular disease risk.

Using Machine Learning to Predict Obesity Based on Genome-Wide and Epigenome-Wide Gene-Gene and Gene-Diet Interactions.

Obesity is associated with many chronic diseases that impair healthy aging and is governed by genetic, epigenetic, and environmental factors and their complex interactions. This study aimed to develop a model that predicts an individual's risk of obesity by better characterizing these complex relations and interactions focusing on dietary factors. For this purpose, we conducted a combined genome-wide and epigenome-wide scan for body mass index (BMI) and up to three-way interactions among 402,793 single nucleotide polymorphisms (SNPs), 415,202 DNA methylation sites (DMSs), and 397 dietary and lifestyle factors using the generalized multifactor dimensionality reduction (GMDR) method. The training set consisted of 1,573 participants in exam 8 of the Framingham Offspring Study (FOS) cohort. After identifying genetic, epigenetic, and dietary factors that passed statistical significance, we applied machine learning (ML) algorithms to predict participants' obesity status in the test set, taken as a subset of independent samples (n = 394) from the same cohort. The quality and accuracy of prediction models were evaluated using the area under the receiver operating characteristic curve (ROC-AUC). GMDR identified 213 SNPs, 530 DMSs, and 49 dietary and lifestyle factors as significant predictors of obesity. Comparing several ML algorithms, we found that the stochastic gradient boosting model provided the best prediction accuracy for obesity with an overall accuracy of 70%, with ROC-AUC of 0.72 in test set samples. Top predictors of the best-fit model were 21 SNPs, 230 DMSs in genes such as CPT1A, ABCG1, SLC7A11, RNF145, and SREBF1, and 26 dietary factors, including processed meat, diet soda, French fries, high-fat dairy, artificial sweeteners, alcohol intake, and specific nutrients and food components, such as calcium and flavonols. In conclusion, we developed an integrated approach with ML to predict obesity using omics and dietary data. This extends our knowledge of the drivers of obesity, which can inform precision nutrition strategies for the prevention and treatment of obesity. Clinical Trial Registration: [www.ClinicalTrials.gov], the Framingham Heart Study (FHS), [NCT00005121].

Diet-derived fruit and vegetable metabolites show sex-specific inverse relationships to osteoporosis status.

BACKGROUND: The impact of nutrition on the metabolic profile of osteoporosis (OS) is unknown. OBJECTIVE: Identify biochemical factors driving the association of fruit and vegetable (FV) intakes with OS prevalence using an untargeted metabolomics approach. DESIGN: Cross-sectional dietary, anthropometric and plasma metabolite data were examined from the Boston Puerto Rican Osteoporosis Study, n = 600 (46-79 yr). METHODS: Bone mineral density was assessed by DXA. OS was defined by clinical standards. A culturally adapted FFQ assessed usual dietary intake. Principal components analysis (PCA) of 42 FV items created 6 factors. Metabolomic profiles derived from plasma samples were assessed on a commercial platform. Differences in levels of 525 plasma metabolites between disease groups (OS vs no-OS) were compared using logistic regression; and associations with FV intakes by multivariable linear regression, adjusted for covariates. Metabolites significantly associated with OS status or with total FV intake were analyzed for enrichment in various biological pathways using Mbrole 2.0, MetaboAnalyst, and Reactome, using FDR correction of P-values. Correlation coefficients were calculated as Spearman's rho rank correlations, followed by hierarchical clustering of the resulting correlation coefficients using PCA FV factors and sex-specific sets of OS-associated metabolites. RESULTS: High FV intake was inversely related to OS prevalence (Odds Ratio = 0.73; 95% CI = 0.57, 0.94; P = 0.01). Several biological processes affiliated with the FV-associating metabolites, including caffeine metabolism, carnitines and fatty acids, and glycerophospholipids. Important processes identified with OS-associated metabolites were steroid hormone biosynthesis in women and branched-chain amino acid metabolism in men. Factors derived from PCA were correlated with the OS-associated metabolites, with high intake of dark leafy greens and berries/melons appearing protective in both sexes. CONCLUSIONS: These data warrant investigation into whether increasing intakes of dark leafy greens, berries and melons causally affect bone turnover and BMD among middle-aged and older adults at risk for osteoporosis via sex-specific metabolic pathways, and how gene-diet interactions alter these sex-specific metabolomic-osteoporosis links. ClinicalTrials.gov Identifier: NCT01231958.