Childhood Non-HDL Cholesterol and LDL Cholesterol and Adult Atherosclerotic Cardiovascular Events.

BACKGROUND: Although low-density lipoprotein cholesterol (LDL-C) remains the primary cholesterol target in clinical practice in children and adults, non-high-density lipoprotein cholesterol (non-HDL-C) has been suggested as a more accurate measure of atherosclerotic cardiovascular disease (ASCVD) risk. We examined the associations of childhood non-HDL-C and LDL-C levels with adult ASCVD events and determined whether non-HDL-C has better utility than LDL-C in predicting adult ASCVD events. METHODS: This prospective cohort study included 21 126 participants from the i3C Consortium (International Childhood Cardiovascular Cohorts). Proportional hazards regressions were used to estimate the risk for incident fatal and fatal/nonfatal ASCVD events associated with childhood non-HDL-C and LDL-C levels (age- and sex-specific z scores; concordant/discordant categories defined by guideline-recommended cutoffs), adjusted for sex, Black race, cohort, age at and calendar year of child measurement, body mass index, and systolic blood pressure. Predictive utility was determined by the C index. RESULTS: After an average follow-up of 35 years, 153 fatal ASCVD events occurred in 21 126 participants (mean age at childhood visits, 11.9 years), and 352 fatal/nonfatal ASCVD events occurred in a subset of 11 296 participants who could be evaluated for this outcome. Childhood non-HDL-C and LDL-C levels were each associated with higher risk of fatal and fatal/nonfatal ASCVD events (hazard ratio ranged from 1.27 [95% CI, 1.14-1.41] to 1.35 [95% CI, 1.13-1.60] per unit increase in the risk factor z score). Non-HDL-C had better discriminative utility than LDL-C (difference in C index, 0.0054 [95% CI, 0.0006-0.0102] and 0.0038 [95% CI, 0.0008-0.0068] for fatal and fatal/nonfatal events, respectively). The discordant group with elevated non-HDL-C and normal LDL-C had a higher risk of ASCVD events compared with the concordant group with normal non-HDL-C and LDL-C (fatal events: hazard ratio, 1.90 [95% CI, 0.98-3.70]; fatal/nonfatal events: hazard ratio, 1.94 [95% CI, 1.23-3.06]). CONCLUSIONS: Childhood non-HDL-C and LDL-C levels are associated with ASCVD events in midlife. Non-HDL-C is better than LDL-C in predicting adult ASCVD events, particularly among individuals who had normal LDL-C but elevated non-HDL-C. These findings suggest that both non-HDL-C and LDL-C are useful in identifying children at higher risk of ASCVD events, but non-HDL-C may provide added prognostic information when it is discordantly higher than the corresponding LDL-C and has the practical advantage of being determined without a fasting sample.

Childhood Cardiovascular Risk Factors and Adult Cardiovascular Events.

BACKGROUND: Childhood cardiovascular risk factors predict subclinical adult cardiovascular disease, but links to clinical events are unclear. METHODS: In a prospective cohort study involving participants in the International Childhood Cardiovascular Cohort (i3C) Consortium, we evaluated whether childhood risk factors (at the ages of 3 to 19 years) were associated with cardiovascular events in adulthood after a mean follow-up of 35 years. Body-mass index, systolic blood pressure, total cholesterol level, triglyceride level, and youth smoking were analyzed with the use of i3C-derived age- and sex-specific z scores and with a combined-risk z score that was calculated as the unweighted mean of the five risk z scores. An algebraically comparable adult combined-risk z score (before any cardiovascular event) was analyzed jointly with the childhood risk factors. Study outcomes were fatal cardiovascular events and fatal or nonfatal cardiovascular events, and analyses were performed after multiple imputation with the use of proportional-hazards regression. RESULTS: In the analysis of 319 fatal cardiovascular events that occurred among 38,589 participants (49.7% male and 15.0% Black; mean [±SD] age at childhood visits, 11.8±3.1 years), the hazard ratios for a fatal cardiovascular event in adulthood ranged from 1.30 (95% confidence interval [CI], 1.14 to 1.47) per unit increase in the z score for total cholesterol level to 1.61 (95% CI, 1.21 to 2.13) for youth smoking (yes vs. no). The hazard ratio for a fatal cardiovascular event with respect to the combined-risk z score was 2.71 (95% CI, 2.23 to 3.29) per unit increase. The hazard ratios and their 95% confidence intervals in the analyses of fatal cardiovascular events were similar to those in the analyses of 779 fatal or nonfatal cardiovascular events that occurred among 20,656 participants who could be evaluated for this outcome. In the analysis of 115 fatal cardiovascular events that occurred in a subgroup of 13,401 participants (31.0±5.6 years of age at the adult measurement) who had data on adult risk factors, the adjusted hazard ratio with respect to the childhood combined-risk z score was 3.54 (95% CI, 2.57 to 4.87) per unit increase, and the mutually adjusted hazard ratio with respect to the change in the combined-risk z score from childhood to adulthood was 2.88 (95% CI, 2.06 to 4.05) per unit increase. The results were similar in the analysis of 524 fatal or nonfatal cardiovascular events. CONCLUSIONS: In this prospective cohort study, childhood risk factors and the change in the combined-risk z score between childhood and adulthood were associated with cardiovascular events in midlife. (Funded by the National Institutes of Health.).

Gene expression networks regulated by human personality.

Genome-wide association studies of human personality have been carried out, but transcription of the whole genome has not been studied in relation to personality in humans. We collected genome-wide expression profiles of adults to characterize the regulation of expression and function in genes related to human personality. We devised an innovative multi-omic approach to network analysis to identify the key control elements and interactions in multi-modular networks. We identified sets of transcribed genes that were co-expressed in specific brain regions with genes known to be associated with personality. Then we identified the minimum networks for the co-localized genes using bioinformatic resources. Subjects were 459 adults from the Young Finns Study who completed the Temperament and Character Inventory and provided peripheral blood for genomic and transcriptomic analysis. We identified an extrinsic network of 45 regulatory genes from seed genes in brain regions involved in self-regulation of emotional reactivity to extracellular stimuli (e.g., self-regulation of anxiety) and an intrinsic network of 43 regulatory genes from seed genes in brain regions involved in self-regulation of interpretations of meaning (e.g., production of concepts and language). We discovered that interactions between the two networks were coordinated by a control hub of 3 miRNAs and 3 protein-coding genes shared by both. Interactions of the control hub with proteins and ncRNAs identified more than 100 genes that overlap directly with known personality-related genes and more than another 4000 genes that interact indirectly. We conclude that the six-gene hub is the crux of an integrative network that orchestrates information-transfer throughout a multi-modular system of over 4000 genes enriched in liquid-liquid-phase-separation (LLPS)-related RNAs, diverse transcription factors, and hominid-specific miRNAs and lncRNAs. Gene expression networks associated with human personality regulate neuronal plasticity, epigenesis, and adaptive functioning by the interactions of salience and meaning in self-awareness.

Genetics of osteopontin in patients with chronic kidney disease: The German Chronic Kidney Disease study.

Osteopontin (OPN), encoded by SPP1, is a phosphorylated glycoprotein predominantly synthesized in kidney tissue. Increased OPN mRNA and protein expression correlates with proteinuria, reduced creatinine clearance, and kidney fibrosis in animal models of kidney disease. But its genetic underpinnings are incompletely understood. We therefore conducted a genome-wide association study (GWAS) of OPN in a European chronic kidney disease (CKD) population. Using data from participants of the German Chronic Kidney Disease (GCKD) study (N = 4,897), a GWAS (minor allele frequency [MAF]≥1%) and aggregated variant testing (AVT, MAF<1%) of ELISA-quantified serum OPN, adjusted for age, sex, estimated glomerular filtration rate (eGFR), and urinary albumin-to-creatinine ratio (UACR) was conducted. In the project, GCKD participants had a mean age of 60 years (SD 12), median eGFR of 46 mL/min/1.73m2 (p25: 37, p75: 57) and median UACR of 50 mg/g (p25: 9, p75: 383). GWAS revealed 3 loci (p<5.0E-08), two of which replicated in the population-based Young Finns Study (YFS) cohort (p<1.67E-03): rs10011284, upstream of SPP1 encoding the OPN protein and related to OPN production, and rs4253311, mapping into KLKB1 encoding prekallikrein (PK), which is processed to kallikrein (KAL) implicated through the kinin-kallikrein system (KKS) in blood pressure control, inflammation, blood coagulation, cancer, and cardiovascular disease. The SPP1 gene was also identified by AVT (p = 2.5E-8), comprising 7 splice-site and missense variants. Among others, downstream analyses revealed colocalization of the OPN association signal at SPP1 with expression in pancreas tissue, and at KLKB1 with various plasma proteins in trans, and with phenotypes (bone disorder, deep venous thrombosis) in human tissue. In summary, this GWAS of OPN levels revealed two replicated associations. The KLKB1 locus connects the function of OPN with PK, suggestive of possible further post-translation processing of OPN. Further studies are needed to elucidate the complex role of OPN within human (patho)physiology.

Randomized 20-year infancy-onset dietary intervention, life-long cardiovascular risk factors and retinal microvasculature.

BACKGROUND AND AIMS: Retinal microvasculature characteristics predict cardiovascular morbidity and mortality. This study investigated associations of lifelong cardiovascular risk factors and effects of dietary intervention on retinal microvasculature in young adulthood. METHODS: The cohort is derived from the longitudinal Special Turku Coronary Risk Factor Intervention Project study. The Special Turku Coronary Risk Factor Intervention Project is a 20-year infancy-onset randomized controlled dietary intervention study with frequent study visits and follow-up extending to age 26 years. The dietary intervention aimed at a heart-healthy diet. Fundus photographs were taken at the 26-year follow-up, and microvascular measures [arteriolar and venular diameters, tortuosity (simple and curvature) and fractal dimensions] were derived (n = 486). Cumulative exposure as the area under the curve for cardiovascular risk factors and dietary components was determined for the longest available time period (e.g. from age 7 months to 26 years). RESULTS: The dietary intervention had a favourable effect on retinal microvasculature resulting in less tortuous arterioles and venules and increased arteriolar fractal dimension in the intervention group when compared with the control group. The intervention effects were found even when controlled for the cumulative cardiovascular risk factors. Reduced lifelong cumulative intake of saturated fats, main target of the intervention, was also associated with less tortuous venules. Several lifelong cumulative risk factors were independently associated with the retinal microvascular measures, e.g. cumulative systolic blood pressure with narrower arterioles. CONCLUSIONS: Infancy-onset 20-year dietary intervention had favourable effects on the retinal microvasculature in young adulthood. Several lifelong cumulative cardiovascular risk factors were independently associated with retinal microvascular structure.

Lipoprotein(a) in Youth and Prediction of Major Cardiovascular Outcomes in Adulthood.

BACKGROUND: Elevated lipoprotein(a) [Lp(a)] is a common risk factor for cardiovascular disease outcomes with unknown mechanisms. We examined its potential role in identifying youths who are at increased risk of developing adult atherosclerotic cardiovascular disease (ASCVD). METHODS: Lp(a) levels measured in youth 9 to 24 years of age were linked to adult ASCVD and carotid intima-media thickness in the YFS (Cardiovascular Risk in Young Finns Study), in which 95 of the original 3596 participants (2.7%) recruited as children have been diagnosed with ASCVD at a median of 47 years of age. Results observed in YFS were replicated with the use of data for White participants from the BHS (Bogalusa Heart Study). In BHS, 587 White individuals had data on youth Lp(a) (measured at 8-17 years of age) and information on adult events, including 15 cases and 572 noncases. Analyses were performed with the use of Cox proportional hazard regression. RESULTS: In YFS, those who had been exposed to high Lp(a) level in youth [defined as Lp(a) ≥30 mg/dL] had ≈2 times greater risk of developing adult ASCVD compared with nonexposed individuals (hazard ratio, 2.0 [95% CI, 1.4-2.6]). Youth risk factors, including Lp(a), low-density lipoprotein cholesterol, body mass index, and smoking, were all independently associated with higher risk. In BHS, in an age- and sex-adjusted model, White individuals who had been exposed to high Lp(a) had 2.5 times greater risk (95% CI, 0.9-6.8) of developing adult ASCVD compared with nonexposed individuals. When also adjusted for low-density lipoprotein cholesterol and body mass index, the risk associated with high Lp(a) remained unchanged (hazard ratio, 2.4 [95% CI, 0.8-7.3]). In a multivariable model for pooled data, individuals exposed to high Lp(a) had 2.0 times greater risk (95% CI, 1.0-3.7) of developing adult ASCVD compared with nonexposed individuals. No association was detected between youth Lp(a) and adult carotid artery thickness in either cohort or pooled data. CONCLUSIONS: Elevated Lp(a) level identified in youth is a risk factor for adult atherosclerotic cardiovascular outcomes but not for increased carotid intima-media thickness.

Mitochondrial genome-wide analysis of nuclear DNA methylation quantitative trait loci.

Mitochondria have a complex communication network with the surrounding cell and can alter nuclear DNA methylation (DNAm). Variation in the mitochondrial DNA (mtDNA) has also been linked to differential DNAm. Genome-wide association studies have identified numerous DNAm quantitative trait loci, but these studies have not examined the mitochondrial genome. Herein, we quantified nuclear DNAm from blood and conducted a mitochondrial genome-wide association study of DNAm, with an additional emphasis on sex- and prediabetes-specific heterogeneity. We used the Young Finns Study (n = 926) with sequenced mtDNA genotypes as a discovery sample and sought replication in the Ludwigshafen Risk and Cardiovascular Health study (n = 2317). We identified numerous significant associations in the discovery phase (P < 10-9), but they were not replicated when accounting for multiple testing. In total, 27 associations were nominally replicated with a P < 0.05. The replication analysis presented no evidence of sex- or prediabetes-specific heterogeneity. The 27 associations were included in a joint meta-analysis of the two cohorts, and 19 DNAm sites associated with mtDNA variants, while four other sites showed haplogroup associations. An expression quantitative trait methylation analysis was performed for the identified DNAm sites, pinpointing two statistically significant associations. This study provides evidence of a mitochondrial genetic control of nuclear DNAm with little evidence found for sex- and prediabetes-specific effects. The lack of a comparable mtDNA data set for replication is a limitation in our study and further studies are needed to validate our results.

Metabolic syndrome and epigenetic aging: a twin study.

BACKGROUND: Metabolic syndrome (MetS) is associated with premature aging, but whether this association is driven by genetic or lifestyle factors remains unclear. METHODS: Two independent discovery cohorts, consisting of twins and unrelated individuals, were examined (N = 268, aged 23-69 years). The findings were replicated in two cohorts from the same base population. One consisted of unrelated individuals (N = 1 564), and the other of twins (N = 293). Participants' epigenetic age, estimated using blood DNA methylation data, was determined using the epigenetic clocks GrimAge and DunedinPACE. The individual-level linear regression models for investigating the associations of MetS and its components with epigenetic aging were followed by within-twin-pair analyses using fixed-effects regression models to account for genetic factors. RESULTS: In individual-level analyses, GrimAge age acceleration was higher among participants with MetS (N = 56) compared to participants without MetS (N = 212) (mean 2.078 [95% CI = 0.996,3.160] years vs. -0.549 [-1.053,-0.045] years, between-group p = 3.5E-5). Likewise, the DunedinPACE estimate was higher among the participants with MetS compared to the participants without MetS (1.032 [1.002,1.063] years/calendar year vs. 0.911 [0.896,0.927] years/calendar year, p = 4.8E-11). An adverse profile in terms of specific MetS components was associated with accelerated aging. However, adjustments for lifestyle attenuated these associations; nevertheless, for DunedinPACE, they remained statistically significant. The within-twin-pair analyses suggested that genetics explains these associations fully for GrimAge and partly for DunedinPACE. The replication analyses provided additional evidence that the association between MetS components and accelerated aging is independent of the lifestyle factors considered in this study, however, suggesting that genetics is a significant confounder in this association. CONCLUSIONS: The results of this study suggests that MetS is associated with accelerated epigenetic aging, independent of physical activity, smoking or alcohol consumption, and that the association may be explained by genetics.

Association of Serum Trimethylamine-N-Oxide Concentration from Childhood to Early Adulthood with Age and Sex.

BACKGROUND: Primary prevention is the cornerstone of cardiometabolic health. In the randomized, controlled Special Turku Coronary Risk Factor Intervention Project (STRIP), dietary counseling intervention was given to children from infancy to 20 years of age and a follow-up was completed at age 26 years. We investigated the associations of age, sex, gut microbiome, and dietary intervention with the gut metabolite and the cardiac biomarker trimethylamine-N-oxide (TMAO). METHODS: Overall, 592 healthy participants (females 46%) from STRIP were investigated. Compared to the control group, the intervention group had received dietary counseling between ages 7 months and 20 years focused on low intakes of saturated fat and cholesterol and the promotion of fruit, vegetable, and whole-grain consumption. TMAO serum concentrations were measured by a liquid chromatography-tandem mass spectrometry method at ages 11, 13, 15, 17, 19, and 26 years. Microbiome composition was assessed using 16S rRNA gene sequencing at 26 years of age. RESULTS: TMAO concentrations increased from age 11 to 26 years in both sexes. At all measurement time points, males showed significantly higher serum TMAO concentrations compared to females, but concentrations were similar between the intervention and control groups. A direct association between TMAO concentrations and reported fiber intake was found in females. Gut microbiome analysis did not reveal associations with TMAO. CONCLUSIONS: TMAO concentration increased from childhood to early adulthood but was not affected by the given dietary intervention. In females, TMAO concentrations could be directly associated with higher fiber intake suggesting sex-specific differences in TMAO metabolism.

The Influence of Dietary Counseling Over 20 Years on Tracking of Non-High-Density Lipoprotein Cholesterol from Infancy to Young Adulthood.

This 26-year study found that non-high-density lipoprotein cholesterol (non-HDL-C) levels tracked from infancy to young adulthood suggesting early-life non-HDL-C could predict future levels. However, infancy-onset dietary counseling reduced the odds of maintaining at-risk non-HDL-C, highlighting the potential importance of early interventions in preventing cardiovascular risk associated with high pediatric non-HDL-C.

Association of Long-Term Habitual Dietary Fiber Intake since Infancy with Gut Microbiota Composition in Young Adulthood.

BACKGROUND: Dietary fiber is an important health-promoting component of the diet, which is fermented by the gut microbes that produce metabolites beneficial for the host's health. OBJECTIVES: We studied the associations of habitual long-term fiber intake from infancy with gut microbiota composition in young adulthood by leveraging data from the Special Turku Coronary Risk Factor Intervention Project, an infancy-onset 20-y dietary counseling study. METHODS: Fiber intake was assessed annually using food diaries from infancy ≤ age 20 y. At age 26 y, the first postintervention follow-up study was conducted including food diaries and fecal sample collection (N = 357). Cumulative dietary fiber intake was assessed as the area under the curve for energy-adjusted fiber intake throughout the study (age 0-26 y). Gut microbiota was profiled using 16S ribosomal ribonucleic acid amplicon sequencing. The primary outcomes were 1) α diversity expressed as the observed richness and Shannon index, 2) ß diversity using Bray-Curtis dissimilarity scores, and 3) differential abundance of each microbial taxa with respect to the cumulative energy-adjusted dietary fiber intake. RESULTS: Higher cumulative dietary fiber intake was associated with decreased Shannon index (ß = -0.019 per unit change in cumulative fiber intake, P = 0.008). Overall microbial community composition was related to the amount of fiber consumed (permutational analysis of variation R2 = 0.005, P = 0.024). The only genus that was increased with higher cumulative fiber intake was butyrate-producing Butyrivibrio (log2 fold-change per unit change in cumulative fiber intake 0.40, adjusted P = 0.023), whereas some other known butyrate producers such as Faecalibacterium and Subdoligranulum were decreased with higher cumulative fiber intake. CONCLUSIONS: As early-life nutritional exposures may affect the lifetime microbiota composition and disease risk, this study adds novel information on the associations of long-term dietary fiber intake with the gut microbiota. This trial was registered at clinicaltrials.gov as NCT00223600.

Trajectories of cardiovascular risk predict pregnancy outcomes: The Bogalusa Heart Study and the Cardiovascular Risk in Young Finns Study.

BACKGROUND: Life course patterns of change in risk-trajectories-affect health. OBJECTIVES: To examine how trajectories of cardiovascular risk factors are associated with pregnancy and birth outcomes. METHODS: Data from two cohort studies participating in the International Childhood Cardiovascular Consortium-The Bogalusa Heart Study (BHS; started in 1973, N = 903 for this analysis) and the Cardiovascular Risk in Young Finns Study (YFS; started in 1980, N = 499) were used. Both followed children into adulthood and measured cardiovascular risk factors, including body mass index (BMI), systolic and diastolic blood pressure (SBP/DBP), total, lipoprotein (LDL)- and high density lipoprotein (HDL)-cholesterol and serum triglycerides. Discrete mixture modelling was used to divide each cohort into distinct trajectories according to these risk factors from childhood to early adulthood, and these groups were then used to predict pregnancy outcomes including small for gestational age (SGA; <10th study-specific percentile of gestational age by sex), preterm birth (PTB; <37 weeks' gestation), hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM), with control for age at baseline and at first birth, parity, socioeconomic status, BMI and smoking. RESULTS: The models created more trajectories for BMI, SBP and HDL-cholesterol in the YFS than in BHS, for which three classes generally seemed to be sufficient to represent the groups in the population across risk factors. In BHS, the association between the higher and flatter DBP trajectory and PTB was aRR 1.77, 95% confidence interval [CI] 1.06, 2.96. In BHS the association between consistent total cholesterol and PTB was aRR 2.16, 95% CI 1.22, 3.85 and in YFS the association between elevated high trajectory and PTB was aRR 3.35, 95% CI 1.28, 8.79. Elevated-increasing SBP was associated with a higher risk of GH in BHS and increasing or persistent-obese BMI trajectories were associated with GDM in both cohorts (BHS: aRR 3.51, 95% CI 1.95, 6.30; YFS: aRR 2.61, 95% CI 0.96, 7.08). CONCLUSIONS: Trajectories of cardiovascular risk, particularly those that represent a consistent or more rapid worsening of cardiovascular health, are associated with a higher risk of pregnancy complications.

Tracking of apolipoprotein B levels measured in childhood and adolescence: systematic review and meta-analysis.

To quantify the tracking of apolipoprotein B (apoB) levels from childhood and adolescence and compare the tracking of apoB with low-density lipoprotein (LDL) cholesterol, a systematic search of MEDLINE, Embase, Web of Science, and Google Scholar was performed in October 2023 (PROSPERO protocol: CRD42022298663). Cohort studies that measured tracking of apoB from childhood/adolescence (< 19 years) with a minimum follow-up of 1 year, using tracking estimates such as correlation coefficients or tracking coefficients, were eligible. Pooled correlations were estimated using random-effects meta-analysis. Risk of bias was assessed with a review-specific tool. Ten studies of eight unique cohorts involving 4677 participants met the inclusion criteria. Tracking of apoB was observed (pooled r = 0.63; 95% confidence interval [CI] = 0.53-0.71; I2 = 96%) with no significant sources of heterogeneity identified. Data from five cohorts with tracking data for both lipids showed the degree of tracking was similar for apoB (pooled r = 0.59; 95% CI = 0.55-0.63) and LDL cholesterol (pooled r = 0.58; 95% CI = 0.47-0.68). Study risk of bias was moderate, mostly due to attrition and insufficient reporting. CONCLUSION: ApoB levels track strongly from childhood, but do not surpass LDL cholesterol in this regard. While there is strong evidence that apoB is more effective at predicting ASCVD risk than LDL cholesterol in adults, there is currently insufficient evidence to support its increased utility in pediatric settings. This also applies to tracking data, where more comprehensive data are required. WHAT IS KNOWN: • Apolipoprotein B is a known cause of atherosclerotic cardiovascular disease. • Apolipoprotein B levels are not typically measured in pediatric settings, where low-density lipoprotein cholesterol remains the primary lipid screening measure. WHAT IS NEW: • This meta-analysis of 10 studies showed apolipoprotein B levels tracked strongly from childhood but did not exceed low-density lipoprotein cholesterol in this regard. • More comprehensive tracking data are needed to provide sufficient evidence for increased utility of apolipoprotein B in pediatric settings.

Association of childhood socioeconomic status with adulthood maximal exercise blood pressure: the Cardiovascular Risk in Young Finns Study.

PURPOSE: Socioeconomic status has been related to resting blood pressure (BP) levels at different stages of life. However, the association of childhood socioeconomic status (SES) and adulthood exercise BP is largely unknown. Therefore, we studied the association of childhood SES with adulthood maximal exercise BP. MATERIALS AND METHODS: This investigation consisted of 373 individuals (53% women) participating in the Cardiovascular Risk in Young Finns Study who had data concerning family SES in childhood (baseline in 1980, at age of 6-18 years) and exercise BP response data in adulthood (follow-up in adulthood in 27-29 years since baseline). A maximal cardiopulmonary exercise test with BP measurements was performed by participants, and peak exercise BP was measured. RESULTS: In stepwise multivariable analysis including childhood risk factors and lifestyle factors (body mass index, systolic BP, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, insulin, fruit consumption, vegetable consumption, and physical activity), lower family SES in childhood was associated with higher maximal exercise BP in adulthood (ß value ± SE, 1.63 ± 0.77, p = 0.035). The association remained significant after further adjustment with participants SES in adulthood (ß value ± SE, 1.68 ± 0.65, p = 0.011) and after further adjustment with adulthood body-mass index, systolic BP, maximal exercise capacity, and peak heart rate in exercise (ß value ± SE, 1.25 ± 0.56, p = 0.027). CONCLUSIONS: These findings suggest that lower childhood family SES is associated with higher maximal exercise BP in adulthood.

Limited data are available about the association of childhood socioeconomic status and adulthood exercise blood pressure.We prospectively examined whether childhood socioeconomic status is associated with adulthood exercise blood pressure in 373 participants aged 6­18 years at baseline (1980) from the longitudinal Cardiovascular Risk in Young Finns cohort study.In multivariable analysis, including childhood cardiovascular risk factors and lifestyle factors, lower family socioeconomic status in childhood was associated with higher maximal exercise blood pressure in adulthood.The association remained significant after further adjustment with participants socioeconomic status in adulthood and also after further adjustment with adulthood body mass index, systolic blood pressure, maximal exercise capacity and peak heart rate in exercise.Low childhood socioeconomic status predicted also higher risk of exaggerated exercise blood pressure response in adulthood, although this finding was diluted to non-significant after adjustment with adulthood body mass index and systolic blood pressure.These findings suggest that lower childhood family socioeconomic status is associated with higher maximal exercise blood pressure in adulthood.

Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data.

BACKGROUND: Machine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class imbalances. However, little is known about which ML classifier, omics data, or upstream dimension reduction strategy has the strongest influence on prediction quality in such settings. Our study aimed to illustrate and compare different machine learning strategies to predict CVD risk factors under different scenarios. METHODS: We compared the use of six ML classifiers in predicting CVD risk factors using blood-derived metabolomics, epigenetics and transcriptomics data. Upstream omic dimension reduction was performed using either unsupervised or semi-supervised autoencoders, whose downstream ML classifier performance we compared. CVD risk factors included systolic and diastolic blood pressure measurements and ultrasound-based biomarkers of left ventricular diastolic dysfunction (LVDD; E/e' ratio, E/A ratio, LAVI) collected from 1,249 Finnish participants, of which 80% were used for model fitting. We predicted individuals with low, high or average levels of CVD risk factors, the latter class being the most common. We constructed multi-omic predictions using a meta-learner that weighted single-omic predictions. Model performance comparisons were based on the F1 score. Finally, we investigated whether learned omic representations from pre-trained semi-supervised autoencoders could improve outcome prediction in an external cohort using transfer learning. RESULTS: Depending on the ML classifier or omic used, the quality of single-omic predictions varied. Multi-omics predictions outperformed single-omics predictions in most cases, particularly in the prediction of individuals with high or low CVD risk factor levels. Semi-supervised autoencoders improved downstream predictions compared to the use of unsupervised autoencoders. In addition, median gains in Area Under the Curve by transfer learning compared to modelling from scratch ranged from 0.09 to 0.14 and 0.07 to 0.11 units for transcriptomic and metabolomic data, respectively. CONCLUSIONS: By illustrating the use of different machine learning strategies in different scenarios, our study provides a platform for researchers to evaluate how the choice of omics, ML classifiers, and dimension reduction can influence the quality of CVD risk factor predictions.

Non-High-Density Lipoprotein Cholesterol Levels From Childhood to Adulthood and Cardiovascular Disease Events.

Importance: Elevated non-high-density lipoprotein cholesterol (non-HDL-C; a recommended measure of lipid-related cardiovascular risk) is common in children and increases risk of adult cardiovascular disease (CVD). Whether resolution of elevated childhood non-HDL-C levels by adulthood is associated with reduced risk of clinical CVD events is unknown. Objective: To examine the associations of non-HDL-C status between childhood and adulthood with incident CVD events. Design, Setting, and Participants: Individual participant data from 6 prospective cohorts of children (mean age at baseline, 10.7 years) in the US and Finland. Recruitment took place between 1970 and 1996, with a final follow-up in 2019. Exposures: Child (age 3-19 years) and adult (age 20-40 years) non-HDL-C age- and sex-specific z scores and categories according to clinical guideline-recommended cutoffs for dyslipidemia. Main Outcomes and Measures: Incident fatal and nonfatal CVD events adjudicated by medical records. Results: Over a mean length of follow-up of 8.9 years after age 40 years, 147 CVD events occurred among 5121 participants (60% women; 15% Black). Both childhood and adult non-HDL-C levels were associated with increased risk of CVD events (hazard ratio [HR], 1.42 [95% CI, 1.18-1.70] and HR, 1.50 [95% CI, 1.26-1.78] for a 1-unit increase in z score, respectively), but the association for childhood non-HDL-C was reduced when adjusted for adult levels (HR, 1.12 [95% CI, 0.89-1.41]). A complementary analysis showed that both childhood non-HDL-C levels and the change between childhood and adulthood were independently associated with the outcome, suggesting that from a preventive perspective, both childhood non-HDL-C levels and the change into adulthood are informative. Compared with those whose non-HDL-C levels remained within the guideline-recommended range in childhood and adulthood, participants who had incident non-HDL-C dyslipidemia from childhood to adulthood and those with persistent dyslipidemia had increased risks of CVD events (HR, 2.17 [95% CI, 1.00-4.69] and HR, 5.17 [95% CI, 2.80-9.56], respectively). Individuals who had dyslipidemic non-HDL-C in childhood but whose non-HDL-C levels were within the guideline-recommended range in adulthood did not have a significantly increased risk (HR, 1.13 [95% CI, 0.50-2.56]). Conclusions and Relevance: Individuals with persistent non-HDL-C dyslipidemia from childhood to adulthood had an increased risk of CVD events, but those in whom dyslipidemic non-HDL-C levels resolve by adulthood have similar risk to individuals who were never dyslipidemic. These findings suggest that interventions to prevent and reduce elevated childhood non-HDL-C levels may help prevent premature CVD.

Effect of common pregnancy and perinatal complications on offspring metabolic traits across the life course: a multi-cohort study.

BACKGROUND: Common pregnancy and perinatal complications are associated with offspring cardiometabolic risk factors. These complications may influence multiple metabolic traits in the offspring and these associations might differ with offspring age. METHODS: We used data from eight population-based cohort studies to examine and compare associations of pre-eclampsia (PE), gestational hypertension (GH), gestational diabetes (GD), preterm birth (PTB), small (SGA) and large (LGA) for gestational age (vs. appropriate size for gestational age (AGA)) with up to 167 plasma/serum-based nuclear magnetic resonance-derived metabolic traits encompassing lipids, lipoproteins, fatty acids, amino acids, ketones, glycerides/phospholipids, glycolysis, fluid balance, and inflammation. Confounder-adjusted regression models were used to examine associations (adjusted for maternal education, parity age at pregnancy, ethnicity, pre/early pregnancy body mass index and smoking, and offspring sex and age at metabolic trait assessment), and results were combined using meta-analysis by five age categories representing different periods of the offspring life course: neonates (cord blood), infancy (mean ages: 1.1-1.6 years), childhood (4.2-7.5 years); adolescence (12.0-16.0 years), and adulthood (22.0-67.8 years). RESULTS: Offspring numbers for each age category/analysis varied from 8925 adults (441 PTB) to 1181 infants (135 GD); 48.4% to 60.0% were females. Pregnancy complications (PE, GH, GD) were each associated with up to three metabolic traits in neonates (P≤0.001) with some evidence of persistence to older ages. PTB and SGA were associated with 32 and 12 metabolic traits in neonates respectively, which included an adjusted standardised mean difference of -0.89 standard deviation (SD) units for albumin with PTB (95% CI: -1.10 to -0.69, P=1.3×10-17) and -0.41 SD for total lipids in medium HDL with SGA (95% CI: -0.56 to -0.25, P=2.6×10-7), with some evidence of persistence to older ages. LGA was inversely associated with 19 metabolic traits including lower levels of cholesterol, lipoproteins, fatty acids, and amino acids, with associations emerging in adolescence, (e.g. -0.11 SD total fatty acids, 95% CI: -0.18 to -0.05, P=0.0009), and attenuating with older age across adulthood. CONCLUSIONS: These reassuring findings suggest little evidence of wide-spread and long-term impact of common pregnancy and perinatal complications on offspring metabolic traits, with most associations only observed for newborns rather than older ages, and for perinatal rather than pregnancy complications.

Longitudinal metabolomics of increasing body-mass index and waist-hip ratio reveals two dynamic patterns of obesity pandemic.

BACKGROUND/OBJECTIVE: This observational study dissects the complex temporal associations between body-mass index (BMI), waist-hip ratio (WHR) and circulating metabolomics using a combination of longitudinal and cross-sectional population-based datasets and new systems epidemiology tools. SUBJECTS/METHODS: Firstly, a data-driven subgrouping algorithm was employed to simplify high-dimensional metabolic profiling data into a single categorical variable: a self-organizing map (SOM) was created from 174 metabolic measures from cross-sectional surveys (FINRISK, n = 9708, ages 25-74) and a birth cohort (NFBC1966, n = 3117, age 31 at baseline, age 46 at follow-up) and an expert committee defined four subgroups of individuals based on visual inspection of the SOM. Secondly, the subgroups were compared regarding BMI and WHR trajectories in an independent longitudinal dataset: participants of the Young Finns Study (YFS, n = 1286, ages 24-39 at baseline, 10 years follow-up, three visits) were categorized into the four subgroups and subgroup-specific age-dependent trajectories of BMI, WHR and metabolic measures were modelled by linear regression. RESULTS: The four subgroups were characterised at age 39 by high BMI, WHR and dyslipidemia (designated TG-rich); low BMI, WHR and favourable lipids (TG-poor); low lipids in general (Low lipid) and high low-density-lipoprotein cholesterol (High LDL-C). Trajectory modelling of the YFS dataset revealed a dynamic BMI divergence pattern: despite overlapping starting points at age 24, the subgroups diverged in BMI, fasting insulin (three-fold difference at age 49 between TG-rich and TG-poor) and insulin-associated measures such as triglyceride-cholesterol ratio. Trajectories also revealed a WHR progression pattern: despite different starting points at the age of 24 in WHR, LDL-C and cholesterol-associated measures, all subgroups exhibited similar rates of change in these measures, i.e. WHR progression was uniform regardless of the cross-sectional metabolic profile. CONCLUSIONS: Age-associated weight variation in adults between 24 and 49 manifests as temporal divergence in BMI and uniform progression of WHR across metabolic health strata.

Polygenic risk for schizophrenia predicting social trajectories in a general population sample.

BACKGROUND: We investigated (a) whether polygenic risk for schizophrenia predicts different trajectories of social development among those who have not developed psychoses and (b) whether possible associations are PRSSCZ-specific or evident also for any polygenic risk for mental disorders, e.g. for major depression. METHODS: Participants came from the population-based Young Finns Study (n = 2377). We calculated a polygenic risk score for schizophrenia (PRSSCZ) and for major depression (PRSDEP). Diagnoses of psychotic disorders were derived from the hospital care register. Social development from adolescence to middle age was measured by (a) perceived social support from friends, family, and a close other, (b) perceived sociability, and (c) family structure (partnership status, number of children, age of first-time parenthood). RESULTS: Among those without manifest psychoses, high PRSSCZ predicted lower experienced support from friends (B = -0.04, p = 0.009-0.035) and family (B = -0.04, p = 0.009-0.035) especially after early adulthood, and also lower perceived sociability (B = -0.05, p = 0.010-0.026). PRSSCZ was not related to family structure. PRSDEP did not predict any domain of social development. CONCLUSIONS: Individuals at high PRSSCZ (not converted to psychosis) seem to experience a lower preference to be with others over being alone. Individuals with high (v. low) PRSSCZ seem to have a similar family structure in terms of partnership status or number of children but, nevertheless, they experience less support from their family. Among those not converted to psychosis in a typical age period, high PRSSCZ may predict a 'later risk phase' and reduced functional resilience when approaching middle age.

Magical thinking in individuals with high polygenic risk for schizophrenia but no non-affective psychoses-a general population study.

A strong genetic background for psychoses is well-established. Most individuals with a high genetic risk for schizophrenia, however, do not develop the disorder. We investigated whether individuals, who have a high genetic risk for schizophrenia but no non-affective psychotic disorders, are predisposed to develop milder forms of deviant thinking in terms of magical thinking. Participants came from the population-based Young Finns Study (n = 1292). The polygenic risk score for schizophrenia (PRS) was calculated on the basis of the most recent genome-wide association study (GWAS). Psychiatric diagnoses over the lifespan were collected up to 2017 from the registry of hospital care. Magical thinking was evaluated with the Spiritual Acceptance Scale (e.g., beliefs in telepathy, miracles, mystical events, or sixth sense) of the Temperament and Character Inventory in 1997, 2001, and 2012 (participants were 20-50-year-olds). We found that, among those who did not develop non-affective psychotic disorders, high PRS predicted higher magical thinking in adulthood (p = 0.001). Further, PRS predicted different developmental courses: a low PRS predicted a steady decrease in magical thinking from age 20 to 50 years, while in individuals with high PRS the decrease in magical thinking ceased in middle age so that their level of magical thinking remained higher than expected for that age. These findings remained when controlling for sex, childhood family environment, and adulthood socioeconomic factors. In conclusion, if high PRS does not lead to a non-affective psychotic disorder, it predicts milder forms of deviant thinking such as elevated magical thinking in adulthood, especially in middle age. The finding enhances our understanding of different outcomes of high genetic psychosis risk.