DNA methylation-based epigenetic clocks are reliable measures of biological age and aging rate. Chronic inflammation may contribute to aging and various diseases, but population-based studies on specific inflammatory biomarkers’ impact on epigenetic clocks are limited. The aim of this study was to investigate the associations between 38 circulating inflammatory biomarkers, as well as a combined systemic inflammation variable, and epigenetic clocks in a middle-aged population. The cohort included 1,327 Finnish participants (aged 30–45 years, 50–55% female) from the Young Finns Study. Biomarkers were measured in 2007, and epigenetic clocks were assessed in 2011 and 2018. DunedinPACE and PCGrimAgeDev clocks were calculated using blood methylation data. Multiple linear regression models adjusted for age, sex, BMI, smoking, socioeconomic status, alcohol consumption, and physical activity were used. Results showed 11 biomarkers positively associated with DunedinPACE across both follow-ups. Seven biomarkers were positively associated with PCGrimAgeDev in the 4-year follow-up, but not in the 11-year follow-up. The combined systemic inflammation marker was positively associated with both clocks in both follow-ups. Although previous cross-sectional studies have reported associations between pro-inflammatory cytokines and epigenetic ageing, longitudinal findings remain sparse. Our results extend this literature by showing that several cytokines predict accelerated epigenetic ageing across an 11-year follow-up.

MicroRNAs have been suggested as essential hypertension biomarkers, but evidence remains inconclusive due to limited high-throughput studies in population cohorts. We analyzed data from the Young Finns Study (YFS) from 2011 and 2018-2020 to assess cross-sectional and prospective associations between circulatory microRNAs, blood pressure (BP), and hypertension. Hypertension risk prediction potential was assessed using nested logistic and Weibull survival models; model performance was evaluated with likelihood ratio (LR) test and c-statistic. All models were adjusted with relevant risk factors. In 2011, whole blood microRNAs were profiled for 871 individuals (83 with hypertension); in 2018-2020, 760 were re-examined, with 67 newly diagnosed. Cross-sectionally, 16 miRNAs correlated with BP (Spearman, PFDR  < 0.05); miR-122-5p (fold change = 1.33) and miR-144-5p (fold change = -1.10) differentiated hypertensive individuals ( U test, PFDR  < 0.05). Associations persisted in adjusted regression models and some replicated in LURIC ( n  = 999) and YFS serum data ( n  = 126). Prospectively, miR-19a-3p [odds ratio (OR) = 1.51, 95% confidence interval (95% CI): 1.14-2.18], miR-19b-3p (OR = 1.50, 95% CI:1.11-2.04), and miR-329-3p (OR = 0.58, 95% CI: 0.39-0.74) levels prognosed hypertension incident. miR-329-3p improved model fit (LR test, P  = 2.85×10 -4 ) and discrimination (c-statistic = 0.849, Δ = 0.026). miR-19b-3p predicted time to onset (hazard ratio = 2.13, 95% CI: 1.38-4.45), improving model fit (LR test, P  = 0.0012) and time-dependent discrimination at 7 and 8-year horizons. Our findings highlight both novel and previously reported miRNAs associating with BP and hypertension and suggest that miR-329-3p, miR-19a-3p, and miR-19b-3p as promising candidates for further investigation in hypertension risk prediction.

BACKGROUND:The role of diet in epigenetic aging over long follow-up periods and the possible moderating role of physical activity have remained unclear. OBJECTIVES:We examined: 1) whether dietary habits over follow-ups of 17-32 y are associated with the level or change of epigenetic aging over a 7-y follow-up, and 2) whether physical activity moderates these associations. METHODS:The prospective population-based Young Finns Study data (n = 1039) were used. Epigenetic aging was measured in 2011 and 2018 using PhenoAge and GrimAge age deviation (AgeDevPheno, AgeDevGrim) and Dunedin pace of aging computed from the epigenome (DunedinPACE). Food Frequency Questionnaires were used in 2001, 2007, 2011, and 2018 to calculate 5 diet indices: Mediterranean Diet Index, Findiet Index, Alternative Healthy Eating Index (AHEI) Dietscore (additionally used in 1986), and Baltic Sea Diet Index. The applied physical activity index included, e.g., frequency and intensity of exercise. Covariates included cardiovascular and metabolic factors, other health behaviors, and socioeconomic factors. RESULTS:More favorable scores in: 1) all diet indices except Dietscore were associated with decelerated AgeDevGrim cross-sectionally (β = -0.08 to -0.06, P = 0.003-0.022), 2) the means of all diet indices over follow-ups of 17-32 y were associated with slower epigenetic aging in all 3 epigenetic clocks (β = -0.01 to -0.23, P = 2e-5-0.042), and 3) AHEI and Findiet Index were most consistently associated with a decelerated change in AgeDevGrim and AgeDevPheno over a 7-y follow-up. Modest interaction effects were also observed: among those with high physical activity, epigenetic aging was approximately similar irrespective of diet healthiness, whereas among those with low physical activity, more favorable diet index scores were associated with less accelerated epigenetic aging. CONCLUSIONS:Healthier eating over the follow-up was associated with decelerated epigenetic changes across different diet indices. In terms of biological aging, having a healthy diet may be especially crucial for those with low levels of physical activity.

Metabolic dysfunction-associated fatty liver disease (MAFLD) and carotid artery plaque (CAP) are both linked to circulatory lipid and lipoprotein metabolism. However, the shared lipidome-wide mechanisms underlying these diseases remain unexplored. To identify plasma lipid species associated with both MAFLD and CAP to uncover their shared metabolic pathways. We analyzed data from the Young Finns Study cohort from the 2007 and 2018 follow-ups (n = 1496, aged 41-56 years, 56.3% females). Ultrasound was used to determine the prevalence of both CAP and MAFLD during the 2018 follow-up. The participants were categorized into three mutually exclusive groups: participants with CAP without MAFLD (n = 257), participants with MAFLD without CAP (n = 150), and a control group free from both diseases (n = 436). Lipidomic profiling of 437 lipid species from plasma was performed during the 2007 follow-up (aged 30-45 years) via liquid chromatography‒tandem mass spectrometry. Logistic regression models, both unadjusted and adjusted for age, sex, physical activity, alcohol consumption, and smoking, were used to assess lipid associations with both disease outcomes separately. Odds ratios (ORs) and confidence intervals (95% CIs) were calculated for each lipid species, and multiple testing corrections were performed via the false discovery rate (FDR) method (< 0.05). Additionally, we performed a hypergeometric enrichment analysis to determine whether certain lipid classes appear more often than expected among the lipids associated with disease. In the unadjusted models, there were a total of 51 significant (FDR < 0.05) overlapping lipids between the CAP and MAFLD groups. In the adjusted models, four lipids were significantly associated with CAP, and 202 lipids were significantly associated with MAFLD. Notably, only one lipid-phosphatidylcholine (PC) 40:4-was significantly associated with both diseases. PC 40:4 was associated with an increased risk of CAP (OR 2.59; 95% CI, 1.57-4.32) and MAFLD (OR 5.26; 95% CI, 2.81-9.85). Our findings highlight PC 40:4 as a novel shared lipid signature for both MAFLD and CAP. This dual association suggests that overlapping metabolic disturbances and potentially common lipid-based pathogenic mechanisms link liver and vascular health. PC 40:4 may serve as a promising early biomarker or therapeutic target for metabolic-vascular comorbidities.

Abstract Background DNA methylation (DNAm) may capture cumulative genetic, environmental, and lifestyle influences on cardiovascular health. Composite DNAm score based on the American Heart Association Life’s Essential 8 (LE8) framework have been linked to clinical events, but their association with early vascular changes and intergenerational effects is unclear. Methods We studied up to 1432 participants from the multigenerational Young Finns Study (YFS-3G), including parents (G0) and adult offspring (G1). DNAm was measured using Illumina EPIC arrays in 2011 and/or 2018, and carotid intima–media thickness (cIMT) was assessed in 2018. The LE8 DNAm score was calculated as a weighted sum of methylation levels. Associations with cIMT were evaluated in intergenerational, prospective, and cross-sectional settings, adjusting for demographic, technical, and biological covariates and conventional cardiovascular risk factors. Results Higher parental LE8 DNAm score was associated with lower offspring cIMT (β = −0.022 mm/SD; p-value = 0.02), although the association was attenuated after adjustment for parental cardiovascular risk factors. In G1, a higher baseline DNAm score was associated with lower cIMT measured seven years later (β = −0.030 mm/SD; p-value = 1.1 × 10⁻⁵). This association remained significant after adjustment for follow-up cardiovascular risk factors (p-value=0.009) but not after additional adjustment for prior cIMT. Cross-sectionally, higher DNAm score was associated with lower cIMT in both generations, with attenuation after risk factor adjustment in G1 but not G0. Associations with carotid plaque were not significant. Genes associated with the DNAm score were enriched for immune and inflammatory pathways. Conclusions An LE8-derived DNAm score was associated with lower cIMT across the life course and, to a lesser extent, across generations. These findings suggest that blood DNAm reflects cumulative cardiovascular health and vascular burden and may complement conventional cardiovascular risk assessment.

BACKGROUND:High body mass index (BMI) in adolescence is associated with accelerated biological aging, which might predict the onset of obesity-related diseases before they develop. Genetic factors may shape both adolescent BMI and weight trajectories. METHODS:Participants were from the Young Finns Study (n = 3 596, ages 3-18 at baseline), followed from 1980 to 2018-2020. Biological aging was estimated using DNA methylation based epigenetic clocks DunedinPACE (years/calendar year) and PC-GrimAge (years) at three follow-ups (ages 15-56, n = 2045). Genetic predispositions to BMI and childhood body size were quantified using polygenic risk scores (PRSs) (941 and 286 genetic variants). BMI trajectories were modelled from BMI measured at ages 9, 12, 15 and 18 using latent growth curve modelling. Path analysis was used to examine whether genetic liability to BMI is associated with biological aging and if BMI trajectories in adolescence mediate this association. The causal effect of genetically predicted adolescent BMI on biological aging in adulthood was examined with Mendelian randomisation (MR) using individual-level data. RESULTS:Higher level of adolescent BMI partly mediated the association between higher BMI-PRS and accelerated biological aging from late adolescence to middle adulthood. MR analyses supported a positive causal effect from genetically predicted adolescent BMI on biological aging, and the causal effect was more consistent when DunedinPACE was used to measure biological aging in 2011 (causal estimate = 0.020 [95% CI = 0.008, 0.031]) and 2018 (0.019 [0.003, 0.035]). CONCLUSIONS:Our findings indicate that high BMI in adolescence may accelerate biological aging, especially in individuals with a genetic predisposition to high BMI. Adolescents with a genetic susceptibility to high BMI and elevated BMI might be prone to obesity-related health risks, highlighting early prevention strategies' importance.

Sleep disturbances are known to have adverse effects on health, but knowledge on the effect of sleep disturbances on epigenetic ageing is limited. We investigated (1) whether symptoms of insomnia, obstructive sleep apnoea, sleep deprivation, and circadian rhythm lateness are associated with epigenetic ageing, and (2) whether years spent in shift work moderates these associations. We used the population-based Young Finns data (n = 1618). Epigenetic clocks such as AgeDevHannum, AgeDevHorvath, AgeDevPheno, AgeDevGrim, and DunedinPACE were utilized to measure epigenetic ageing. Sleep was evaluated using various validated self-report questionnaires. Covariates included sex, array type, smoking status, health behaviours, socioeconomic factors, and cardiovascular health factors. Among the various sleep measures, obstructive sleep apnoea symptoms were most consistently linked to accelerated epigenetic ageing, as measured by AgeDevGrim and DunedinPACE. Insomnia, sleep deprivation, and years spent in shift work were not associated with epigenetic ageing after adjusting for health-related or socioeconomic covariates. Additionally, we found interactions between years spent in shift work and sleep disturbances when accounting for epigenetic ageing. Among those with little to no history of shift work, both insomnia and sleep deprivation were associated with more accelerated epigenetic ageing in AgeDevGrim when compared to long-term shift workers. However, the pace of epigenetic ageing (measured with DunedinPACE) appears to be higher in those with both sleep deprivation and longer history of shift work. Among various sleep measures, symptoms of obstructive sleep apnoea appear to be most consistently associated with accelerated epigenetic ageing even after adjusting for various health-related and socioeconomic factors. Shift work seems to have a crucial role in the relationship between sleep disturbances and epigenetic ageing in working-age adults.

Polygenic scores (PGSs) for body mass index (BMI) may guide early prevention and targeted treatment of obesity. Using genetic data from up to 5.1 million people (4.6% African ancestry, 14.4% American ancestry, 8.4% East Asian ancestry, 71.1% European ancestry and 1.5% South Asian ancestry) from the GIANT consortium and 23andMe, Inc., we developed ancestry-specific and multi-ancestry PGSs. The multi-ancestry score explained 17.6% of BMI variation among UK Biobank participants of European ancestry. For other populations, this ranged from 16% in East Asian-Americans to 2.2% in rural Ugandans. In the ALSPAC study, children with higher PGSs showed accelerated BMI gain from age 2.5 years to adolescence, with earlier adiposity rebound. Adding the PGS to predictors available at birth nearly doubled explained variance for BMI from age 5 onward (for example, from 11% to 21% at age 8). Up to age 5, adding the PGS to early-life BMI improved prediction of BMI at age 18 (for example, from 22% to 35% at age 5). Higher PGSs were associated with greater adult weight gain. In intensive lifestyle intervention trials, individuals with higher PGSs lost modestly more weight in the first year (0.55 kg per s.d.) but were more likely to regain it. Overall, these data show that PGSs have the potential to improve obesity prediction, particularly when implemented early in life.

Non-coding 886 (nc886, vtRNA2-1) is a polymorphically imprinted gene. The methylation status of this locus has been shown to be associated with periconceptional conditions, and both the methylation status and the levels of nc886 RNAs have been shown to associate with later-life health traits. We have previously shown that nc886 RNA levels are associated not only with the methylation status of the locus, but also with a genetic polymorphism upstream from the locus. In this study, we describe the genetic and epigenetic regulators that predict lifelong nc886 RNA levels, as well as their association with cardiometabolic disease (CMD) risk factors and events. We utilised six population cohorts and one CMD cohort comprising 9058 individuals in total. The association of nc886 RNA levels, as predicted by epigenetic and genetic regulators, with CMD phenotypes was analysed using regression models, with a meta-analysis of the results. The meta-analysis showed that individuals with upregulated nc886 RNA levels have higher diastolic blood pressure (β = 0.07, p = 0.008), lower HDL levels (β = − 0.07, p = 0.006) and an increased incidence of type 2 diabetes (OR = 1.260, p = 0.013). Moreover, CMD patients with upregulated nc886 RNA levels have an increased incidence of stroke (OR = 1.581, p = 0.006) and death (OR = 1.290, p = 0.046). In conclusion, we show that individuals who are predicted to present elevated nc886 RNA levels have poorer cardiovascular health and are at an elevated risk of complications in secondary prevention. This unique mechanism yields metabolic variation in human populations, constituting a CMD risk factor that cannot be modified through lifestyle choices.

Recent genome wide association studies (GWAS) found associations between clozapine serum levels and single nucleotide polymorphisms (SNP) in intragenic region between cytochrome P450 1A1 (CYP1A1) and CYP1A2 and nuclear factor 1B (NFIB). The aim of this study was to perform another GWAS of polymorphisms associated with the serum levels of clozapine and norclozapine, their ratios, and to perform meta-analyses with two previous GWAS. Finnish clozapine patients (n = 170) with known smoking habits were genotyped. GWAS was performed with clozapine concentration/dose ratio (C/D), norclozapine C/D and clozapine/norclozapine-ratio as phenotypes, adjusting for age, sex and first four genetic principal components, and additionally for smoking and valproate use. The two other patient populations were from the British CLOZUK2 study (n = 2989) and Norwegian Diakonhjemmet Hospital study (n = 484). In the three population (n = 3643) meta-analyses the top SNP associated with the clozapine C/D ratio was rs2472297, located between the CYP1A1 and CYP1A2 genes. For the norclozapine C/D ratio, an association signal was found near uridine-5´-diphospho-glucunorosyltransferase (UGT) UGT2B10 gene. Additionally, rs3732218, an intron variant in the UGT1A family gene complex, was associated with norclozapine C/D. Lead SNP associated with the clozapine/norclozapine ratio was rs6827692, an intron variant near UGT2B7 gene. In the two population meta-analyses (n = 654) adjusting for smoking and valproate use, the UGT2B10 intron variant rs835309 was associated with the clozapine/norclozapine ratio. We suggest a UGT2B10 missense SNP rs61750900, in perfect linkage disequilibrium with UGT2B10 rs835309, as the probable causal variant. Our study confirms and extends the number of genetic variants affecting clozapine and norclozapine metabolism.

X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits ( n = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4 , CLDN2 , TSPAN6 and the female-specific DRP2 . Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R , and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1 . All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.

BackgroundStudies have shown that cardiovascular health (CVH) is related to depression. We aimed to identify gene networks jointly associated with depressive symptoms and cardiovascular health metrics using the whole blood transcriptome.Materials and methodsWe analyzed human blood transcriptomic data to identify gene co-expression networks, termed gene modules, shared by Beck’s depression inventory (BDI-II) scores and cardiovascular health (CVH) metrics as markers of depression and cardiovascular health, respectively. The BDI-II scores were derived from Beck’s Depression Inventory, a 21-item self-report inventory that measures the characteristics and symptoms of depression. CVH metrics were defined according to the American Heart Association criteria using seven indices: smoking, diet, physical activity, body mass index (BMI), blood pressure, total cholesterol, and fasting glucose. Joint association of the modules, identified with weighted co-expression analysis, as well as the member genes of the modules with the markers of depression and CVH were tested with multivariate analysis of variance (MANOVA).ResultsWe identified a gene module with 256 genes that were significantly correlated with both the BDI-II score and CVH metrics. Based on the MANOVA test results adjusted for age and sex, the module was associated with both depression and CVH markers. The three most significant member genes in the module were YOD1, RBX1, and LEPR. Genes in the module were enriched with biological pathways involved in brain diseases such as Alzheimer’s, Parkinson’s, and Huntington’s.ConclusionsThe identified gene module and its members can provide new joint biomarkers for depression and CVH.

BACKGROUND:Sialorrhea is a common and uncomfortable adverse effect of clozapine, and its severity varies between patients. The aim of the study was to select broadly genes related to the regulation of salivation and study associations between sialorrhea and dry mouth and polymorphisms in the selected genes. METHODS:The study population consists of 237 clozapine-treated patients, of which 172 were genotyped. Associations between sialorrhea and dry mouth with age, sex, BMI, smoking, clozapine dose, clozapine and norclozapine serum levels, and other comedication were studied. Genetic associations were analyzed with linear and logistic regression models explaining sialorrhea and dry mouth with each SNP added separately to the model as coefficients. RESULTS:Clozapine dose, clozapine or norclozapine concentration and their ratio were not associated with sialorrhea or dryness of mouth. Valproate use (p = 0.013) and use of other antipsychotics (p = 0.015) combined with clozapine were associated with excessive salivation. No associations were found between studied polymorphisms and sialorrhea. In analyses explaining dry mouth with logistic regression with age and sex as coefficients, two proxy-SNPs were associated with dry mouth: epidermal growth factor receptor 4 (ERBB4) rs3942465 (adjusted p = 0.025) and tachykinin receptor 1 (TACR1) rs58933792 (adjusted p = 0.029). CONCLUSION:Use of valproate or antipsychotic polypharmacy may increase the risk of sialorrhea. Genetic variations in ERBB4 and TACR1 might contribute to experienced dryness of mouth among patients treated with clozapine.

Evidence is accumulating on the connection of early adversities and harsh family environment with epigenetic ageing. We investigated whether early psychosocial resilience is associated with epigenetic ageing in adulthood. We used the population-based Young Finns data (n = 1593). Early psychosocial resilience was assessed in 1980-1989 across five broad domains: (1) index of psychological strength (self-esteem at home/in general/at school, perceived possibilities to influence at home, internal life control), (2) index of social satisfaction (perceived support from family/friends and life satisfaction), (3) index of leisure time activities (hobbies and physical fitness), (4) index of responsible health behaviors (infrequent smoking or alcohol consumption), and (5) index of school career (school grades and adaptation). Epigenetic ages were calculated for blood samples from 2011, and the analyses were performed with variables describing age deviation (AgeDevHannum, AgeDevHorvath, AgeDevPheno, AgeDevGrim) and DunedinPACE. Covariates included early family environment, polygenic risk scores for schizophrenia and major depression, adulthood education, and adulthood health behaviors. All of the early resilience indexes were associated with lower levels of epigenetic ageing in adulthood, most consistently with AgeDevGrim and DunedinPACE. The associations of psychological strength and social satisfaction, in particular, seemed to be non-linear. In a smaller subsample (n = 289), high early resilience was related to lower AgeDevGrim over a 25-year follow-up in those who had high "baseline" levels of AgeDevGrim. In conclusion, early resilience seems to associate with lower level of epigenetic ageing in adulthood. Our results tentatively suggest that early resilience may increase "equality in epigenetic ageing" in a general population.

Objective:Cloninger's temperament dimensions have been studied widely in relation to genetics. In this study, we examined Cloninger's temperament dimensions grouped with cluster analyses and their association with single nucleotide polymorphisms (SNPs). This study included 212 genotyped Finnish patients from the Ostrobothnia Depression Study.Methods:The temperament clusters were analysed at baseline and at six weeks from the beginning of the depression intervention study. We selected depression-related catecholamine and serotonin genes based on a literature search, and 59 SNPs from ten different genes were analysed. The associations of single SNPs with temperament clusters were studied. Using the selected genes, genetic risk score (GRS) analyses were conducted considering appropriate confounding factors.Results:No single SNP had a significant association with the temperament clusters. Associations between GRSs and temperament clusters were observed in multivariate models that were significant after permutation analyses. Two SNPs from the DRD3 gene, two SNPs from the SLC6A2 gene, one SNP from the SLC6A4 gene, and one SNP from the HTR2A gene associated with the HHA/LRD/LP (high harm avoidance, low reward dependence, low persistence) cluster at baseline. Two SNPs from the HTR2A gene were associated with the HHA/LRD/LP cluster at six weeks. Two SNPs from the HTR2A gene and two SNPs from the COMT gene were associated with the HP (high persistence) cluster at six weeks.Conclusion:GRSs seem to associate with an individual's temperament profile, which can be observed in the clusters used. Further research needs to be conducted on these types of clusters and their clinical applicability.

Objective:Associations between leptin (LEP) and leptin receptor (LEPR) gene polymorphismsand mood disorders have been found but not yet confirmed in multiple studies. The aim of ourstudy was to study the associations betweenLEPandLEPRsingle nucleotide polymorphisms(SNPs) and treatment response of depression. Associations between leptin levels anddepression severity were also investigated.Methods:The data included 242 depressed patientsin secondary psychiatric care. Symptoms of depression were assessed with the Montgomery-& Aring;sberg Depression Rating Scale (MADRS). Previously foundLEPandLEPRSNPs associatedwith depression and other mood disorders were studied. Furthermore, all availableLEPandLEPRSNPs were clumped using proxy SNPs to represent gene areas inr(2)>0.2 linkagedisequilibrium and their association with treatment response was analysed with logisticregression.Results:Two proxy SNPs ofLEPRgene, rs12564738 and rs12029311, were associatedwith MADRS response at 6 weeks (padjusted=0.024,padjusted=0.024). SNPs from previousstudies were not associated with MADRS response, butLEPRrs12145690 from a previous studywas strongly associated with rs12564738 (r(2)=0.94). The positive association between leptinlevels and MADRS score at baseline after adjusting with age, sex, body mass index (BMI),Alcohol Use Disorders Identification Test score, and smoking was found (p=0.011).Conclusion:Our findings suggest thatLEPRpolymorphisms are associated with depressiontreatment response. We also found associations between leptin levels and depressionindependently of BMI. Further studies and meta-analyses are needed to confirm thesignificance of found SNPs and the role of leptin in depression.

Eastern and Western Finns show a striking difference in coronary heart disease-related mortality; genetics is a known contributor for this discrepancy. Here, we discuss the potential role of DNA methylation in mediating the discrepancy in cardiometabolic disease-risk phenotypes between the sub-populations. We used data from the Young Finns Study (n = 969) to compare the genome-wide DNA methylation levels of East- and West-originating Finns. We identified 21 differentially methylated loci (FDR < 0.05; Δβ >2.5%) and 7 regions (smoothed FDR < 0.05; CpGs ≥ 5). Methylation at all loci and regions associates with genetic variants (p < 5 × 10−8). Independently of genetics, methylation at 11 loci and 4 regions associates with transcript expression, including genes encoding zinc finger proteins. Similarly, methylation at 5 loci and 4 regions associates with cardiometabolic disease-risk phenotypes including triglycerides, glucose, cholesterol, as well as insulin treatment. This analysis was also performed in LURIC (n = 2371), a German cardiovascular patient cohort, and results replicated for the association of methylation at cg26740318 and DMR_11p15 with diabetes-related phenotypes and methylation at DMR_22q13 with triglyceride levels. Our results indicate that DNA methylation differences between East and West Finns may have a functional role in mediating the cardiometabolic disease discrepancy between the sub-populations.

Background Pubertal growth patterns correlate with future health outcomes. However, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Translation And Rotation (SITAR) growth curve analysis on ~ 56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pubertal growth spurt. To investigate the lifelong impact of genetic variants associated with pubertal growth trajectories, we performed genetic correlation analyses and phenome-wide association studies in the Penn Medicine BioBank and the UK Biobank. Results Large-scale growth modeling enables an unprecedented view of adolescent growth across contemporary and 20th-century pediatric cohorts. We identify 26 genome-wide significant loci and leverage trans-ancestry data to perform fine-mapping. Our data reveals genetic relationships between pediatric height growth and health across the life course, with different growth trajectories correlated with different outcomes. For instance, a faster tempo of pubertal growth correlates with higher bone mineral density, HOMA-IR, fasting insulin, type 2 diabetes, and lung cancer, whereas being taller at early puberty, taller across puberty, and having quicker pubertal growth were associated with higher risk for atrial fibrillation. Conclusion We report novel genetic associations with the tempo of pubertal growth and find that genetic determinants of growth are correlated with reproductive, glycemic, respiratory, and cardiac traits in adulthood. These results aid in identifying specific growth trajectories impacting lifelong health and show that there may not be a single “optimal” pubertal growth pattern.