Trans-ancestral genome-wide association study of longitudinal pubertal height growth and shared heritability with adult health outcomes.

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.

Using collective intelligence methods to improve government data infrastructures and promote the use of complex data: The example of the Northern Ireland Longitudinal Study.

BACKGROUND: This paper discusses how collective intelligence (CI) methods can be implemented to improve government data infrastructures, not only to support understanding and primary use of complex national data but also to increase the dissemination and secondary impact of research based on these data. The case study uses the Northern Ireland Longitudinal Study (NILS), a member of the UK family of census/administrative data longitudinal studies (UKLS). METHODS: A stakeholder-engaged CI approach was applied to inform the transformation of the NILS Research Support Unit (RSU) infrastructure to support researchers in their use of government data, including collaborative decision-making and better dissemination of research outputs. RESULTS: We provide an overview of NILS RSU infrastructure design changes that have been implemented to date, focusing on a website redesign to meet user information requirements and the formation of better working partnerships between data users and providers within the Northern Ireland data landscape. We also discuss the key challenges faced by the design team during this project of transformation. CONCLUSION: Our primary objective to improve government data infrastructure and to increase dissemination and the impact of research based on data was a complex and multifaceted challenge due to the number of stakeholders involved and their often conflicting perspectives. Results from this CI approach have been pivotal in highlighting how NILS RSU can work collaboratively with users to maximize the potential of this data, in terms of forming multidisciplinary networks to ensure the research is utilized in policy and in the literature and providing academic support and resources to attract new researchers.

Neonatal mortality risk of large-for-gestational-age and macrosomic live births in 15 countries, including 115.6 million nationwide linked records, 2000-2020.

OBJECTIVE: We aimed to compare the prevalence and neonatal mortality associated with large for gestational age (LGA) and macrosomia among 115.6 million live births in 15 countries, between 2000 and 2020. DESIGN: Population-based, multi-country study. SETTING: National healthcare systems. POPULATION: Liveborn infants. METHODS: We used individual-level data identified for the Vulnerable Newborn Measurement Collaboration. We calculated the prevalence and relative risk (RR) of neonatal mortality among live births born at term + LGA (>90th centile, and also >95th and >97th centiles when the data were available) versus term + appropriate for gestational age (AGA, 10th-90th centiles) and macrosomic (≥4000, ≥4500 and ≥5000 g, regardless of gestational age) versus 2500-3999 g. INTERGROWTH 21st served as the reference population. MAIN OUTCOME MEASURES: Prevalence and neonatal mortality risks. RESULTS: Large for gestational age was common (median prevalence 18.2%; interquartile range, IQR, 13.5%-22.0%), and overall was associated with a lower neonatal mortality risk compared with AGA (RR 0.83, 95% CI 0.77-0.89). Around one in ten babies were ≥4000 g (median prevalence 9.6% (IQR 6.4%-13.3%), with 1.2% (IQR 0.7%-2.0%) ≥4500 g and with 0.2% (IQR 0.1%-0.2%) ≥5000 g). Overall, macrosomia of ≥4000 g was not associated with increased neonatal mortality risk (RR 0.80, 95% CI 0.69-0.94); however, a higher risk was observed for birthweights of ≥4500 g (RR 1.52, 95% CI 1.10-2.11) and ≥5000 g (RR 4.54, 95% CI 2.58-7.99), compared with birthweights of 2500-3999 g, with the highest risk observed in the first 7 days of life. CONCLUSIONS: In this population, birthweight of ≥4500 g was the most useful marker for early mortality risk in big babies and could be used to guide clinical management decisions.

Neonatal mortality risk for vulnerable newborn types in 15 countries using 125.5 million nationwide birth outcome records, 2000-2020.

OBJECTIVE: To compare neonatal mortality associated with six novel vulnerable newborn types in 125.5 million live births across 15 countries, 2000-2020. DESIGN: Population-based, multi-country study. SETTING: National data systems in 15 middle- and high-income countries. METHODS: We used individual-level data sets identified for the Vulnerable Newborn Measurement Collaboration. We examined the contribution to neonatal mortality of six newborn types combining gestational age (preterm [PT] versus term [T]) and size-for-gestational age (small [SGA], <10th centile, appropriate [AGA], 10th-90th centile or large [LGA], >90th centile) according to INTERGROWTH-21st newborn standards. Newborn babies with PT or SGA were defined as small and T + LGA was considered as large. We calculated risk ratios (RRs) and population attributable risks (PAR%) for the six newborn types. MAIN OUTCOME MEASURES: Mortality of six newborn types. RESULTS: Of 125.5 million live births analysed, risk ratios were highest among PT + SGA (median 67.2, interquartile range [IQR] 45.6-73.9), PT + AGA (median 34.3, IQR 23.9-37.5) and PT + LGA (median 28.3, IQR 18.4-32.3). At the population level, PT + AGA was the greatest contributor to newborn mortality (median PAR% 53.7, IQR 44.5-54.9). Mortality risk was highest among newborns born before 28 weeks (median RR 279.5, IQR 234.2-388.5) compared with babies born between 37 and 42 completed weeks or with a birthweight less than 1000 g (median RR 282.8, IQR 194.7-342.8) compared with those between 2500 g and 4000 g as a reference group. CONCLUSION: Preterm newborn types were the most vulnerable, and associated with the highest mortality, particularly with co-existence of preterm and SGA. As PT + AGA is more prevalent, it is responsible for the greatest burden of neonatal deaths at population level.

Vulnerable newborn types: Analysis of population-based registries for 165 million births in 23 countries, 2000-2021.

OBJECTIVE: To examine the prevalence of novel newborn types among 165 million live births in 23 countries from 2000 to 2021. DESIGN: Population-based, multi-country analysis. SETTING: National data systems in 23 middle- and high-income countries. POPULATION: Liveborn infants. METHODS: Country teams with high-quality data were invited to be part of the Vulnerable Newborn Measurement Collaboration. We classified live births by six newborn types based on gestational age information (preterm <37 weeks versus term ≥37 weeks) and size for gestational age defined as small (SGA, <10th centile), appropriate (10th-90th centiles), or large (LGA, >90th centile) for gestational age, according to INTERGROWTH-21st standards. We considered small newborn types of any combination of preterm or SGA, and term + LGA was considered large. Time trends were analysed using 3-year moving averages for small and large types. MAIN OUTCOME MEASURES: Prevalence of six newborn types. RESULTS: We analysed 165 017 419 live births and the median prevalence of small types was 11.7% - highest in Malaysia (26%) and Qatar (15.7%). Overall, 18.1% of newborns were large (term + LGA) and was highest in Estonia 28.8% and Denmark 25.9%. Time trends of small and large infants were relatively stable in most countries. CONCLUSIONS: The distribution of newborn types varies across the 23 middle- and high-income countries. Small newborn types were highest in west Asian countries and large types were highest in Europe. To better understand the global patterns of these novel newborn types, more information is needed, especially from low- and middle-income countries.

The relationship of life-course patterns of adiposity with type 2 diabetes, depression, and their comorbidity in the Northern Finland Birth Cohort 1966.

OBJECTIVES: Type 2 diabetes (T2D) and comorbid depression challenges clinical management particularly in individuals with overweight. We aim to explore the shared etiology, via lifecourse adiposity, between T2D and depression. METHODS: We used data from birth until 46years from Northern Finland Birth Cohort 1966 (n = 6,372; 53.8% females). We conducted multivariate analyses on three outcomes: T2D (4.2%), depression (19.2%) and as comorbidity (1.8%). We conducted (i) Path analysis to clarify time-dependent body mass index (BMI) related pathways, including BMI polygenic risk scores (PRS); and (ii) Cox regression models to assess whether reduction of overweight between 7years and 31years influence T2D, depression and/or comorbidity. The models were tested for covariation with sex, education, smoking, physical activity, and diet score. RESULTS: The odd ratios (OR) of T2D in individuals with depression was 1.68 [95% confidence interval (CI): 1.34-2.11], and no change in estimate was observed when adjusted for covariates. T2D and comorbidity showed similar patterns of relationships in the path analyses (P < 0.001). The genetic risk for obesity (PRS BMI) did not show direct effect on T2D or comorbidity in adulthood but indirectly through measures of adiposity in early childhood and mid-adulthood in the path analysis (P < 0.001). Having early-onset of overweight at 7years and 31years showed highest risk of T2D (OR 3.8, 95%CI 2.4-6.1) and comorbidity (OR 5.0, 95%CI 2.7-9.5), with mild-to-moderate attenuation with adjustments. Depression showed no significant associations. CONCLUSIONS: We found evidence for overweight since childhood as a risk factor for T2D and co-morbidity between T2D and depression, influenced moderately by lifestyle factors in later life. However, no shared early life adiposity related risk factors were observed between T2D and depression when assessed independently in this Finnish setting.

Maternal haemoglobin levels in pregnancy and child DNA methylation: a study in the pregnancy and childhood epigenetics consortium.

Altered maternal haemoglobin levels during pregnancy are associated with pre-clinical and clinical conditions affecting the fetus. Evidence from animal models suggests that these associations may be partially explained by differential DNA methylation in the newborn with possible long-term consequences. To test this in humans, we meta-analyzed the epigenome-wide associations of maternal haemoglobin levels during pregnancy with offspring DNA methylation in 3,967 newborn cord blood and 1,534 children and 1,962 adolescent whole-blood samples derived from 10 cohorts. DNA methylation was measured using Illumina Infinium Methylation 450K or MethylationEPIC arrays covering 450,000 and 850,000 methylation sites, respectively. There was no statistical support for the association of maternal haemoglobin levels with offspring DNA methylation either at individual methylation sites or clustered in regions. For most participants, maternal haemoglobin levels were within the normal range in the current study, whereas adverse perinatal outcomes often arise at the extremes. Thus, this study does not rule out the possibility that associations with offspring DNA methylation might be seen in studies with more extreme maternal haemoglobin levels.

DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespan.

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 × 10-7; Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.

Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts.

BACKGROUND: There are various maternal prenatal biopsychosocial (BPS) predictors of birth weight, making it difficult to quantify their cumulative relationship. METHODS: We studied two birth cohorts: Northern Finland Birth Cohort 1986 (NFBC1986) born in 1985-1986 and the Generation R Study (from the Netherlands) born in 2002-2006. In NFBC1986, we selected variables depicting BPS exposure in association with birth weight and performed factor analysis to derive latent constructs representing the relationship between these variables. In Generation R, the same factors were generated weighted by loadings of NFBC1986. Factor scores from each factor were then allocated into tertiles and added together to calculate a cumulative BPS score. In all cases, we used regression analyses to explore the relationship with birth weight corrected for sex and gestational age and additionally adjusted for other factors. RESULTS: Factor analysis supported a four-factor structure, labelled closely to represent their characteristics as 'Factor1-BMI' (body mass index), 'Factor2-DBP' (diastolic blood pressure), 'Factor3-Socioeconomic-Obstetric-Profile' and 'Factor4-Parental-Lifestyle'. In both cohorts, 'Factor1-BMI' was positively associated with birth weight, whereas other factors showed negative association. 'Factor3-Socioeconomic-Obstetric-Profile' and 'Factor4-Parental-Lifestyle' had the greatest effect size, explaining 30% of the variation in birth weight. Associations of the factors with birth weight were largely driven by 'Factor1-BMI'. Graded decrease in birth weight was observed with increasing cumulative BPS score, jointly evaluating four factors in both cohorts. CONCLUSION: Our study is a proof of concept for maternal prenatal BPS hypothesis, highlighting the components snowball effect on birth weight in two different European birth cohorts.

Early exposure to social disadvantages and later life body mass index beyond genetic predisposition in three generations of Finnish birth cohorts.

BACKGROUND: The study aimed to explore the association between early life and life-course exposure to social disadvantage and later life body mass index (BMI) accounting for genetic predisposition and maternal BMI. METHODS: We studied participants of Helsinki Birth Cohort Study born in 1934-1944 (HBCS1934-1944, n = 1277) and Northern Finland Birth Cohorts born in 1966 and 1986 (NFBC1966, n = 5807, NFBC1986, n = 6717). Factor analysis produced scores of social disadvantage based on social and economic elements in early life and adulthood/over the life course, and was categorized as high, intermediate and low. BMI was measured at 62 years in HBCS1934-1944, at 46 years in NFBC1966 and at 16 years in NFBC1986. Multivariable linear regression analysis was used to explore associations between social disadvantages and BMI after adjustments for polygenic risk score for BMI (PRS BMI), maternal BMI and sex. RESULTS: The association between exposure to high early social disadvantage and increased later life BMI persisted after adjustments (ß = 0.79, 95% CI, 0.33, 1.25, p < 0.001) in NFBC1966. In NFBC1986 this association was attenuated by PRS BMI (p = 0.181), and in HBCS1934-1944 there was no association between high early social disadvantage and increased later life BMI (ß 0.22, 95% CI -0.91,1.35, p = 0.700). In HBCS1934-1944 and NFBC1966, participants who had reduced their exposure to social disadvantage during the life-course had lower later life BMI than those who had increased their exposure (ß - 1.34, [- 2.37,-0.31], p = 0.011; ß - 0.46, [- 0.89,-0.03], p = 0.038, respectively). CONCLUSIONS: High social disadvantage in early life appears to be associated with higher BMI in later life. Reducing exposure to social disadvantage during the life-course may be a potential pathway for obesity reduction.

Could vitamin D reduce obesity-associated inflammation? Observational and Mendelian randomization study.

BACKGROUND: Obesity is associated with inflammation but the role of vitamin D in this process is not clear. OBJECTIVES: We aimed to assess the associations between serum 25-hydroxyvitamin D [25(OH)D], BMI, and 16 inflammatory biomarkers, and to assess the role of vitamin D as a potential mediator in the association between higher BMI and inflammation. METHODS: Northern Finland Birth Cohort 1966 (NFBC1966) 31-y data on 3586 individuals were analyzed to examine the observational associations between BMI, 25(OH)D, and 16 inflammatory biomarkers. Multivariable regression analyses and 2-sample regression-based Mendelian randomization (MR) mediation analysis were performed to assess any role of vitamin D in mediating a causal effect of BMI on inflammatory biomarkers [soluble intercellular adhesion molecule 1 (sICAM-1), high sensitivity C-reactive protein (hs-CRP), and α1-acid glycoprotein (AGP)] for which observational associations were detected. For MR, genome-wide association study summary results ranging from 5163 to 806,834 individuals were used for biomarkers, 25(OH)D, and BMI. Findings were triangulated with a literature review of vitamin D supplementation trials. RESULTS: In NFBC1966, mean BMI (kg/m2) was 24.8 (95% CI: 24.7, 25.0) and mean 25(OH)D was 50.3 nmol/L (95% CI: 49.8, 50.7 nmol/L). Inflammatory biomarkers correlated as 4 independent clusters: interleukins, adhesion molecules, acute-phase proteins, and chemokines. BMI was positively associated with 9 inflammatory biomarkers and inversely with 25(OH)D (false discovery rate < 0.05). 25(OH)D was inversely associated with sICAM-1, hs-CRP, and AGP, which were positively associated with BMI. The MR analyses showed causal association of BMI on these 3 inflammatory biomarkers. There was no observational or MR evidence that circulating 25(OH)D concentrations mediated the association between BMI and these 3 inflammatory markers. Review of randomized controlled trials (RCTs) supported our findings showing no impact of vitamin D supplementation on inflammatory biomarkers. CONCLUSIONS: The findings from our observational study and causal MR analyses, together with data from RCTs, do not support a beneficial role of vitamin D supplementation on obesity-related inflammation.

GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI.

Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.

A trans-ancestral meta-analysis of genome-wide association studies reveals loci associated with childhood obesity.

Although hundreds of genome-wide association studies-implicated loci have been reported for adult obesity-related traits, less is known about the genetics specific for early-onset obesity and with only a few studies conducted in non-European populations to date. Searching for additional genetic variants associated with childhood obesity, we performed a trans-ancestral meta-analysis of 30 studies consisting of up to 13 005 cases (≥95th percentile of body mass index (BMI) achieved 2-18 years old) and 15 599 controls (consistently <50th percentile of BMI) of European, African, North/South American and East Asian ancestry. Suggestive loci were taken forward for replication in a sample of 1888 cases and 4689 controls from seven cohorts of European and North/South American ancestry. In addition to observing 18 previously implicated BMI or obesity loci, for both early and late onset, we uncovered one completely novel locus in this trans-ancestral analysis (nearest gene, METTL15). The variant was nominally associated with only the European subgroup analysis but had a consistent direction of effect in other ethnicities. We then utilized trans-ancestral Bayesian analysis to narrow down the location of the probable causal variant at each genome-wide significant signal. Of all the fine-mapped loci, we were able to narrow down the causative variant at four known loci to fewer than 10 single nucleotide polymorphisms (SNPs) (FAIM2, GNPDA2, MC4R and SEC16B loci). In conclusion, an ethnically diverse setting has enabled us to both identify an additional pediatric obesity locus and further fine-map existing loci.

Maternal hemoglobin associates with preterm delivery and small for gestational age in two Finnish birth cohorts.

OBJECTIVE: To test whether maternal hemoglobin during pregnancy associates with offspring perinatal outcomes in a developed country. Changes in maternal hemoglobin concentration during pregnancy are partly physiological phenomena reflecting alterations of maternal blood volume. Especially hemoglobin measures outside the physiological range may influence maternal health and fetal growth with long-lasting consequences. STUDY DESIGN: We studied an unselected sample drawn from two regional birth cohorts born 20 years apart: The Northern Finland Birth Cohorts 1966 and 1986. These are two mother-and-child population-based birth cohorts together comprising 21,710 mothers and their children. After exclusions, the sample size of the current study was 20,554. Concentrations of maternal hemoglobin at first and last antenatal visits were categorized as low (lowest 10%), medium (reference) or high (highest 10%). Multinomial logistic regression analyses for categories of maternal hemoglobin and perinatal outcomes such as preterm delivery and full-term small and large for gestational age were conducted with adjustments for maternal cofactors. RESULTS: Low maternal hemoglobin at early pregnancy associated with decreased risk of full-term small for gestational age (adjusted OR 0.73, 95% CI [0.58, 0.93], p = 0.010). At late pregnancy, low maternal hemoglobin associated with increased risk of preterm delivery (adjusted OR 1.60, 95% CI [1.26, 2.02], p < 0.0005) whereas high maternal hemoglobin associated with increased risk of full-term small for gestational age (adjusted OR 1.29, 95% CI [1.07, 1.56], p = 0.009). Maternal hemoglobin did not show constant association with risk of large for gestational age. CONCLUSION: The results from this study support evidence that both low and high maternal hemoglobin associate with adverse perinatal outcomes. Low maternal hemoglobin associated with preterm delivery and high with full-term small for gestational age. Association was mainly present when maternal hemoglobin was measured during the third trimester. These results indicate that it is important to monitor both extremes of maternal hemoglobin throughout the pregnancy.

Understanding the complexity of glycaemic health: systematic bio-psychosocial modelling of fasting glucose in middle-age adults; a DynaHEALTH study.

BACKGROUND: The prevention of the risk of type 2 diabetes (T2D) is complicated by multidimensional interplays between biological and psychosocial factors acting at the individual level. To address the challenge we took a systematic approach, to explore the bio-psychosocial predictors of blood glucose in mid-age. METHODS: Based on the 31-year and 46-year follow-ups (5,078 participants, 43% male) of Northern Finland Birth Cohort 1966, we used a systematic strategy to select bio-psychosocial variables at 31 years to enable a data-driven approach. As selection criteria, the variable must be (i) a component of the metabolic syndrome or an indicator of psychosocial health using WHO guidelines, (ii) easily obtainable in general health check-ups and (iii) associated with fasting blood glucose at 46 years (P < 0.10). Exploratory and confirmatory factor analysis were used to derive latent factors, and stepwise linear regression allowed exploration of relationships between factors and fasting glucose. RESULTS: Of all 26 variables originally considered, 19 met the selection criteria and were included in an exploratory factor analysis. Two variables were further excluded due to low loading (<0.3). We derived four latent factors, which we named as socioeconomic, metabolic, psychosocial and blood pressure status. The combination of metabolic and psychosocial factors, adjusted for sex, provided best prediction of fasting glucose at 46 years (explaining 10.7% of variation in glucose; P < 0.001). Regarding different bio-psychosocial pathways and relationships, the importance of psychosocial factors in addition to established metabolic risk factors was highlighted. CONCLUSIONS: The present study supports evidence for the bio-psychosocial nature of adult glycemic health and exemplifies an evidence-based approach to model the bio-psychosocial relationships. The factorial model may help further research and public health practice in focusing also on psychosocial aspects in maintaining normoglycaemia in the prevention of cardio-metabolic diseases.

Association of maternal prenatal smoking GFI1-locus and cardio-metabolic phenotypes in 18,212 adults.

BACKGROUND: DNA methylation at the GFI1-locus has been repeatedly associated with exposure to smoking from the foetal period onwards. We explored whether DNA methylation may be a mechanism that links exposure to maternal prenatal smoking with offspring's adult cardio-metabolic health. METHODS: We meta-analysed the association between DNA methylation at GFI1-locus with maternal prenatal smoking, adult own smoking, and cardio-metabolic phenotypes in 22 population-based studies from Europe, Australia, and USA (n = 18,212). DNA methylation at the GFI1-locus was measured in whole-blood. Multivariable regression models were fitted to examine its association with exposure to prenatal and own adult smoking. DNA methylation levels were analysed in relation to body mass index (BMI), waist circumference (WC), fasting glucose (FG), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), diastolic, and systolic blood pressure (BP). FINDINGS: Lower DNA methylation at three out of eight GFI1-CpGs was associated with exposure to maternal prenatal smoking, whereas, all eight CpGs were associated with adult own smoking. Lower DNA methylation at cg14179389, the strongest maternal prenatal smoking locus, was associated with increased WC and BP when adjusted for sex, age, and adult smoking with Bonferroni-corrected P < 0·012. In contrast, lower DNA methylation at cg09935388, the strongest adult own smoking locus, was associated with decreased BMI, WC, and BP (adjusted 1 × 10-7 < P < 0.01). Similarly, lower DNA methylation at cg12876356, cg18316974, cg09662411, and cg18146737 was associated with decreased BMI and WC (5 × 10-8 < P < 0.001). Lower DNA methylation at all the CpGs was consistently associated with higher TG levels. INTERPRETATION: Epigenetic changes at the GFI1 were linked to smoking exposure in-utero/in-adulthood and robustly associated with cardio-metabolic risk factors. FUND: European Union's Horizon 2020 research and innovation programme under grant agreement no. 633595 DynaHEALTH.

Early Motor Developmental Milestones and Schizotypy in the Northern Finland Birth Cohort Study 1966.

Delayed motor developmental milestones have been reported to be associated with schizophrenia in previous studies, but no study has examined the relationship between early motor developmental milestones and schizotypy. We have examined this relationship in a prospective birth cohort.In the Northern Finland Birth Cohort 1966, data on 9 early motor developmental milestones were collected prospectively from visits to child welfare centers, and data on adult schizotypy were collected through a questionnaire (N = 4557-4674). Positive schizotypy was measured by the Perceptual Aberration Scale (PAS), negative schizotypy was measured by Physical Anhedonia Scale (PhAS) and Social Anhedonia Scale (SAS). Three related scales were included: Schizoidia Scale (SCHD), Hypomanic Personality Scale (HPS), and Bipolar II Scale (BIP2). We examined the milestone-schizotypy associations before and after excluding cases of schizophrenia from this population-based sample. Hierarchical regression analyses adjusted for covariates and separately for both genders were performed. In men, each extra month of delay in achievement of touching thumb with index finger, sitting unsupported, standing up, walking with support, or walking unsupported was associated with an increase in PAS, PhAS, or SCHD scores, or decrease in BIP2 score (P < .05). In women, each extra month of delay in achievement of turning from back to tummy was associated with an increase in PhAS and SAS scores (P < .05). Schizotypy is associated with delayed motor developmental milestones in early-life, but there is some heterogeneity with regards to types of milestones and gender. These findings suggest delayed motor development confers risk across the continuum of schizophrenia syndrome.

Potential determinants of vitamin D in Finnish adults: a cross-sectional study from the Northern Finland birth cohort 1966.

OBJECTIVE: Evidence from randomised controlled trials suggests that vitamin D may reduce multimorbidity, but very few studies have investigated specific determinants of vitamin D2 and D3 (two isoforms of 25-hydroxyvitamin D). The aim of the study was to investigate the determinants of vitamin D2 and D3 and to identify the risk factors associated with hypovitaminosis D. DESIGN: Cross-sectional study. SETTING: Northern Finland Birth Cohort 1966. PARTICIPANTS: 2374 male and 2384 female participants with data on serum 25(OH)D2 and 25(OH)D3 concentrations measured at 31 years of age (1997), together with comprehensive measures of daylight, anthropometric, social, lifestyle and contraceptive cofactors. METHODS: We assessed a wide range of potential determinants prior to a nationwide fortification programme introduced in Finland. The determinants of 25(OH)D2, 25(OH)D3 and 25(OH)D concentrations were analysed by linear regression and risk factors for being in lower tertile of 25(OH)D concentration by ordinal logistic regression. RESULTS: At the time of sampling, 72% of the participants were vitamin D sufficient (≥50 nmol/L). Low sunlight exposure period (vs high) was associated positively with 25(OH)D2 and negatively with 25(OH)D3 concentrations. Use of oral contraceptives (vs non-users) was associated with an increase of 0.17 nmol/L (95% CI 0.08 to 0.27) and 0.48 nmol/L (95% CI 0.41 to 0.56) in 25(OH)D2 and 25(OH)D3 concentrations. Sex, season, latitude, alcohol consumption and physical activity were the factors most strongly associated with 25(OH)D concentration. Risk factors for low vitamin D status were low sunlight exposure defined by time of sampling, residing in northern latitudes, obesity, higher waist circumference, low physical activity and unhealthy diet. CONCLUSIONS: We demonstrate some differential associations of environmental and lifestyle factors with 25(OH)D2 and 25(OH)D3 raising important questions related to personalised healthcare. Future strategies could implement lifestyle modification and supplementation to improve vitamin D2 and D3 status, accounting for seasonal, lifestyle, metabolic and endocrine status.