Systematic comparison of family history and polygenic risk across 24 common diseases.

Family history is the standard indirect measure of inherited susceptibility in clinical care, whereas polygenic risk scores (PRSs) have more recently demonstrated potential for more directly capturing genetic risk in many diseases. Few studies have systematically compared how these overlap and complement each other across common diseases. Within FinnGen (N = 306,418), we leverage family relationships, up to 50 years of nationwide registries, and genome-wide genotyping to examine the interplay of family history and genome-wide PRSs. We explore the dynamic for three types of family history across 24 common diseases: first- and second-degree family history and parental causes of death. Covering a large proportion of the burden of non-communicable diseases in adults, we show that family history and PRS are independent and not interchangeable measures, but instead provide complementary information on inherited disease susceptibility. The PRSs explained on average 10% of the effect of first-degree family history, and first-degree family history 3% of PRSs, and PRS effects were independent of both early- and late-onset family history. The PRS stratified the risk similarly in individuals with and without family history. In most diseases, including coronary artery disease, glaucoma, and type 2 diabetes, a positive family history with a high PRS was associated with a considerably elevated risk, whereas a low PRS compensated completely for the risk implied by positive family history. This study provides a catalogue of risk estimates for both family history of disease and PRSs and highlights opportunities for a more comprehensive way of assessing inherited disease risk across common diseases.

Genome-wide association meta-analysis identifies 48 risk variants and highlights the role of the stria vascularis in hearing loss.

Hearing loss is one of the top contributors to years lived with disability and is a risk factor for dementia. Molecular evidence on the cellular origins of hearing loss in humans is growing. Here, we performed a genome-wide association meta-analysis of clinically diagnosed and self-reported hearing impairment on 723,266 individuals and identified 48 significant loci, 10 of which are novel. A large proportion of associations comprised missense variants, half of which lie within known familial hearing loss loci. We used single-cell RNA-sequencing data from mouse cochlea and brain and mapped common-variant genomic results to spindle, root, and basal cells from the stria vascularis, a structure in the cochlea necessary for normal hearing. Our findings indicate the importance of the stria vascularis in the mechanism of hearing impairment, providing future paths for developing targets for therapeutic intervention in hearing loss.

Genetic contribution to microglial activation in schizophrenia.

Several lines of evidence indicate the involvement of neuroinflammatory processes in the pathophysiology of schizophrenia (SCZ). Microglia are brain resident immune cells responding toward invading pathogens and injury-related products, and additionally, have a critical role in improving neurogenesis and synaptic functions. Aberrant activation of microglia in SCZ is one of the leading hypotheses for disease pathogenesis, but due to the lack of proper human cell models, the role of microglia in SCZ is not well studied. We used monozygotic twins discordant for SCZ and healthy individuals to generate human induced pluripotent stem cell-derived microglia to assess the transcriptional and functional differences in microglia between healthy controls, affected twins and unaffected twins. The microglia from affected twins had increased expression of several common inflammation-related genes compared to healthy individuals. Microglia from affected twins had also reduced response to interleukin 1 beta (IL1ß) treatment, but no significant differences in migration or phagocytotic activity. Ingenuity Pathway Analysis (IPA) showed abnormalities related to extracellular matrix signaling. RNA sequencing predicted downregulation of extracellular matrix structure constituent Gene Ontology (GO) terms and hepatic fibrosis pathway activation that were shared by microglia of both affected and unaffected twins, but the upregulation of major histocompatibility complex (MHC) class II receptors was observed only in affected twin microglia. Also, the microglia of affected twins had heterogeneous response to clozapine, minocycline, and sulforaphane treatments. Overall, despite the increased expression of inflammatory genes, we observed no clear functional signs of hyperactivation in microglia from patients with SCZ. We conclude that microglia of the patients with SCZ have gene expression aberrations related to inflammation response and extracellular matrix without contributing to increased microglial activation.

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.

Genome-wide association study meta-analysis of dizygotic twinning illuminates genetic regulation of female fecundity.

STUDY QUESTION: Which genetic factors regulate female propensity for giving birth to spontaneous dizygotic (DZ) twins? SUMMARY ANSWER: We identified four new loci, GNRH1, FSHR, ZFPM1, and IPO8, in addition to previously identified loci, FSHB and SMAD3. WHAT IS KNOWN ALREADY: The propensity to give birth to DZ twins runs in families. Earlier, we reported that FSHB and SMAD3 as associated with DZ twinning and female fertility measures. STUDY DESIGN, SIZE, DURATION: We conducted a genome-wide association meta-analysis (GWAMA) of mothers of spontaneous dizygotic (DZ) twins (8265 cases, 264 567 controls) and of independent DZ twin offspring (26 252 cases, 417 433 controls). PARTICIPANTS/MATERIALS, SETTING, METHODS: Over 700 000 mothers of DZ twins, twin individuals and singletons from large cohorts in Australia/New Zealand, Europe, and the USA were carefully screened to exclude twins born after use of ARTs. Genetic association analyses by cohort were followed by meta-analysis, phenome wide association studies (PheWAS), in silico and in vivo annotations, and Zebrafish functional validation. MAIN RESULTS AND THE ROLE OF CHANCE: This study enlarges the sample size considerably from previous efforts, finding four genome-wide significant loci, including two novel signals and a further two novel genes that are implicated by gene level enrichment analyses. The novel loci, GNRH1 and FSHR, have well-established roles in female reproduction whereas ZFPM1 and IPO8 have not previously been implicated in female fertility. We found significant genetic correlations with multiple aspects of female reproduction and body size as well as evidence for significant selection against DZ twinning during human evolution. The 26 top single nucleotide polymorphisms (SNPs) from our GWAMA in European-origin participants weakly predicted the crude twinning rates in 47 non-European populations (r = 0.23 between risk score and population prevalence, s.e. 0.11, 1-tail P = 0.058) indicating that genome-wide association studies (GWAS) are needed in African and Asian populations to explore the causes of their respectively high and low DZ twinning rates. In vivo functional tests in zebrafish for IPO8 validated its essential role in female, but not male, fertility. In most regions, risk SNPs linked to known expression quantitative trait loci (eQTLs). Top SNPs were associated with in vivo reproductive hormone levels with the top pathways including hormone ligand binding receptors and the ovulation cycle. LARGE SCALE DATA: The full DZT GWAS summary statistics will made available after publication through the GWAS catalog (https://www.ebi.ac.uk/gwas/). LIMITATIONS, REASONS FOR CAUTION: Our study only included European ancestry cohorts. Inclusion of data from Africa (with the highest twining rate) and Asia (with the lowest rate) would illuminate further the biology of twinning and female fertility. WIDER IMPLICATIONS OF THE FINDINGS: About one in 40 babies born in the world is a twin and there is much speculation on why twinning runs in families. We hope our results will inform investigations of ovarian response in new and existing ARTs and the causes of female infertility. STUDY FUNDING/COMPETING INTEREST(S): Support for the Netherlands Twin Register came from the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organization for Health Research and Development (ZonMW) grants, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, 911-09-032, Biobanking and Biomolecular Resources Research Infrastructure (BBMRI.NL, 184.021.007), Royal Netherlands Academy of Science Professor Award (PAH/6635) to DIB, European Research Council (ERC-230374), Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the Avera Institute, Sioux Falls, South Dakota (USA) and the National Institutes of Health (NIH R01 HD042157-01A1) and the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health and Grand Opportunity grants 1RC2 MH089951. The QIMR Berghofer Medical Research Institute (QIMR) study was supported by grants from the National Health and Medical Research Council (NHMRC) of Australia (241944, 339462, 389927, 389875, 389891, 389892, 389938, 443036, 442915, 442981, 496610, 496739, 552485, 552498, 1050208, 1075175). L.Y. is funded by Australian Research Council (Grant number DE200100425). The Minnesota Center for Twin and Family Research (MCTFR) was supported in part by USPHS Grants from the National Institute on Alcohol Abuse and Alcoholism (AA09367 and AA11886) and the National Institute on Drug Abuse (DA05147, DA13240, and DA024417). The Women's Genome Health Study (WGHS) was funded by the National Heart, Lung, and Blood Institute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913), with support for genotyping provided by Amgen. Data collection in the Finnish Twin Registry has been supported by the Wellcome Trust Sanger Institute, the Broad Institute, ENGAGE-European Network for Genetic and Genomic Epidemiology, FP7-HEALTH-F4-2007, grant agreement number 201413, National Institute of Alcohol Abuse and Alcoholism (grants AA-12502, AA-00145, AA-09203, AA15416, and K02AA018755) and the Academy of Finland (grants 100499, 205585, 118555, 141054, 264146, 308248, 312073 and 336823 to J. Kaprio). TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. For NESDA, funding was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10000-1002), the Center for Medical Systems Biology (CSMB, NVVO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University's Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, ROI D0042157-01A, MH081802, Grand Opportunity grants 1 RC2 Ml-1089951 and IRC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO. Work in the Del Bene lab was supported by the Programme Investissements d'Avenir IHU FOReSIGHT (ANR-18-IAHU-01). C.R. was supported by an EU Horizon 2020 Marie Sklodowska-Curie Action fellowship (H2020-MSCA-IF-2014 #661527). H.S. and K.S. are employees of deCODE Genetics/Amgen. The other authors declare no competing financial interests. TRIAL REGISTRATION NUMBER: N/A.

Trans-ancestry epigenome-wide association meta-analysis of DNA methylation with lifetime cannabis use.

Cannabis is widely used worldwide, yet its links to health outcomes are not fully understood. DNA methylation can serve as a mediator to link environmental exposures to health outcomes. We conducted an epigenome-wide association study (EWAS) of peripheral blood-based DNA methylation and lifetime cannabis use (ever vs. never) in a meta-analysis including 9436 participants (7795 European and 1641 African ancestry) from seven cohorts. Accounting for effects of cigarette smoking, our trans-ancestry EWAS meta-analysis revealed four CpG sites significantly associated with lifetime cannabis use at a false discovery rate of 0.05 [Formula: see text]: cg22572071 near gene ADGRF1, cg15280358 in ADAM12, cg00813162 in ACTN1, and cg01101459 near LINC01132. Additionally, our EWAS analysis in participants who never smoked cigarettes identified another epigenome-wide significant CpG site, cg14237301 annotated to APOBR. We used a leave-one-out approach to evaluate methylation scores constructed as a weighted sum of the significant CpGs. The best model can explain 3.79% of the variance in lifetime cannabis use. These findings unravel the DNA methylation changes associated with lifetime cannabis use that are independent of cigarette smoking and may serve as a starting point for further research on the mechanisms through which cannabis exposure impacts health outcomes.

Sex Differences in Case Fatality of Aneurysmal Subarachnoid Hemorrhage: A Systematic Review.

INTRODUCTION: Aneurysmal subarachnoid hemorrhage (SAH) is more common in women than in men, contrary to most cardiovascular diseases. However, it is unclear whether the case fatality rate (CFR) of SAH also differs by sex. Thus, we performed a systematic review to address the relationship between sex and SAH CFRs. METHODS: We conducted a systematic literature search in PubMed, Scopus, and Cochrane library databases. We focused on population-based studies that included both nonhospitalized and hospitalized SAHs and had either reported 1-month (28-31 day) SAH CFRs separately for men and women or calculated risk estimates for SAH CFR by sex. For quality classification, we used the Cochrane Collaboration Handbook and Critical Appraisal Skills Program guidelines. We pooled the study cohorts and calculated relative risk ratios (RRs) with 95% confidence intervals (CIs) for SAH death between women and men using a random-effects meta-analysis model. RESULTS: The literature search yielded 5,592 initial publications, of which 33 study cohorts were included in the final review. Of the 33 study cohorts, only three reported significant sex differences, although the findings were contradictory. In the pooled analysis of all 53,141 SAH cases (60.3% women) from 26 countries, the 1-month CFR did not differ (RR = 0.99 [95% CI: 0.93-1.05]) between women (35.5%) and men (35.0%). According to our risk-of-bias evaluation, all 33 study cohorts were categorized as low quality. The most important sources of bias risks were related to the absence of proper confounding control (all 33 study cohorts), insufficient sample size (27 of 33 study cohorts), and poor/unclear diagnostic accuracy (27 of 33 study cohorts). CONCLUSION: Contrary to SAH incidence rates, the SAH CFRs do not seem to differ between men and women. However, since none of the studies were specifically designed to examine the sex differences in SAH CFRs, future studies on the topic are warranted.

Bone marrow metabolism is affected by body weight and response to exercise training varies according to anatomical location.

AIM: High body weight is a protective factor against osteoporosis, but obesity also suppresses bone metabolism and whole-body insulin sensitivity. However, the impact of body weight and regular training on bone marrow (BM) glucose metabolism is unclear. We studied the effects of regular exercise training on bone and BM metabolism in monozygotic twin pairs discordant for body weight. METHODS: We recruited 12 monozygotic twin pairs (mean ± SD age 40.4 ± 4.5 years; body mass index 32.9 ± 7.6, mean difference between co-twins 7.6 kg/m2 ; eight female pairs). Ten pairs completed the 6-month long training intervention. We measured lumbar vertebral and femoral BM insulin-stimulated glucose uptake (GU) using 18 F-FDG positron emission tomography, lumbar spine bone mineral density and bone turnover markers. RESULTS: At baseline, heavier co-twins had higher lumbar vertebral BM GU (p < .001) and lower bone turnover markers (all p < .01) compared with leaner co-twins but there was no significant difference in femoral BM GU, or bone mineral density. Training improved whole-body insulin sensitivity, aerobic capacity (both p < .05) and femoral BM GU (p = .008). The training response in lumbar vertebral BM GU was different between the groups (time × group, p = .02), as GU tended to decrease in heavier co-twins (p = .06) while there was no change in leaner co-twins. CONCLUSIONS: In this study, regular exercise training increases femoral BM GU regardless of weight and genetics. Interestingly, lumbar vertebral BM GU is higher in participants with higher body weight, and training counteracts this effect in heavier co-twins even without reduction in weight. These data suggest that BM metabolism is altered by physical activity.

Longitudinal leisure-time physical activity profiles throughout adulthood and related characteristics: a 36-year follow-up study of the older Finnish Twin Cohort.

BACKGROUND: Personalized interventions aiming to increase physical activity in individuals are effective. However, from a public health perspective, it would be important to stimulate physical activity in larger groups of people who share the vulnerability to be physically inactive throughout adulthood. To find these high-risk groups, we identified 36-year leisure-time physical activity profiles from young adulthood to late midlife in females and males. Moreover, we uncovered which anthropometric-, demographic-, lifestyle-, and health-related characteristics were associated with these physical activity profiles. METHODS: We included 2,778 females and 1,938 males from the population-based older Finnish Twin Cohort Study, who responded to health and behavior surveys at the mean ages of 24, 30, 40 and 60. Latent profile analysis was used to identify longitudinal leisure-time physical activity profiles. RESULTS: We found five longitudinal leisure-time physical activity profiles for both females and males. Females' profiles were: 1) Low increasing moderate (29%), 2) Moderate stable (23%), 3) Very low increasing low (20%), 4) Low stable (20%) and 5) High increasing high (9%). Males' profiles were: 1) Low increasing moderate (29%), 2) Low stable very low (26%), 3) Moderate decreasing low (21%), 4) High fluctuating high (17%) and 5) Very low stable (8%). In both females and males, lower leisure-time physical activity profiles were associated with lower education, higher body mass index, smoking, poorer perceived health, higher sedentary time, high blood pressure, and a higher risk for type 2 diabetes. Furthermore, lower leisure-time physical activity was linked to a higher risk of depression in females. CONCLUSIONS: We found several longitudinal leisure-time physical activity profiles with unique changes in both sexes. Fewer profiles in females than in males remained or became low physically active during the 36-year follow-up. We observed that lower education, higher body mass index, and more smoking already in young adulthood were associated with low leisure-time physical activity profiles. However, the fact that several longitudinal profiles demonstrated a change in their physical activity behavior over time implies the potential for public health interventions to improve leisure-time physical activity levels.

Cohort Effects on Tobacco Consumption and its Genetic and Environmental Variance Among Finnish Adults born between 1880-1957.

INTRODUCTION: Population research indicates that smoking behaviors in Finland have varied over time by sex and birth cohort. Smoking behaviors are influenced by genes and the environment; like the behaviors themselves, these underlying influences are not necessarily stable over time and may be modifiable by national drug policy. METHODS: We utilized longitudinal mixed effects models and causal-common-contingent twin models to evaluate sex and cohort effects on tobacco consumption and the underlying genetic and environmental variance components in a birth cohort sample of same-sex twins born in Finland between 1880-1957, assessed in 1975, 1981, 1990, and 2011. RESULTS: We identified significant main effects of age, sex, and cohort on quantity of cigarette consumption, as well as significant age×cohort and sex×cohort interactions. We also identified sex and cohort effects on the liability to initiate regular smoking and the magnitude of variation underlying quantity of cigarette consumption. That said, heritability and environmental contributions to both traits were not different between the four sex×cohort groups. CONCLUSIONS: Our results indicate sex and cohort effects on the prevalence of smoking and its underlying variation. Our results on changing prevalence mirror existing population-level research in Finnish samples, but we did not identify differences in heritability found in other studies of cohort effects in tobacco use, potentially due to power issues. These results highlight the importance of considering age, cohort, and timing of policy changes when evaluating changes in substance consumption across time. IMPLICATIONS: This study identifies sex and cohort effects influencing tobacco consumption in a sample of Finnish adult twins born between 1880-1957. Our results are in line with other population level research in Finland and research on cohort effects influencing alcohol use in the same sample. Our results highlight the intertwining effects of age, cohort, sex, and substance policies on substance use.

Patterns and predictors of alcohol misuse trajectories from adolescence through early midlife.

We took a multilevel developmental contextual approach and characterized trajectories of alcohol misuse from adolescence through early midlife, examined genetic and environmental contributions to individual differences in those trajectories, and identified adolescent and young adult factors associated with change in alcohol misuse. Data were from two longitudinal population-based studies. FinnTwin16 is a study of Finnish twins assessed at 16, 17, 18, 25, and 35 years (N = 5659; 52% female; 32% monozygotic). The National Longitudinal Study of Adolescent to Adult Health (Add Health) is a study of adolescents from the United States, who were assessed at five time points from 1994 to 2018 (N = 18026; 50% female; 64% White, 21% Black, 4% Native American, 7% Asian, 9% Other race/ethnicity). Alcohol misuse was measured as frequency of intoxication in FinnTwin16 and frequency of binge drinking in Add Health. In both samples, trajectories of alcohol misuse were best described by a quadratic growth curve: Alcohol misuse increased across adolescence, peaked in young adulthood, and declined into early midlife. Individual differences in these trajectories were primarily explained by environmental factors. Several adolescent and young adult correlates were related to the course of alcohol misuse, including other substance use, physical and mental health, and parenthood.

Temporal Changes in CSF Cell Parameters After SAH: Comparison of Ventricular and Spinal Drain Samples.

BACKGROUND: Forty percent of patients with aneurysmatic subarachnoid hemorrhage (aSAH) develop acute hydrocephalus requiring treatment with cerebrospinal fluid (CSF) drainage. CSF cell parameters are used in the diagnosis of nosocomial infections but also reflect sterile inflammation after aSAH. We aimed to study the temporal changes in CSF parameters and compare external ventricular drain (EVD)-derived and lumbar spinal drain-derived samples. METHODS: We retrospectively identified consecutive patients with aSAH treated at our neurointensive care unit between January 2014 and May 2019. We mapped the temporal changes in CSF leucocyte count, erythrocyte count, cell ratio, and cell index during the first 19 days after aSAH separately for EVD-derived and spinal drain-derived samples. We compared the sample sources using a linear mixed model, controlling for repeated sampling. RESULTS: We included 1360 CSF samples from 197 patients in the analyses. In EVD-derived samples, the CSF leucocyte count peaked at days 4-5 after aSAH, reaching a median of 225 × 106 (interquartile range [IQR] 64-618 × 106). The cell ratio and index peaked at 8-9 days (0.90% [IQR 0.35-1.98%] and 2.71 [IQR 1.25-6.73], respectively). In spinal drain-derived samples, the leucocyte count peaked at days 6-7, reaching a median of 238 × 106 (IQR 60-396 × 106). The cell ratio and index peaked at 14-15 days (4.12% [IQR 0.63-10.61%]) and 12-13 days after aSAH (8.84 [IQR 3.73-18.84]), respectively. Compared to EVD-derived samples, the leucocyte count was significantly higher in spinal drain-derived samples at days 6-17, and the cell ratio as well as the cell index was significantly higher in spinal drain-derived samples compared to EVD samples at days 10-15. CONCLUSIONS: CSF cell parameters undergo dynamic temporal changes after aSAH. CSF samples from different CSF compartments are not comparable.

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.

Self-reported sleep bruxism and mortality in 1990-2020 in a nationwide twin cohort.

BACKGROUND: The association of sleep bruxism with mortality has not been studied. OBJECTIVES: Altogether 12 040 subjects from the nationwide Finnish twin cohort were included in the analyses. We examined whether self-reported sleep bruxism is associated with increased risk of mortality, and if so, whether the effect is independent of known common risk factors. The time span of the follow-up was 30 years. METHODS: Cox proportional hazards regression models (Hazard Ratios and their 95% Confidence Intervals) adjusted by age, sex and covariates were used to assess the effect of baseline bruxism status in 1990 on future mortality in 1990-2020. RESULTS: The risk of mortality among all participants (n = 12 040), independent of missing covariates and adjusted by age and sex, was 40% higher in weekly bruxers than in never bruxers (HR 1.40, 95% CI 1.16-1.68, p < .001). However, when adjusted by all studied covariates, (n = 11 427) the risk was no longer observed (HR 1.04, 95% CI 0.86-1.25, p = .717). Despite the overall lack of between bruxism and mortality after adjustment for covariates, we examined the cause-specific risks for major cause-of-death groups. There were no substantial associations of weekly bruxism with major disease outcomes by the fully adjusted hazard ratios for them. CONCLUSION: Bruxism does not kill-in line with its definition of being rather a behaviour (with all its phenotypes) than a disease.

Adolescent leisure-time physical activity and eating disorders: a longitudinal population-based twin study.

PURPOSE: High levels of physical activity have been documented in eating disorder patients. Our aim was to examine whether adolescent leisure-time physical activity is prospectively associated with eating disorders in adolescence and young adulthood. METHODS: Finnish twins born in 1983-1987 reported their physical activity frequency at ages 12, 14, and 17. A subsample of participants underwent structured, retrospective interviews for eating disorders at the mean age of 22.4 years. Associations between female twins' physical activity and future eating disorders (571-683 twins/wave) were investigated with the Cox proportional hazards model. To illustrate the physical activity similarity of the co-twins in a twin pair, we used cross-tabulation of eating disorder-discordant twin pairs (13-24 pairs/wave). RESULTS: After adjusting for several covariates, we found no statistically significant longitudinal association between physical activity and eating disorders. This applied when all eating disorders were combined but also when assessed separately as restrictive and non-restrictive eating disorders. Co-twins' physical activity in adolescence tended to be similar irrespective of their future eating disorder, supporting the results of the regression analysis. CONCLUSION: We observed no evidence of adolescent physical activity frequency being prospectively associated with eating disorders in female twins. Further longitudinal studies with larger sample sizes and more detailed physical activity data are needed. LEVEL OF EVIDENCE: III, evidence obtained from cohort or case-control analytic studies.

Genetic associations vary across the spectrum of fasting serum insulin: results from the European IDEFICS/I.Family children's cohort.

AIMS/HYPOTHESIS: There is increasing evidence for the existence of shared genetic predictors of metabolic traits and neurodegenerative disease. We previously observed a U-shaped association between fasting insulin in middle-aged women and dementia up to 34 years later. In the present study, we performed genome-wide association (GWA) analyses for fasting serum insulin in European children with a focus on variants associated with the tails of the insulin distribution. METHODS: Genotyping was successful in 2825 children aged 2-14 years at the time of insulin measurement. Because insulin levels vary during childhood, GWA analyses were based on age- and sex-specific z scores. Five percentile ranks of z-insulin were selected and modelled using logistic regression, i.e. the 15th, 25th, 50th, 75th and 85th percentile ranks (P15-P85). Additive genetic models were adjusted for age, sex, BMI, survey year, survey country and principal components derived from genetic data to account for ethnic heterogeneity. Quantile regression was used to determine whether associations with variants identified by GWA analyses differed across quantiles of log-insulin. RESULTS: A variant in the SLC28A1 gene (rs2122859) was associated with the 85th percentile rank of the insulin z score (P85, p value=3×10-8). Two variants associated with low z-insulin (P15, p value <5×10-6) were located on the RBFOX1 and SH3RF3 genes. These genes have previously been associated with both metabolic traits and dementia phenotypes. While variants associated with P50 showed stable associations across the insulin spectrum, we found that associations with variants identified through GWA analyses of P15 and P85 varied across quantiles of log-insulin. CONCLUSIONS/INTERPRETATION: The above results support the notion of a shared genetic architecture for dementia and metabolic traits. Our approach identified genetic variants that were associated with the tails of the insulin spectrum only. Because traditional heritability estimates assume that genetic effects are constant throughout the phenotype distribution, the new findings may have implications for understanding the discrepancy in heritability estimates from GWA and family studies and for the study of U-shaped biomarker-disease associations.

Longitudinal multi-omics study reveals common etiology underlying association between plasma proteome and BMI trajectories in adolescent and young adult twins.

BACKGROUND: The influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remains underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers. METHODS: Our study included two cohorts of longitudinally followed twins: FinnTwin12 (N = 651) and the Netherlands Twin Register (NTR) (N = 665). Follow-up comprised 4 BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated in latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. In FinnTwin12, the sources of genetic and environmental variation underlying the protein abundances were quantified by twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) applying mixed-effects models and correlation networks. RESULTS: We identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 7 and 3 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers. CONCLUSIONS: Associations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.

Genetic regulation of body size and morphology in children: a twin study of 22 anthropometric traits.

BACKGROUND: Anthropometric measures show high heritability, and genetic correlations have been found between obesity-related traits. However, we lack a comprehensive analysis of the genetic background of human body morphology using detailed anthropometric measures. METHODS: Height, weight, 7 skinfold thicknesses, 7 body circumferences and 4 body diameters (skeletal breaths) were measured in 214 pairs of twin children aged 3-18 years (87 monozygotic pairs) in the Autonomous Region of Madeira, Portugal. Factor analysis (Varimax rotation) was used to analyze the underlying structure of body physique. Genetic twin modeling was used to estimate genetic and environmental contributions to the variation and co-variation of the anthropometric traits. RESULTS: Together, two factors explained 80% of the variation of all 22 anthropometric traits in boys and 73% in girls. Obesity measures (body mass index, skinfold thickness measures, as well as waist and hip circumferences) and limb circumferences loaded most strongly on the first factor, whereas height and body diameters loaded especially on the second factor. These factors as well as all anthropometric measures showed high heritability (80% or more for most of the traits), whereas the rest of the variation was explained by environmental factors not shared by co-twins. Obesity measures showed high genetic correlations (0.75-0.98). Height showed the highest genetic correlations with body diameter measures (0.58-0.76). Correlations between environmental factors not shared by co-twins were weaker than the genetic correlations but still substantial. The correlation patterns were roughly similar in boys and girls. CONCLUSIONS: Our results show high genetic correlations underlying the human body physique, suggesting that there are sets of genes widely affecting anthropometric traits. Better knowledge of these genetic variants can help to understand the development of obesity and other features of the human physique.

Modeling dependency structures in 450k DNA methylation data.

MOTIVATION: DNA methylation has been shown to be spatially dependent across chromosomes. Previous studies have focused on the influence of genomic context on the dependency structure, while not considering differences in dependency structure between individuals. RESULTS: We modeled spatial dependency with a flexible framework to quantify the dependency structure, focusing on inter-individual differences by exploring the association between dependency parameters and technical and biological variables. The model was applied to a subset of the Finnish Twin Cohort study (N = 1611 individuals). The estimates of the dependency parameters varied considerably across individuals, but were generally consistent across chromosomes within individuals. The variation in dependency parameters was associated with bisulfite conversion plate, zygosity, sex and age. The age differences presumably reflect accumulated environmental exposures and/or accumulated small methylation differences caused by stochastic mitotic events, establishing recognizable, individual patterns more strongly seen in older individuals. AVAILABILITY AND IMPLEMENTATION: The twin dataset used in the current study are located in the Biobank of the National Institute for Health and Welfare, Finland. All the biobanked data are publicly available for use by qualified researchers following a standardized application procedure (https://thl.fi/en/web/thl-biobank/for-researchers). A R-script for fitting the dependency structure to publicly available DNA methylation data with the software used in this article is provided in supplementary data. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Clinical, environmental, and genetic risk factors for substance use disorders: characterizing combined effects across multiple cohorts.

Substance use disorders (SUDs) incur serious social and personal costs. The risk for SUDs is complex, with risk factors ranging from social conditions to individual genetic variation. We examined whether models that include a clinical/environmental risk index (CERI) and polygenic scores (PGS) are able to identify individuals at increased risk of SUD in young adulthood across four longitudinal cohorts for a combined sample of N = 15,134. Our analyses included participants of European (NEUR = 12,659) and African (NAFR = 2475) ancestries. SUD outcomes included: (1) alcohol dependence, (2) nicotine dependence; (3) drug dependence, and (4) any substance dependence. In the models containing the PGS and CERI, the CERI was associated with all three outcomes (ORs = 01.37-1.67). PGS for problematic alcohol use, externalizing, and smoking quantity were associated with alcohol dependence, drug dependence, and nicotine dependence, respectively (OR = 1.11-1.33). PGS for problematic alcohol use and externalizing were also associated with any substance dependence (ORs = 1.09-1.18). The full model explained 6-13% of the variance in SUDs. Those in the top 10% of CERI and PGS had relative risk ratios of 3.86-8.04 for each SUD relative to the bottom 90%. Overall, the combined measures of clinical, environmental, and genetic risk demonstrated modest ability to distinguish between affected and unaffected individuals in young adulthood. PGS were significant but added little in addition to the clinical/environmental risk index. Results from our analysis demonstrate there is still considerable work to be done before tools such as these are ready for clinical applications.