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Objective: This study explores the association between obesity, diabetes, and somatosensory functioning in patients with knee osteoarthritis (OA), aiming to understand how metabolic conditions are related to pain mechanisms in this patient population. We hypothesized that higher body mass index (BMI), fat mass, and glycated hemoglobin levels (HbA1c) are associated with signs of altered somatosensory functioning. Methods: A cross-sectional analysis was conducted as part of a larger multicentre prospective cohort study. Data were collected from patients awaiting total knee arthroplasty in Belgium and the Netherlands. Associations between BMI, fat mass, HbA1c, and various pain-related variables were examined employing Pearson and Spearman correlation analyses which were further analyzed with linear regression techniques. Results: The study included 223 participants. Analysis revealed a significant although weak negative correlation between fat mass and pressure pain thresholds (PPT) at multiple locations, suggesting a link between higher fat mass and increased mechanical hyperalgesia. There were no significant correlations between BMI and pain-related outcomes. HbA1c levels showed very weak positive correlations with pain measures but did not withstand correction for multiple testing. Conclusion: The findings indicate that fat mass may be closely associated with altered somatosensory functioning in patients with knee OA. However, no significant correlations were found between BMI or HbA1c levels and pain-related outcomes. Future research should focus on longitudinal studies to elucidate the causal relationships and further explore the impact of metabolic factors on pain mechanisms in this patient population. Key Points • The findings indicate that fat mass may be closely associated with altered somatosensory functioning in patients with knee OA. [ABSTRACT FROM AUTHOR]

Objective: To review findings on attention-deficit/hyperactivity disorder and attention problems (AP) in children, adolescents, and adults, as established in the database of the Netherlands Twin Register and increase the understanding of stability in AP across the lifespan as a function of genetic and environmental influences. Method: A longitudinal model was fitted on Netherlands Twin Register AP scores from 44,607 child (less than 12-year-old), adolescent (12- to 18-year-old), and adult (greater than 18-year-old) twins. Results: Mean AP showed a downward trend with age. Age-to-age correlations ranged from 0.33 (50-[greater than or equal to]60 years old) to 0.73 (10-12 years old). Stability in individual differences in AP was due to genetic and environmental factors, and change was due primarily to environmental factors. Nonadditive genetic influences were present from childhood to adulthood. Total genetic variance decreased slightly throughout aging, whereas environmental variance increased substantially with the switch from maternal to self-ratings at 12 years of age. As a result, heritability coefficients decreased from 0.70 to 0.74 in childhood (maternal ratings) to 0.51 to 0.56 in adolescence (self-ratings), and 0.40 to 0.54 in adulthood (self-ratings). In childhood, male subjects scored higher than female subjects. After the rater switch at 12 years of age, female subjects tended to score higher than male subjects. Conclusions: Stability of AP is the result of genetic and environmental stability. The decrease in estimated heritability at 12 years of age is due to an increase in occasion-specific environmental variance and likely reflects a methodologic effect. Because environmental influences have lasting effects on AP, their early detection is crucial. (Contains 2 figures and 3 tables.)

There are research questions whose answers require record linkage of multiple databases that may be characterized by limited options for full data sharing. For this purpose, the Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI) consortium has supported the development of the ODISSEI Secure Supercomputer (OSSC) platform that allows researchers to link cohort data to data from Statistics Netherlands and run large-scale analyses in a high-performance computing (HPC) environment. Here, we report a successful record linkage genomewide association (GWA) study on expenditure for total health, mental health, primary and hospital care, and medication. Record linkage for genotype data from 16,726 participants from the Netherlands Twin Register (NTR) with data from Statistics Netherlands was accomplished in the secure OSSC platform, followed by gene-based tests and estimation of total and single nucleotide polymorphism (SNP)-based heritability. The total heritability of expenditure ranged between 29.4% (SE 0.8) and 37.5% (SE 0.8), but GWA analyses did not identify SNPs or genes that were genomewide significantly associated with health care expenditure. SNP-based heritability was between 0.0% (SE 3.5) and 5.4% (SE 4.0) and was different from zero for mental health care and primary care expenditure. We conclude that successfully linking genotype data to administrative health care expenditure data from Statistics Netherlands is feasible and demonstrates a series of analyses on health care expenditure. The OSSC platform offers secure possibilities for analyzing linked data in large scale and realizing sample sizes required for GWA studies, providing invaluable opportunities to answer many new research questions. [ABSTRACT FROM AUTHOR]

Background: Given the role of childhood aggressive behavior (AGG) in everyday child development, precise and accurate measurement is critical in clinical practice and research. This study aims to quantify agreement among widely used measures of childhood AGG regarding item content, clinical concordance, correlation, and underlying genetic construct. Methods: We analyzed data from 1254 Dutch twin pairs (age 8–10 years, 51.1% boys) from a general population sample for whom both parents completed the A‐TAC, CBCL, and SDQ at the same occasion. Results: There was substantial variation in item content among AGG measures, ranging from.00 (i.e., mutually exclusive) to.50 (moderate agreement). Clinical concordance (i.e., do the same children score above a clinical threshold among AGG measures) was very weak to moderate with estimates ranging between.01 and.43 for mother‐reports and between.12 and.42 for father‐reports. Correlations among scales were weak to strong, ranging from.32 to.70 for mother‐reports and from.32 to.64 for father‐reports. We found weak to very strong genetic correlations among the measures, with estimates between.65 and.84 for mother‐reports and between.30 and.87 for father‐reports. Conclusions: Our results demonstrated that degree of agreement between measures of AGG depends on the type (i.e., item content, clinical concordance, correlation, genetic correlation) of agreement considered. Because agreement was higher for correlations compared to clinical concordance (i.e., above or below a clinical cutoff), we propose the use of continuous scores to assess AGG, especially for combining data with different measures. Although item content can be different and agreement among observed measures may not be high, the genetic correlations indicate that the underlying genetic liability for childhood AGG is consistent across measures. [ABSTRACT FROM AUTHOR]

Background: Several nonpsychotic psychiatric disorders in childhood and adolescence can precede the onset of schizophrenia, but the etiology of this relationship remains unclear. We investigated to what extent the association between schizophrenia and psychiatric disorders in childhood is explained by correlated genetic risk factors. Methods: Polygenic risk scores (PRS), reflecting an individual's genetic risk for schizophrenia, were constructed for 2588 children from the Netherlands Twin Register (NTR) and 6127 from the Avon Longitudinal Study of Parents And Children (ALSPAC). The associations between schizophrenia PRS and measures of anxiety, depression, attention deficit hyperactivity disorder (ADHD), and oppositional defiant disorder/conduct disorder (ODD/CD) were estimated at age 7, 10, 12/13, and 15 years in the 2 cohorts. Results were then meta-analyzed, and a meta-regression analysis was performed to test differences in effects sizes over, age and disorders. Results: Schizophrenia PRS were associated with childhood and adolescent psychopathology. Meta-regression analysis showed differences in the associations over disorders, with the strongest association with childhood and adolescent depression and a weaker association for ODD/CD at age 7. The associations increased with age and this increase was steepest for ADHD and ODD/CD. Genetic correlations varied between 0.10 and 0.25. Conclusion: By optimally using longitudinal data across diagnoses in a multivariate meta-analysis this study sheds light on the development of childhood disorders into severe adult psychiatric disorders. The results are consistent with a common genetic etiology of schizophrenia and developmental psychopathology as well as with a stronger shared genetic etiology between schizophrenia and adolescent onset psychopathology. [ABSTRACT FROM AUTHOR]

Smoking and caffeine consumption show a strong positive correlation, but the mechanism underlying this association is unclear. Explanations include shared genetic/environmental factors or causal effects. This study employed three methods to investigate the association between smoking and caffeine. First, bivariate genetic models were applied to data of 10 368 twins from the Netherlands Twin Register in order to estimate genetic and environmental correlations between smoking and caffeine use. Second, from the summary statistics of meta-analyses of genome-wide association studies on smoking and caffeine, the genetic correlation was calculated by LD-score regression. Third, causal effects were tested using Mendelian randomization analysis in 6605 Netherlands Twin Register participants and 5714 women from the Avon Longitudinal Study of Parents and Children. Through twin modelling, a genetic correlation of r0.47 and an environmental correlation of r0.30 were estimated between current smoking (yes/no) and coffee use (high/low). Between current smoking and total caffeine use, this was r0.44 and r0.00, respectively. LD-score regression also indicated sizeable genetic correlations between smoking and coffee use (r0.44 between smoking heaviness and cups of coffee per day, r0.28 between smoking initiation and coffee use and r0.25 between smoking persistence and coffee use). Consistent with the relatively high genetic correlations and lower environmental correlations, Mendelian randomization provided no evidence for causal effects of smoking on caffeine or vice versa. Genetic factors thus explain most of the association between smoking and caffeine consumption. These findings suggest that quitting smoking may be more difficult for heavy caffeine consumers, given their genetic susceptibility. [ABSTRACT FROM AUTHOR]

Tic disorders are moderately heritable common psychiatric disorders that can be highly troubling, both in childhood and in adulthood. In this study, we report results obtained in the first epigenome-wide association study (EWAS) of tic disorders. The subjects are participants in surveys at the Netherlands Twin Register (NTR) and the NTR biobank project. Tic disorders were measured with a self-report version of the Yale Global Tic Severity Scale Abbreviated version (YGTSS-ABBR), included in the 8th wave NTR data collection (2008). DNA methylation data consisted of 411,169 autosomal methylation sites assessed by the Illumina Infinium HumanMethylation450 BeadChip Kit (HM450k array). Phenotype and DNA methylation data were available in 1,678 subjects (mean age = 41.5). No probes reached genome-wide significance (p < 1.2 × 10−7). The strongest associated probe was cg15583738, located in an intergenic region on chromosome 8 (p = 1.98 × 10−6). Several of the top ranking probes (p < 1 × 10−4) were in or nearby genes previously associated with neurological disorders (e.g., GABBRI, BLM, and ADAM10), warranting their further investigation in relation to tic disorders. The top significantly enriched gene ontology (GO) terms among higher ranking methylation sites included anatomical structure morphogenesis (GO:0009653, p = 4.6 × 10−15) developmental process (GO:0032502, p = 2.96 × 10−12), and cellular developmental process (GO:0048869, p = 1.96 × 10−12). Overall, these results provide a first insight into the epigenetic mechanisms of tic disorders. This first study assesses the role of DNA methylation in tic disorders, and it lays the foundations for future work aiming to unravel the biological mechanisms underlying the architecture of this disorder. [ABSTRACT FROM PUBLISHER]

Genetic variation in a population can be summarized through principal component analysis (PCA) on genome-wide data. PCs derived from such analyses are valuable for genetic association studies, where they can correct for population stratification. We investigated how to capture the genetic population structure in a well-characterized sample from the Netherlands and in a worldwide data set and examined whether (1) removing long-range linkage disequilibrium (LD) regions and LD-based SNP pruning significantly improves correlations between PCs and geography and (2) whether genetic differentiation may have been influenced by migration and/or selection. In the Netherlands, three PCs showed significant correlations with geography, distinguishing between: (1) North and South; (2) East and West; and (3) the middle-band and the rest of the country. The third PC only emerged with minimized LD, which also significantly increased correlations with geography for the other two PCs. In addition to geography, the Dutch North-South PC showed correlations with genome-wide homozygosity (r=0.245), which may reflect a serial-founder effect due to northwards migration, and also with height (♂: r=0.142, ♀: r=0.153). The divergence between subpopulations identified by PCs is partly driven by selection pressures. The first three PCs showed significant signals for diversifying selection (545 SNPs - the majority within 184 genes). The strongest signal was observed between North and South for the functional SNP in HERC2 that determines human blue/brown eye color. Thus, this study demonstrates how to increase ancestry signals in a relatively homogeneous population and how those signals can reveal evolutionary history. [ABSTRACT FROM AUTHOR]

Background and Aim: Previous studies have shown a relationship between schizophrenia and cannabis use. As both traits are substantially heritable, a shared genetic liability could explain the association. We use two recently developed genomics methods to investigate the genetic overlap between schizophrenia and cannabis use.Methods: Firstly, polygenic risk scores for schizophrenia were created based on summary statistics from the largest schizophrenia genome-wide association (GWA) meta-analysis to date. We analysed the association between these schizophrenia polygenic scores and multiple cannabis use phenotypes (lifetime use, regular use, age at initiation, and quantity and frequency of use) in a sample of 6,931 individuals. Secondly, we applied LD-score regression to the GWA summary statistics of schizophrenia and lifetime cannabis use to calculate the genome-wide genetic correlation.Results: Polygenic risk scores for schizophrenia were significantly (α<0.05) associated with five of the eight cannabis use phenotypes, including lifetime use, regular use, and quantity of use, with risk scores explaining up to 0.5% of the variance. Associations were not significant for age at initiation of use and two measures of frequency of use analyzed in lifetime users only, potentially because of reduced power due to a smaller sample size. The LD-score regression revealed a significant genetic correlation of rg=0.22 (SE=0.07, p=0.003) between schizophrenia and lifetime cannabis use.Conclusions: Common genetic variants underlying schizophrenia and lifetime cannabis use are partly overlapping. Individuals with a stronger genetic predisposition to schizophrenia are more likely to initiate cannabis use, use cannabis more regularly, and consume more cannabis over their lifetime. [ABSTRACT FROM AUTHOR]

Background: The objective of this study was to examine the prevalence of unhealthy lifestyle behaviors, overweight, and obesity in Dutch childhood cancer survivors (CCSs) compared with sibling controls and the Dutch general population. Other aims were to assess associated factors of unhealthy lifestyle behaviors, overweight, and obesity and to identify subgroups of CCSs at risk for these unhealthy statuses., Methods: The authors included 2253 CCSs and 906 siblings from the Dutch Childhood Cancer Survivor Study-Late Effects After Childhood Cancer cohort, part 1, and added data from the Dutch general population. Questionnaire data were collected on overweight and obesity (body mass index >25.0 kg/m 2 ), meeting physical activity guidelines (>150 minutes per week of moderate or vigorous exercises), excessive alcohol consumption (>14 and >21 alcoholic consumptions per week for women and men, respectively), daily smoking, and monthly drug use. Multivariable logistic regression analyses and two-step cluster analyses were performed to examine sociodemographic-related, health-related, cancer-related, and treatment-related associated factors of unhealthy lifestyle behaviors and to identify subgroups of CCSs at risk for multiple unhealthy behaviors., Results: CCSs more often did not meet physical activity guidelines than their siblings (30.0% vs. 19.3%; p < .001). Married as marital status, lower education level, nonstudent status, and comorbidities were common associated factors for a body mass index ≥25.0 kg/m 2 and insufficient physical activity, whereas male sex and lower education were shared associated factors for excessive alcohol consumption, daily smoking, and monthly drug use. A subgroup of CCSs was identified as excessive alcohol consumers, daily smokers, and monthly drug users., Conclusions: The current results emphasize the factors associated with unhealthy behaviors and the potential identification of CCSs who exhibit multiple unhealthy lifestyle behaviors., (© 2024 The Authors. Cancer published by Wiley Periodicals LLC on behalf of American Cancer Society.)

The association between circadian rhythms and diseases has been well established, while the association with mental health is less explored. Given the heritable nature of circadian rhythms, this study aimed to investigate the relationship between genes underlying circadian rhythms and mental health outcomes, as well as a possible gene-environment correlation for circadian rhythms. Polygenic scores (PGSs) represent the genetic predisposition to develop a certain trait or disease. In a sample from the Netherlands Twin Register ( N  = 14,021), PGSs were calculated for two circadian rhythm measures: morningness and relative amplitude (RA). The PGSs were used to predict mental health outcomes such as subjective happiness, quality of life, and depressive symptoms. In addition, we performed the same prediction analysis in a within-family design in a subset of dizygotic twins. The PGS for morningness significantly predicted morningness ( R 2  = 1.55%) and depressive symptoms ( R 2  = 0.22%). The PGS for RA significantly predicted general health ( R 2  = 0.12%) and depressive symptoms ( R 2  = 0.20%). Item analysis of the depressive symptoms showed that 4 out of 14 items were significantly associated with the PGSs. Overall, the results showed that people with a genetic predisposition of being a morning person or with a high RA are likely to have fewer depressive symptoms. The four associated depressive symptoms described symptoms related to decision-making, energy, and feeling worthless or inferior, rather than sleep. Based on our findings future research should include a substantial role for circadian rhythms in depression research and should further explore the gene-environment correlation in circadian rhythms., Competing Interests: Conflict Of Interest StatementThe authors have no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

We test whether genetic influences that explain individual differences in aggression in early life also explain individual differences across the life-course. In two cohorts from The Netherlands (N = 13,471) and Australia (N = 5628), polygenic scores (PGSs) were computed based on a genome-wide meta-analysis of childhood/adolescence aggression. In a novel analytic approach, we ran a mixed effects model for each age (Netherlands: 12-70 years, Australia: 16-73 years), with observations at the focus age weighted as 1, and decaying weights for ages further away. We call this approach a 'rolling weights' model. In The Netherlands, the estimated effect of the PGS was relatively similar from age 12 to age 41, and decreased from age 41-70. In Australia, there was a peak in the effect of the PGS around age 40 years. These results are a first indication from a molecular genetics perspective that genetic influences on aggressive behavior that are expressed in childhood continue to play a role later in life., (© 2021. The Author(s).)

Objective: Loneliness is an aversive response to a discrepancy between desired and actual social relationships and correlates with personality. We investigate the relationship of loneliness and personality in twin family and molecular genetic data., Method: Phenotypic correlations between loneliness and the Big Five personality traits were estimated in 29,625 adults, and in a group with genome-wide genotype data (N = 4,222), genetic correlations were obtained. We explored whether genetic correlations may reflect causal relationships by investigating within monozygotic twin pair differences (N pairs  = 2,662), by longitudinal within-subject changes in personality and loneliness (N = 4,260-9,238 longitudinal comparisons), and by longitudinal cross-lagged panel analyses (N = 15,628). Finally, we tested whether genetic correlations were due to cross-trait assortative mating (N spouse pairs  = 4,436)., Results: The strongest correlations with loneliness were observed for Neuroticism (r = .55) and Extraversion (r = -.33). Only Neuroticism showed a high correlation with loneliness independent of other personality traits (r = .50), so follow-up analyses focused on Neuroticism. The genetic correlation between loneliness and Neuroticism from genotyped variants was .71; a significant reciprocal causal relationship and nonsignificant cross-trait assortative mating imply that this is at least partly due to mediated pleiotropy., Conclusions: We show that the relationship between loneliness and personality is largely explained by its relationship with Neuroticism, which is substantially genetic in nature., (© 2018 Wiley Periodicals, Inc.)

Importance: Urban life has been proposed as an environmental risk factor accounting for the increased prevalence of schizophrenia in urban areas. An alternative hypothesis is that individuals with increased genetic risk tend to live in urban/dense areas., Objective: To assess whether adults with higher genetic risk for schizophrenia have an increased probability to live in more populated areas than those with lower risk., Design, Setting, and Participants: Four large, cross-sectional samples of genotyped individuals of European ancestry older than 18 years with known addresses in Australia, the United Kingdom, and the Netherlands were included in the analysis. Data were based on the postcode of residence at the time of last contact with the participants. Community-based samples who took part in studies conducted by the Queensland Institute for Medical Research Berghofer Medical Research Institute (QIMR), UK Biobank (UKB), Netherlands Twin Register (NTR), or QSkin Sun and Health Study (QSKIN) were included. Genome-wide association analysis and mendelian randomization (MR) were included. The study was conducted between 2016 and 2018., Exposures: Polygenic risk scores for schizophrenia derived from genetic data (genetic risk is independently measured from the occurrence of the disease). Socioeconomic status of the area was included as a moderator in some of the models., Main Outcomes and Measures: Population density of the place of residence of the participants determined from census data. Remoteness and socioeconomic status of the area were also tested., Results: The QIMR participants (15 544; 10 197 [65.6%] women; mean [SD] age, 54.4 [13.2] years) living in more densely populated areas (people per square kilometer) had a higher genetic loading for schizophrenia (r2 = 0.12%; P = 5.69 × 10-5), a result that was replicated across all 3 other cohorts (UKB: 345 246; 187 469 [54.3%] women; age, 65.7 [8.0] years; NTR: 11 212; 6727 [60.0%] women; age, 48.6 [17.5] years; and QSKIN: 15 726; 8602 [54.7%] women; age, 57.0 [7.9] years). This genetic association could account for 1.7% (95% CI, 0.8%-3.2%) of the schizophrenia risk. Estimates from MR analyses performed in the UKB sample were significant (b = 0.049; P = 3.7 × 10-7 using GSMR), suggesting that the genetic liability to schizophrenia may have a causal association with the tendency to live in urbanized locations., Conclusions and Relevance: The results of this study appear to support the hypothesis that individuals with increased genetic risk tend to live in urban/dense areas and suggest the need to refine the social stress model for schizophrenia by including genetics as well as possible gene-environment interactions.

Objective: To review findings on attention-deficit/hyperactivity disorder and attention problems (AP) in children, adolescents, and adults, as established in the database of the Netherlands Twin Register and increase the understanding of stability in AP across the lifespan as a function of genetic and environmental influences., Method: A longitudinal model was fitted on Netherlands Twin Register AP scores from 44,607 child (<12-year-old), adolescent (12- to 18-year-old), and adult (>18-year-old) twins., Results: Mean AP showed a downward trend with age. Age-to-age correlations ranged from 0.33 (50-≥60 years old) to 0.73 (10-12 years old). Stability in individual differences in AP was due to genetic and environmental factors, and change was due primarily to environmental factors. Nonadditive genetic influences were present from childhood to adulthood. Total genetic variance decreased slightly throughout aging, whereas environmental variance increased substantially with the switch from maternal to self-ratings at 12 years of age. As a result, heritability coefficients decreased from 0.70 to 0.74 in childhood (maternal ratings) to 0.51 to 0.56 in adolescence (self-ratings), and 0.40 to 0.54 in adulthood (self-ratings). In childhood, male subjects scored higher than female subjects. After the rater switch at 12 years of age, female subjects tended to score higher than male subjects., Conclusions: Stability of AP is the result of genetic and environmental stability. The decrease in estimated heritability at 12 years of age is due to an increase in occasion-specific environmental variance and likely reflects a methodologic effect. Because environmental influences have lasting effects on AP, their early detection is crucial., (Copyright © 2013 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)