Genetic associations of risk behaviours and educational achievement.

Risk behaviours are common in adolescent and persist into adulthood, people who engage in more risk behaviours are more likely to have lower educational attainment. We applied genetic causal inference methods to explore the causal relationship between adolescent risk behaviours and educational achievement. Risk behaviours were phenotypically associated with educational achievement at age 16 after adjusting for confounders (-0.11, 95%CI: -0.11, -0.09). Genomic-based restricted maximum likelihood (GREML) results indicated that both traits were heritable and have a shared genetic architecture (Risk h 2 = 0.18, 95% CI: -0.11,0.47; education h 2 = 0.60, 95%CI: 0.50,0.70). Consistent with the phenotypic results, genetic variation associated with risk behaviour was negatively associated with education ( r g = -0.51, 95%CI: -1.04,0.02). Lastly, the bidirectional MR results indicate that educational achievement or a closely related trait is likely to affect risk behaviours PGI (ß=-1.04, 95% CI: -1.41, -0.67), but we found little evidence that the genetic variation associated with risk behaviours affected educational achievement (ß=0.00, 95% CI: -0.24,0.24). The results suggest engagement in risk behaviour may be partly driven by educational achievement or a closely related trait.

Genetics impact risk of Alzheimer's disease through mechanisms modulating structural brain morphology in late life.

BACKGROUND: Alzheimer's disease (AD)-related neuropathological changes can occur decades before clinical symptoms. We aimed to investigate whether neurodevelopment and/or neurodegeneration affects the risk of AD, through reducing structural brain reserve and/or increasing brain atrophy, respectively. METHODS: We used bidirectional two-sample Mendelian randomisation to estimate the effects between genetic liability to AD and global and regional cortical thickness, estimated total intracranial volume, volume of subcortical structures and total white matter in 37 680 participants aged 8-81 years across 5 independent cohorts (Adolescent Brain Cognitive Development, Generation R, IMAGEN, Avon Longitudinal Study of Parents and Children and UK Biobank). We also examined the effects of global and regional cortical thickness and subcortical volumes from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium on AD risk in up to 37 741 participants. RESULTS: Our findings show that AD risk alleles have an age-dependent effect on a range of cortical and subcortical brain measures that starts in mid-life, in non-clinical populations. Evidence for such effects across childhood and young adulthood is weak. Some of the identified structures are not typically implicated in AD, such as those in the striatum (eg, thalamus), with consistent effects from childhood to late adulthood. There was little evidence to suggest brain morphology alters AD risk. CONCLUSIONS: Genetic liability to AD is likely to affect risk of AD primarily through mechanisms affecting indicators of brain morphology in later life, rather than structural brain reserve. Future studies with repeated measures are required for a better understanding and certainty of the mechanisms at play.

Assessing causal links between age at menarche and adolescent mental health: a Mendelian randomisation study.

BACKGROUND: The timing of puberty may have an important impact on adolescent mental health. In particular, earlier age at menarche has been associated with elevated rates of depression in adolescents. Previous research suggests that this relationship may be causal, but replication and an investigation of whether this effect extends to other mental health domains is warranted. METHODS: In this Registered Report, we triangulated evidence from different causal inference methods using a new wave of data (N = 13,398) from the Norwegian Mother, Father, and Child Cohort Study. We combined multiple regression, one- and two-sample Mendelian randomisation (MR), and negative control analyses (using pre-pubertal symptoms as outcomes) to assess the causal links between age at menarche and different domains of adolescent mental health. RESULTS: Our results supported the hypothesis that earlier age at menarche is associated with elevated depressive symptoms in early adolescence based on multiple regression (ß = - 0.11, 95% CI [- 0.12, - 0.09], pone-tailed < 0.01). One-sample MR analyses suggested that this relationship may be causal (ß = - 0.07, 95% CI [- 0.13, 0.00], pone-tailed = 0.03), but the effect was small, corresponding to just a 0.06 standard deviation increase in depressive symptoms with each earlier year of menarche. There was also some evidence of a causal relationship with depression diagnoses during adolescence based on one-sample MR (OR = 0.74, 95% CI [0.54, 1.01], pone-tailed = 0.03), corresponding to a 29% increase in the odds of receiving a depression diagnosis with each earlier year of menarche. Negative control and two-sample MR sensitivity analyses were broadly consistent with this pattern of results. Multivariable MR analyses accounting for the genetic overlap between age at menarche and childhood body size provided some evidence of confounding. Meanwhile, we found little consistent evidence of effects on other domains of mental health after accounting for co-occurring depression and other confounding. CONCLUSIONS: We found evidence that age at menarche affected diagnoses of adolescent depression, but not other domains of mental health. Our findings suggest that earlier age at menarche is linked to problems in specific domains rather than adolescent mental health in general.

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.

Trends and patterns of antiseizure medication prescribing during pregnancy between 1995 and 2018 in the United Kingdom: A cohort study.

OBJECTIVE: To examine antiseizure medication (ASM) prescription during pregnancy. DESIGN: Population-based drug utilisation study. SETTING: UK primary and secondary care data, 1995-2018, from the Clinical Practice Research Datalink GOLD version. POPULATION OR SAMPLE: 752 112 completed pregnancies among women registered for a minimum of 12 months with an 'up to standard' general practice prior to the estimated start of pregnancy and for the duration of their pregnancy. METHODS: We described ASM prescription across the study period, overall and by ASM indication, examined patterns of prescription during pregnancy including continuous prescription and discontinuation, and used logistic regression to investigate factors associated with those ASM prescription patterns. MAIN OUTCOME MEASURES: Prescription of ASMs during pregnancy and discontinuation of ASMs before and during pregnancy. RESULTS: ASM prescription during pregnancy increased from 0.6% of pregnancies in 1995 to 1.6% in 2018, driven largely by an increase in women with indications other than epilepsy. Epilepsy was an indication for 62.5% of pregnancies with an ASM prescription and non-epilepsy indications were present for 66.6%. Continuous prescription of ASMs during pregnancy was more common in women with epilepsy (64.3%) than in women with other indications (25.3%). Switching ASMs was infrequent (0.8% of ASM users). Factors associated with discontinuation included age ≥35, higher social deprivation, more frequent contact with the GP and being prescribed antidepressants or antipsychotics. CONCLUSIONS: ASM prescription during pregnancy increased between 1995 and 2018 in the UK. Patterns of prescription around the pregnancy period vary by indication and are associated with several maternal characteristics.

Dementia prevention: the Mendelian randomisation perspective.

Understanding the causes of Alzheimer's disease and related dementias remains a challenge. Observational studies investigating dementia risk factors are limited by the pervasive issues of confounding, reverse causation and selection biases. Conducting randomised controlled trials for dementia prevention is often impractical due to the long prodromal phase and the inability to randomise many potential risk factors. In this essay, we introduce Mendelian randomisation as an alternative approach to examine factors that may prevent or delay Alzheimer's disease. Mendelian randomisation is a causal inference method that has successfully identified risk factors and treatments in various other fields. However, applying this method to dementia risk factors has yielded unexpected findings. Here, we consider five potential explanations and provide recommendations to enhance causal inference from Mendelian randomisation studies on dementia. By employing these strategies, we can better understand factors affecting dementia risk.

The bidirectional effects between cognitive ability and brain morphology: A life course Mendelian randomization analysis.

Introduction: Little is understood about the dynamic interplay between brain morphology and cognitive ability across the life course. Additionally, most existing research has focused on global morphology measures such as estimated total intracranial volume, mean thickness, and total surface area. Methods: Mendelian randomization was used to estimate the bidirectional effects between cognitive ability, global and regional measures of cortical thickness and surface area, estimated total intracranial volume, total white matter, and the volume of subcortical structures (N=37,864). Analyses were stratified for developmental periods (childhood, early adulthood, mid-to-late adulthood; age range: 8-81 years). Results: The earliest effects were observed in childhood and early adulthood in the frontoparietal lobes. A bidirectional relationship was identified between higher cognitive ability, larger estimated total intracranial volume (childhood, mid-to-late adulthood) and total surface area (all life stages). A thicker posterior cingulate cortex and a larger surface area in the caudal middle frontal cortex and temporal pole were associated with greater cognitive ability. Contrary, a thicker temporal pole was associated with lower cognitive ability. Discussion: Stable effects of cognitive ability on brain morphology across the life course suggests that childhood is potentially an important window for intervention.

Antidepressants in pregnancy: applying causal epidemiological methods to understand service-use outcomes in women and long-term neurodevelopmental outcomes in exposed children.

Background: Antidepressants are commonly prescribed during pregnancy, despite a lack of evidence from randomised trials on the benefits or risks. Some studies have reported associations of antidepressants during pregnancy with adverse offspring neurodevelopment, but whether or not such associations are causal is unclear. Objectives: To study the associations of antidepressants for depression in pregnancy with outcomes using multiple methods to strengthen causal inference. Design: This was an observational cohort design using multiple methods to strengthen causal inference, including multivariable regression, propensity score matching, instrumental variable analysis, negative control exposures, comparison across indications and exposure discordant pregnancies analysis. Setting: This took place in UK general practice. Participants: Participants were pregnant women with depression. Interventions: The interventions were initiation of antidepressants in pregnancy compared with no initiation, and continuation of antidepressants in pregnancy compared with discontinuation. Main outcome measures: The maternal outcome measures were the use of primary care and secondary mental health services during pregnancy, and during four 6-month follow-up periods up to 24 months after pregnancy, and antidepressant prescription status 24 months following pregnancy. The child outcome measures were diagnosis of autism, diagnosis of attention deficit hyperactivity disorder and intellectual disability. Data sources: UK Clinical Practice Research Datalink. Results: Data on 80,103 pregnancies were used to study maternal primary care outcomes and were linked to 34,274 children with at least 4-year follow-up for neurodevelopmental outcomes. Women who initiated or continued antidepressants during pregnancy were more likely to have contact with primary and secondary health-care services during and after pregnancy and more likely to be prescribed an antidepressant 2 years following the end of pregnancy than women who did not initiate or continue antidepressants during pregnancy (odds ratioinitiation 2.16, 95% confidence interval 1.95 to 2.39; odds ratiocontinuation 2.40, 95% confidence interval 2.27 to 2.53). There was little evidence for any substantial association with autism (odds ratiomultivariableregression 1.10, 95% confidence interval 0.90 to 1.35; odds ratiopropensityscore 1.06, 95% confidence interval 0.84 to 1.32), attention deficit hyperactivity disorder (odds ratiomultivariableregression 1.02, 95% confidence interval 0.80 to 1.29; odds ratiopropensityscore 0.97, 95% confidence interval 0.75 to 1.25) or intellectual disability (odds ratiomultivariableregression 0.81, 95% confidence interval 0.55 to 1.19; odds ratiopropensityscore 0.89, 95% confidence interval 0.61 to 1.31) in children of women who continued antidepressants compared with those who discontinued antidepressants. There was inconsistent evidence of an association between initiation of antidepressants in pregnancy and diagnosis of autism in offspring (odds ratiomultivariableregression 1.23, 95% confidence interval 0.85 to 1.78; odds ratiopropensityscore 1.64, 95% confidence interval 1.01 to 2.66) but not attention deficit hyperactivity disorder or intellectual disability; however, but results were imprecise owing to smaller numbers. Limitations: Several causal-inference analyses lacked precision owing to limited numbers. In addition, adherence to the prescribed treatment was not measured. Conclusions: Women prescribed antidepressants during pregnancy had greater service use during and after pregnancy than those not prescribed antidepressants. The evidence against any substantial association with autism, attention deficit hyperactivity disorder or intellectual disability in the children of women who continued compared with those who discontinued antidepressants in pregnancy is reassuring. Potential association of initiation of antidepressants during pregnancy with offspring autism needs further investigation. Future work: Further research on larger samples could increase the robustness and precision of these findings. These methods applied could be a template for future pharmaco-epidemiological investigation of other pregnancy-related prescribing safety concerns. Funding: This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (15/80/19) and will be published in full in Health Technology Assessment; Vol. 27, No. 15. See the NIHR Journals Library website for further project information.

About one in seven women experience depression during pregnancy. Left untreated, this may harm them and their unborn babies. However, the decision to take antidepressants during pregnancy is difficult because women often worry about the risks to their unborn baby. Research findings have been inconsistent, so women often do not have clear information to enable them to make informed decisions. We studied women's and children's outcomes after starting (compared with not starting) or continuing (compared with stopping) antidepressants in pregnancy. We used a large UK primary care database and several novel methods of analysis. We tracked 80,103 pregnancies of women with depression for up to 2 years after pregnancy. We also tracked 34,274 children from these pregnancies for at least 4 years to check for developmental outcomes. Women prescribed antidepressants were more likely than women not prescribed antidepressants to use general practice and mental health services during and after pregnancy, and to be prescribed antidepressants 2 years after pregnancy. This suggests that antidepressants were being prescribed to women with greater clinical need. Women who continued antidepressants in pregnancy had no higher likelihood than those who discontinued antidepressants of autism, attention deficit hyperactivity disorder or intellectual disability in their children. This should reassure women making the decision to continue taking their medications in pregnancy. Women who started antidepressants in pregnancy may possibly have had a slightly higher likelihood of autism in their children than those who did not start them. These findings were not seen in all analyses and were based on smaller numbers; therefore, they should be viewed with caution. Importantly, over 98 in every 100 children of women who initiated or continued antidepressants in pregnancy did not receive an autism diagnosis. The findings may help women and clinicians make informed decisions on treatment with antidepressants in pregnancy.

Quantifying the causal impact of biological risk factors on healthcare costs.

Understanding the causal impact that clinical risk factors have on healthcare-related costs is critical to evaluate healthcare interventions. Here, we used a genetically-informed design, Mendelian Randomization (MR), to infer the causal impact of 15 risk factors on annual total healthcare costs. We calculated healthcare costs for 373,160 participants from the FinnGen Study and replicated our results in 323,774 individuals from the United Kingdom and Netherlands. Robust causal effects were observed for waist circumference (WC), adult body mass index, and systolic blood pressure, in which a standard deviation increase corresponded to 22.78% [95% CI: 18.75-26.95], 13.64% [10.26-17.12], and 13.08% [8.84-17.48] increased healthcare costs, respectively. A lack of causal effects was observed for certain clinically relevant biomarkers, such as albumin, C-reactive protein, and vitamin D. Our results indicated that increased WC is a major contributor to annual total healthcare costs and more attention may be given to WC screening, surveillance, and mitigation.

The causal effects of education on adult health, mortality and income: evidence from Mendelian randomization and the raising of the school leaving age.

BACKGROUND: On average, educated people are healthier, wealthier and have higher life expectancy than those with less education. Numerous studies have attempted to determine whether education causes differences in later health outcomes or whether another factor ultimately causes differences in education and subsequent outcomes. Previous studies have used a range of natural experiments to provide causal evidence. Here we compare two natural experiments: a policy reform, raising the school leaving age in the UK in 1972; and Mendelian randomization. METHODS: We used data from 334 974 participants of the UK Biobank, sampled between 2006 and 2010. We estimated the effect of an additional year of education on 25 outcomes, including mortality, measures of morbidity and health, ageing and income, using multivariable adjustment, the policy reform and Mendelian randomization. We used a range of sensitivity analyses and specification tests to assess the plausibility of each method's assumptions. RESULTS: The three different estimates of the effects of educational attainment were largely consistent in direction for diabetes, stroke and heart attack, mortality, smoking, income, grip strength, height, body mass index (BMI), intelligence, alcohol consumption and sedentary behaviour. However, there was evidence that education reduced rates of moderate exercise and increased alcohol consumption. Our sensitivity analyses suggest that confounding by genotypic or phenotypic confounders or specific forms of pleiotropy are unlikely to explain our results. CONCLUSIONS: Previous studies have suggested that the differences in outcomes associated with education may be due to confounding. However, the two independent sources of exogenous variation we exploit largely imply consistent causal effects of education on outcomes later in life.

Educational attainment, health outcomes and mortality: a within-sibship Mendelian randomization study.

BACKGROUND: Previous Mendelian randomization (MR) studies using population samples (population MR) have provided evidence for beneficial effects of educational attainment on health outcomes in adulthood. However, estimates from these studies may have been susceptible to bias from population stratification, assortative mating and indirect genetic effects due to unadjusted parental genotypes. MR using genetic association estimates derived from within-sibship models (within-sibship MR) can avoid these potential biases because genetic differences between siblings are due to random segregation at meiosis. METHODS: Applying both population and within-sibship MR, we estimated the effects of genetic liability to educational attainment on body mass index (BMI), cigarette smoking, systolic blood pressure (SBP) and all-cause mortality. MR analyses used individual-level data on 72 932 siblings from UK Biobank and the Norwegian HUNT study, and summary-level data from a within-sibship Genome-wide Association Study including >140 000 individuals. RESULTS: Both population and within-sibship MR estimates provided evidence that educational attainment decreased BMI, cigarette smoking and SBP. Genetic variant-outcome associations attenuated in the within-sibship model, but genetic variant-educational attainment associations also attenuated to a similar extent. Thus, within-sibship and population MR estimates were largely consistent. The within-sibship MR estimate of education on mortality was imprecise but consistent with a putative effect. CONCLUSIONS: These results provide evidence of beneficial individual-level effects of education (or liability to education) on adulthood health, independently of potential demographic and family-level confounders.

Weakening of the cognition and height association from 1957 to 2018: Findings from four British birth cohort studies.

Background: Taller individuals have been repeatedly found to have higher scores on cognitive assessments. Recent studies have suggested that this association can be explained by genetic factors, yet this does not preclude the influence of environmental or social factors that may change over time. We thus tested whether the association changed across time using data from four British birth cohorts (born in 1946, 1958, 1970, and 2001). Methods: In each cohort height was measured and cognition via verbal reasoning, vocabulary/comprehension, and mathematical tests; at ages 10/11 and 14/17 years (N=41,418). We examined associations between height and cognition at each age, separately in each cohort, and for each cognitive test administered. Linear and quantile regression models were used. Results: Taller participants had higher mean cognitive assessment scores in childhood and adolescence, yet the associations were weaker in later (1970 and 2001) cohorts. For example, the mean difference in height comparing the highest with lowest verbal cognition scores at 10/11 years was 0.57 SD (95% CI = 0.44-0.70) in the 1946 cohort, yet 0.30 SD (0.23-0.37) in the 2001 cohort. Expressed alternatively, there was a reduction in correlation from 0.17 (0.15-0.20) to 0.08 (0.06-0.10). This pattern of change in the association was observed across all ages and cognition measures used, was robust to adjustment for social class and parental height, and modeling of plausible missing-not-at-random scenarios. Quantile regression analyses suggested that these differences were driven by differences in the lower centiles of height, where environmental influence may be greatest. Conclusions: Associations between height and cognitive assessment scores in childhood-adolescence substantially weakened from 1957-2018. These results support the notion that environmental and social change can markedly weaken associations between cognition and other traits. Funding: DB is supported by the Economic and Social Research Council (grant number ES/M001660/1); DB and LW by the Medical Research Council (MR/V002147/1). The Medical Research Council (MRC) and the University of Bristol support the MRC Integrative Epidemiology Unit [MC_UU_00011/1]. NMD is supported by an Norwegian Research Council Grant number 295989. VM is supported by the CLOSER Innovation Fund WP19 which is funded by the Economic and Social Research Council (award reference: ES/K000357/1) and Economic and Social Research Council (ES/M001660/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The association between cognitive ability and body mass index: A sibling-comparison analysis in four longitudinal studies.

BACKGROUND: Body mass index (BMI) and obesity rates have increased sharply since the 1980s. While multiple epidemiologic studies have found that higher adolescent cognitive ability is associated with lower adult BMI, residual and unobserved confounding due to family background may explain these associations. We used a sibling design to test this association accounting for confounding factors shared within households. METHODS AND FINDINGS: We used data from four United States general youth population cohort studies: the National Longitudinal Study of Youth 1979 (NLSY-79), the NLSY-79 Children and Young Adult, the NLSY 1997 (NLSY-97), and the Wisconsin Longitudinal Study (WLS); a total of 12,250 siblings from 5,602 households followed from adolescence up to age 62. We used random effects within-between (REWB) and residualized quantile regression (RQR) models to compare between- and within-family estimates of the association between adolescent cognitive ability and adult BMI (20 to 64 years). In REWB models, moving from the 25th to 75th percentile of adolescent cognitive ability was associated with -0.95 kg/m2 (95% CI = -1.21, -0.69) lower BMI between families. Adjusting for family socioeconomic position reduced the association to -0.61 kg/m2 (-0.90, -0.33). However, within families, the association was just -0.06 kg/m2 (-0.35, 0.23). This pattern of results was found across multiple specifications, including analyses conducted in separate cohorts, models examining age-differences in association, and in RQR models examining the association across the distribution of BMI. Limitations include the possibility that within-family estimates are biased due to measurement error of the exposure, confounding via non-shared factors, and carryover effects. CONCLUSIONS: The association between high adolescent cognitive ability and low adult BMI was substantially smaller in within-family compared with between-family analysis. The well-replicated associations between cognitive ability and subsequent BMI may largely reflect confounding by family background factors.

Intergenerational effects of parental educational attainment on parenting and childhood educational outcomes: Evidence from MoBa using within-family Mendelian randomization.

The intergenerational transmission of educational attainment from parents to their children is one of the most important and studied relationships in social science. Longitudinal studies have found strong associations between parents' and their children's educational outcomes, which could be due to the effects of parents. Here we provide new evidence about whether parents' educational attainment affects their parenting behaviours and children's early educational outcomes using within-family Mendelian randomization and data from 40,879 genotyped parent-child trios from the Norwegian Mother, Father and Child Cohort (MoBa) study. We found evidence suggesting that parents' educational attainment affects their children's educational outcomes from age 5 to 14. More studies are needed to provide more samples of parent-child trios and assess the potential consequences of selection bias and grandparental effects.

Impact of altering referral threshold from out-of-hours primary care to hospital on patient safety and further health service use: a cohort study.

OBJECTIVES: To estimate the impact of altering referral thresholds from out-of-hours services on older patients' further use of health services and risk of death. DESIGN: Cohort study using patient data from primary and specialised health services and demographic data from Statistics Norway and the Norwegian Cause of Death Registry. SETTING: Norway PARTICIPANTS: 491 653 patients aged 65 years and older contacting Norwegian out-of-hours services between 2008 and 2016. ANALYSIS: Multivariable adjusted and instrumental variable associations between referrals to hospital from out-of-hours services and further health services use and death for up to 6 months.Physicians' proportions of acute referrals of older, unknown patients from out-of-hours work were used as an instrumental variable ('physician referral preference') for their threshold of referral for such patients whose clinical presentations were less clear cut. RESULTS: For older patients, whose referrals could be attributed to their physicians' threshold for referral, mean length of stay in hospital increased 3.30 days (95% CI 3.13 to 3.27) within the first 10 days, compared with non-referred patients. Such referrals also increased 6 months use of outpatient specialist clinics and primary care physicians. Importantly, patients with referrals attributable to their physicians' threshold had a substantially reduced risk of death the first 10 days (HR 0.53, 95% CI 0.31 to 0.91), an effect sustaining through the 6-month follow-up period (HR 0.72, 95% CI 0.54 to 0.97). CONCLUSIONS: Out-of-hours patients whose referrals are affected by physician referral threshold contribute substantially to the use of health services. However, the referral seems protective by reducing the risk of death in the first 6 months after the referral. Thus, raising the threshold for referral to lower pressure on overcrowded emergency departments and hospitals should not be encouraged without ensuring the accuracy of the referral decisions, ideally through high-quality randomised controlled trial evidence.

Genetic nurture versus genetic transmission of risk for ADHD traits in the Norwegian Mother, Father and Child Cohort Study.

Identifying mechanisms underlying the intergenerational transmission of risk for attention-deficit/hyperactivity disorder (ADHD) traits can inform interventions and provide insights into the role of parents in shaping their children's outcomes. We investigated whether genetic transmission and genetic nurture (environmentally mediated effects) underlie associations between polygenic scores indexing parental risk and protective factors and their offspring's ADHD traits. This birth cohort study included 19,506 genotyped mother-father-offspring trios from the Norwegian Mother, Father and Child Cohort Study. Polygenic scores were calculated for parental factors previously associated with ADHD, including psychopathology, substance use, neuroticism, educational attainment, and cognitive performance. Mothers reported on their 8-year-old children's ADHD traits (n = 9,454 children) using the Parent/Teacher Rating Scale for Disruptive Behaviour Disorders. We found that associations between ADHD maternal and paternal polygenic scores and child ADHD traits decreased significantly when adjusting for the child polygenic score (pΔß = 9.95 × 10-17 for maternal and pΔß = 1.48 × 10-14 for paternal estimates), suggesting genetic transmission of ADHD risk. Similar patterns suggesting genetic transmission of risk were observed for smoking, educational attainment, and cognition. The maternal polygenic score for neuroticism remained associated with children's ADHD ratings even after adjusting for the child polygenic score, indicating genetic nurture. There was no robust evidence of genetic nurture for other parental factors. Our findings indicate that the intergenerational transmission of risk for ADHD traits is largely explained by the transmission of genetic variants from parents to offspring rather than by genetic nurture. Observational associations between parental factors and childhood ADHD outcomes should not be interpreted as evidence for predominantly environmentally mediated effects.

How to estimate heritability: a guide for genetic epidemiologists.

Traditionally, heritability has been estimated using family-based methods such as twin studies. Advancements in molecular genomics have facilitated the development of methods that use large samples of (unrelated or related) genotyped individuals. Here, we provide an overview of common methods applied in genetic epidemiology to estimate heritability, i.e. the proportion of phenotypic variation explained by genetic variation. We provide a guide to key genetic concepts required to understand heritability estimation methods from family-based designs (twin and family studies), genomic designs based on unrelated individuals [linkage disequilibrium score regression, genomic relatedness restricted maximum-likelihood (GREML) estimation] and family-based genomic designs (sibling regression, GREML-kinship, trio-genome-wide complex trait analysis, maternal-genome-wide complex trait analysis, relatedness disequilibrium regression). We describe how heritability is estimated for each method and the assumptions underlying its estimation, and discuss the implications when these assumptions are not met. We further discuss the benefits and limitations of estimating heritability within samples of unrelated individuals compared with samples of related individuals. Overall, this article is intended to help the reader determine the circumstances when each method would be appropriate and why.

Body mass index and childhood symptoms of depression, anxiety, and attention-deficit hyperactivity disorder: A within-family Mendelian randomization study.

Background: Higher BMI in childhood is associated with emotional and behavioural problems, but these associations may not be causal. Results of previous genetic studies imply causal effects but may reflect influence of demography and the family environment. Methods: This study used data on 40,949 8-year-old children and their parents from the Norwegian Mother, Father and Child Cohort Study (MoBa) and Medical Birth Registry of Norway (MBRN). We investigated the impact of BMI on symptoms of depression, anxiety, and attention-deficit hyperactivity disorder (ADHD) at age 8. We applied within-family Mendelian randomization, which accounts for familial effects by controlling for parental genotype. Results: Within-family Mendelian randomization estimates using genetic variants associated with BMI in adults suggested that a child's own BMI increased their depressive symptoms (per 5 kg/m2 increase in BMI, beta = 0.26 S.D., CI = -0.01,0.52, p=0.06) and ADHD symptoms (beta = 0.38 S.D., CI = 0.09,0.63, p=0.009). These estimates also suggested maternal BMI, or related factors, may independently affect a child's depressive symptoms (per 5 kg/m2 increase in maternal BMI, beta = 0.11 S.D., CI:0.02,0.09, p=0.01). However, within-family Mendelian randomization using genetic variants associated with retrospectively-reported childhood body size did not support an impact of BMI on these outcomes. There was little evidence from any estimate that the parents' BMI affected the child's ADHD symptoms, or that the child's or parents' BMI affected the child's anxiety symptoms. Conclusions: We found inconsistent evidence that a child's BMI affected their depressive and ADHD symptoms, and little evidence that a child's BMI affected their anxiety symptoms. There was limited evidence of an influence of parents' BMI. Genetic studies in samples of unrelated individuals, or using genetic variants associated with adult BMI, may have overestimated the causal effects of a child's own BMI. Funding: This research was funded by the Health Foundation. It is part of the HARVEST collaboration, supported by the Research Council of Norway. Individual co-author funding: the European Research Council, the South-Eastern Norway Regional Health Authority, the Research Council of Norway, Helse Vest, the Novo Nordisk Foundation, the University of Bergen, the South-Eastern Norway Regional Health Authority, the Trond Mohn Foundation, the Western Norway Regional Health Authority, the Norwegian Diabetes Association, the UK Medical Research Council. The Medical Research Council (MRC) and the University of Bristol support the MRC Integrative Epidemiology Unit.

Some studies show that children with obesity are more likely to receive a diagnosis of depression, anxiety, or attention-deficit hyperactivity disorder (ADHD). But this does not necessarily mean obesity causes these conditions. Depression, anxiety, or ADHD could cause obesity. A child's environment, including family income or their parents' mental health, could also affect a child's weight and mental health. Understanding the nature of these relationships could help scientists develop better interventions for both obesity and mental health conditions. Genetic studies may help scientists better understand the role of the environment in these conditions, but it's important to consider both the child's and their parents' genetics in these analyses. This is because parents and children share not only genes, but also environmental conditions. For example, families that carry genetic variants associated with higher body weight might also have lower incomes, if parents have been affected by biases against heavier people in society and the workplace. Children in these families could have worse mental health because of effects of their parent's weight, rather than their own weight. Looking at both child and adult genetics can help disentangle these processes. Hughes et al. show that a child's own body mass index, a ratio of weight and height, is not strongly associated with the child's mental health symptoms. They analysed genetic, weight, and health survey data from about 41,000 8-year-old children and their parents. The results suggest that a child's own BMI does not have a large effect on their anxiety symptoms. There was also no clear evidence that a child's BMI affected their symptoms of depression or ADHD. These results contradict previous studies, which did not account for parental genetics. Hughes et al. suggest that, at least for eight-year-olds, factors linked with adult weight and which differ between families may be more critical to a child's mental health than a child's own weight. For older children and adolescents, this may not be the case, and the individual's own weight may be more important. As a result, policies designed to reduce obesity in mid-childhood are unlikely to greatly improve the mental health of children. On the other hand, policies targeting the environmental or societal factors contributing to higher body weights, bias against people with higher weights, and poor child mental health directly may be more beneficial.