A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

A Bivariate Twin Study of Lifetime cannabis Initiation and Lifetime Regular Tobacco Smoking Across Three Different Countries.

Regular cigarette smoking and cannabis consumption are strongly positively related to each other, yet few studies explore their underlying variation and covariation. We evaluated the genetic and environmental decomposition of variance and covariance of these two traits in twin data from three countries with different social norms and legislation. Data from the Netherlands Twin Register, FinnTwin12/16, and the Minnesota Center for Twin Family Research (total N = 21,617) were analyzed in bivariate threshold models of lifetime regular smoking initiation (RSI) and lifetime cannabis initiation (CI). We ran unstratified models and models stratified by sex and country. Prevalence of RSI was lowest in the Netherlands and prevalence of CI was highest in Minnesota. In the unstratified model, genetic (A) and common environmental factors (C) contributed substantially to the liabilities of RSI (A = 0.47, C = 0.34) and CI (A = 0.28, C = 0.51). The two liabilities were significantly phenotypically (rP = 0.56), genetically (rA = 0.74), and environmentally correlated in the unstratified model (rC = 0.47and rE = 0.48, representing correlations between common and unique environmental factors). The magnitude of phenotypic correlation between liabilities varied by country but not sex (Minnesota rP ~ 0.70, Netherlands rP ~ 0.59, Finland rP ~ 0.45). Comparisons of decomposed correlations could not be reliably tested in the stratified models. The prevalence and association of RSI and CI vary by sex and country. These two behaviors are correlated because there is genetic and environmental overlap between their underlying latent liabilities. There is heterogeneity in the genetic architecture of these traits across country.

Associations between adolescent cannabis use and young-adult functioning in three longitudinal twin studies.

Observational studies have linked cannabis use to an array of negative outcomes, including psychiatric symptoms, cognitive impairment, and educational and occupational underachievement. These associations are particularly strong when cannabis use occurs in adolescence. Nevertheless, causality remains unclear. The purpose of the present study was thus to examine associations between prospectively assessed adolescent cannabis use and young-adult outcomes (psychiatric, cognitive, and socioeconomic) in three longitudinal studies of twins (n = 3,762). Twins reporting greater cumulative cannabis use in adolescence reported higher levels of psychopathology as well as poorer socioeconomic outcomes in young adulthood. However, cannabis use remained associated only with socioeconomic outcomes (i.e., educational attainment, occupational status, and income) in monozygotic-cotwin control analyses, which account fully for shared genetic and environmental confounding. Follow-up analyses examining associations between twin differences in adolescent cannabis use and longitudinal change in academic functioning during the middle- and high-school years provided a possible mechanism for these associations, indicating that greater cannabis use during this period was associated with decreases in grade point average and academic motivation as well as increases in academic problem behavior and school disciplinary problems. Our findings thus suggest that cannabis use in adolescence has potentially causal, deleterious effects on adolescent academic functioning and young-adult socioeconomic outcomes despite little evidence suggesting a strong, causal influence on adult mental health or cognitive ability.

Recreational cannabis legalization has had limited effects on a wide range of adult psychiatric and psychosocial outcomes.

BACKGROUND: The causal impacts of recreational cannabis legalization are not well understood due to the number of potential confounds. We sought to quantify possible causal effects of recreational cannabis legalization on substance use, substance use disorder, and psychosocial functioning, and whether vulnerable individuals are more susceptible to the effects of cannabis legalization than others. METHODS: We used a longitudinal, co-twin control design in 4043 twins (N = 240 pairs discordant on residence), first assessed in adolescence and now age 24-49, currently residing in states with different cannabis policies (40% resided in a recreationally legal state). We tested the effect of legalization on outcomes of interest and whether legalization interacts with established vulnerability factors (age, sex, or externalizing psychopathology). RESULTS: In the co-twin control design accounting for earlier cannabis frequency and alcohol use disorder (AUD) symptoms respectively, the twin living in a recreational state used cannabis on average more often (ßw = 0.11, p = 1.3 × 10-3), and had fewer AUD symptoms (ßw = -0.11, p = 6.7 × 10-3) than their co-twin living in an non-recreational state. Cannabis legalization was associated with no other adverse outcome in the co-twin design, including cannabis use disorder. No risk factor significantly interacted with legalization status to predict any outcome. CONCLUSIONS: Recreational legalization was associated with increased cannabis use and decreased AUD symptoms but was not associated with other maladaptations. These effects were maintained within twin pairs discordant for residence. Moreover, vulnerabilities to cannabis use were not exacerbated by the legal cannabis environment. Future research may investigate causal links between cannabis consumption and outcomes.

Associations between polygenic risk of substance use and use disorder and alcohol, cannabis, and nicotine use in adolescence and young adulthood in a longitudinal twin study.

BACKGROUND: Recent well-powered genome-wide association studies have enhanced prediction of substance use outcomes via polygenic scores (PGSs). Here, we test (1) whether these scores contribute to prediction over-and-above family history, (2) the extent to which PGS prediction reflects inherited genetic variation v. demography (population stratification and assortative mating) and indirect genetic effects of parents (genetic nurture), and (3) whether PGS prediction is mediated by behavioral disinhibition prior to substance use onset. METHODS: PGSs for alcohol, cannabis, and nicotine use/use disorder were calculated for Minnesota Twin Family Study participants (N = 2483, 1565 monozygotic/918 dizygotic). Twins' parents were assessed for histories of substance use disorder. Twins were assessed for behavioral disinhibition at age 11 and substance use from ages 14 to 24. PGS prediction of substance use was examined using linear mixed-effects, within-twin pair, and structural equation models. RESULTS: Nearly all PGS measures were associated with multiple types of substance use independently of family history. However, most within-pair PGS prediction estimates were substantially smaller than the corresponding between-pair estimates, suggesting that prediction is driven in part by demography and indirect genetic effects of parents. Path analyses indicated the effects of both PGSs and family history on substance use were mediated via disinhibition in preadolescence. CONCLUSIONS: PGSs capturing risk of substance use and use disorder can be combined with family history measures to augment prediction of substance use outcomes. Results highlight indirect sources of genetic associations and preadolescent elevations in behavioral disinhibition as two routes through which these scores may relate to substance use.

Exploring Relationships Between Internalizing Problems and Risky Sexual Behavior: A Twin Study.

Previous research links risky sexual behavior (RSB) to externalizing problems and to substance use, but little research has been conducted on relationships between internalizing problems (INT) and RSB. The current study addresses that literature gap, using both a twin sample from Colorado (N = 2567) and a second twin sample from Minnesota (N = 1131) in attempt to replicate initial results. We explored the hypothesis that the latent variable INT would be more strongly associated with the latent variable RSB for females than for males, examining relationships between INT and RSB via phenotypic confirmatory factor analysis and multivariate twin analyses. We found a small but significant phenotypic association between the latent variables. However, despite using two large twin samples, limited power restricted our ability to identify the genetic and environmental mechanisms underlying this association. Our sex differences hypothesis was not fully supported in either sample and requires further investigation. Our findings illustrate the complexity of the relationship between internalizing problems and risky sexual behavior.

Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis.

Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 28 discovery samples (N = 85,359) and five independent replication samples (N = 8058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, p = 6.32 × 10-10). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/cJ strain) from controls (BALB/cByJ strain). Polygenic risk score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial genetic correlations of ASB with mental health (depression rg = 0.63, insomnia rg = 0.47), physical health (overweight rg = 0.19, waist-to-hip ratio rg = 0.32), smoking (rg = 0.54), cognitive ability (intelligence rg = -0.40), educational attainment (years of schooling rg = -0.46) and reproductive traits (age at first birth rg = -0.58, father's age at death rg = -0.54). Our findings provide a starting point toward identifying critical biosocial risk mechanisms for the development of ASB.

Addendum to "Evaluating substance use outcomes of recreational cannabis legalization using a unique co-twin control design".

An earlier version of this article was published in error. Our prior publication was missing reference to a prior study on this topic. Our prior research has not found an association between recreational cannabis legalization (RCL) and negative psychosocial and psychiatric outcomes. We reported significant associations between RCL with greater cannabis frequency and fewer alcohol use disorder symptoms. The current study expands on our previous research by using a cross-sectional design and different measures of problems from cannabis and alcohol use and including additional substance use variables. The current study found similar results to our previous research.

Evaluating substance use outcomes of recreational cannabis legalization using a unique co-twin control design.

Background: As more states pass recreational cannabis legalization (RCL), we must understand how RCL affects substance use.Objectives: The current study aims to examine the effect of RCL on lifetime and past-year use of cannabis, alcohol, tobacco, and other drugs, frequency of cannabis, alcohol, and tobacco use, co-use of cannabis with alcohol and tobacco, and consequences from cannabis and alcohol use.Methods: We used a unique, co-twin control design of twin pairs who were discordant for living in a state with RCL between 2018 and 2021. The sample consisted of 3,830 adult twins (41% male), including 232 twin pairs discordant for RCL. Problems from alcohol and cannabis use were assessed via the Brief Marijuana Consequences Questionnaire and the Brief Young Adult Alcohol Consequences Questionnaire.Results: Results indicated that the twin living in an RCL state was more likely to endorse past-year cannabis use (OR = 1.56, p = .009), greater number of cannabis use days in the past 6 months (ß = 0.47, p = .019), but not more negative consequences from cannabis use (ß = 0.21, p = .456) compared to their co-twin in a non-RCL state. There were no differences within-twin pairs in frequency of alcohol use (ß=-0.05, p = .601), but the RCL twin reported fewer negative consequences from alcohol use (ß=-0.29, p = .016) compared to their co-twin in a non-RCL state. We did not observe any other differences within-twin pairs on other outcomes.Conclusion: These results suggest that living in an RCL state is associated with greater cannabis frequency but not more negative consequences from cannabis use than living in a non-RCL state.

The association between saving disposition and financial distress: A genetically informed approach.

Saving disposition, the tendency to save rather than consume, has been found to be associated with economic outcomes. People lacking the disposition to save are more likely to experience financial distress. This association could be driven by other economic factors, behavioral traits, or even genetic effects. Using a sample of 3,920 American twins, we develop scales to measure saving disposition and financial distress. We find genetic influences on both traits, but also a large effect of the rearing family environment on saving disposition. We estimate that 44% of the covariance between the two traits is due to genetic effects. Saving disposition remains strongly associated with lower financial distress, even after controlling for family income, cognitive ability, and personality traits. The association persists within families and monozygotic twin pairs; the twin who saves more tends to be the twin who experiences less financial distress. This result suggest that there is a direct association between saving disposition and financial distress, although the direction of causation remains unclear.

Genes for Good: Engaging the Public in Genetics Research via Social Media.

The Genes for Good study uses social media to engage a large, diverse participant pool in genetics research and education. Health history and daily tracking surveys are administered through a Facebook application, and participants who complete a minimum number of surveys are mailed a saliva sample kit ("spit kit") to collect DNA for genotyping. As of March 2019, we engaged >80,000 individuals, sent spit kits to >32,000 individuals who met minimum participation requirements, and collected >27,000 spit kits. Participants come from all 50 states and include a diversity of ancestral backgrounds. Rates of important chronic health indicators are consistent with those estimated for the general U.S. population using more traditional study designs. However, our sample is younger and contains a greater percentage of females than the general population. As one means of verifying data quality, we have replicated genome-wide association studies (GWASs) for exemplar traits, such as asthma, diabetes, body mass index (BMI), and pigmentation. The flexible framework of the web application makes it relatively simple to add new questionnaires and for other researchers to collaborate. We anticipate that the study sample will continue to grow and that future analyses may further capitalize on the strengths of the longitudinal data in combination with genetic information.

Genetic correlation, pleiotropy, and causal associations between substance use and psychiatric disorder.

BACKGROUND: Substance use occurs at a high rate in persons with a psychiatric disorder. Genetically informative studies have the potential to elucidate the etiology of these phenomena. Recent developments in genome-wide association studies (GWAS) allow new avenues of investigation. METHOD: Using results of GWAS meta-analyses, we performed a factor analysis of the genetic correlation structure, a genome-wide search of shared loci, and causally informative tests for six substance use phenotypes (four smoking, one alcohol, and one cannabis use) and five psychiatric disorders (ADHD, anorexia, depression, bipolar disorder, and schizophrenia). RESULTS: Two correlated externalizing and internalizing/psychosis factor were found, although model fit was beneath conventional standards. Of 458 loci reported in previous univariate GWAS of substance use and psychiatric disorders, about 50% (230 loci) were pleiotropic with additional 111 pleiotropic loci not reported from past GWAS. Of the 341 pleiotropic loci, 152 were associated with both substance use and psychiatric disorders, implicating neurodevelopment, cell morphogenesis, biological adhesion pathways, and enrichment in 13 different brain tissues. Seventy-five and 114 pleiotropic loci were specific to either psychiatric disorders or substance use phenotypes, implicating neuronal signaling pathway and clathrin-binding functions/structures, respectively. No consistent evidence for phenotypic causation was found across different Mendelian randomization methods. CONCLUSIONS: Genetic etiology of substance use and psychiatric disorders is highly pleiotropic and involves shared neurodevelopmental path, neurotransmission, and intracellular trafficking. In aggregate, the patterns are not consistent with vertical pleiotropy, more likely reflecting horizontal pleiotropy or more complex forms of phenotypic causation.

Longitudinal effects and environmental moderation of ALDH2 and ADH1B gene variants on substance use from age 14 to 40.

Alcohol use and dependence are strongly affected by variation in aldehyde dehydrogenase (ALDH2) and, to a lesser extent, alcohol dehydrogenase (ADH1B) genes. We use this genetic variation with an adoption design to test the causal role of alcohol use on other drug use, as well as the moderating role of adoptive parent, sibling, and peer alcohol use. Longitudinal models were run on 412 genotyped adopted individuals of East Asian ancestry with multiple assessments between ages 14 and 40. We found robust associations between alcohol frequency, quantity, and maximum drinks and ALDH2, but not ADH1B, status. The magnitude of the ALDH2 protective effect increased with age, particularly for maximum drinks, though estimates were smaller than previously reported in ancestrally similar individuals in East/North-East Asian countries. These results suggest that sociocultural factors in Minnesota may reduce the protective effects of ALDH2. We found that peer alcohol use, but not parent or sibling use, predicted adopted offspring's use, and that these environmental influences did not vary by ALDH2 status. Finally, we did not find strong evidence of associations between ALDH2 status and tobacco, marijuana, or illegal drug use, contrary to expectation if alcohol serves as a gateway to use of other drugs.

A Century of Behavioral Genetics at the University of Minnesota.

The University of Minnesota has played an important role in the resurgence and eventual mainstreaming of human behavioral genetics in psychology and psychiatry. We describe this history in the context of three major movements in behavioral genetics: (1) radical eugenics in the early 20th century, (2) resurgence of human behavioral genetics in the 1960s, largely using twin and adoption designs to obtain more precise estimates of genetic and environmental influences on individual differences in behavior; and (3) use of measured genotypes to understand behavior. University of Minnesota scientists made significant contributions especially in (2) and (3) in the domains of cognitive ability, drug abuse and mental health, and endophenotypes. These contributions are illustrated through a historical perspective of major figures and events in behavioral genetics.

Dissecting the genetic overlap of smoking behaviors, lung cancer, and chronic obstructive pulmonary disease: A focus on nicotinic receptors and nicotine metabolizing enzyme.

Smoking is a major contributor to lung cancer and chronic obstructive pulmonary disease (COPD). Two of the strongest genetic associations of smoking-related phenotypes are the chromosomal regions 15q25.1, encompassing the nicotinic acetylcholine receptor subunit genes CHRNA5-CHRNA3-CHRNB4, and 19q13.2, encompassing the nicotine metabolizing gene CYP2A6. In this study, we examined genetic relations between cigarettes smoked per day, smoking cessation, lung cancer, and COPD. Data consisted of genome-wide association study summary results. Genetic correlations were estimated using linkage disequilibrium score regression software. For each pair of outcomes, z-score-z-score (ZZ) plots were generated. Overall, heavier smoking and decreased smoking cessation showed positive genetic associations with increased lung cancer and COPD risk. The chromosomal region 19q13.2, however, showed a different correlational pattern. For example, the effect allele-C of the sentinel SNP (rs56113850) within CYP2A6 was associated with an increased risk of heavier smoking (z-score = 19.2; p = 1.10 × 10-81 ), lung cancer (z-score = 8.91; p = 5.02 × 10-19 ), and COPD (z-score = 4.04; p = 5.40 × 10-5 ). Surprisingly, this allele-C (rs56113850) was associated with increased smoking cessation (z-score = -8.17; p = 2.52 × 10-26 ). This inverse relationship highlights the need for additional investigation to determine how CYP2A6 variation could increase smoking cessation while also increasing the risk of lung cancer and COPD likely through increased cigarettes smoked per day.

Using multivariate endophenotypes to identify psychophysiological mechanisms associated with polygenic scores for substance use, schizophrenia, and education attainment.

BACKGROUND: To better characterize brain-based mechanisms of polygenic liability for psychopathology and psychological traits, we extended our previous report (Liu et al. Psychophysiological endophenotypes to characterize mechanisms of known schizophrenia genetic loci. Psychological Medicine, 2017), focused solely on schizophrenia, to test the association between multivariate psychophysiological candidate endophenotypes (including novel measures of θ/δ oscillatory activity) and a range of polygenic scores (PGSs), namely alcohol/cannabis/nicotine use, an updated schizophrenia PGS (containing 52 more genome-wide significant loci than the PGS used in our previous report) and educational attainment. METHOD: A large community-based twin/family sample (N = 4893) was genome-wide genotyped and imputed. PGSs were constructed for alcohol use, regular smoking initiation, lifetime cannabis use, schizophrenia, and educational attainment. Eleven endophenotypes were assessed: visual oddball task event-related electroencephalogram (EEG) measures (target-related parietal P3 amplitude, frontal θ, and parietal δ energy/inter-trial phase clustering), band-limited resting-state EEG power, antisaccade error rate. Principal component analysis exploited covariation among endophenotypes to extract a smaller number of meaningful dimensions/components for statistical analysis. RESULTS: Endophenotypes were heritable. PGSs showed expected intercorrelations (e.g. schizophrenia PGS correlated positively with alcohol/nicotine/cannabis PGSs). Schizophrenia PGS was negatively associated with an event-related P3/δ component [ß = -0.032, nonparametric bootstrap 95% confidence interval (CI) -0.059 to -0.003]. A prefrontal control component (event-related θ/antisaccade errors) was negatively associated with alcohol (ß = -0.034, 95% CI -0.063 to -0.006) and regular smoking PGSs (ß = -0.032, 95% CI -0.061 to -0.005) and positively associated with educational attainment PGS (ß = 0.031, 95% CI 0.003-0.058). CONCLUSIONS: Evidence suggests that multivariate endophenotypes of decision-making (P3/δ) and cognitive/attentional control (θ/antisaccade error) relate to alcohol/nicotine, schizophrenia, and educational attainment PGSs and represent promising targets for future research.

Proper conditional analysis in the presence of missing data: Application to large scale meta-analysis of tobacco use phenotypes.

Meta-analysis of genetic association studies increases sample size and the power for mapping complex traits. Existing methods are mostly developed for datasets without missing values, i.e. the summary association statistics are measured for all variants in contributing studies. In practice, genotype imputation is not always effective. This may be the case when targeted genotyping/sequencing assays are used or when the un-typed genetic variant is rare. Therefore, contributed summary statistics often contain missing values. Existing methods for imputing missing summary association statistics and using imputed values in meta-analysis, approximate conditional analysis, or simple strategies such as complete case analysis all have theoretical limitations. Applying these approaches can bias genetic effect estimates and lead to seriously inflated type-I or type-II errors in conditional analysis, which is a critical tool for identifying independently associated variants. To address this challenge and complement imputation methods, we developed a method to combine summary statistics across participating studies and consistently estimate joint effects, even when the contributed summary statistics contain large amounts of missing values. Based on this estimator, we proposed a score statistic called PCBS (partial correlation based score statistic) for conditional analysis of single-variant and gene-level associations. Through extensive analysis of simulated and real data, we showed that the new method produces well-calibrated type-I errors and is substantially more powerful than existing approaches. We applied the proposed approach to one of the largest meta-analyses to date for the cigarettes-per-day phenotype. Using the new method, we identified multiple novel independently associated variants at known loci for tobacco use, which were otherwise missed by alternative methods. Together, the phenotypic variance explained by these variants was 1.1%, improving that of previously reported associations by 71%. These findings illustrate the extent of locus allelic heterogeneity and can help pinpoint causal variants.

Adolescent Externalizing Psychopathology and Its Prospective Relationship to Marijuana Use Development from Age 14 to 30: Replication Across Independent Longitudinal Twin Samples.

Externalizing psychopathology in early adolescence is a highly heritable risk factor for drug use, yet how it relates to marijuana use development is not well-characterized. We evaluate this issue in independent twin samples from Colorado (N = 2608) and Minnesota (N = 3630), assessed from adolescence to early adulthood. We used a biometric latent growth model of marijuana use frequency with data from up to five waves of assessment from ages 14 to 30, to examine change in marijuana use and its relationship with a factor model of adolescent externalizing psychopathology. The factor structure of adolescent externalizing psychopathology was similar across samples, as was the association between that common factor and early marijuana use (Minnesota r = 0.67 [0.60, 0.75]; Colorado r = 0.69 [0.59, 0.78]), and increase in use (Minnesota r = 0.18 [0.10, 0.26]; Colorado r = 0.20 [0.07, 0.34]). Early use was moderately heritable in both samples (Minnesota h2 = 0.57 [0.37, 0.79]; Colorado h2 = 0.42 [0.14, 0.73]). Increase in use was highly heritable in Minnesota (h2 = 0.82 [0.72, 0.88]), less so in Colorado (h2 = 0.22 [0.01, 0.66]), and shared environmental effects were larger in Colorado (c2 = 0.55 [0.14, 0.83]) than Minnesota (c2 = 0 [0, 0.06]). We found moderate genetic correlations between externalizing psychopathology and early use in both samples. Finally, additional analyses in the Minnesota sample indicated that marijuana use decreased during the late 20s. This decline is strongly heritable (h2 = 0.73 [0.49, 0.91]) and moderately negatively correlated with adolescent externalizing psychopathology (r = - 0.41 [- 0.54, - 0.28]). Adolescent externalizing psychopathology is genetically correlated with change in late adolescent marijuana use (late teens, early 20s), as well as maintenance of use in early adulthood (late 20 s) even after controlling for the effects of early use.

Minnesota Center for Twin and Family Research.

The Minnesota Center for Twin and Family Research (MCTFR) comprises multiple longitudinal, community-representative investigations of twin and adoptive families that focus on psychological adjustment, personality, cognitive ability and brain function, with a special emphasis on substance use and related psychopathology. The MCTFR includes the Minnesota Twin Registry (MTR), a cohort of twins who have completed assessments in middle and older adulthood; the Minnesota Twin Family Study (MTFS) of twins assessed from childhood and adolescence into middle adulthood; the Enrichment Study (ES) of twins oversampled for high risk for substance-use disorders assessed from childhood into young adulthood; the Adolescent Brain (AdBrain) study, a neuroimaging study of adolescent twins; and the Siblings Interaction and Behavior Study (SIBS), a study of adoptive and nonadoptive families assessed from adolescence into young adulthood. Here we provide a brief overview of key features of these established studies and describe new MCTFR investigations that follow up and expand upon existing studies or recruit and assess new samples, including the MTR Study of Relationships, Personality, and Health (MTR-RPH); the Colorado-Minnesota (COMN) Marijuana Study; the Adolescent Brain Cognitive Development (ABCD) study; the Colorado Online Twins (CoTwins) study and the Children of Twins (CoT) study.

Narrow-sense heritability estimation of complex traits using identity-by-descent information.

Heritability is a fundamental parameter in genetics. Traditional estimates based on family or twin studies can be biased due to shared environmental or non-additive genetic variance. Alternatively, those based on genotyped or imputed variants typically underestimate narrow-sense heritability contributed by rare or otherwise poorly tagged causal variants. Identical-by-descent (IBD) segments of the genome share all variants between pairs of chromosomes except new mutations that have arisen since the last common ancestor. Therefore, relating phenotypic similarity to degree of IBD sharing among classically unrelated individuals is an appealing approach to estimating the near full additive genetic variance while possibly avoiding biases that can occur when modeling close relatives. We applied an IBD-based approach (GREML-IBD) to estimate heritability in unrelated individuals using phenotypic simulation with thousands of whole-genome sequences across a range of stratification, polygenicity levels, and the minor allele frequencies of causal variants (CVs). In simulations, the IBD-based approach produced unbiased heritability estimates, even when CVs were extremely rare, although precision was low. However, population stratification and non-genetic familial environmental effects shared across generations led to strong biases in IBD-based heritability. We used data on two traits in ~120,000 people from the UK Biobank to demonstrate that, depending on the trait and possible confounding environmental effects, GREML-IBD can be applied to very large genetic datasets to infer the contribution of very rare variants lost using other methods. However, we observed apparent biases in these real data, suggesting that more work may be required to understand and mitigate factors that influence IBD-based heritability estimates.