In the late 1980s The Netherlands Twin Register (NTR) was established by recruiting young twins and multiples at birth and by approaching adolescent and young adult twins through city councils. The Adult NTR (ANTR) includes twins, their parents, siblings, spouses and their adult offspring. The number of participants in the ANTR who take part in survey and / or laboratory studies is over 22,000 subjects. A special group of participants consists of sisters who are mothers of twins. In the Young NTR (YNTR), data on more than 50,000 young twins have been collected. Currently we are extending the YNTR by including siblings of twins. Participants in YNTR and ANTR have been phenotyped every 2 to 3 years in longitudinal survey studies, since 1986 and 1991 for the YNTR and ANTR, respectively. The resulting large population-based datasets are used for genetic epidemiological studies and also, for example, to advance phenotyping through the development of new syndrome scales based on existing items from other inventories. New research developments further include brain imaging studies in selected and unselected groups, clinical assessment of psychopathology through interviews, and cross-referencing the NTR database to other national databases. A large biobank enterprise is ongoing in the ANTR in which blood and urine samples are collected for genotyping, expression analysis, and meta-bolomics studies. In this paper we give an update on the YNTR and ANTR phenotyping and on the ongoing ANTR biobank studies.

Cannabis is the most widely produced and consumed illicit psychoactive substance worldwide. Occasional cannabis use can progress to frequent use, abuse and dependence with all known adverse physical, psychological and social consequences. Individual differences in cannabis initiation are heritable (40–48%). The International Cannabis Consortium was established with the aim to identify genetic risk variants of cannabis use. We conducted a meta-analysis of genome-wide association data of 13 cohorts (N=32 330) and four replication samples (N=5627). In addition, we performed a gene-based test of association, estimated single-nucleotide polymorphism (SNP)-based heritability and explored the genetic correlation between lifetime cannabis use and cigarette use using LD score regression. No individual SNPs reached genome-wide significance. Nonetheless, gene-based tests identified four genes significantly associated with lifetime cannabis use:NCAM1,CADM2,SCOCandKCNT2. Previous studies reported associations ofNCAM1with cigarette smoking and other substance use, and those ofCADM2with body mass index, processing speed and autism disorders, which are phenotypes previously reported to be associated with cannabis use. Furthermore, we showed that, combined across the genome, all common SNPs explained 13–20% (P<0.001) of the liability of lifetime cannabis use. Finally, there was a strong genetic correlation (r_g=0.83;P=1.85 × 10⁻⁸) between lifetime cannabis use and lifetime cigarette smoking implying that the SNP effect sizes of the two traits are highly correlated. This is the largest meta-analysis of cannabis GWA studies to date, revealing important new insights into the genetic pathways of lifetime cannabis use. Future functional studies should explore the impact of the identified genes on the biological mechanisms of cannabis use.

Poor sleep quality and insomnia have been associated with the use of tobacco, alcohol, and cannabis, but it is unclear if there is a causal link. In this Mendelian Randomization (MR) study we examine if insomnia causes substance use and/or if substance use causes insomnia. MR uses summary effect estimates from a genome-wide association study (GWAS) to create a genetic instrumental variable for a proposed 'exposure' variable and then identifies that same genetic instrument in an 'outcome' GWAS. Using GWASs of insomnia, smoking (initiation, heaviness, cessation), alcohol use (drinks per week, dependence), and cannabis initiation, bi-directional causal effects were tested. Multiple sensitivity analyses were applied to assess the robustness of the findings. There was strong evidence for positive causal effects of liability to insomnia on all substance use phenotypes (smoking traits, alcohol dependence, cannabis initiation), except alcohol per week. In the other direction, there was strong evidence that smoking initiation increased insomnia risk (smoking heaviness and cessation could not be tested as exposures). We found no evidence that alcohol use per week, alcohol dependence, or cannabis initiation causally affect insomnia risk. There were unidirectional effects of liability to insomnia on alcohol dependence and cannabis initiation, and bidirectional effects between liability to insomnia and smoking measures. Bidirectional effects between smoking and insomnia might give rise to a vicious circle. Future research should investigate if interventions aimed at insomnia are beneficial for substance use treatment.