Late-onset Alzheimer’s disease (AD) is associated with sleep-related phenotypes (SRPs). The fact that whether they share a common genetic etiology remains largely unknown. We explored the shared genetics and causality between AD and SRPs by using high-definition likelihood (HDL), cross-phenotype association study (CPASSOC), transcriptome-wide association study (TWAS), and bidirectional Mendelian randomization (MR) in summary-level data for AD (N = 455,258) and summary-level data for seven SRPs (sample size ranges from 359,916 to 1,331,010). AD shared a strong genetic basis with insomnia (rg = 0.20; p = 9.70 × 10–5), snoring (rg = 0.13; p = 2.45 × 10–3), and sleep duration (rg = −0.11; p = 1.18 × 10–3). The CPASSOC identifies 31 independent loci shared between AD and SRPs, including four novel shared loci. Functional analysis and the TWAS showed shared genes were enriched in liver, brain, breast, and heart tissues and highlighted the regulatory roles of immunological disorders, very-low-density lipoprotein particle clearance, triglyceride-rich lipoprotein particle clearance, chylomicron remnant clearance, and positive regulation of T-cell–mediated cytotoxicity pathways. Protein–protein interaction analysis identified three potential drug target genes (APOE, MARK4, and HLA-DRA) that interacted with known FDA-approved drug target genes. The CPASSOC and TWAS demonstrated three regions 11p11.2, 6p22.3, and 16p11.2 may account for the shared basis between AD and sleep duration or snoring. MR showed insomnia had a causal effect on AD (ORIVW = 1.02, PIVW = 6.7 × 10–6), and multivariate MR suggested a potential role of sleep duration and major depression in this association. Our findings provide strong evidence of shared genetics and causation between AD and sleep abnormalities and advance our understanding of the genetic overlap between them. Identifying shared drug targets and molecular pathways can be beneficial for treating AD and sleep disorders more efficiently.

Background and Aims: Excessive cannabis use may lead to lower educational attainment. However, this association may be due to confounders and reverse causality. We tested the potential causal relationship between cannabis use disorder (CUD) or life-time cannabis use (LCU) and educational attainment.Design: Bidirectional two-sample Mendelian randomization (MR) study was conducted.Our primary method was inverse-variance weighted (IVW) MR, with a series of sensitivity analyses. Multivariable MR (MVMR) was performed to estimate any direct effect independent of intelligence, smoking initiation or attention deficit hyperactivity disorder (ADHD).Setting and participants: European ancestry individuals. The sample sizes of the genome-wide association study ranged from 55 374 to 632 802 participants.Measurements: Genetic variants of CUD, LCU or educational attainment.Findings: Using univariable MR, we found evidence of a potential causal effect of genetic liability to CUD on a lower educational attainment [MR, 95% confidence interval (CI) inverse variance weighted (IVW) = −1.2 month (−1.9 month, −0.5 month); P = 0.0008]. However, we found no evidence of an effect of genetic liability to LCU on educational attainment [MR, 95% CI IVW = 0.5 month (−1.5 month, 2.6 month), P = 0.6032]. Reverse direction analysis suggested that genetic liability to higher educational attainment had a potential causal effect on lower risk of CUD [odds ratio (OR), 95% CI IVW = 0.39 (0.29, 0.52), P = 1.69 × 10 −10 ]. We also found evidence of potential causal effect from genetic liability to higher educational attainment to higher risk of LCU [OR, 95% CI IVW = 1.35(1.11, 1.66), P = 0.0033].Conclusions: Genetic liability to cannabis use disorder may lead to lower educational attainment. Genetic liability to higher educational attainment may also lead to higher life-time cannabis use risk and lower cannabis use disorder risk. However, the bidirectional effect between cannabis use disorder and educational attainment may be due to shared risk factors (e.g. attention-deficit hyperactivity disorder).

BackgroundEpidemiological investigations have established unhealthy lifestyles, such as excessive leisurely sedentary behavior (especially TV/television watching) and breakfast skipping, increase the risk of type 2 diabetes (T2D), but the causal relationship is unclear. We aimed to understand how single nucleotide variants contribute to the co-occurrence of unhealthy lifestyles and T2D, thereby providing meaningful insights into disease mechanisms.MethodsCombining summary statistics from genome-wide association studies (GWAS) on TV watching (N = 422218), breakfast skipping (N = 193860) and T2D (N = 159208) in European pedigrees, we conducted comprehensive pairwise genetic analysis, including high-definition likelihood (HDL-method), cross-phenotype association studies (CPASSOC), GWAS-eQTL colocalization analysis and transcriptome-wide association studies (TWAS), to understand the genetic overlap between them. We also performed bidirectional two-sample Mendelian randomization (MR) analysis for causal inference using genetic instrumental variables, and two-step MR mediation analysis was used to assess any effects explained by body mass index, lipid traits and glycemic traits.ResultsHDL-method showed that T2D shared a strong genetic correlation with TV watching (rg = 0.26; P = 1.63×10-29) and skipping breakfast (rg = 0.15; P =2.02×10-6). CPASSOC identifies eight independent SNPs shared between T2D and TV watching, including one novel shared locus. TWAS and CPASSOC showed that shared genes were enriched in lung, esophageal, adipose, and thyroid tissues and highlighted potential shared regulatory pathways for lipoprotein metabolism, pancreatic β-cell function, cellular senescence and multi-mediator factors. MR showed TV watching had a causal effect on T2D (βIVW = 0.629, PIVW = 1.80×10-10), but no significant results were observed between breakfast skipping and T2D. Mediation analysis provided evidence that body mass index, fasting glucose, hemoglobin A1c and high-density lipoprotein are potential factors that mediate the causal relationship between TV and T2D.ConclusionsOur findings provide strong evidence of shared genetics and causation between TV watching and T2D and facilitate our identification of common genetic architectures shared between them.

Background: Alzheimer’s disease (AD) was associated with sleep-related phenotypes (SRPs). Whether they share common genetic etiology remains largely unknown. We explored the shared genetics and causality between AD and SRPs by using high-definition likelihood (HDL), cross phenotype association study (CPASSOC), transcriptome wide association study (TWAS), and bidirectional Mendelian randomization (MR) in summary-level data for AD (n = 79145) and summary-level data for seven SRPs (sample size ranges from 345552 to 386577). Results: AD shared strong genetic basis with insomnia (rg = 0.20; P = 9.70×10-5), snoring (rg = 0.13; P = 2.45×10-3), and sleep duration (rg = -0.11; P = 1.18×10-3). CPASSOC identifies 31 independent loci shared between AD and SRPs, including four novel shared loci. Functional analysis and TWAS showed shared genes were enriched in liver, brain, breast, and heart tissues, and highlighted the regulatory role of immunological disorders, very-low-density lipoprotein particle clearance, triglyceride-rich lipoprotein particle clearance, chylomicron remnant clearance and positive regulation of T cell mediated cytotoxicity pathways. Protein-protein interaction analysis provided three potential drug target genes (APOE, MARK4 and HLA-DRA) that interacted with known FDA-approved drug target genes. CPASSOC and TWAS demonstrated three regions 11p11.2, 6p22.3 and 16p11.2 may account for the shared basis between AD and sleep duration or snoring. MR showed AD had causal effect on sleep duration (βIVW = -0.056, PIVW = 1.03×10-3). Conclusion: Our findings provide strong evidence of shared genetics and causation between AD and sleep, and advance our understanding the genetic overlap between them. Identifying shared drug targets and molecular pathways can be beneficial to treat AD and sleep disorders more efficiently.