UNASSIGNED: Observational studies suggest an association between telomere length (TL) and blood lipid (BL) levels. Nevertheless, the causal connections between these two traits remain unclear. We aimed to elucidate whether genetically predicted TL is associated with BL levels via Mendelian randomization (MR) and vice versa.
UNASSIGNED: We obtained genetic instruments associated with TL, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A-1 (ApoA-1) and apolipoprotein B (ApoB) from large-scale genome-wide association studies (GWASs). The causal relationships between TL and BL were investigated via bidirectional MR, multivariable MR and mediation analysis methods. The inverse variance weighted (IVW) method was employed as the principal methodology, complemented by several other estimators to enhance the robustness of the analysis.
UNASSIGNED: In the forward MR analyses, we identified significant positive correlation between genetically predicted TL and the levels of TG (β=0.04, 95% confidence interval [CI]: 0.01 to 0.06, p = 0.003). In the reverse MR analysis, TG (β=0.02, 95% CI: 0.01 to 0.03, p = 0.004), LDL-C (β=0.03, 95% CI: 0.01 to 0.04, p = 0.001) and ApoB (β=0.03, 95% CI: 0.01 to 0.04, p = 9.71×10-5) were significantly positively associated with TL, although this relationship was not observed in the multivariate MR analysis. The mediation analysis via two-step MR showed no significant mediation effects acting through obesity-related phenotypes in analysis of TL with TG, while the effect of LDL-C on TL was partially mediated by body mass index (BMI) in the reverse direction, with mediated proportion of 12.83% (95% CI: 0.62% to 25.04%).
UNASSIGNED: Our study indicated that longer TL were associated with higher TG levels, while conversely, higher TG, LDL-C, and ApoB levels predicted longer TL, with BMI partially mediating these effects. Our findings present valuable insights into the development of preventive strategies and interventions that specifically target TL-related aging and age-related diseases.

BACKGROUND: Cerebral resting-state networks were suggested to be strongly associated with depressive disorders. However, the causal relationship between cerebral networks and depressive disorders remains controversial. In this study, we aimed to investigate the effect of resting-state networks on depressive disorders using a bidirectional Mendelian randomization (MR) design.
METHODS: Updated summary-level genome-wide association study (GWAS) data correlated with resting-state networks were obtained from a meta-analysis of European-descent GWAS from the Complex Trait Genetics Lab. Depression-related GWAS data were obtained from the FinnGen study involving participants with European ancestry. Resting-state functional magnetic resonance imaging and multiband diffusion imaging of the brain were performed to measure functional and structural connectivity in seven well-known networks. Inverse-variance weighting was used as the primary estimate, whereas the MR-Pleiotropy RESidual Sum and Outliers (PRESSO), MR-Egger, and weighted median were used to detect heterogeneity, sensitivity, and pleiotropy.
RESULTS: In total, 20,928 functional and 20,573 structural connectivity data as well as depression-related GWAS data from 48,847 patients and 225,483 controls were analyzed. Evidence for a causal effect of the structural limbic network on depressive disorders was found in the inverse variance-weighted limbic network (odds ratio, [Formula: see text]; 95% confidence interval, [Formula: see text]; [Formula: see text]), whereas the causal effect of depressive disorders on SC LN was not found(OR=1.0025; CI,1.0005-1.0046; P=0.012). No significant associations between functional connectivity of the resting-state networks and depressive disorders were found in this MR study.
CONCLUSIONS: These results suggest that genetically determined structural connectivity of the limbic network has a causal effect on depressive disorders and may play a critical role in its neuropathology.

Mitochondrial DNA (mtDNA) copy number and telomere length (TL) are dynamic factors that have been linked to the aging process in organisms. However, the causal relationship between these variables remains uncertain. In this research, instrumental variables (IVs) related to mtDNA copy number and TL were obtained from publicly available genome-wide association studies (GWAS). Through bidirectional Mendelian randomization (MR) analysis, we examined the potential causal relationship between these factors. The forward analysis, with mtDNA copy number as the exposure and TL as the outcome, did not reveal a significant effect (B=-0.004, P>0.05). On the contrary, upon conducting a reverse analysis, it was found that there exists a positive causal relationship (B=0.054, P<0.05). Sensitivity analyses further confirmed the reliability of these results. The outcomes of this study indicate a one-way positive causal relationship, indicating that telomere shortening in the aging process may lead to a decrease in mtDNA copy number, providing new perspectives on their biological mechanisms.

Traditional observational research has revealed an association between severe COVID-19 and chronic kidney disease (CKD). It is unclear whether there is a causative connection between them. Our goal was to determine whether genetically predicted CKD is associated with the risk of critical COVID-19. We aimed to investigate potential underlying genetic mechanisms that could explain this relationship, paving the way for personalized risk assessment and targeted interventions to mitigate the effects of COVID-19 on individuals with CKD. Using combined data from a GWAS on European ancestry and CKD (n = 117,165) and critical COVID-19 (n = 1,059,456), bidirectional Mendelian randomization analysis was performed. Four single nucleotide polymorphisms (SNPs) were chosen from the genome as CKD instrumental variables (IVs). In addition to MR‒Egger regression, weighted mode approaches, and weighted medians, we employed the inverse-variance weighted estimate as our primary analytical method. A significant association of CKD with critical COVID-19 (OR = 1.28, 95% confidence interval [CI]: 1.04-1.58, p = 0.01811) was found. However, using 6 genome-wide significant SNPs as IVs for critical COVID-19, we could not discover a meaningful correlation between severe COVID-19 and CKD (OR = 1.03, 95% CI: 0.96-1.10, p = 0.3947). We found evidence to support a causal relationship between CKD and severe COVID-19 in European population. This underscores the need for comprehensive monitoring and specialized care strategies for individuals with CKD to mitigate the heightened risk and severity of COVID-19 complications.

UNASSIGNED: Coronavirus disease 2019 (COVID-19) is strongly associated with myocarditis or pericarditis risk in observational studies, however, there are still studies that do not support the above conclusion. Whether the observed association reflects causation needs to be confirmed. We performed a bidirectional Mendelian randomization (MR) study to assess the causal relationship of COVID-19, which was divided into three groups, namely severe COVID-19, hospitalized COVID-19, and COVID-19 infection, measured by myocarditis or pericarditis.
UNASSIGNED: We extracted summary genome-wide association statistics for the severe COVID-19 (case: 13,769, control: 1,072,442), hospitalized COVID-19 (case: 32,519, control: 2,062,805), COVID-19 infection (case: 122,616, control: 2,475,240), myocarditis (case 1,521, control 191,924), and pericarditis (case 979, control 286,109) among individuals of European ancestry. Independent genetic variants that exhibited a significant association with each phenotype at the genome-wide level of significance were utilized as instrumental variables. Estimation of the causal effect was mainly performed using the random effects inverse-variance weighted method (IVW). Additionally, other tests such as MR-Egger intercept, MR-PRESSO, Cochran\'s Q-test, \"Leave-one-out\", and funnel plots were conducted to assess the extent of pleiotropy and heterogeneity.
UNASSIGNED: Non-associations in the IVW and sensitivity analyses were observed for COVID-19 with myocarditis or pericarditis. Severe COVID-19 was not associated with myocarditis [odds ratio (OR), 1.00; 95% confidence interval (CI), 0.89-1.12; P = 0.99], pericarditis (OR = 0.90, 95% CI, 0.78-1.04, P = 0.17). Similar results can be observed in hospitalized COVID-19, and COVID-19 infection. At the same time, null associations were observed for myocarditis or pericarditis with COVID-19 traits in the reverse direction. The main results are kept stable in the sensitivity analysis.
UNASSIGNED: There is no evidence that COVID-19 is independently and causally associated with myocarditis or pericarditis.

Existing cross-sectional and retrospective studies were unable to establish a causal relationship between psoriasis and cutaneous melanoma (CM). We sought to evaluate the causal role between psoriasis and CM.
We performed a bidirectional two-sample Mendelian randomization analysis using summary statistics from genome-wide association studies of psoriasis and CM among individuals of predominantly European ancestry. Mendelian randomization-Egger regression, inverse variance weighting, Mendelian Randomization Pleiotropy RESidual Sum and Outlier, weighted mode, and weighted median were used to examine the causal effect between psoriasis and CM.
Genetically predicted psoriasis was a significant risk factor for CM (odds ratio, 1.69; 95% confidence interval, 1.15-2.48; P = 0.025). In contrast, no association was observed between genetically predicted CM and psoriasis.
Our findings corroborated the existence of genetically predicted psoriasis increases risk of CM. Enhanced early screening of cutaneous melanoma in patients with psoriasis may improve clinical burden. However, we did not find evidence for a causal link from CM to psoriasis, so further studies are required to elucidate the effect of CM activity on psoriasis.

Several traditional observational studies suggested an association between COVID-19 and leukocyte telomere length (LTL), a biomarker for biological age. However, whether there was a causal association between them remained unclear. We aimed to investigate whether genetically predicted COVID-19 is related to the risk of LTL, and vice versa. We performed bidirectional Mendelian randomization (MR) study using summary statistics from the genome-wide association studies of critically ill COVID-19 (n = 1 388 342) and LTL (n = 472 174) of European ancestry. The random-effects inverse-variance weighted estimation method was applied as the primary method with several other estimators as complementary methods. Using six single-nucleotide polymorphisms (SNPs) of genome-wide significance as instrumental variables for critically ill COVID-19, we did not find a significant association of COVID-19 on LTL (β = 0.0075, 95% confidence interval [CI]: -0.018 to 0.021, p = 0.733). Likewise, using 97 SNPs of genome-wide significance as instrumental variables for LTL, we did not find a significant association of LTL on COVID-19 (odds ratio = 1.00, 95% CI: 0.79-1.28, p = 0.973). Comparable results were obtained using MR-Egger regression, weighted median, and weighted mode approaches. We did not find evidence to support a causal association between COVID-19 and LTL in either direction.