Mendelian randomization

Inflammation compared to low-density lipoprotein cholesterol: two different causes of atherosclerotic cardiovascular disease

PURPOSE OF REVIEW

Inflammation is gaining attention as a target for prevention of atherosclerotic cardiovascular disease (ASCVD). The purpose of this review is to compare the evidence for inflammation with the evidence for low-density lipoprotein (LDL) cholesterol in ASCVD.

RECENT FINDINGS

Evidence from human genetic studies and randomized controlled trials implicate the inflammatory pathway from the inflammasome through interleukin (IL)-1 to IL-6 as a cause of ASCVD. Higher levels of IL-6 may lead to proportionally increased risk of ASCVD, and randomized controlled trials of IL-6 inhibitors are underway. The causal evidence for LDL cholesterol in ASCVD is overwhelming and recent important findings instead revolve around development of improved LDL cholesterol lowering therapy through RNA and DNA based therapeutics. Even though some lipid-lowering therapies lower IL-6, the IL-6 inflammatory pathway and LDL cholesterol are two separate causes of ASCVD.

SUMMARY

IL-6 mediated inflammation most likely causes ASCVD, in parallel with LDL cholesterol. However, fewer individuals in the general population are exposed to high IL-6 than high LDL cholesterol. For inflammation, future research should focus on improving efficacy and safety of anti-inflammatory therapy, and for LDL cholesterol, future research should focus on wider and more effective implementation of LDL cholesterol lowering therapy.

Identifying novel proteins underlying loneliness by integrating GWAS summary data with human brain proteomes

Enduring loneliness is associated with mental disorders and physical diseases. Although genome-wide association studies (GWAS) have identified risk loci associated with loneliness, how these loci confer the risk remains largely unknown. In the current study, we aimed to investigate key proteins underlying loneliness in the brain by integrating human brain proteomes and transcriptomes with loneliness GWAS to perform a discovery proteome-wide association study (PWAS), followed by a confirmatory PWAS, transcriptome-wide association analysis (TWAS), Mendelian randomization (MR), Steigering filtering analysis and Bayesian colocalization analysis. Moreover, given the fact that loneliness is associated with mental disorders, we explored the shared genetic architecture between loneliness and mental disorders. Totally, we identified 18 genes to be associated with loneliness via their cis-regulated brain protein abundance. Eleven of the 18 genes (61.1%) were replicated in the confirmatory PWAS, and mRNA levels of 4 genes were further validated to be associated with loneliness.MR and genetic colocalization analysis further confirmed that the increased protein abundance of ALDH2 and ICA1L was protective against loneliness, while the increased protein abundance of GPX1 was a risk for developing loneliness. Furthermore, we found genetic correlations, bidirectional causal associations and overlapping phenotype-associated protein profiles between loneliness and mental disorders including major depression and schizophrenia. In summary, our findings provided clues about the brain-related molecular basis underlying loneliness, which warrants further investigation.

A Genome-Wide Association Study Meta-Analysis of Alpha Angle Suggests Cam-Type Morphology May Be a Specific Feature of Hip Osteoarthritis in Older Adults

OBJECTIVE

To examine the genetic architecture of cam morphology using alpha angle (AA) as a proxy measure and conduct an AA genome-wide association study (GWAS) followed by Mendelian randomization (MR) to evaluate its causal relationship with hip osteoarthritis (OA).

METHODS

Observational analyses examined associations between AA measurements derived from hip dual x-ray absorptiometry (DXA) scans from the UK Biobank study and radiographic hip OA outcomes and subsequent total hip replacement. Following these analyses, an AA GWAS meta-analysis was performed (N = 44,214) using AA measurements previously derived in the Rotterdam Study. Linkage disequilibrium score regression assessed the genetic correlation between AA and hip OA. Genetic associations considered significant (P < 5 × 10-8 ) were used as AA genetic instrument for 2-sample MR analysis.

RESULTS

DXA-derived AA showed expected associations between AA and radiographic hip OA (adjusted odds ratio [OR] 1.63 [95% confidence interval (95% CI) 1.58, 1.67]) and between AA and total hip replacement (adjusted hazard ratio 1.45 [95% CI 1.33, 1.59]) in the UK Biobank study cohort. The heritability of AA was 10%, and AA had a moderate genetic correlation with hip OA (rg  = 0.26 [95% CI 0.10, 0.43]). Eight independent genetic signals were associated with AA. Two-sample MR provided weak evidence of causal effects of AA on hip OA risk (inverse variance weighted OR 1.84 [95% CI 1.14, 2.96], P = 0.01). In contrast, genetic predisposition for hip OA had stronger evidence of a causal effect on increased AA (inverse variance weighted β = 0.09 [95% CI 0.04, 0.13], P = 4.58 × 10-5 ).

CONCLUSION

Expected observational associations between AA and related clinical outcomes provided face validity for the DXA-derived AA measurements. Evidence of bidirectional associations between AA and hip OA, particularly for risk of hip OA on AA, suggests that hip shape modeling secondary to a genetic predisposition to hip OA contributes to the well-established relationship between hip OA and cam morphology in older adults.

The PANcreatic Disease ReseArch (PANDoRA) consortium: Ten years' experience of association studies to understand the genetic architecture of pancreatic cancer

Pancreatic cancer has an incidence that almost matches its mortality. Only a small number of risk factors and 33 susceptibility loci have been identified. so Moreover, the relative rarity of pancreatic cancer poses significant hurdles for research aimed at increasing our knowledge of the genetic mechanisms contributing to the disease. Additionally, the inability to adequately power research questions prevents small monocentric studies from being successful. Several consortia have been established to pursue a better understanding of the genetic architecture of pancreatic cancers. The Pancreatic disease research (PANDoRA) consortium is the largest in Europe. PANDoRA is spread across 12 European countries, Brazil and Japan, bringing together 29 basic and clinical research groups. In the last ten years, PANDoRA has contributed to the discovery of 25 susceptibility loci, a feat that will be instrumental in stratifying the population by risk and optimizing preventive strategies.

Genetic Determinants of the Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome (ARDS) is a life-threatening lung condition that arises from multiple causes, including sepsis, pneumonia, trauma, and severe coronavirus disease 2019 (COVID-19). Given the heterogeneity of causes and the lack of specific therapeutic options, it is crucial to understand the genetic and molecular mechanisms that underlie this condition. The identification of genetic risks and pharmacogenetic loci, which are involved in determining drug responses, could help enhance early patient diagnosis, assist in risk stratification of patients, and reveal novel targets for pharmacological interventions, including possibilities for drug repositioning. Here, we highlight the basis and importance of the most common genetic approaches to understanding the pathogenesis of ARDS and its critical triggers. We summarize the findings of screening common genetic variation via genome-wide association studies and analyses based on other approaches, such as polygenic risk scores, multi-trait analyses, or Mendelian randomization studies. We also provide an overview of results from rare genetic variation studies using Next-Generation Sequencing techniques and their links with inborn errors of immunity. Lastly, we discuss the genetic overlap between severe COVID-19 and ARDS by other causes.

Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

Background

Tumour-promoting inflammation is a "hallmark" of cancer and conventional epidemiological studies have reported links between various inflammatory markers and cancer risk. The causal nature of these relationships and, thus, the suitability of these markers as intervention targets for cancer prevention is unclear.

Methods

We meta-analysed 6 genome-wide association studies of circulating inflammatory markers comprising 59,969 participants of European ancestry. We then used combined cis-Mendelian randomization and colocalisation analysis to evaluate the causal role of 66 circulating inflammatory markers in risk of 30 adult cancers in 338,162 cancer cases and up to 824,556 controls. Genetic instruments for inflammatory markers were constructed using genome-wide significant (P < 5.0 x 10-8) cis-acting SNPs (i.e. in or ±250 kb from the gene encoding the relevant protein) in weak linkage disequilibrium (LD, r2 < 0.10). Effect estimates were generated using inverse-variance weighted random-effects models and standard errors were inflated to account for weak LD between variants with reference to the 1000 Genomes Phase 3 CEU panel. A false discovery rate (FDR)-corrected P-value ("q-value") < 0.05 was used as a threshold to define "strong evidence" to support associations and 0.05 ≤ q-value < 0.20 to define "suggestive evidence". A colocalisation posterior probability (PPH4) > 70% was employed to indicate support for shared causal variants across inflammatory markers and cancer outcomes.

Results

We found strong evidence to support an association of genetically-proxied circulating pro-adrenomedullin concentrations with increased breast cancer risk (OR 1.19, 95% CI 1.10-1.29, q-value=0.033, PPH4=84.3%) and suggestive evidence to support associations of interleukin-23 receptor concentrations with increased pancreatic cancer risk (OR 1.42, 95% CI 1.20-1.69, q-value=0.055, PPH4=73.9%), prothrombin concentrations with decreased basal cell carcinoma risk (OR 0.66, 95% CI 0.53-0.81, q-value=0.067, PPH4=81.8%), macrophage migration inhibitory factor concentrations with increased bladder cancer risk (OR 1.14, 95% CI 1.05-1.23, q-value=0.072, PPH4=76.1%), and interleukin-1 receptor-like 1 concentrations with decreased triple-negative breast cancer risk (OR 0.92, 95% CI 0.88-0.97, q-value=0.15), PPH4=85.6%). For 22 of 30 cancer outcomes examined, there was little evidence (q-value ≥ 0.20) that any of the 66 circulating inflammatory markers examined were associated with cancer risk.

Conclusion

Our comprehensive joint Mendelian randomization and colocalisation analysis of the role of circulating inflammatory markers in cancer risk identified potential roles for 5 circulating inflammatory markers in risk of 5 site-specific cancers. Contrary to reports from some prior conventional epidemiological studies, we found little evidence of association of circulating inflammatory markers with the majority of site-specific cancers evaluated.

Combining Mendelian randomization and network deconvolution for inference of causal networks with GWAS summary data

Mendelian randomization (MR) has been increasingly applied for causal inference with observational data by using genetic variants as instrumental variables (IVs). However, the current practice of MR has been largely restricted to investigating the total causal effect between two traits, while it would be useful to infer the direct causal effect between any two of many traits (by accounting for indirect or mediating effects through other traits). For this purpose we propose a two-step approach: we first apply an extended MR method to infer (i.e. both estimate and test) a causal network of total effects among multiple traits, then we modify a graph deconvolution algorithm to infer the corresponding network of direct effects. Simulation studies showed much better performance of our proposed method than existing ones. We applied the method to 17 large-scale GWAS summary datasets (with median N = 256879 and median #IVs = 48) to infer the causal networks of both total and direct effects among 11 common cardiometabolic risk factors, 4 cardiometabolic diseases (coronary artery disease, stroke, type 2 diabetes, atrial fibrillation), Alzheimer's disease and asthma, identifying some interesting causal pathways. We also provide an R Shiny app (https://zhaotongl.shinyapps.io/cMLgraph/) for users to explore any subset of the 17 traits of interest.

Average Causal Effect Estimation Via Instrumental Variables: the No Simultaneous Heterogeneity Assumption

BACKGROUND

Instrumental variables (IVs) can be used to provide evidence as to whether a treatment has a causal effect on an outcome . Even if the instrument satisfies the three core IV assumptions of relevance, independence, and exclusion restriction, further assumptions are required to identify the average causal effect (ACE) of on . Sufficient assumptions for this include homogeneity in the causal effect of on ; homogeneity in the association of with ; and no effect modification.

METHODS

We describe the no simultaneous heterogeneity assumption, which requires the heterogeneity in the - causal effect to be mean independent of (i.e., uncorrelated with) both and heterogeneity in the - association. This happens, for example, if there are no common modifiers of the - effect and the - association, and the - effect is additive linear. We illustrate the assumption of no simultaneous heterogeneity using simulations and by re-examining selected published studies.

RESULTS

Under no simultaneous heterogeneity, the Wald estimand equals the ACE even if both homogeneity assumptions and no effect modification (which we demonstrate to be special cases of-and therefore stronger than-no simultaneous heterogeneity) are violated.

CONCLUSIONS

The assumption of no simultaneous heterogeneity is sufficient for identifying the ACE using IVs. Since this assumption is weaker than existing assumptions for ACE identification, doing so may be more plausible than previously anticipated.

Cerebrovascular Disorders

Cerebrovascular disorders pose a global health concern. Advances in basic and clinical research, including induced pluripotent stem cell models and multi-omic approaches, have improved our understanding and management of these disorders. However, gaps in our knowledge remain. BMC Cardiovascular Disorders invites authors to submit articles investigating what drives and affects Cerebrovascular disorders to improve patient care.

Common genetic variations in telomere length genes and lung cancer: a Mendelian randomisation study and its novel application in lung tumour transcriptome

Background

Genome-wide association studies (GWASs) have identified genetic susceptibility variants for both leukocyte telomere length (LTL) and lung cancer susceptibility. Our study aims to explore the shared genetic basis between these traits and investigate their impact on somatic environment of lung tumours.

Methods

We performed genetic correlation, Mendelian randomisation (MR), and colocalisation analyses using the largest available GWASs summary statistics of LTL (N=464,716) and lung cancer (N=29,239 cases and 56,450 controls). Principal components analysis based on RNA-sequencing data was used to summarise gene expression profile in lung adenocarcinoma cases from TCGA (N=343).

Results

Although there was no genome-wide genetic correlation between LTL and lung cancer risk, longer LTL conferred an increased risk of lung cancer regardless of smoking status in the MR analyses, particularly for lung adenocarcinoma. Of the 144 LTL genetic instruments, 12 colocalised with lung adenocarcinoma risk and revealed novel susceptibility loci, including MPHOSPH6, PRPF6, and POLI. The polygenic risk score for LTL was associated with a specific gene expression profile (PC2) in lung adenocarcinoma tumours. The aspect of PC2 associated with longer LTL was also associated with being female, never smokers, and earlier tumour stages. PC2 was strongly associated with cell proliferation score and genomic features related to genome stability, including copy number changes and telomerase activity.

Conclusions

This study identified an association between longer genetically predicted LTL and lung cancer and sheds light on the potential molecular mechanisms related to LTL in lung adenocarcinomas.

Funding

Institut National du Cancer (GeniLuc2017-1-TABAC-03-CIRC-1-TABAC17-022), INTEGRAL/NIH (5U19CA203654-03), CRUK (C18281/A29019), and Agence Nationale pour la Recherche (ANR-10-INBS-09).

Comparison of intergenerational instrumental variable analyses of body mass index and mortality in UK Biobank

BACKGROUND

An increasing proportion of people have a body mass index (BMI) classified as overweight or obese and published studies disagree whether this will be beneficial or detrimental to health. We applied and evaluated two intergenerational instrumental variable methods to estimate the average causal effect of BMI on mortality in a cohort with many deaths: the parents of UK Biobank participants.

METHODS

In Cox regression models, parental BMI was instrumented by offspring BMI using an 'offspring as instrument' (OAI) estimation and by offspring BMI-related genetic variants in a 'proxy-genotype Mendelian randomization' (PGMR) estimation.

RESULTS

Complete-case analyses were performed in parents of 233 361 UK Biobank participants with full phenotypic, genotypic and covariate data. The PGMR method suggested that higher BMI increased mortality with hazard ratios per kg/m2 of 1.02 (95% CI: 1.01, 1.04) for mothers and 1.04 (95% CI: 1.02, 1.05) for fathers. The OAI method gave considerably higher estimates, which varied according to the parent-offspring pairing between 1.08 (95% CI: 1.06, 1.10; mother-son) and 1.23 (95% CI: 1.16, 1.29; father-daughter).

CONCLUSION

Both methods supported a causal role of higher BMI increasing mortality, although caution is required regarding the immediate causal interpretation of these exact values. Evidence of instrument invalidity from measured covariates was limited for the OAI method and minimal for the PGMR method. The methods are complementary for interrogating the average putative causal effects because the biases are expected to differ between them.

Using allele scores to identify confounding by reverse causation: studies of alcohol consumption as an exemplar

BACKGROUND

Mendelian randomization (MR) is a form of instrumental variable analysis used to investigate causality using observational data. Another important, although less frequently applied, use of this technique is to investigate confounding due to reverse causality.

METHODS

We used a form of reverse MR and data from UK Biobank in a proof-of-principle study to investigate confounding due to reverse causation. Here we focus on the association between alcohol consumption (exposure) and outcomes including educational attainment, and physical and mental health. First, we examined the observational relationship between alcohol consumption and these outcomes. Allele scores were then derived for educational attainment, and physical and mental health, and the association with alcohol consumption (as the outcome) was explored. Sample sizes ranged from 114 941-336 473 in observational analyses and 142 093-336 818 in genetic analyses.

RESULTS

Conventional observational analyses indicated associations between alcohol consumption and a number of outcomes (e.g. neuroticism, body mass index, educational attainment). Analyses using allele scores suggested evidence of reverse causation for several of these relationships (in particular physical health and educational attainment).

CONCLUSION

Allele scores allow us to investigate reverse causation in observational studies. Our findings suggest that observed associations implying beneficial effects of alcohol consumption may be due to confounding by reverse causation in many cases.

Evaluating the effect of metabolic traits on oral and oropharyngeal cancer risk using Mendelian randomization

A recent World Health Organization report states that at least 40% of all cancer cases may be preventable, with smoking, alcohol consumption, and obesity identified as three of the most important modifiable lifestyle factors. Given the significant decline in smoking rates, particularly within developed countries, other potentially modifiable risk factors for head and neck cancer warrant investigation. Obesity and related metabolic disorders such as type 2 diabetes (T2D) and hypertension have been associated with head and neck cancer risk in multiple observational studies. However, adiposity has also been correlated with smoking, with bias, confounding or reverse causality possibly explaining these findings. To overcome the challenges of observational studies, we conducted two-sample Mendelian randomization (inverse variance weighted [IVW] method) using genetic variants which were robustly associated with adiposity, glycaemic and blood pressure traits in genome-wide association studies (GWAS). Outcome data were taken from the largest available GWAS of 6034 oral and oropharyngeal cases, with 6585 controls. We found limited evidence of a causal effect of genetically proxied body mass index (BMI; OR IVW = 0.89, 95% CI 0.72-1.09, p = 0.26 per 1 standard deviation in BMI [4.81kg/m2]) on oral and oropharyngeal cancer risk. Similarly, there was limited evidence for related traits including T2D and hypertension. Small effects cannot be excluded given the lack of power to detect them in currently available GWAS.

Variation in ERAP2 has opposing effects on severe respiratory infection and autoimmune disease

ERAP2 is an aminopeptidase involved in immunological antigen presentation. Genotype data in human samples from before and after the Black Death, an epidemic due to Yersinia pestis, have marked changes in allele frequency of the single-nucleotide polymorphism (SNP) rs2549794, with the T allele suggested to be deleterious during this period, while ERAP2 is also implicated in autoimmune diseases. This study explored the association between variation at ERAP2 and (1) infection, (2) autoimmune disease, and (3) parental longevity. Genome-wide association studies (GWASs) of these outcomes were identified in contemporary cohorts (UK Biobank, FinnGen, and GenOMICC). Effect estimates were extracted for rs2549794 and rs2248374, a haplotype tagging SNP. Additionally, cis expression and protein quantitative trait loci (QTLs) for ERAP2 were used in Mendelian randomization (MR) analyses. Consistent with decreased survival in the Black Death, the T allele of rs2549794 showed evidence of association with respiratory infection (odds ratio; OR for pneumonia 1.03; 95% CI 1.01-1.05). Effect estimates were larger for more severe phenotypes (OR for critical care admission with pneumonia 1.08; 95% CI 1.02-1.14). In contrast, opposing effects were identified for Crohn disease (OR 0.86; 95% CI 0.82-0.90). This allele was shown to associate with decreased ERAP2 expression and protein levels, independent of haplotype. MR analyses suggest that ERAP2 expression may be mediating disease associations. Decreased ERAP2 expression is associated with severe respiratory infection with an opposing association with autoimmune diseases. These data support the hypothesis of balancing selection at this locus driven by autoimmune and infectious disease.

Multiomic approach and Mendelian randomization analysis identify causal associations between blood biomarkers and subcortical brain structure volumes

Alterations in subcortical brain structure volumes have been found to be associated with several neurodegenerative and psychiatric disorders. At the same time, genome-wide association studies (GWAS) have identified numerous common variants associated with brain structure. In this study, we integrate these findings, aiming to identify proteins, metabolites, or microbes that have a putative causal association with subcortical brain structure volumes via a two-sample Mendelian randomization approach. This method uses genetic variants as instrument variables to identify potentially causal associations between an exposure and an outcome. The exposure data that we analyzed comprised genetic associations for 2,994 plasma proteins, 237 metabolites, and 103 microbial genera. The outcome data included GWAS data for seven subcortical brain structure volumes including accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Eleven proteins and six metabolites were found to have a significant association with subcortical structure volumes. We found causal associations between amygdala volume and granzyme A as well as association between accumbens volume and plasma protease c1 inhibitor. Among metabolites, urate had the strongest association with thalamic volume. No significant associations were detected between the microbial genera and subcortical brain structure volumes. We also observed significant enrichment for biological processes such as proteolysis, regulation of the endoplasmic reticulum apoptotic signaling pathway, and negative regulation of DNA binding. Our findings provide insights to the mechanisms through which brain volumes may be affected in the pathogenesis of neurodevelopmental and psychiatric disorders and point to potential treatment targets for disorders that are associated with subcortical brain structure volumes.

Examining the shared etiology of psychopathology with genome-wide association studies

Genome-wide association studies (GWASs) have ushered in a new era of reproducible discovery in psychiatric genetics. The field has now identified hundreds of common genetic variants that are associated with mental disorders, and many of them influence more than one disorder. By advancing the understanding of causal biology underlying psychopathology, GWAS results are poised to inform the development of novel therapeutics, stratification of at-risk patients, and perhaps even the revision of top-down classification systems in psychiatry. Here, we provide a concise review of GWAS findings with an emphasis on findings that have elucidated the shared genetic etiology of psychopathology, summarizing insights at three levels of analysis: 1) genome-wide architecture; 2) networks, pathways, and gene sets; and 3) individual variants/genes. Three themes emerge from these efforts. First, all psychiatric phenotypes are heritable, highly polygenic, and influenced by many pleiotropic variants with incomplete penetrance. Second, GWAS results highlight the broad etiological roles of neuronal biology, system-wide effects over localized effects, and early neurodevelopment as a critical period. Third, many loci that are robustly associated with multiple forms of psychopathology harbor genes that are involved in synaptic structure and function. Finally, we conclude our review by discussing the implications that GWAS results hold for the field of psychiatry, as well as expected challenges and future directions in the next stage of psychiatric genetics.

The effect of interleukin-6 signaling on severe malaria: A Mendelian randomization analysis

OBJECTIVES

Severe malaria remains a deadly disease for many young children in low- and middle-income countries. Levels of interleukin (IL)-6 have been shown to identify cases of severe malaria and associate with severity, but it is unknown if this association is causal.

METHODS

A single nucleotide polymorphism (SNP; rs2228145) in the IL-6 receptor was chosen as a genetic variant that is known to alter IL-6 signaling. We tested this, then took this forward as an instrument to perform Mendelian randomization (MR) in MalariaGEN, a large cohort study of patients with severe malaria at 11 worldwide sites.

RESULTS

In MR analyses using rs2228145, we did not identify an effect of decreased IL-6 signaling on severe malaria (odds ratio 1.14, 95% confidence interval 0.56-2.34, P = 0.713). The estimates of the association with any severe malaria subphenotype were similarly null, although with some imprecision. Further analyses using other MR approaches had similar results.

CONCLUSION

These analyses do not support a causal role for IL-6 signaling in the development of severe malaria. This result suggests IL-6 may not be causal for severe outcomes in malaria, and that therapeutic manipulation of IL-6 is unlikely to be a suitable treatment for severe malaria.

Tobacco and alcohol consumption and the risk of frailty and falling: a Mendelian randomisation study

Background

Epidemiological data have suggested that tobacco and alcohol consumption were associated with the risk of frailty and falling, but it is yet unclear whether these associations are of a causal nature. Thus, we conducted two-sample Mendelian randomisation analysis using genetic instruments to determine the causal associations of tobacco and alcohol consumption on frailty and falls.

Methods

Independent instrumental variables strongly (p<5E–09) associated with tobacco and alcohol consumption were obtained from the genome-wide association study (GWAS) and Sequencing Consortium of Alcohol and Nicotine use (up to 2 669 029 participants). Summary statistics of the frailty index (FI, N=175 226) and falling risk (N=451 179) were from the two latest published GWAS datasets on FI and falling risk.

Results

Using the inverse-variance weighted method, our results showed that genetically determined initiation of smoking was significantly associated with an increased FI (β=0.34, 95% CI=0.29 to 0.40, p=5.48E–33) and risk of falling (OR=1.39, 95% CI=1.30 to 1.50, p=1.01E–20). In addition, the age of initiation of smoking and cigarettes consumption per day was negatively and positively associated with both FI and falls, respectively. Current smokers were prone to having a higher FI and falling risk than individuals who quit smoking. There was no significant causal association between alcohol use and the risk of frailty and falling. Similar results were obtained using other statistical approaches with good stability.

Conclusions

Our findings demonstrate that tobacco use, but not alcohol drinking, significantly increases the risk of frailty and falling. Future studies are warranted to clarify the underlying physiopathological mechanisms.

Association of atopic dermatitis with autoimmune diseases: A bidirectional and multivariable two-sample mendelian randomization study

Background

Observational studies have suggested the association between atopic dermatitis (AD) and the risks of autoimmune diseases. It is still unclear, however, whether or in which direction causal relationships exist, because these associations could be confounded.

Objectives

Our study seeks to assess the possibility of AD as a cause of autoimmune diseases, and to estimate the magnitude of the causal effect.

Methods

Two-sample mendelian randomization (MR) analyses were performed using genome-wide association study (GWAS) summary-level statistics. Specifically, bidirectional MR analyses were conducted to examine the direction of association of AD with autoimmune diseases; multivariable MR analyses (MVMR1) were used to test the independence of causal association of AD with autoimmune diseases after controlling other atopic disorders (asthma and allergic rhinitis), while MVMR2 analyses were conducted to account for potential confounding factors such as smoking, drinking, and obesity. Genetic instruments for AD (Ncases=22 474) were from the latest GWAS meta-analysis. The GWAS summary data for asthma and allergic rhinitis were obtained from UK Biobank. The GWAS summary data for smoking, alcohol consumption, obesity and autoimmune diseases (alopecia areata, vitiligo, systemic lupus erythematosus, ankylosing spondylitis, rheumatoid arthritis, and type 1 diabetes) were selected from the largest GWASs available. Causal estimates were derived by the inverse-variance weighted method and verified through a series of sensitivity analyses.

Results

Genetically predicted AD linked to higher risks of rheumatoid arthritis (OR, 1.28; P=0.0068) (ORMVMR1, 1.65; P=0.0020) (ORMVMR2, 1.36; P<0.001), type 1 diabetes (OR, 1.37; P=0.0084) (ORMVMR1, 1.42; P=0.0155) (ORMVMR2, 1.45; P=0.002), and alopecia areata (OR, 1.98; P=0.0059) (ORMVMR1, 2.55; P<0.001) (ORMVMR2, 1.99; P=0.003) in both univariable and multivariable MR. These causal relationships were supported by sensitivity analyses. No causal effect of AD was identified in relation to systemic lupus erythematosus, vitiligo, and ankylosing spondylitis. Concerning the reverse directions, no significant association was noted.

Conclusion

The results of this MR study provide evidence to support the idea that AD causes a greater risk of rheumatoid arthritis, type 1 diabetes and alopecia areata. Further replication in larger samples is needed to validate our findings, and experimental studies are needed to explore the underlying mechanisms of these causal effects.

Cortisol and periodontitis: Prospective observational and Mendelian randomization studies

Purpose

Cortisol has obesogenic, hyperglycemic and immunomodulating effects. Preclinical and observational research suggested that it is associated with periodontitis but the evidence for potential causality in humans is sparse. We triangulated results from prospective observational and Mendelian randomization (MR) analyses to further explore this.

Methods

Using pooled data from 3,388 participants of two population cohort studies embedded in the Study of Health in Pomerania (SHIP) project, we associated serum cortisol levels with periodontal outcomes measured after a median follow-up time of 6.9 years, adjusting for confounding and selection bias using propensity score weighting and multiple imputation. We further examined the effect of genetically proxied plasma morning cortisol levels on periodontitis using two-sample MR of 17,353 cases and 28,210 controls.

Results

In SHIP, we found that cortisol levels were positively associated with follow-up levels of mean clinical attachment level (CAL), deep interdental CAL and bleeding on probing but were unrelated to mean probing pocket depth and deep periodontal pockets. In MR analysis, cortisol was not associated with periodontitis.

Conclusion

The observational study revealed a prospective association of spot cortisol with makers of periodontitis. Contrary to observational studies, genetically instrumented, long-term cortisol was unrelated to periodontitis. Our results find no univocal evidence that cortisol plays a role in periodontitis pathology, casting doubt on cortisol-related pathways.

Exploring the Lifetime Effect of Children on Wellbeing Using Two-Sample Mendelian Randomisation

BACKGROUND

Observational research implies a negative effect of having children on wellbeing.

OBJECTIVES

To provide Mendelian randomisation evidence of the effect of having children on parental wellbeing.

DESIGN

Two-sample Mendelian randomisation.

SETTING

Non-clinical European ancestry participants.

PARTICIPANTS

We used the UK Biobank (460,654 male and female European ancestry participants) as a source of genotype-exposure associations, the Social Science Genetics Consortia (SSGAC) (298,420 male and female European ancestry participants), and the Within-Family Consortia (effective sample of 22,656 male and female European ancestry participants) as sources of genotype-outcome associations.

INTERVENTIONS

The lifetime effect of an increase in the genetic liability to having children.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary analysis was an inverse variance weighed analysis of subjective wellbeing measured in the 2016 SSGAC Genome Wide Association Study (GWAS). Secondary outcomes included pleiotropy robust estimators applied in the SSGAC and an analysis using the Within-Family consortia GWAS.

RESULTS

We did not find strong evidence of a negative (standard deviation) change in wellbeing (β = 0.153 (95% CI: -0.210 to 0.516) per child parented. Secondary outcomes were generally slightly deflated (e.g., -0.049 [95% CI: -0.533 to 0.435] for the Within-Family Consortia and 0.090 [95% CI: -0.167 to 0.347] for weighted median), implying the presence of some residual confounding and pleiotropy.

CONCLUSIONS

Contrary to the existing literature, our results are not compatible with a measurable negative effect of number of children on the average wellbeing of a parent over their life course. However, we were unable to explore non-linearities, interactions, or time-varying effects.

The Associations Between Cataracts and Alzheimer's Disease: A Bidirectional Two-Sample Mendelian Randomization Study

BACKGROUND

The relationship between cataracts and Alzheimer's disease (AD) has been reported in recent observational studies. However, it is still unclear whether a causal effect of cataracts on AD or reverse causation exists.

OBJECTIVE

To explore the association between cataracts and AD genetically, we performed a bidirectional two-sample Mendelian randomization study.

METHODS

We obtained genetic instrumental variables related to cataracts and AD from recently published genome-wide association studies (GWASs). SNP-outcome associations for AD were obtained from a GWAS with 111,326 cases and 677,663 controls. SNP-outcome associations for cataracts were drawn from two sources: a GWAS with 67,844 cases and 517,399 controls and the FinnGen consortium (42,843 cases and 262,698 controls). Inverse variance weighted (IVW) was used as the primary method for Mendelian randomization (MR) analyses.

RESULTS

No genetic evidence suggested that cataracts were associated with the risk of AD (IVW odds ratio =1.04, 95% confidence interval: 0.98-1.10, p=0.199). In contrast, an effect of genetically determined AD on a decreased risk of cataract was observed with suggestive evidence (IVW odds ratio =0.96, 95% confidence interval: 0.93-0.99, p=0.004). However, this result might be distorted by survival bias.

CONCLUSION

Genetically determined cataracts were not related to AD, as demonstrated by our study. In contrast, there was suggestive evidence that AD might prevent cataract development, but there might be potential survival bias. To define the exact association between the two diseases, more prospective research and studies on the pathogenesis are needed.

The next step in Mendelian randomization

Expanding a statistical approach called Mendelian randomization to include multiple variables may help researchers to identify new molecular causes of specific traits.

Conditioning on parental mating types can reduce necessary assumptions for Mendelian randomization

Mendelian randomization (MR) has become a common tool used in epidemiological studies. However, when confounding variables are correlated with the instrumental variable (in this case, a genetic/variant/marker), the estimation can remain biased even with MR. We propose conditioning on parental mating types (a function of parental genotypes) in MR to eliminate the need for one set of assumptions, thereby plausibly reducing such bias. We illustrate a situation in which the instrumental variable and confounding variables are correlated using two unlinked diallelic genetic loci: one, an instrumental variable and the other, a confounding variable. Assortative mating or population admixture can create an association between the two unlinked loci, which can violate one of the necessary assumptions for MR. We simulated datasets involving assortative mating and population admixture and analyzed them using three different methods: 1) conventional MR, 2) MR conditioning on parental genotypes, and 3) MR conditioning on parental mating types. We demonstrated that conventional MR leads to type I error rate inflation and biased estimates for cases with assortative mating or population admixtures. In the presence of non-additive effects, MR with an adjustment for parental genotypes only partially reduced the type I error rate inflation and bias. In contrast, conditioning on parental mating types in MR eliminated the type I error inflation and bias under these circumstances. Conditioning on parental mating types is a useful strategy to reduce the burden of assumptions and the potential bias in MR when the correlation between the instrument variable and confounders is due to assortative mating or population stratification but not linkage.

Association between vascular risk factors and idiopathic normal pressure hydrocephalus: a Mendelian randomization study

BACKGROUND AND OBJECTIVE

Patients with idiopathic normal pressure hydrocephalus (iNPH) have a higher prevalence of hypertension and diabetes. However, the causal effects of these vascular risk factors on iNPH remain unclear. This study aimed to explore the causal relationship between vascular risk factors (VRFs) and iNPH.

METHODS

We conducted the Mendelian randomization (MR) analysis of iNPH. We included nineteen vascular risk factors related to hypertension, diabetes, lipids, obesity, smoking, alcohol consumption, exercise, sleep, and cardiovascular events as exposure factors. We used the inverse-variance weighted method for causal effect estimation and weighted median, maximum likelihood, and MR Egger regression methods for sensitivity analyses.

RESULTS

We found that genetically predicting essential hypertension (OR = 1.608 (1.330-1.944), p = 0.013) and increased sleep duration (OR = 16.395 (5.624-47.799), p = 0.009) were associated with higher odds of iNPH. Type 1 diabetes (OR = 0.869 (0.828-0.913), p = 0.004) was associated with lower odds of iNPH. For the other 16 VRFs, there was no evidence that they were significantly associated with iNPH. Sensitivity analyses showed that essential hypertension and type 1 diabetes were significantly associated with iNPH.

CONCLUSION

In our MR study on VRFs and iNPH, we found essential hypertension to be a causal risk factor for iNPH. This suggests that hypertension may be involved in the pathophysiological mechanism of iNPH.

Inhibition of tumor necrosis factor receptor 1 and the risk of periodontitis

Aim

To investigate the effect of genetically proxied inhibition of tumor necrosis factor receptor 1 (TNFR1) on the risk of periodontitis.

Materials and methods

Genetic instruments were selected from the vicinity of TNFR superfamily member 1A (TNFRSF1A) gene (chromosome 12; base pairs 6,437,923-6,451,280 as per GRCh37 assembly) based on their association with C-reactive protein (N= 575,531). Summary statistics of these variants were obtained from a genome-wide association study (GWAS) of 17,353 periodontitis cases and 28,210 controls to estimate the effect of TNFR1 inhibition on periodontitis using a fixed-effects inverse method.

Results

Considering rs1800693 as an instrument, we found no effect of TNFR1 inhibition on periodontitis risk (Odds ratio (OR) scaled per standard deviation increment in CRP: 1.57, 95% confidence interval (CI): 0.38;6.46). Similar results were derived from a secondary analysis that used three variants (rs767455, rs4149570, and rs4149577) to index TNFR1 inhibition.

Conclusions

We found no evidence of a potential efficacy of TNFR1 inhibition on periodontitis risk.

Tools for assessing quality and risk of bias in Mendelian randomization studies: a systematic review

BACKGROUND

The use of Mendelian randomization (MR) in epidemiology has increased considerably in recent years, with a subsequent increase in systematic reviews of MR studies. We conducted a systematic review of tools designed for assessing risk of bias and/or quality of evidence in MR studies and a review of systematic reviews of MR studies.

METHODS

We systematically searched MEDLINE, Embase, the Web of Science, preprints servers and Google Scholar for articles containing tools for assessing, conducting and/or reporting MR studies. We also searched for systematic reviews and protocols of systematic reviews of MR studies. From eligible articles we collected data on tool characteristics and content, as well as details of narrative description of bias assessment.

RESULTS

Our searches retrieved 2464 records to screen, from which 14 tools, 35 systematic reviews and 38 protocols were included in our review. Seven tools were designed for assessing risk of bias/quality of evidence in MR studies and evaluation of their content revealed that all seven tools addressed the three core assumptions of instrumental variable analysis, violation of which can potentially introduce bias in MR analysis estimates.

CONCLUSION

We present an overview of tools and methods to assess risk of bias/quality of evidence in MR analysis. Issues commonly addressed relate to the three standard assumptions of instrumental variables analyses, the choice of genetic instrument(s) and features of the population(s) from which the data are collected (particularly in two-sample MR), in addition to more traditional non-MR-specific epidemiological biases. The identified tools should be tested and validated for general use before recommendations can be made on their widespread use. Our findings should raise awareness about the importance of bias related to MR analysis and provide information that is useful for assessment of MR studies in the context of systematic reviews.

Inflammatory Diseases, Inflammatory Biomarkers, and Alzheimer Disease: An Observational Analysis and Mendelian Randomization

BACKGROUND AND OBJECTIVES

Whether chronic autoimmune inflammatory diseases causally affect the risk of Alzheimer disease (AD) is controversial. We characterized the relationship between inflammatory diseases and risk of AD and explored the role of circulating inflammatory biomarkers in the relationships between inflammatory diseases and AD.

METHODS

We performed observational analyses for chronic autoimmune inflammatory diseases and risk of AD using data from 2,047,513 participants identified in the UK Clinical Practice Research Datalink (CPRD). Using data of a total of more than 1,100,000 individuals from 15 large-scale genome-wide association study data sets, we performed 2-sample Mendelian randomizations (MRs) to investigate the relationships between chronic autoimmune inflammatory diseases, circulating inflammatory biomarker levels, and risk of AD.

RESULTS

Cox regression models using CPRD data showed that the overall incidence of AD was higher among patients with inflammatory bowel disease (hazard ratio [HR] 1.17; 95% CI 1.15-1.19; p = 2.1 × 10-4), other inflammatory polyarthropathies and systematic connective tissue disorders (HR 1.13; 95% CI 1.12-1.14; p = 8.6 × 10-5), psoriasis (HR 1.13; 95% CI 1.10-1.16; p = 2.6 × 10-4), rheumatoid arthritis (HR 1.08; 95% CI 1.06-1.11; p = 4.0 × 10-4), and multiple sclerosis (HR 1.06; 95% CI 1.04-1.07; p = 2.8 × 10-4) compared with the age (±5 years) and sex-matched comparison groups free from all inflammatory diseases under investigation. Bidirectional MR analysis identified relationships between chronic autoimmune inflammatory diseases and circulating inflammatory biomarkers. Particularly, circulating monokine induced by gamma interferon (MIG) level was suggestively associated with a higher risk of AD (odds ratio from inverse variance weighted [ORIVW] 1.23; 95% CI 1.06-1.42; p IVW = 0.007) and lower risk of Crohn disease (ORIVW 0.73; 95% CI -0.62 to 0.86; p IVW = 1.3 × 10-4). Colocalization supported a common causal single nucleotide polymorphism for MIG and Crohn disease (posterior probability = 0.74), but not AD (posterior probability = 0.03). Using a 2-sample MR approach, genetically predicted risks of inflammatory diseases were not associated with higher AD risk.

DISCUSSION

Our data suggest that the association between inflammatory diseases and risk of AD is unlikely to be causal and may be a result of confounding. In support, although inflammatory biomarkers showed evidence for causal associations with inflammatory diseases, evidence was weak that they affected both inflammatory disease and AD.

The effect of maternal BMI, smoking and alcohol on congenital heart diseases: a Mendelian randomisation study

BACKGROUND

Congenital heart diseases (CHDs) remain a significant cause of infant morbidity and mortality. Epidemiological studies have explored maternal risk factors for offspring CHDs, but few have used genetic epidemiology methods to improve causal inference.

METHODS

Three birth cohorts, including 65,510 mother/offspring pairs (N = 562 CHD cases) were included. We used Mendelian randomisation (MR) analyses to explore the effects of genetically predicted maternal body mass index (BMI), smoking and alcohol on offspring CHDs. We generated genetic risk scores (GRS) using summary data from large-scale genome-wide association studies (GWAS) and validated the strength and relevance of the genetic instrument for exposure levels during pregnancy. Logistic regression was used to estimate the odds ratio (OR) of CHD per 1 standard deviation (SD) higher GRS. Results for the three cohorts were combined using random-effects meta-analyses. We performed several sensitivity analyses including multivariable MR to check the robustness of our findings.

RESULTS

The GRSs associated with the exposures during pregnancy in all three cohorts. The associations of the GRS for maternal BMI with offspring CHD (pooled OR (95% confidence interval) per 1SD higher GRS: 0.95 (0.88, 1.03)), lifetime smoking (pooled OR: 1.01 (0.93, 1.09)) and alcoholic drinks per week (pooled OR: 1.06 (0.98, 1.15)) were close to the null. Sensitivity analyses yielded similar results.

CONCLUSIONS

Our results do not provide robust evidence of an effect of maternal BMI, smoking or alcohol on offspring CHDs. However, results were imprecise. Our findings need to be replicated, and highlight the need for more and larger studies with maternal and offspring genotype and offspring CHD data.

Insights into Causal Cardiovascular Risk Factors from Mendelian Randomization

PURPOSE OF THE REVIEW

This review summarizes major insights into causal risk factors for cardiovascular disease (CVD) by using Mendelian randomization (MR) to obtain unconfounded estimates, contextualized within its strengths and weaknesses.

RECENT FINDINGS

MR studies have confirmed the role of major CVD risk factors, including alcohol, smoking, adiposity, blood pressure, type 2 diabetes, lipids, and possibly inflammation, but added that the relation with alcohol is likely linear, confirmed the role of diastolic blood pressure, identified apolipoprotein B as the major target lipid, and foreshadowed results of some trials concerning anti-inflammatories. Identifying a healthy diet and the role of early life influences, such as birth weight, has proved more difficult. Use of MR has winnowed empirically driven hypotheses about CVD into a set of genetically validated targets of intervention. Greater inclusion of global diversity in genetic studies and the use of an overarching framework would enable even more informative MR studies.

Phenome-wide Mendelian randomisation analysis identifies causal factors for age-related macular degeneration

Background

Age-related macular degeneration (AMD) is a leading cause of blindness in the industrialised world and is projected to affect >280 million people worldwide by 2040. Aiming to identify causal factors and potential therapeutic targets for this common condition, we designed and undertook a phenome-wide Mendelian randomisation (MR) study.

Methods

We evaluated the effect of 4591 exposure traits on early AMD using univariable MR. Statistically significant results were explored further using: validation in an advanced AMD cohort; MR Bayesian model averaging (MR-BMA); and multivariable MR.

Results

Overall, 44 traits were found to be putatively causal for early AMD in univariable analysis. Serum proteins that were found to have significant relationships with AMD included S100-A5 (odds ratio [OR] = 1.07, p-value = 6.80E-06), cathepsin F (OR = 1.10, p-value = 7.16E-05), and serine palmitoyltransferase 2 (OR = 0.86, p-value = 1.00E-03). Univariable MR analysis also supported roles for complement and immune cell traits. Although numerous lipid traits were found to be significantly related to AMD, MR-BMA suggested a driving causal role for serum sphingomyelin (marginal inclusion probability [MIP] = 0.76; model-averaged causal estimate [MACE] = 0.29).

Conclusions

The results of this MR study support several putative causal factors for AMD and highlight avenues for future translational research.

Funding

This project was funded by the Wellcome Trust (224643/Z/21/Z; 200990/Z/16/Z); the University of Manchester's Wellcome Institutional Strategic Support Fund (Wellcome ISSF) grant (204796/Z/16/Z); the UK National Institute for Health Research (NIHR) Academic Clinical Fellow and Clinical Lecturer Programmes; Retina UK and Fight for Sight (GR586); the Australian National Health and Medical Research Council (NHMRC) (1150144).

Clonal Hematopoiesis and Its Impact on Human Health

Aging is associated with increased mutational burden in every tissue studied. Occasionally, fitness-increasing mutations will arise, leading to stem cell clonal expansion. This process occurs in several tissues but has been best studied in blood. Clonal hematopoiesis is associated with an increased risk of blood cancers, such as acute myeloid leukemia, which result if additional cooperating mutations occur. Surprisingly, it is also associated with an increased risk of nonmalignant diseases, such as atherosclerotic cardiovascular disease. This may be due to enhanced inflammation in mutated innate immune cells, which could be targeted clinically with anti-inflammatory drugs. Recent studies have uncovered other factors that predict poor outcomes in patients with clonal hematopoiesis, such as size of the mutant clone, mutated driver genes, and epigenetic aging. Though clonality is inevitable and largely a function of time, recent work has shown that inherited genetic variation can also influence this process. Clonal hematopoiesis provides a paradigm for understanding how age-related changes in tissue stem cell composition and function influence human health.

An overview on neurobiology and therapeutics of attention-deficit/hyperactivity disorder

Attention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent psychiatric condition characterized by developmentally inappropriate symptoms of inattention and/or hyperactivity/impulsivity, which leads to impairments in the social, academic, and professional contexts. ADHD diagnosis relies solely on clinical assessment based on symptom evaluation and is sometimes challenging due to the substantial heterogeneity of the disorder in terms of clinical and pathophysiological aspects. Despite the difficulties imposed by the high complexity of ADHD etiology, the growing body of research and technological advances provide good perspectives for understanding the neurobiology of the disorder. Such knowledge is essential to refining diagnosis and identifying new therapeutic options to optimize treatment outcomes and associated impairments, leading to improvements in all domains of patient care. This review is intended to be an updated outline that addresses the etiological and neurobiological aspects of ADHD and its treatment, considering the impact of the "omics" era on disentangling the multifactorial architecture of ADHD.

Association between genetically proxied PCSK9 inhibition and prostate cancer risk: A Mendelian randomisation study

BACKGROUND

Prostate cancer (PrCa) is the second most prevalent malignancy in men worldwide. Observational studies have linked the use of low-density lipoprotein cholesterol (LDL-c) lowering therapies with reduced risk of PrCa, which may potentially be attributable to confounding factors. In this study, we performed a drug target Mendelian randomisation (MR) analysis to evaluate the association of genetically proxied inhibition of LDL-c-lowering drug targets on risk of PrCa.

METHODS AND FINDINGS

Single-nucleotide polymorphisms (SNPs) associated with LDL-c (P < 5 × 10-8) from the Global Lipids Genetics Consortium genome-wide association study (GWAS) (N = 1,320,016) and located in and around the HMGCR, NPC1L1, and PCSK9 genes were used to proxy the therapeutic inhibition of these targets. Summary-level data regarding the risk of total, advanced, and early-onset PrCa were obtained from the PRACTICAL consortium. Validation analyses were performed using genetic instruments from an LDL-c GWAS conducted on male UK Biobank participants of European ancestry (N = 201,678), as well as instruments selected based on liver-derived gene expression and circulation plasma levels of targets. We also investigated whether putative mediators may play a role in findings for traits previously implicated in PrCa risk (i.e., lipoprotein a (Lp(a)), body mass index (BMI), and testosterone). Applying two-sample MR using the inverse-variance weighted approach provided strong evidence supporting an effect of genetically proxied inhibition of PCSK9 (equivalent to a standard deviation (SD) reduction in LDL-c) on lower risk of total PrCa (odds ratio (OR) = 0.85, 95% confidence interval (CI) = 0.76 to 0.96, P = 9.15 × 10-3) and early-onset PrCa (OR = 0.70, 95% CI = 0.52 to 0.95, P = 0.023). Genetically proxied HMGCR inhibition provided a similar central effect estimate on PrCa risk, although with a wider 95% CI (OR = 0.83, 95% CI = 0.62 to 1.13, P = 0.244), whereas genetically proxied NPC1L1 inhibition had an effect on higher PrCa risk with a 95% CI that likewise included the null (OR = 1.34, 95% CI = 0.87 to 2.04, P = 0.180). Analyses using male-stratified instruments provided consistent results. Secondary MR analyses supported a genetically proxied effect of liver-specific PCSK9 expression (OR = 0.90 per SD reduction in PCSK9 expression, 95% CI = 0.86 to 0.95, P = 5.50 × 10-5) and circulating plasma levels of PCSK9 (OR = 0.93 per SD reduction in PCSK9 protein levels, 95% CI = 0.87 to 0.997, P = 0.04) on PrCa risk. Colocalization analyses identified strong evidence (posterior probability (PPA) = 81.3%) of a shared genetic variant (rs553741) between liver-derived PCSK9 expression and PrCa risk, whereas weak evidence was found for HMGCR (PPA = 0.33%) and NPC1L1 expression (PPA = 0.38%). Moreover, genetically proxied PCSK9 inhibition was strongly associated with Lp(a) levels (Beta = -0.08, 95% CI = -0.12 to -0.05, P = 1.00 × 10-5), but not BMI or testosterone, indicating a possible role for Lp(a) in the biological mechanism underlying the association between PCSK9 and PrCa. Notably, we emphasise that our estimates are based on a lifelong exposure that makes direct comparisons with trial results challenging.

CONCLUSIONS

Our study supports a strong association between genetically proxied inhibition of PCSK9 and a lower risk of total and early-onset PrCa, potentially through an alternative mechanism other than the on-target effect on LDL-c. Further evidence from clinical studies is needed to confirm this finding as well as the putative mediatory role of Lp(a).

Therapeutic potential of IL6R blockade for the treatment of sepsis and sepsis-related death: A Mendelian randomisation study

BACKGROUND

Sepsis is characterised by dysregulated, life-threatening immune responses, which are thought to be driven by cytokines such as interleukin 6 (IL-6). Genetic variants in IL6R known to down-regulate IL-6 signalling are associated with improved Coronavirus Disease 2019 (COVID-19) outcomes, a finding later confirmed in randomised trials of IL-6 receptor antagonists (IL6RAs). We hypothesised that blockade of IL6R could also improve outcomes in sepsis.

METHODS AND FINDINGS

We performed a Mendelian randomisation (MR) analysis using single nucleotide polymorphisms (SNPs) in and near IL6R to evaluate the likely causal effects of IL6R blockade on sepsis (primary outcome), sepsis severity, other infections, and COVID-19 (secondary outcomes). We weighted SNPs by their effect on CRP and combined results across them in inverse variance weighted meta-analysis, proxying the effect of IL6RA. Our outcomes were measured in UK Biobank, FinnGen, the COVID-19 Host Genetics Initiative (HGI), and the GenOSept and GainS consortium. We performed several sensitivity analyses to test assumptions of our methods, including utilising variants around CRP and gp130 in a similar analysis. In the UK Biobank cohort (N = 486,484, including 11,643 with sepsis), IL6R blockade was associated with a decreased risk of our primary outcome, sepsis (odds ratio (OR) = 0.80; 95% confidence interval (CI) 0.66 to 0.96, per unit of natural log-transformed CRP decrease). The size of this effect increased with severity, with larger effects on 28-day sepsis mortality (OR = 0.74; 95% CI 0.47 to 1.15); critical care admission with sepsis (OR = 0.48, 95% CI 0.30 to 0.78) and critical care death with sepsis (OR = 0.37, 95% CI 0.14 to 0.98). Similar associations were seen with severe respiratory infection: OR for pneumonia in critical care 0.69 (95% CI 0.49 to 0.97) and for sepsis survival in critical care (OR = 0.22; 95% CI 0.04 to 1.31) in the GainS and GenOSept consortium, although this result had a large degree of imprecision. We also confirm the previously reported protective effect of IL6R blockade on severe COVID-19 (OR = 0.69, 95% CI 0.57 to 0.84) in the COVID-19 HGI, which was of similar magnitude to that seen in sepsis. Sensitivity analyses did not alter our primary results. These results are subject to the limitations and assumptions of MR, which in this case reflects interpretation of these SNP effects as causally acting through blockade of IL6R, and reflect lifetime exposure to IL6R blockade, rather than the effect of therapeutic IL6R blockade.

CONCLUSIONS

IL6R blockade is causally associated with reduced incidence of sepsis. Similar but imprecisely estimated results supported a causal effect also on sepsis related mortality and critical care admission with sepsis. These effects are comparable in size to the effect seen in severe COVID-19, where IL-6 receptor antagonists were shown to improve survival. These data suggest that a randomised trial of IL-6 receptor antagonists in sepsis should be considered.

Impact of Adolescent Cannabis Use on Neurocognitive and Brain Development

Research examining associations between frequent cannabis use in adolescence and brain-behavior outcomes has increased substantially over the past 2 decades. This review attempts to synthesize the state of evidence in this area of research while acknowledging challenges in interpretation. Although there is converging evidence that ongoing, frequent cannabis use in adolescence is associated with small reductions in cognitive functioning, there is still significant debate regarding the persistence of reductions after a period of abstinence. Similarly, there is controversy regarding the replicability of structural and functional neuroimaging findings related to frequent cannabis use in adolescence. Larger studies with informative designs are needed.

Vitamin D Levels and Risk of Male Factor Infertility: A Mendelian Randomization Study

PURPOSE

No consensus exists about the causal relationship between vitamin D (VD) and male factor infertility due to heterogeneity and confounding factors even in randomized controlled trials (RCTs). This study aimed to investigate the causal association between 25 hydroxyvitamin D (25OHD) levels and male factor infertility through Mendelian randomization (MR) and provide complementary information for optimization of future RCTs.

MATERIALS AND METHODS

Two-sample MR analyses with four steps were performed. Single-nucleotide polymorphisms (SNPs) for VD were extracted from 417,580 Europeans in the UK Biobank, and the summary-level data of male factor infertility (825 cases and 85,722 controls) were extracted from the FinnGen.

RESULTS

Totally 99 SNPs robustly associated with the 25OHD were included, and a 1-unit increase in genetically predicted natural-log transformed 25OHD levels was associated with decreased risk of male factor infertility (odds ratio [OR], 0.62; 95% confidence interval [CI], 0.44-0.89; p=0.010), which was consistent in all three sensitivity analyses (MR-Egger, weighted median, and weighted mode methods). The conclusion still stands after removing SNPs which explained more variation in the male factor infertility than the 25OHD (OR, 0.61; 95% CI, 0.42-0.88; p=0.009; n=62), and which were associated with confounders (body mass index, type 2 diabetes, smoking, and coronary artery diseases) of male factor infertility (OR, 0.58; 95% CI, 0.39-0.85; p=0.005; n=55).

CONCLUSIONS

VD supplement to increase serum 25OHD levels may be clinically beneficial for male factor infertility in the general population. The well-designed RCTs should be performed in priority to address this question.

The Effect of Blood Lipids, Type 2 Diabetes, and Body Mass Index on Parkinson's Disease: A Korean Mendelian Randomization Study

OBJECTIVE

Associations between various metabolic conditions and Parkinson's disease (PD) have been previously identified in epidemiological studies. We aimed to investigate the causal effect of lipid levels, type 2 diabetes mellitus (T2DM), and body mass index (BMI) on PD in a Korean population via Mendelian randomization (MR).

METHODS

Two-sample MR analyses were performed with inverse-variance weighted (IVW), weighted median, and MR-Egger regression approaches. We identified genetic variants associated with lipid concentrations, T2DM, and BMI in publicly available summary statistics, which were either collected from genome-wide association studies (GWASs) or from meta-analyses of GWAS that targeted only Korean individuals or East Asian individuals, including Korean individuals. The outcome dataset was a GWAS on PD performed in a Korean population.

RESULTS

From previous GWASs and meta-analyses, we selected single nucleotide polymorphisms as the instrumental variables. Variants associated with serum levels of low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides, as well as with T2DM and BMI, were selected (n = 11, 19, 17, 89, and 9, respectively). There were no statistically significant causal associations observed between the five exposures and PD using either the IVW, weighted median, or MR-Egger methods (p-values of the IVW method: 0.332, 0.610, 0.634, 0.275, and 0.860, respectively).

CONCLUSION

This study does not support a clinically relevant causal effect of lipid levels, T2DM, and BMI on PD risk in a Korean population.

Genotype-driven NPC1L1 and PCSK9 inhibition and reduced risk of periodontitis

AIM

Epidemiological and pre-clinical studies suggest a chemoprotective role of lipid-lowering agents in periodontitis. We tested the association of genetically proxied inhibition of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR), Niemann-Pick C1-Like 1 (NPC1L1) and proprotein convertase subtilisin/kexin type 9 (PCSK9) with periodontitis.

MATERIALS AND METHODS

Genetic variants in HMGCR, NCP1L1 and PCSK9 associated with low-density lipoprotein (LDL) cholesterol in a genome-wide association study (GWAS) meta-analysis (N = 188,578) were used to proxy therapeutic inhibition of HMGCR, NPC1L1 and PCSK9. For these genetic variants, associations with periodontitis were obtained from GWAS of 17,353 cases and 28,210 controls in the GeneLifestyle Interactions in Dental Endpoints consortium. Generalized weighted least squares analysis accounted for linkage disequilibrium of genotypes to derive pooled estimates.

RESULTS

While genetically proxied HMGCR inhibition equivalent to 1 mmol/L reduction in LDL was not associated with odds of periodontitis (odds ratio [OR] = 0.92 [95% confidence interval [CI]: 0.73; 1.16]; p = .4905; false discovery rate [FDR] = 0.4905), genetically proxied NPC1L1 (OR = 0.53 [95% CI: 0.35; 0.81]; p = .0038; FDR = 0.0077) and PCSK9 (OR = 0.84 [95% CI: 0.74; 0.95]; p = .0051; FDR = 0.0077) inhibition lowered the odds of periodontitis.

CONCLUSIONS

Genetically proxied inhibition of NCP1L1 and PCSK9 was associated with lower odds of periodontitis.

Genomics and phenomics of body mass index reveals a complex disease network

Elevated body mass index (BMI) is heritable and associated with many health conditions that impact morbidity and mortality. The study of the genetic association of BMI across a broad range of common disease conditions offers the opportunity to extend current knowledge regarding the breadth and depth of adiposity-related diseases. We identify 906 (364 novel) and 41 (6 novel) genome-wide significant loci for BMI among participants of European (N~1.1 million) and African (N~100,000) ancestry, respectively. Using a BMI genetic risk score including 2446 variants, 316 diagnoses are associated in the Million Veteran Program, with 96.5% showing increased risk. A co-morbidity network analysis reveals seven disease communities containing multiple interconnected diseases associated with BMI as well as extensive connections across communities. Mendelian randomization analysis confirms numerous phenotypes across a breadth of organ systems, including conditions of the circulatory (heart failure, ischemic heart disease, atrial fibrillation), genitourinary (chronic renal failure), respiratory (respiratory failure, asthma), musculoskeletal and dermatologic systems that are deeply interconnected within and across the disease communities. This work shows that the complex genetic architecture of BMI associates with a broad range of major health conditions, supporting the need for comprehensive approaches to prevent and treat obesity.

Joint inference of physiological network and survival analysis identifies factors associated with aging rate

We describe methodology for joint reconstruction of physiological-survival networks from observational data capable of identifying key survival-associated variables, inferring a minimal physiological network structure, and bridging this network to the Gompertzian survival layer. Using synthetic network structures, we show that the method is capable of identifying aging variables in cohorts as small as 5,000 participants. Applying the methodology to the observational human cohort, we find that interleukin-6, vascular calcification, and red-blood distribution width are strong predictors of baseline fitness. More important, we find that red blood cell counts, kidney function, and phosphate level are directly linked to the Gompertzian aging rate. Our model therefore enables discovery of processes directly linked to the aging rate of our species. We further show that this epidemiological framework can be applied as a causal inference engine to simulate the effects of interventions on physiology and longevity.

Biobanking as a Tool for Genomic Research: From Allele Frequencies to Cross-Ancestry Association Studies

In recent years, great advances have been made in the field of collection, storage, and analysis of biological samples. Large collections of samples, biobanks, have been established in many countries. Biobanks typically collect large amounts of biological samples and associated clinical information; the largest collections include over a million samples. In this review, we summarize the main directions in which biobanks aid medical genetics and genomic research, from providing reference allele frequency information to allowing large-scale cross-ancestry meta-analyses. The largest biobanks greatly vary in the size of the collection, and the amount of available phenotype and genotype data. Nevertheless, all of them are extensively used in genomics, providing a rich resource for genome-wide association analysis, genetic epidemiology, and statistical research into the structure, function, and evolution of the human genome. Recently, multiple research efforts were based on trans-biobank data integration, which increases sample size and allows for the identification of robust genetic associations. We provide prominent examples of such data integration and discuss important caveats which have to be taken into account in trans-biobank research.

Observational studies in Alzheimer disease: bridging preclinical studies and clinical trials

Recent high-profile failures of Alzheimer disease treatments at the clinical trial stage have led to renewed efforts to identify and test novel interventions for Alzheimer disease and related dementias (ADRD). In this Perspective, we highlight the importance of including well-designed observational studies as part of these efforts. Observational research is an important cornerstone for gathering evidence on risk factors and causes of ADRD; this evidence can then be combined with data from preclinical studies and randomized controlled trials to inform the development of effective interventions. Observational study designs can be particularly beneficial for hypothesis generation, posing questions that are unethical or impractical for a trial setting, studying life-course associations, research in populations typically not included in trials, and public health surveillance. Here, we discuss each of these situations in the specific context of ADRD research. We also highlight novel approaches to enhance causal inference and provide a timely discussion on how observational epidemiological studies help provide a bridge between preclinical studies and successful interventions for ADRD.

Heart failure and late-onset Alzheimer's disease: A Mendelian randomization study

Some observational studies suggested that heart failure (HF) is associated with increased risk of late-onset Alzheimer's disease (AD). On the other hand, a recently published Two-Sample Mendelian Randomization (2SMR) study was reported as inconclusive but the estimated odds ratios (ORs) were less than one indicating a potential causal association between genetically predicted HF and lowered risk of AD. Both HF and AD are quite common among elderly persons and frequently occur together resulting in a series of severe medical challenges and increased financial burden on healthcare. It is of great medical and financial interest to further investigate the statistical significance of the potential causal associations between genetically predicted HF and lowered risk of AD using large independent cohorts. To fill this important knowledge gap, the present study used the 2SMR method based on summary data from a recently published large genome-wide association study (GWAS) for AD on subjects with European ancestry. The 2SMR analysis provided statistically significant evidence of an association with ORs less than one between genetically predicted HF and late-onset AD (Inverse Variance Weighted, OR = 0.752, p = 0.004; MR Egger, OR = 0.546, p = 0.100; Weighted Median, OR = 0.757, p = 0.014). Further investigations of the significant associations between HF and late-onset AD, including specific genes related to the potential protective effect of HF-related medications on cognitive decline, are warranted.