Using genetic association data to guide drug discovery and development: Review of methods and applications

Urolithiasis Causes Osteoporosis in Asians: Genetic Evidence from Mendelian Randomization and Pathway Analysis

BACKGROUND

It is an indisputable fact that patients with urolithiasis are prone to osteoporosis (OP), but the specific mechanism of their association is unclear. Previous studies have focused on the mediation of environmental factors such as diet; however, the potential of urolithiasis itself to induce OP remains uncertain.

METHODS

In this study, we used data from the Japan BioBank (6638 urolithiasis and 7788 OP cases) to investigate the direct causal relationship and mechanism between urolithiasis and OP, applying Mendelian randomization, genetic correlation analysis, colocalization, and pathway analysis. We selected 10 genetic variants as instrumental variables for urolithiasis.

RESULTS

The results showed a positive association between genetically predicted urolithiasis and OP, with significant direct effects persisting after adjusting for OP-associated factors in 4 models. Reverse analysis revealed no significant causal effect of genetically predicted OP on urolithiasis. While genetic correlation analysis and colocalization did not find conclusive evidence, mediation analysis identified estimated glomerular rate as a significant contributor. Co-risk factor analysis unveiled cardiovascular elements as common risks for both conditions. Bioanalysis implicates that cytokine, metabolic, and calcium signaling pathways may bridge urolithiasis and OP, with BCAS3, DGKH, TBX2, and TBX2-AS1 identified as potential causal genes.

CONCLUSION

In conclusion, the study establishes a direct causal link between urolithiasis and OP, independent of environmental factors. Regardless of lifestyle, urolithiasis patients should remain vigilant about the risk of OP and consider regular OP screening. The biological mechanism of urolithiasis combined with OP and related drugs still needs to be further explored.

Hypnotic use and the risk of cardiovascular diseases in insomnia patients

AIMS

We aimed to examine the association between hypnotic agents and cardiovascular outcomes in general individuals with insomnia.

METHODS AND RESULTS

In a propensity score matched cohort of UK Biobank (UKB) participants with insomnia, Cox proportional hazard model was used to estimate the association between regular use of hypnotic agents and predetermined cardiovascular outcomes including incident coronary heart diseases (CHD), heart failure (HF), stroke, and cardiovascular death. Inverse probability of treatment weighting, competing risk models, and shared frailty models were further performed during sensitivity analysis. Drug-target Mendelian randomization (MR) analyses were employed for further evaluation of the association between therapeutic targets of hypnotics and cardiovascular diseases. During a median follow-up of 14.3 years, the matched cohort documented a total of 929 CHD cases, 360 HF cases, 262 stroke cases, and 180 cardiovascular deaths. No significant association was detected between Z-meds and CHD, stroke, and cardiovascular mortality. Benzodiazepine use was significantly associated with the increased risk of CHD, HF, and cardiovascular mortality. The inverse probability of treatment weighting, competing risk models, and shared frailty models didn't alter the above associations. Moreover, drug-target MR analyses corroborated the safety of Z-meds in the general population regarding cardiovascular health.

CONCLUSION

Our findings suggested the heterogeneous associations between different categories of hypnotics and incident cardiovascular events in individuals with insomnia. Both observational and genetic evidence raised safety concerns regarding the cardiovascular impact of benzodiazepines. No cardiovascular hazard of Z-meds was discovered in the UKB population with insomnia.

Researching the causal relationship between immune cells and frontotemporal Dementia: A Mendelian Randomization analysis

BACKGROUND

Frontotemporal dementia (FTD) is a prevalent dementia syndrome with poorly understood immunological underpinnings. Despite the widespread adoption of high-density genotyping technologies like SNPs and CNVs, and advances in genome-wide association studies (GWAS), the immunological mechanisms underlying FTD remain elusive. This study aims to elucidate the causal relationships between immune cell traits and FTD using Mendelian randomization (MR).

METHODS

We utilized summary data for FTD (cases = 129, controls = 392,463) from the FinnGen dataset and summary statistics for 731 immune cell traits from the GWAS catalog. These traits included morphological parameters (MP = 32), median fluorescence intensity (MFI = 389), absolute cell counts (AC = 118), and relative cell counts (RC = 192). Our approach encompassed forward MR (immune cell traits as exposure) and reverse MR (FTD as exposure), accompanied by rigorous sensitivity analyses to assess the robustness and heterogeneity of the findings.

RESULTS

FTD did not have a statistically significant impact on immune phenotypes. Notably, we identified 13 immune phenotypes as protective against FTD, including various T cell and B cell markers. Conversely, 8 phenotypes were associated with increased FTD risk, involving markers on myeloid cells and subsets of T and B cells; CONCLUSION: This MR study identifies specific immune phenotypes associated with FTD, highlighting potential pathways for future clinical research and therapeutic intervention.

Exploring the Relationship Between Antipsychotic Drug Target Genes and Epilepsy: Evidence From Food and Drug Administration Adverse Event Reporting System Database and Mendelian Randomization

BACKGROUND

The effect of antipsychotic drugs on epilepsy is controversial, and we performed Food and Drug Administration Adverse Event Reporting System (FAERS) data mining and Mendelian Randomization (MR) analyses to clarify the effects of target genes on epilepsy.

METHOD

We explored antipsychotic-induced epilepsy AE signals in FAERS. Gene expression was obtained from the eQTLGen consortium and GTEx project. Epilepsy data were obtained from FinnGen and the International League Against Epilepsy (ILAE). MR, Summary-data-based Mendelian Randomization (SMR), and colocalization analysis were sequentially performed, and meta-analysis was performed on genes with significant expression in MR or SMR to assess the causal relationship between them and epilepsy.

RESULT

Through FAERS database mining, 63 antipsychotics reported 5121 adverse events in epilepsy. MR identified potential causal associations of 14 drug target genes for epilepsy and its subtypes. MCHR1 and SIGMAR1 were still significant for epilepsy after meta-analysis with no evidence of heterogeneity or pleiotropy. SMR showed that DRD4 and ADRA1D were strongly associated with epilepsy or its subtypes however, neither gene passed the HEIDI test.

CONCLUSION

Our study indicates that antipsychotic drugs are associated with a high incidence of epilepsy-related AEs. MR demonstrated a causal relationship between drug targets and epilepsy. Providing new insights for managing epilepsy patients with psychiatric disorders.

Evaluating the Cardiometabolic Efficacy and Safety of Lipoprotein Lipase Pathway Targets in Combination With Approved Lipid-Lowering Targets: A Drug Target Mendelian Randomization Study

BACKGROUND

Therapies targeting the LPL (lipoprotein lipase) pathway are under development for cardiometabolic disease. Insights into their efficacy-both alone and in combination with existing lipid-lowering therapies-modes of action, and safety of these agents are essential to inform clinical development. Using Mendelian randomization, we aimed to (1) evaluate efficacy, (2) explore shared mechanisms, (3) assess additive effects with approved lipid-lowering drugs, and (4) identify secondary indications and potential adverse effects.

METHODS

We selected triglyceride-lowering genetic variants located in the genes encoding ANGPTL3 (angiopoietin-like 3), ANGPTL4 (angiopoietin-like 4), APOC3 (apolipoprotein C3), and LPL and conducted drug target Mendelian randomization on primary outcomes including coronary artery disease and type 2 diabetes, and secondary outcomes, including apolipoprotein B, waist-to-hip ratio, body mass index, and 233 metabolic biomarkers. We conducted interaction Mendelian randomization analyses in 488 139 UK Biobank participants to test the effect of combination therapy targeting the LPL and LDLR (low-density lipoprotein receptor) pathways. Finally, we investigated potential secondary indications and adverse effects by leveraging genetic association data on 1204 disease end points.

RESULTS

Genetically predicted triglyceride lowering through the perturbation of LPL pathway activation targets ANGPTL4, APOC3, and LPL was associated with a lower risk of coronary artery disease and type 2 diabetes and lower apolipoprotein B. Genetically predicted triglyceride lowering through ANGPTL4 was associated with a lower waist-to-hip ratio, suggestive of a favorable body fat distribution. There was no evidence of a multiplicative interaction between genetically proxied perturbation of ANGPTL4, APOC3, and LPL and that of HMGCR (HMG-CoA reductase) and PCSK9 (proprotein convertase subtilisin/kexin type 9) on coronary artery disease and type 2 diabetes, consistent with additive effects. Finally, associations of genetically predicted LPL pathway targeting were supportive of the broad safety of these targets.

CONCLUSIONS

Our findings provide genetic evidence supporting the efficacy and safety of LPL pathway activation therapies for the prevention of coronary artery disease and type 2 diabetes, alone or in combination with statins or PCSK9 inhibitors.

Genetic Evidence for GLP-1 and GIP Receptors as Targets for Treatment and Prevention of MASLD/MASH

BACKGROUND AND AIMS

Glucagon-like peptide-1 receptor (GLP1R) agonists and glucose-dependent insulinotropic polypeptide receptor (GIPR) agonists may help treat metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH). However, their definitive effects are still unclear. Our study aims to clarify this uncertainty.

METHODS

We utilised conventional Mendelian randomisation (MR) analysis to explore potential causal links between plasma GLP-1/GIP concentrations and MASLD and its related traits. Next, we conducted drug-target MR analysis using highly expressed tissue data to assess the effects of corresponding drug perturbation on these traits. Finally, mediation analysis was performed to ascertain whether the potential causal effect is direct or mediated by other MASLD-related traits.

RESULTS

Circulating 2-h GLP-1 and GIP concentrations measured during an oral glucose tolerance test showed hepatoprotective effects on MASLD risk (ORGLP-1 = 0.168 [95% CI 0.033-0.839], p = 0.030; ORGIP = 0.331 [95% CI 0.222-0.494], p = 6.31 × 10-8). GLP1R expression in the blood had a minimal causal effect on MASLD risk, whereas GIPR expression significantly affected MASLD risk (OR = 0.671 [95% CI 0.531-0.849], p = 9.07 × 10-4). Expression levels of GLP1R or GIPR in the blood significantly influenced MASLD-related clinical traits. Mediation analysis revealed that GIPR expression protected against MASLD, even after adjusting for type 2 diabetes or body mass index.

CONCLUSIONS

GLP-1/GIP receptor agonists offer promise in lowering MASLD/MASH risk. GIP receptor agonists can exert direct and indirect effects on MASLD mediated by weight reduction or glycemic control improvement.

Hypertriglyceridemia as a Key Contributor to Abdominal Aortic Aneurysm Development and Rupture: Insights from Genetic and Experimental Models

Abdominal aortic aneurysm (AAA) is a life-threatening vascular disease without effective medications. This study integrated genetic, proteomic, and metabolomic data to identify causation between increased triglyceride (TG)-rich lipoproteins and AAA risk. Three hypertriglyceridemia mouse models were employed to test the hypothesis that increased plasma TG concentrations accelerate AAA development and rupture. In the angiotensin II-infusion AAA model, most Lpl -deficient mice with severely high plasma TG concentrations died of aortic rupture. Consistently, Apoa5 -deficient mice with moderately increased TG concentrations had accelerated AAA development, while human APOC3 transgenic mice with dramatically increased TG concentrations exhibited aortic dissection and rupture. Increased TG concentrations and palmitate inhibited lysyl oxidase maturation. Locally overexpressing lysyl oxidase eliminated the impact of high TG on AAA formation in human APOC3 transgenic mice. Administration of antisense oligonucleotide targeting Angptl3 profoundly inhibited AAA progression in human APOC3 transgenic mice and Apoe -deficient mice. These results indicate that hypertriglyceridemia is a key contributor to AAA pathogenesis, highlighting the importance of triglyceride-rich lipoprotein management in treating AAA.

Clinical Perspective

What Is New?: This study integrates genetic, proteomic, and metabolomic data to identify causation between increased triglyceride (TG)-rich lipoproteins and AAA risk.TG concentrations influence AAA formation and severity in a dose-dependent manner, potentially by inhibiting lysyl oxidase maturation and extracellular matrix assembly. Administration of antisense oligonucleotide targeting Angptl3 profoundly inhibites AAA progression in human APOC3 transgenic mice and Apoe -deficient mice by lowering TG concentrations. What Are the Clinical Implications?: These findings underscore triglyceride-rich lipoprotein management as a promising therapeutic strategy for AAA treatment.Antisense oligonucleotide therapy targeting liver ANGPTL3 holds potential as a therapeutic approach to reduce AAA risk.

Risk factors for non-responsiveness to 5-aminosalicylic acid in patients with ulcerative colitis identified using retrospective clinical study and Mendelian randomization

This study aimed to identify risk factors and potential targets associated with non-responsiveness to 5-Aminosalicylic acid (5-ASA) in patients with ulcerative colitis (UC). Patients with mild to moderate UC were grouped based on their responsiveness to 5-ASA. Regression analysis was conducted to identify risk factors for non-responsiveness, while Mendelian randomization (MR) analysis was used to evaluate the potential targets. Among 50 patients (11 non-responders and 39 responders), non-responders exhibited higher incidences of fever, back pain, allergy history, and ankylosing spondylitis, as well as elevated monocyte count and alanine aminotransferase (ALT) level, but a lower aspartate aminotransferase-to-ALT (AST/ALT) ratio (all P < 0.05). Allergy history was a risk factor (OR 140.50, P = 0.021), while a high AST/ALT ratio was a protective factor (OR 0.001, P = 0.023) for non-responsiveness. The area under the receiver operating characteristic curve for the AST/ALT ratio was 0.80. MR analysis showed that inhibition of the inhibitor of nuclear factor kappa-B kinase subunit alpha (CHUK) by 5-ASA, targeting ALT, increased the risk of UC (OR 1.02, P = 0.002). Our findings suggested that allergy history and the AST/ALT ratio were associated with non-responsiveness to 5-ASA, and CHUK was identified as a potential target for ALT-related non-responsiveness.Trial Registration: ChiCTR2400084086|| http://www.chictr.org.cn/ , Chinese Clinical Trial Registry, 2024-05-10.

Unraveling the role of proteins in dementia: insights from two UK cohorts with causal evidence

Population-based proteomics offers a groundbreaking avenue to predict future disease risks, enhance our understanding of disease mechanisms, and discover novel therapeutic targets and biomarkers. The role of plasma proteins in dementia, however, requires further exploration. This study investigated 276 protein-dementia associations in 229 incident all-cause dementia, 89 Alzheimer's disease, and 41 vascular dementia among 3249 participants (55% women, 97.2% white ethnicity) from the English Longitudinal Study of Ageing (ELSA) over a median 9.8-year follow-up. We used Cox proportional hazard regression for the analysis. Receiver operating characteristic analyses were conducted to assess the precision of the identified proteins from the fully adjusted Cox regression models in predicting incident all-cause dementia, both individually and in combination with demographic predictors, APOE genotype, and memory score, to estimate the area under the curve. Additionally, the eXtreme Gradient Boosting machine learning algorithm was used to identify the most important features predictive of future all-cause dementia onset. These associations were then validated in 1506 incident all-cause dementia, 732 Alzheimer's disease, 281 vascular dementia, and 111 frontotemporal dementia cases among 52 745 individuals (53.9% women, 93.3% White ethnicity) from the UK Biobank over a median 13.7-year follow-up. Two-sample bi-directional Mendelian randomization and drug target Mendelian randomization were further employed to determine the causal direction between protein concentration and dementia. NEFL (hazard ratio [HR] [95% confidence intervals (CIs)]: 1.54 [1.29, 1.84]) and RPS6KB1 (HR [95% CI]: 1.33 [1.16, 1.52]) were robustly associated with incident all-cause dementia; MMP12 (HR [95% CI]: 2.06 [1.41, 2.99]) was associated with vascular dementia in ELSA, after correcting for multiple testing. Additional markers EDA2R and KIM1 were identified from subgroup and sensitivity analyses. Combining NEFL and RPS6KB1 with other predictors yielded high predictive accuracy (area under the curve = 0.871) for incident all-cause dementia. The eXtreme Gradient Boosting machine learning algorithm also identified RPS6KB1, NEFL, and KIM1 as the most important protein features for predicting future all-cause dementia. Sex difference was evident for the association between RPS6KB1 and all-cause dementia, with stronger association in men (P for interaction = 0.037). Replication in the UK Biobank confirmed the associations between the identified proteins and various dementia subtypes. The results from Mendelian randomization in the reverse direction indicated that several proteins serve as early markers for dementia, rather than being direct causes of the disease. These findings provide insights into putative mechanisms for dementia. Future studies are needed to validate the findings on RPS6KB1 in relation to dementia risk.

The Causal Relationship Between Dietary Factors and the Risk of Intracranial Aneurysms: A Mendelian Randomization Analysis

Background: Some studies have shown that dietary factors can influence the occurrence of intracranial aneurysms (IAs). This study aimed to investigate whether dietary factors and habits are associated with intracranial aneurysms using Mendelian randomization (MR) analysis. Methods: A two-sample MR study was conducted to evaluate the association of dietary factors with IAs. Heterogeneity was evaluated using Cochran's Q test, and horizontal pleiotropy was assessed through MR-Egger regression and MR-pleiotropy residual sum and outlier (MR-PRESSO). Results: Fresh fruit intake (OR: 0.28, 95% CI: [0.13, 0.59]) was related to a decreased risk of IAs. Lamb/mutton intake may be associated with IAs, although the meta-analysis results were not significant (OR: 1.43, 95% CI: [0.27, 7.67]). Furthermore, MR analyses based on two aneurysm databases showed that alcoholic intake was not associated with IAs (alcoholic drinks per week: OR: 1.057, 95% CI: [0.788, 1.42]; OR: 0.509, 95% CI: [0.1665, 1.56]; alcohol intake frequency: OR: 1.084, 95% CI: [0.909, 1.29]; OR: 1.307, 95% CI: [0.814, 2.1]). Our results showed no causal relationship between coffee intake and IAs (OR: 1.149, 95% CI: [0.575, 2.3]; OR: 0863, 95% CI: [0.2979, 2.5]). Other dietary intakes were also found to have no causal relationship with IAs. Conclusions: This study found that fresh fruit intake was associated with a reduced risk of IAs. Lamb/mutton intake may be associated with IAs. However, other dietary factors, including alcohol intake and coffee intake, were found not to be associated with IAs.

Validation of L-type calcium channel blocker amlodipine as a novel ADHD treatment through cross-species analysis, drug-target Mendelian randomization, and clinical evidence from medical records

ADHD is a chronic neurodevelopmental disorder that significantly affects life outcomes, and current treatments often have adverse side effects, high abuse potential, and a 25% non-response rate, highlighting the need for new therapeutics. This study investigates amlodipine, an L-type calcium channel blocker, as a potential foundation for developing a novel ADHD treatment by integrating findings from animal models and human genetic data. Amlodipine reduced hyperactivity in SHR rats and decreased both hyperactivity and impulsivity in adgrl3.1-/- zebrafish. It also crosses the blood-brain barrier, reducing telencephalic activation. Crucially, Mendelian Randomization analysis linked ADHD to genetic variations in L-type calcium channel subunits (α1-C; CACNA1C, β1; CACNB1, α2δ3; CACNA2D3) targeted by amlodipine, while polygenic risk score analysis showed symptom mitigation in individuals with high ADHD genetic liability. With its well-tolerated profile and efficacy across species, supported by genetic evidence, amlodipine shows potential to be refined and developed into a novel treatment for ADHD.

Cell state-dependent allelic effects and contextual Mendelian randomization analysis for human brain phenotypes

Gene expression quantitative trait loci are widely used to infer relationships between genes and central nervous system (CNS) phenotypes; however, the effect of brain disease on these inferences is unclear. Using 2,348,438 single-nuclei profiles from 391 disease-case and control brains, we report 13,939 genes whose expression correlated with genetic variation, of which 16.7-40.8% (depending on cell type) showed disease-dependent allelic effects. Across 501 colocalizations for 30 CNS traits, 23.6% had a disease dependency, even after adjusting for disease status. To estimate the unconfounded effect of genes on outcomes, we repeated the analysis using nondiseased brains (n = 183) and reported an additional 91 colocalizations not present in the larger mixed disease and control dataset, demonstrating enhanced interpretation of disease-associated variants. Principled implementation of single-cell Mendelian randomization in control-only brains identified 140 putatively causal gene-trait associations, of which 11 were replicated in the UK Biobank, prioritizing candidate peripheral biomarkers predictive of CNS outcomes.

Human Genetic Evidence to Inform Clinical Development of IL-6 Signaling Inhibition for Abdominal Aortic Aneurysm

BACKGROUND

Abdominal aortic aneurysm (AAA) represents a significant cause of mortality, yet no medical therapies have proven efficacious. The aim of the current study was to leverage human genetic evidence to inform clinical development of IL-6 (interleukin-6) signaling inhibition for the treatment of AAA.

METHODS

Associations of rs2228145, a missense variant in the IL6R gene region, are expressed per additional copy of the C allele, corresponding to the genetically predicted effect of IL-6 signaling inhibition. We consider genetic associations with AAA risk in the AAAgen consortium (39 221 cases and 1 086 107 controls) and UK Biobank (1963 cases and 365 680 controls). To validate against known effects of IL-6 signaling inhibition, we present associations with rheumatoid arthritis, polymyalgia rheumatica, and severe COVID-19. To explore mechanism specificity, we present associations with thoracic aortic aneurysm, intracranial aneurysm, and coronary artery disease. We further explored genetic associations in clinically relevant subgroups of the population.

RESULTS

We observed strong genetic associations with AAA risk in the AAAgen consortium, UK Biobank, and FinnGen (odds ratios: 0.91 [95% CI, 0.90-0.92], P=4×10-30; 0.90 [95% CI, 0.84-0.96], P=0.001; and 0.86 [95% CI, 0.82-0.91], P=7×10-9, respectively). The association was similar for fatal AAA but with greater uncertainty due to the lower number of events. The association with AAA was of greater magnitude than associations with coronary artery disease and even rheumatological disorders for which IL-6 inhibitors have been approved. No strong associations were observed with thoracic aortic aneurysm or intracranial aneurysm. Associations attenuated toward the null in populations with concomitant rheumatological or connective tissue disease.

CONCLUSIONS

Inhibition of IL-6 signaling is a promising strategy for treating AAA but not other types of aneurysmal disease. These findings serve to help inform clinical development of IL-6 signaling inhibition for AAA treatment.

Integrative proteogenomic analysis identifies COL6A3-derived endotrophin as a mediator of the effect of obesity on coronary artery disease

Obesity strongly increases the risk of cardiometabolic diseases, yet the underlying mediators of this relationship are not fully understood. Given that obesity strongly influences circulating protein levels, we investigated proteins mediating the effects of obesity on coronary artery disease, stroke and type 2 diabetes. By integrating two-step proteome-wide Mendelian randomization, colocalization, epigenomics and single-cell RNA sequencing, we identified five mediators and prioritized collagen type VI α3 (COL6A3). COL6A3 levels were strongly increased by body mass index and increased coronary artery disease risk. Notably, the carboxyl terminus product of COL6A3, endotrophin, drove this effect. COL6A3 was highly expressed in disease-relevant cell types and tissues. Finally, we found that body fat reduction could reduce plasma levels of COL6A3-derived endotrophin, indicating a tractable way to modify endotrophin levels. In summary, we provide actionable insights into how circulating proteins mediate the effects of obesity on cardiometabolic diseases and prioritize endotrophin as a potential therapeutic target.

Identification of Potential Therapeutic Targets for Sensorineural Hearing Loss and Evaluation of Drug Development Potential Using Mendelian Randomization Analysis

Background: Sensorineural hearing loss (SNHL) is a major contributor to hearing impairment, yet effective therapeutic options remain elusive. Mendelian randomization (MR) has proven valuable for drug repurposing and identifying new therapeutic targets. This study aims to pinpoint novel treatment targets for SNHL, exploring their pathophysiological roles and potential adverse effects. Methods: This research utilized the UKB-PPP database to access cis-protein quantitative trait locus (cis-pQTL) data, with SNHL data sourced from the FinnGen database as the endpoint for the MR causal analysis of drug targets. Colocalization analysis was employed to determine whether SNHL risk and protein expression share common SNPs. A phenotype-wide association analysis was conducted to assess the potential side effects of these targets. Drug prediction and molecular docking were subsequently used to evaluate the therapeutic potential of the identified targets. Results: Four drug target proteins significantly associated with sensorineural hearing loss (SNHL) were determined by Mendelian randomization (MR) analysis and co-localization analysis. These drug targets include LATS1, TEF, LMNB2, and OGFR and were shown to have fewer potential side effects when acting on these target proteins by phenotype-wide association analysis. Genes associated with sensorineural hearing loss are primarily implicated in the Hippo signaling pathway, cell-cell adhesion, and various binding regulatory activities and are involved in the regulation of cell proliferation and apoptosis. Next, drugs for the treatment of SNHL were screened by the DsigDB database and molecular docking, and the top 10 drugs were selected based on p-value. Among them, atrazine CTD 00005450 was identified as the most likely therapeutic target, followed by ampyrone HL60 DOWN and genistein CTD 00007324. In addition, LMNB2, LATS1, and OGFR could be intervened in by multiple drugs; however, fewer drugs intervened in TEF. Conclusion: This study has successfully identified four promising drug targets for SNHL, which are likely to be effective in clinical trials with minimal side effects. These findings could significantly streamline drug development for SNHL, potentially reducing the costs and time associated with pharmaceutical research and development.

Causal relationships between hippocampal volumetric traits and the risk of Alzheimer's disease: a Mendelian randomization study

Alzheimer's disease, a common and progressive neurodegenerative disorder, is associated with alterations in hippocampal volume, as revealed by neuroimaging research. However, the causal links between the volumes of the hippocampus and its subfield structures with Alzheimer's disease remain unknown. A genetic correlation analysis using linkage disequilibrium score regression was conducted to identify hippocampal volumetric traits linked to Alzheimer's disease. Following this, to examine the causal links between Alzheimer's disease and hippocampal volumetric traits, we applied a two-sample Mendelian randomization approach, utilizing a bidirectional framework. Seven hippocampal volumetric traits were found as genetically correlated with Alzheimer's disease in the genetic correlation analysis and were then included in the Mendelian randomization analyses. Inverse variance weighted Mendelian randomization analyses revealed that increased volumes in the left whole hippocampus, left hippocampal body, right presubiculum head and right cornu ammonis 1 head were causally related to higher risks of Alzheimer's disease. Conversely, a higher risk of Alzheimer's disease was causally associated with decreased volumes of the left hippocampal body and left whole hippocampus. These results were validated through other Mendelian randomization approaches and sensitivity analysis. Our findings uncover bidirectional causal relationships between Alzheimer's disease and hippocampal volumetric traits, suggesting not only the potential significance of these traits in predicting Alzheimer's disease but also the reciprocal influence of Alzheimer's disease on hippocampal volumes.

Causal relationship between 14 micronutrients and chronic periodontitis: a Mendelian randomization study

BACKGROUND

Chronic periodontitis is one of the most common inflammatory diseases worldwide. Micronutrients play a significant impact on health and periodontal disease progression. However, there is still a lack of conclusive studies confirming the causal association of micronutrients with chronic periodontitis.

MATERIALS AND METHODS

Genome-wide association study pooled data on chronic periodontitis were collected from the FinnGen consortium, and 14 micronutrients (calcium, copper, zinc, potassium, magnesium, selenium, iron, carotenoids, vitamin B6, B12, C, D, E and folate) were obtained from the OpenGWAS and UK Biobank Study. Instrumental variables were screened by strict criteria. Five Mendelian randomization (MR) methods were used. Finally, the robustness of the findings was verified by sensitivity analyses.

RESULTS

We found that vitamin D reduced the risk of chronic periodontitis (OR: 0.605, 95%CI: 0.398-0.921, P = 0.019). However, we had no evidence of a significant association between other micronutrients and chronic periodontitis. Multiple sensitivity analyses confirmed the robustness of the findings. A variety of sensitivity analysis methods confirmed the reliability of the results.

CONCLUSION

In this study, we found a potential causal relationship between vitamin D and chronic periodontitis by MR analysis, whereas we did not find an association between 13 other micronutrients and chronic periodontitis. This result might provide new ideas for the prevention and treatment of chronic periodontitis to some extent. However, despite the rigorous analytical methods used in this study, this finding needs to be interpreted with caution. Further randomized controlled studies might provide more in-depth references to the findings of this study.

Multiomic Mendelian Randomization Study Investigating the Impact of PCSK9 and HMGCR Inhibition on Type 2 Diabetes Across Five Populations

The prevalence of type 2 diabetes (T2D) varies among populations of different races/ethnicities. The influence of genetically proxied LDL cholesterol lowering through proprotein convertase subtilisin/kexin 9 (PCSK9) and HMG-CoA reductase (HMGCR) on T2D in non-European populations is not well established. A drug target Mendelian randomization approach was used to assess the effects of PCSK9 and HMGCR inhibition on T2D risk and glycemic traits in five populations: East Asian (EAS), South Asian (SAS), Hispanic (HISP), African (AFR), and Europe (EUR). Our study did not find relationships between genetically proxied PCSK9 inhibition and T2D risk in the EAS (odds ratio [OR] 1.02; 95% CI 0.95-1.10), SAS (1.05; 0.97-1.14), HISP (1.03; 0.94-1.12), or EUR population (1.04; 0.98-1.11). However, in the AFR population, primary analyses suggested an increased risk of T2D resulting from PCSK9 inhibition (OR 1.53; 95% CI 1.058-2.22; P = 0.024), although this was not supported in sensitivity analyses. Genetically proxied HMGCR inhibition was associated with an increased risk of T2D in SAS (OR 1.44; 95% CI 1.30-1.61; P = 9.8 × 10-12), EAS (1.36; 1.22-1.51; P = 4.2 × 10-10), and EUR populations (1.52; 1.21-1.90; P = 3.3 × 10-4). These results were consistent across various sensitivity analyses, including colocalization, indicating a robust finding. The findings indicate a neutral impact of long-term PCSK9 inhibition on T2D and glycemic markers in most non-EUR populations, with a potential increased risk in AFR cohorts. By contrast, HMGCR inhibition increased the risk of T2D in SAS, EAS, and EUR cohorts, underscoring the need to consider diversity in genetic research on metabolic diseases.

ARTICLE HIGHLIGHTS

Optimizing treatment of cardiovascular risk factors in cerebral small vessel disease using genetics

Cerebral small vessel disease (cSVD) causes lacunar stroke (LS), intracerebral haemorrhage, and is the most common pathology underlying vascular dementia. However, there are few trials examining whether treating conventional cardiovascular risk factors reduce stroke risk in cSVD, as opposed to stroke as a whole. We used Mendelian randomization techniques to investigate which risk factors are causally related to cSVD and to evaluate whether specific drugs may be beneficial in cSVD prevention. We identified genetic proxies for blood pressure traits, lipids, glycaemic markers, anthropometry measures, smoking, alcohol consumption, and physical activity from large-scale genome-wide association studies of European ancestry. We also selected genetic variants as proxies for drug target perturbation in hypertension, dyslipidaemia, hyperglycaemia, and obesity. Mendelian randomization was performed to assess their associations with LS from the GIGASTROKE Consortium (n = 6811) and in a sensitivity analysis in a cohort of patients with MRI-confirmed LS (n = 3306). We also investigated associations with three neuroimaging features of cSVD, namely, white matter hyperintensities (n = 55 291), fractional anisotropy (n = 36 460), and mean diffusivity (n = 36 012). Genetic predisposition to higher systolic and diastolic blood pressure was associated with LS and cSVD imaging markers. Genetically predicted liability to diabetes, obesity, smoking, higher triglyceride levels, and the ratio of triglycerides to high density lipoprotein (HDL) also showed detrimental associations with LS risk, while genetic predisposition to higher HDL concentrations and moderate-to-vigorous physical activity showed protective associations. Genetically proxied blood pressure-lowering through calcium channel blockers (CCBs) was associated with cSVD imaging markers, while genetically proxied HDL-raising through Cholesteryl Ester Transfer Protein (CETP) inhibitors, triglyceride-lowering through lipoprotein lipase (LPL), and weight-lowering through gastric inhibitory polypeptide receptor (GIPR) were associated with lower risk of LS. Our findings highlight the importance of some conventional cardiovascular risk factors, including blood pressure and BMI, in cSVD, but not other e.g. LDL. The findings further demonstrate the potential beneficial effects of CCBs on cSVD imaging markers and CETP inhibitors, LPL enhancement, and GIPR obesity-targeted drugs on LS. They provide useful information for initiating future clinical trials examining secondary prevention strategies in cSVD.

Small-cohort GWAS discovery with AI over massive functional genomics knowledge graph

Genome-wide association studies (GWASs) have identified tens of thousands of disease associated variants and provided critical insights into developing effective treatments. However, limited sample sizes have hindered the discovery of variants for uncommon and rare diseases. Here, we introduce KGWAS, a novel geometric deep learning method that leverages a massive functional knowledge graph across variants and genes to improve detection power in small-cohort GWASs significantly. KGWAS assesses the strength of a variant's association to disease based on the aggregate GWAS evidence across molecular elements interacting with the variant within the knowledge graph. Comprehensive simulations and replication experiments showed that, for small sample sizes ( N =1-10K), KGWAS identified up to 100% more statistically significant associations than state-of-the-art GWAS methods and achieved the same statistical power with up to 2.67× fewer samples. We applied KGWAS to 554 uncommon UK Biobank diseases ( N case <5K) and identified 183 more associations (46.9% improvement) than the original GWAS, where the gain further increases to 79.8% for 141 rare diseases (N case <300). The KGWAS-only discoveries are supported by abundant functional evidence, such as rs2155219 (on 11q13) associated with ulcerative colitis potentially via regulating LRRC32 expression in CD4+ regulatory T cells, and rs7312765 (on 12q12) associated with the rare disease myasthenia gravis potentially via regulating PPHLN1 expression in neuron-related cell types. Furthermore, KGWAS consistently improves downstream analyses such as identifying disease-specific network links for interpreting GWAS variants, identifying disease-associated genes, and identifying disease-relevant cell populations. Overall, KGWAS is a flexible and powerful AI model that integrates growing functional genomics data to discover novel variants, genes, cells, and networks, especially valuable for small cohort diseases.

Comparison of caffeine consumption behavior with plasma caffeine levels as exposure measures in drug-target mendelian randomization

Mendelian randomization is an epidemiologic technique that can explore the potential effect of perturbing a pharmacological target. Plasma caffeine levels can be used as a biomarker to measure the pharmacological effects of caffeine. Alternatively, this can be assessed using a behavioral proxy, such as average number of caffeinated drinks consumed per day. Either variable can be used as the exposure in a Mendelian randomization investigation, and to select which genetic variants to use as instrumental variables. Another possibility is to choose variants in gene regions with known biological relevance to caffeine level regulation. These choices affect the causal question that is being addressed by the analysis, and the validity of the analysis assumptions. Further, even when using the same genetic variants, the sign of Mendelian randomization estimates (positive or negative) can change depending on the choice of exposure. Some genetic variants that decrease caffeine metabolism associate with higher levels of plasma caffeine, but lower levels of caffeine consumption, as individuals with these variants require less caffeine consumption for the same physiological effect. We explore Mendelian randomization estimates for the effect of caffeine on body mass index, and discuss implications for variant and exposure choice in drug target Mendelian randomization investigations.

New drugs for treating dyslipidemias. From small molecules to small interfering RNAs

Despite the various therapeutic tools available, many patients do not achieve therapeutic goals, and cardiovascular diseases remain a significant cause of death in our setting. Furthermore, even in patients who manage to reduce their LDL-C levels to the recommended targets, cardiovascular events continue to occur. The therapeutic challenge and the persistent risk have led to active research into new drugs targeting novel therapeutic pathways in the field of lipoprotein metabolism disorders. The therapeutic approach involves new pharmacological mechanisms, ranging from small molecules and monoclonal antibodies to RNA interference, with inclisiran being the first drug approved for clinical use in the cardiovascular domain. In this review, we aim to provide a comprehensive overview of the new therapeutic targets and pharmacological mechanisms under development, as well as their potential clinical impact.

The management of adult and paediatric uveitis for rheumatologists

Uveitis encompasses multiple different conditions that are all characterized by intra-ocular inflammation. Uveitis occurs in the context of many different rheumatological conditions and carries a substantial risk to vision. Uveitis can develop both at the early stages of rheumatic diseases, sometimes even preceding other clinical features, and at later stages of disease. Uveitis can also occur as either a direct or an indirect complication of therapies used to treat patients with rheumatic disease. Conversely, patients with uveitis of non-rheumatic aetiology sometimes require immunosuppression, a treatment option that is not readily accessible to ophthalmologists. Thus, collaborative working between rheumatologists and ophthalmologists is critical for optimal management of patients with uveitis. This Review is written with rheumatologists in mind, to assist in the care of patients with uveitis. We collate and summarize the latest evidence and best practice in the diagnosis, management and prognostication of uveitis, including future trends and research priorities.

Nano-enabled pharmacogenomics: revolutionizing personalized drug therapy

The combination of pharmacogenomics and nanotechnology science of pharmacogenomics into a highly advanced single entity has given birth to personalized medicine known as nano-enabled pharmacogenomics. This review article covers all aspects starting from pharmacogenomics to gene editing tools, how these have evolved or are likely to be evolved for pharmacogenomic application, and how these can be delivered using nanoparticle delivery systems. In this prior work, we explore the evolution of pharmacogenomics over the years, as well as new achievements in the field of genomic sciences, the challenges in drug creation, and application of the strategy of personalized medicine. Particular attention is paid to how nanotechnology helps avoid the problems that accompanied the development of pharmacogenomics earlier, for example, the question of drug resistance and targeted delivery. We also review the latest developments in nano-enabled pharmacogenomics, such as the coupling with other nanobio-technologies, artificial intelligence, and machine learning in pharmacogenomics, and the ethical and regulatory aspects of these developing technologies. The possible uses of nanotechnology in improving the chances of pated and treating drug-resistant cancers are exemplified by case studies together with the current clinical uses of nanotechnology. In the last section, we discuss the future trends and research prospects in this dynamically growing area, stressing the importance of further advancements and collaborations which will advance the nano-enabled pharmacogenomics to their maximum potential.

Application of proteomics for novel drug discovery and risk prediction optimisation in stroke and myocardial infarction: a review of in-human studies

The use of proteomics in human studies investigating stroke and myocardial infarction (MI) has been increasing, prompting a review of the literature. This revealed proteinaceous biomarkers of stroke from thrombi, brain tissue, cells, and particles, some of which cross the blood-brain barrier (BBB). Several proteins were also implicated in coronary artery disease (CAD), which often underlies MI, cholesterol transportation, and inflammation. Furthermore, the platelet proteome revealed itself as a potential therapeutic target, along with differentially expressed proteins associated with MI progression. Moreover, proteomic data enhanced the performance of conventional risk scores and causal protein discovery has improved interventions and drug development for patients with MI and other conditions. These findings suggest that proteomics holds much promise for future stroke and MI research.

Common pitfalls in drug target Mendelian randomization and how to avoid them

BACKGROUND

Drug target Mendelian randomization describes the use of genetic variants as instrumental variables for studying the effects of pharmacological agents. The paradigm can be used to inform on all aspects of drug development and has become increasingly popular over the last decade, particularly given the time- and cost-efficiency with which it can be performed even before commencing clinical studies.

MAIN BODY

In this review, we describe the recent emergence of drug target Mendelian randomization, its common pitfalls, how best to address them, as well as potential future directions. Throughout, we offer advice based on our experiences on how to approach these types of studies, which we hope will be useful for both practitioners and those translating the findings from such work.

CONCLUSIONS

Drug target Mendelian randomization is nuanced and requires a combination of biological, statistical, genetic, epidemiological, clinical, and pharmaceutical expertise to be utilized to its full potential. Unfortunately, these skillsets are relatively infrequently combined in any given study.

Extensive co-regulation of neighboring genes complicates the use of eQTLs in target gene prioritization

Identifying causal genes underlying genome-wide association studies (GWASs) is a fundamental problem in human genetics. Although colocalization with gene expression quantitative trait loci (eQTLs) is often used to prioritize GWAS target genes, systematic benchmarking has been limited due to unavailability of large ground truth datasets. Here, we re-analyzed plasma protein QTL data from 3,301 individuals of the INTERVAL cohort together with 131 eQTL Catalog datasets. Focusing on variants located within or close to the affected protein identified 793 proteins with at least one cis-pQTL where we could assume that the most likely causal gene was the gene coding for the protein. We then benchmarked the ability of cis-eQTLs to recover these causal genes by comparing three Bayesian colocalization methods (coloc.susie, coloc.abf, and CLPP) and five Mendelian randomization (MR) approaches (three varieties of inverse-variance weighted MR, MR-RAPS, and MRLocus). We found that assigning fine-mapped pQTLs to their closest protein coding genes outperformed all colocalization methods regarding both precision (71.9%) and recall (76.9%). Furthermore, the colocalization method with the highest recall (coloc.susie - 46.3%) also had the lowest precision (45.1%). Combining evidence from multiple conditionally distinct colocalizing QTLs with MR increased precision to 81%, but this was accompanied by a large reduction in recall to 7.1%. Furthermore, the choice of the MR method greatly affected performance, with the standard inverse-variance-weighted MR often producing many false positives. Our results highlight that linking GWAS variants to target genes remains challenging with eQTL evidence alone, and prioritizing novel targets requires triangulation of evidence from multiple sources.

Lipid-lowering drugs and risk of rapid renal function decline: a mendelian randomization study

BACKGROUND

Chronic kidney disease (CKD) patients face the risk of rapid kidney function decline leading to adverse outcomes like dialysis and mortality. Lipid metabolism might contribute to acute kidney function decline in CKD patients. Here, we utilized the Mendelian Randomization approach to investigate potential causal relationships between drug target-mediated lipid phenotypes and rapid renal function decline.

METHODS

In this study, we utilized two methodologies: summarized data-based Mendelian randomization (SMR) and inverse variance-weighted Mendelian randomization (IVW-MR), to approximate exposure to lipid-lowering drugs. This entailed leveraging expression quantitative trait loci (eQTL) for drug target genes and genetic variants proximal to drug target gene regions, which encode proteins associated with low-density lipoprotein (LDL) cholesterol, as identified in genome-wide association studies. The objective was to investigate causal associations with the progression of rapid kidney function decline.

RESULTS

The SMR analysis revealed a potential association between high expression of PCSK9 and rapid kidney function decline (OR = 1.11, 95% CI= [1.001-1.23]; p = 0.044). Similarly, IVW-MR analysis demonstrated a negative association between LDL cholesterol mediated by HMGCR and kidney function decline (OR = 0.74, 95% CI = 0.60-0.90; p = 0.003).

CONCLUSION

Genetically predicted inhibition of HMGCR is linked with the progression of kidney function decline, while genetically predicted PCSK9 inhibition is negatively associated with kidney function decline. Future research should incorporate clinical trials to validate the relevance of PCSK9 in preventing kidney function decline.

Utilizing genetics and proteomics to assess the role of antihypertensive drugs in human longevity and the underlying pathways: a Mendelian randomization study

BACKGROUND

Antihypertensive drugs are known to lower cardiovascular mortality, but the role of different types of antihypertensive drugs in lifespan has not been clarified. Moreover, the underlying mechanisms remain unclear.

METHODS AND RESULTS

To minimize confounding, we used Mendelian randomization to assess the role of different antihypertensive drug classes in longevity and examined the pathways via proteins. Genetic variants associated with systolic blood pressure (SBP) corresponding to drug-target genes were used as genetic instruments. The genetic associations with lifespan were obtained from a large genome-wide association study including 1 million European participants from UK Biobank and LifeGen. For significant antihypertensive drug classes, we performed sex-specific analysis, drug-target analysis, and colocalization. To examine the mediation pathways, we assessed the associations of 2291 plasma proteins with lifespan, and examined the associations of drug classes with the proteins affecting lifespan. After correcting for multiple testing, genetically proxied beta-blockers (BBs), calcium channel blockers (CCBs), and vasodilators were related to longer life years (BBs: 2.03, 95% CI 0.78-3.28 per 5 mmHg reduction in SBP, CCBs: 3.40, 95% CI 1.47-5.33, and vasodilators: 2.92, 95% CI 1.08-4.77). The beneficial effects of BBs and CCBs were more obvious in men. ADRB1, CACNA2D2, CACNB3, CPT1A, CPT2, and EDNRA genes were related to extended lifespan, with CPT2 further supported by colocalization evidence. Eighty-six proteins were related to lifespan, of which four proteins were affected by CCBs. CDH1 may mediate the association between CCBs and lifespan.

CONCLUSIONS

Beta-blockers, CCBs, and vasodilators may prolong lifespan, with potential sex differences for BBs and CCBs. The role of CCBs in lifespan is partly mediated by CDH1. Prioritizing the potential protein targets can provide new insights into healthy aging.

Drug-target Mendelian randomisation applied to metabolic dysfunction-associated steatotic liver disease: opportunities and challenges

Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as the most prevalent cause of chronic liver disease worldwide affecting over one-third of the adult population. Despite the recent evolution of new nomenclature and diagnostic criteria for MASLD, progress in drug development for this condition remains limited. This review highlights the potential of drug-target Mendelian randomisation (MR), a study design that leverages human genetics and genomics, for the discovery, repositioning and safety assessment of drug targets in MASLD. We summarised key aspects of designing and appraising a drug-target MR study, discussing its inherent assumptions and considerations for instrument selection. Furthermore, we presented real-world examples from studies in MASLD which focused on opportunities and challenges in identifying novel drug targets, repositing existing drug targets, informing adjunctive treatments and addressing issues in paediatric MASLD.

Exploration of protein and genetic targets causing atrioventricular block: mendelian-randomization analyses based on eQTL data and pQTL data

BACKGROUND

Atrioventricular block (AVB) is a heterogeneous group of arrhythmias. AVB can lead to sudden arrest of the heart and subsequent syncope or sudden cardiac death. Few scholars have investigated the underlying molecular mechanisms of AVB. Finding molecular markers can facilitate understanding of AVB and exploration of therapeutic targets.

METHODS

Two-sample Mendelian randomization (MR) analysis was undertaken with inverse variance weighted (IVW) model and Wald ratio as the primary approach. Reverse MR analysis was undertaken to identify the associated protein targets and gene targets. Expression quantitative trait loci (eQTL) data from the eQTLGen database and protein quantitative trait loci (pQTL) data from three previous large-scale proteomic studies on plasma were retrieved as exposure data. Genome-wide association study (GWAS) summary data (586 cases and 379,215 controls) for AVB were retrieved from the UK Biobank database. Colocalization analyses were undertaken to identify the effect of filtered markers on outcome data. Databases (DrugBank, Therapeutic Target, PubChem) were used to identify drugs that interacted with targets.

RESULTS

We discovered that 692 genes and 42 proteins showed a significant correlation with the AVB phenotype. Proteins (cadherin-5, sTie-1, Notch 1) and genes (DNAJC30, ABO) were putative molecules to AVB. Drug-interaction analyses revealed anticancer drugs such as tyrosine-kinase inhibitors and TIMD3 inhibitors could cause AVB. Other substances (e.g. toxins, neurological drugs) could also cause AVB.

CONCLUSIONS

We identified the proteins (cadherin-5, sTie-1, Notch 1) and gene (DNAJC30, ABO) targets associated with AVB pathogenesis. Anticancer drugs (tyrosine-kinase inhibitors, TIMD3 inhibitors), toxins, or neurological drugs could also cause AVB.

GLP1R Gene Expression and Kidney Disease Progression

Importance

Glucagon-like peptide 1 receptor agonists (GLP-1RAs) may have nephroprotective properties beyond those related to weight loss and glycemic control.

Objective

To investigate the association of genetically proxied GLP-1RAs with kidney disease progression.

Design, Setting, and Participants

This genetic association study assembled a national retrospective cohort of veterans aged 18 years or older from the US Department of Veterans Affairs Million Veteran Program between January 10, 2011, and December 31, 2021. Data were analyzed from November 2023 to February 2024.

Exposures

Genetic risk score for systemic GLP1R gene expression that was calculated for each study participant based on genetic variants associated with GLP1R mRNA levels across all tissue samples within the Genotype-Tissue Expression project.

Main Outcomes and Measures

The primary composite outcome was incident end-stage kidney disease or a 40% decline in estimated glomerular filtration rate. Cox proportional hazards regression survival analysis assessed the association between genetically proxied GLP-1RAs and kidney disease progression.

Results

Among 353 153 individuals (92.5% men), median age was 66 years (IQR, 58.0-72.0 years) and median follow-up was 5.1 years (IQR, 3.1-7.2 years). Overall, 25.7% had diabetes, and 45.0% had obesity. A total of 4.6% experienced kidney disease progression. Overall, higher genetic GLP1R gene expression was associated with a lower risk of kidney disease progression in the unadjusted model (hazard ratio [HR], 0.96; 95% CI, 0.92-0.99; P = .02) and in the fully adjusted model accounting for baseline patient characteristics, body mass index, and the presence or absence of diabetes (HR, 0.96; 95% CI, 0.92-1.00; P = .04). The results were similar in sensitivity analyses stratified by diabetes or obesity status.

Conclusions and Relevance

In this genetic association study, higher GLP1R gene expression was associated with a small reduction in risk of kidney disease progression. These findings support pleiotropic nephroprotective mechanisms of GLP-1RAs independent of their effects on body weight and glycemic control.

Plasma proteomics reveals the potential causal impact of extracellular matrix proteins on abdominal aortic aneurysm

Background

Abdominal aortic aneurysm (AAA) is a common and life-threatening vascular disease. Genetic studies have identified numerous associated loci, many potentially encoding plasma proteins. However, the causal effects of plasma proteins on AAA have not been thoroughly studied. We used genetic causal inference approaches to identify plasma proteins that have a potential causal impact on AAA.

Methods

Causal inference was performed using two-sample Mendelian randomization (MR). For AAA, we utilized recently published summary statistics from a multi-population genome-wide association (GWAS) meta-analysis including 39,221 individuals with, and 1,086,107 individuals without AAA from 14 cohorts. We used protein quantitative trait loci (pQTLs) identified in two large-scale plasma-proteomics studies (deCODE and UKB-PPP) to generate genetic instruments. We tested 2,783 plasma proteins for possible causal effects on AAA using two-sample MR with inverse variance weighting and common sensitivity analyses to evaluate the MR assumptions. Bayesian colocalization and gene ontology (GO) enrichment analyses provided additional insights.

Results

MR identified 90 plasma proteins associated with AAA at FDR<0.05, with 25 supported by colocalization analysis. Among those supported by both MR and colocalization were previously experimentally validated proteins such as PCSK9 (OR 1.3; 95%CI 1.2-1.4; P<1e-10), LTBP4 (OR 3.4; 95%CI 2.6-4.6; P<1e-10) and COL6A3 (OR 0.6; 95%CI 0.5-0.7; P<1e-6). GO analysis revealed enrichment of proteins found in extracellular matrix (ECM, OR 7.8; P<1e-4), some with maximal mRNA levels in aortic tissue. Bi-directional MR suggested plasma level changes were not caused by liability to AAA itself. We then investigated whether variants responsible for expression changes in the aorta also influenced plasma levels and AAA risk. Colocalization analysis showed that an aortic expression quantitative trait locus (eQTL) for COL6A3, and a splicing quantitative trait locus (sQTL) for LTBP4 colocalized with their respective plasma pQTLs and AAA signals (posterior probabilities 0.84 and 0.89, respectively).

Conclusions

Our results highlight proteins and pathways with potential causal effects on AAA, providing a foundation for future functional experiments. These findings suggest a possible causal pathway whereby genetic variation affecting ECM proteins expressed in the aortic wall cause their levels to change in blood plasma, influencing development of AAA.

Impact of SGLT2 inhibitors on lower limb complications: a mendelian randomization perspective

Background

While Sodium-glucose cotransporter 2 (SGLT2) inhibitors are effective in managing diabetes and reducing cardiovascular risk, concerns about their association with lower limb complications, including, osteomyelitis, ulcers, and peripheral artery disease (PAD), persist. This study employs Mendelian Randomization (MR) to assess the causal relationship between SGLT2 inhibitors and these lower limb safety outcomes.

Methods

A two-sample drug-target MR approach was used, complemented by a one-sample MR and genetic association analysis. Six SNPs were selected as instrumental variables to proxy the effect of SGLT2 inhibition. Primary outcomes were major limb safety outcomes, including osteomyelitis, lower limb ulcers, PAD, and cellulitis. The primary analytical method was the generalized inverse variance-weighted (IVW) approach, along with several sensitivity analyses.

Results

The MR analysis indicated no significant causal association between genetically proxied SGLT2 inhibition and most of the studied lower limb safety outcomes. However, a significant association with PAD was observed, necessitating careful interpretation due to discrepancies between IVW and MR-Egger results. Sensitivity analyses supported these findings, showing little evidence of heterogeneity or directional pleiotropy.

Conclusion

This study suggests that SGLT2 inhibitors may not be significantly associated with an increased risk of most lower limb safety outcomes, including osteomyelitis, lower limb ulcers, and cellulitis, in patients with type 2 diabetes. However, the complex relationship with PAD highlights the need for further research. These findings contribute to the understanding of the safety profile of SGLT2 inhibitors, supporting their continued use in diabetes management while underlining the importance of continuous safety monitoring.

Addressing Technical Pitfalls in Pursuit of Molecular Factors That Mediate Immunoglobulin Gene Regulation

The expressed Ab repertoire is a critical determinant of immune-related phenotypes. Ab-encoding transcripts are distinct from other expressed genes because they are transcribed from somatically rearranged gene segments. Human Abs are composed of two identical H and L chain polypeptides derived from genes in IGH locus and one of two L chain loci. The combinatorial diversity that results from Ab gene rearrangement and the pairing of different H and L chains contributes to the immense diversity of the baseline Ab repertoire. During rearrangement, Ab gene selection is mediated by factors that influence chromatin architecture, promoter/enhancer activity, and V(D)J recombination. Interindividual variation in the composition of the Ab repertoire associates with germline variation in IGH, implicating polymorphism in Ab gene regulation. Determining how IGH variants directly mediate gene regulation will require integration of these variants with other functional genomic datasets. In this study, we argue that standard approaches using short reads have limited utility for characterizing regulatory regions in IGH at haplotype resolution. Using simulated and chromatin immunoprecipitation sequencing reads, we define features of IGH that limit use of short reads and a single reference genome, namely 1) the highly duplicated nature of the DNA sequence in IGH and 2) structural polymorphisms that are frequent in the population. We demonstrate that personalized diploid references enhance performance of short-read data for characterizing mappable portions of the locus, while also showing that long-read profiling tools will ultimately be needed to fully resolve functional impacts of IGH germline variation on expressed Ab repertoires.

Causal association between 731 immunocyte phenotypes and liver cirrhosis: A bidirectional two-sample mendelian randomization analysis

BACKGROUND

Liver cirrhosis is a progressive hepatic disease whose immunological basis has attracted increasing attention. However, it remains unclear whether a concrete causal association exists between immunocyte phenotypes and liver cirrhosis.

AIM

To explore the concrete causal relationships between immunocyte phenotypes and liver cirrhosis through a mendelian randomization (MR) study.

METHODS

Data on 731 immunocyte phenotypes were obtained from genome-wide association studies. Liver cirrhosis data were derived from the Finn Gen dataset, which included 214403 individuals of European ancestry. We used inverse variable weighting as the primary analysis method to assess the causal relationship. Sensitivity analyses were conducted to evaluate heterogeneity and horizontal pleiotropy.

RESULTS

The MR analysis demonstrated that 11 immune cell phenotypes have a positive association with liver cirrhosis [P < 0.05, odds ratio (OR) > 1] and that 9 immunocyte phenotypes were negatively correlated with liver cirrhosis (P < 0.05, OR < 1). Liver cirrhosis was positively linked to 9 immune cell phenotypes (P < 0.05, OR > 1) and negatively linked to 10 immune cell phenotypes (P < 0.05; OR < 1). None of these associations showed heterogeneity or horizontally pleiotropy (P > 0.05).

CONCLUSION

This bidirectional two-sample MR study demonstrated a concrete causal association between immunocyte phenotypes and liver cirrhosis. These findings offer new directions for the treatment of liver cirrhosis.

Effects of ACLY Inhibition on Body Weight Distribution: A Drug Target Mendelian Randomization Study

Background: Adenosine triphosphate-citrate lyase (ACLY) inhibition has proven clinically efficacious for low-density lipoprotein cholesterol (LDL-c) lowering and cardiovascular disease (CVD) risk reduction. Clinical and genetic evidence suggests that some LDL-c lowering strategies, such as 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibition with statin therapy increase body weight and the risk of developing type 2 diabetes mellitus (T2DM). However, whether ACLY inhibition affects metabolic risk factors is currently unknown. We aimed to investigate the effects of ACLY inhibition on glycaemic and anthropometric traits using Mendelian randomization (MR). Methods: As genetic instruments for ACLY inhibition, we selected weakly correlated single-nucleotide polymorphisms at the ACLY gene associated with lower ACLY gene expression in the eQTLGen study (N = 31,684) and lower LDL-c levels in the Global Lipid Genetic Consortium study (N = 1.65 million). Two-sample Mendelian randomization was employed to investigate the effects of ACLY inhibition on T2DM risk, and glycaemic and anthropometric traits using summary data from large consortia, with sample sizes ranging from 151,013 to 806,834 individuals. Findings for genetically predicted ACLY inhibition were compared to those obtained for genetically predicted HMGCR inhibition using the same instrument selection strategy and outcome data. Results: Primary MR analyses showed that genetically predicted ACLY inhibition was associated with lower waist-to-hip ratio (β per 1 standard deviation lower LDL-c: -1.17; 95% confidence interval (CI): -1.61 to -0.73; p < 0.001) but not with risk of T2DM (odds ratio (OR) per standard deviation lower LDL-c: 0.74, 95% CI = 0.25 to 2.19, p = 0.59). In contrast, genetically predicted HMGCR inhibition was associated with higher waist-to-hip ratio (β = 0.15; 95%CI = 0.04 to 0.26; p = 0.008) and T2DM risk (OR = 1.73, 95% CI = 1.27 to 2.36, p < 0.001). The MR analyses considering secondary outcomes showed that genetically predicted ACLY inhibition was associated with a lower waist-to-hip ratio adjusted for body mass index (BMI) (β = -1.41; 95%CI = -1.81 to -1.02; p < 0.001). In contrast, genetically predicted HMGCR inhibition was associated with higher HbA1c (β = 0.19; 95%CI = 0.23 to 0.49; p < 0.001) and BMI (β = 0.36; 95%CI = 0.23 to 0.49; p < 0.001). Conclusions: Human genetic evidence supports the metabolically favourable effects of ACLY inhibition on body weight distribution, in contrast to HMGCR inhibition. These findings should be used to guide and prioritize ongoing clinical development efforts.

Benchmarking Mendelian randomization methods for causal inference using genome-wide association study summary statistics

Mendelian randomization (MR), which utilizes genetic variants as instrumental variables (IVs), has gained popularity as a method for causal inference between phenotypes using genetic data. While efforts have been made to relax IV assumptions and develop new methods for causal inference in the presence of invalid IVs due to confounding, the reliability of MR methods in real-world applications remains uncertain. Instead of using simulated datasets, we conducted a benchmark study evaluating 16 two-sample summary-level MR methods using real-world genetic datasets to provide guidelines for the best practices. Our study focused on the following crucial aspects: type I error control in the presence of various confounding scenarios (e.g., population stratification, pleiotropy, and family-level confounders like assortative mating), the accuracy of causal effect estimates, replicability, and power. By comprehensively evaluating the performance of compared methods over one thousand exposure-outcome trait pairs, our study not only provides valuable insights into the performance and limitations of the compared methods but also offers practical guidance for researchers to choose appropriate MR methods for causal inference.

Causal role of immune cells in uveitis: a Mendelian randomization study

Background

Uveitis refers to a group inflammation affecting the uvea, retina, retinal blood vessels as well as vitreous body, which is one of the common causes of blindness. There is growing evidence linking different types of immune cells to uveitis, although it remains uncertain if these associations imply causal relationships. Recent advancements in high-density genetic markers like SNPs or CNVs for genotyping, along with the progress in genome-wide association studies (GWAS) technologies, have improved our understanding of the immunological mechanisms involved in ocular diseases. Therefore, our objective was to investigate the potential causal link between immune cells and uveitis using a Mendelian randomization study.

Methods

The exposure and outcome GWAS data for this study were sourced from an open-access database (https://gwas.mrcieu.ac.uk/). Two-sample MR analysis was utilized to evaluate the causal relationship between 731 immune cell features and uveitis. Various MR methods were employed to reduce bias and obtain dependable estimates of the causal link between the immune cell variables and the outcomes. Instrumental variable selection criteria were carefully chosen to enhance the accuracy and efficacy of the causal relationship between different immune cell types and the risk of uveitis.

Results

Using two-sample MR, IVW modeling showed that GAD had significant effect on immunophenotypes. CD3 levels on CD45RA- CD4+ T cells (OR = 1.087, 95%CI = 1.029 ~ 1.147, p = 0.003) and CD3 levels on CM CD4+ T cells (OR = 1.086, 95%CI = 1.033 ~ 1.141, p = 0.001) were found to be elevated in cases of uveitis. HLA DR levels in CD14- CD16+ monocyte cells (OR = 0.735, 95% CI = 0.635 ~ 0.850, p < 0.001) and HLA DR levels in NK cells (OR = 0.910, 95% CI = 0.851 ~ 0.972, p = 0.005) were observed to be reduced in individuals with uveitis. Furthermore, Two cells were identified to be significantly associated with uveitis risk: HLA DR on in NK cells (OR = 0.938, 95%CI = 0.899 ~ 0.979, p = 0.003), HLA DR on CD14- CD16+ monocytes (OR = 0.924, 95%CI = 0.878 ~ 0.972, p = 0.002).

Conclusion

This study highlights the intricate relationship between immune cells and generalized anxiety disorder using genetic methods, offering valuable insights for future clinical investigations.

Genetic and Epigenetic Landscape for Drug Development in Polycystic Ovary Syndrome

The treatment of polycystic ovary syndrome (PCOS) faces challenges as all known treatments are merely symptomatic. The US Food and Drug Administration has not approved any drug specifically for treating PCOS. As the significance of genetics and epigenetics rises in drug development, their pivotal insights have greatly enhanced the efficacy and success of drug target discovery and validation, offering promise for guiding the advancement of PCOS treatments. In this context, we outline the genetic and epigenetic advancement in PCOS, which provide novel insights into the pathogenesis of this complex disease. We also delve into the prospective method for harnessing genetic and epigenetic strategies to identify potential drug targets and ensure target safety. Additionally, we shed light on the preliminary evidence and distinctive challenges associated with gene and epigenetic therapies in the context of PCOS.

GWAS advancements to investigate disease associations and biological mechanisms

Genome-wide association studies (GWAS) have been instrumental in elucidating the genetic architecture of various traits and diseases. Despite the success of GWAS, inherent limitations such as identifying rare and ultra-rare variants, the potential for spurious associations, and in pinpointing causative agents can undermine diagnostic capabilities. This review provides an overview of GWAS and highlights recent advances in genetics that employ a range of methodologies, including Whole Genome Sequencing (WGS), Mendelian Randomization (MR), the Pangenome's high-quality T2T-CHM13 panel, and the Human BioMolecular Atlas Program (HuBMAP), as potential enablers of current and future GWAS research. State of the literature demonstrate the capabilities of these techniques in enhancing the statistical power of GWAS. WGS, with its comprehensive approach, captures the entire genome, surpassing the capabilities of the traditional GWAS technique focused on predefined Single Nucleotide Polymorphism (SNP) sites. The Pangenome's T2T-CHM13 panel, with its holistic approach, aids in the analysis of regions with high sequence identity, such as segmental duplications (SDs). Mendelian Randomization has advanced causative inference, improving clinical diagnostics and facilitating definitive conclusions. Furthermore, spatial biology techniques like HuBMAP, enable 3D molecular mapping of tissues at single-cell resolution, offering insights into pathology of complex traits. This study aims to elucidate and advocate for the increased application of these technologies, highlighting their potential to shape the future of GWAS research.

Identification of lipid-modifying drug targets for autoimmune diseases: insights from drug target mendelian randomization

BACKGROUNDS

A growing body of evidence has highlighted the interactions of lipids metabolism and immune regulation. Nevertheless, there is still a lack of evidence regarding the causality between lipids and autoimmune diseases (ADs), as well as their possibility as drug targets for ADs.

OBJECTIVES

This study was conducted to comprehensively understand the casual associations between lipid traits and ADs, and evaluate the therapeutic possibility of lipid-lowering drug targets on ADs.

METHODS

Genetic variants for lipid traits and variants encoding targets of various lipid-lowering drugs were derived from Global Lipid Genetics Consortium (GLGC) and verified in Drug Bank. Summary data of ADs were obtained from MRC Integrative Epidemiology Unit (MER-IEU) database and FinnGen consortium, respectively. The causal inferences between lipid traits/genetic agents of lipid-lowering targets and ADs were evaluated by Mendelian randomization (MR), summary data-based MR (SMR), and multivariable MR (MVMR) analyses. Enrichment analysis and protein interaction network were employed to reveal the functional characteristics and biological relevance of potential therapeutic lipid-lowering targets.

RESULTS

There was no evidence of causal effects regarding 5 lipid traits and 9 lipid-lowering drug targets on ADs. Genetically proxied 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) inhibition was associated with a reduced risk of rheumatoid arthritis (RA) in both discovery (OR [odds ratio] = 0.45, 95%CI: 0.32, 0.63, P = 6.79 × 10- 06) and replicate datasets (OR = 0.37, 95%CI: 0.23, 0.61, P = 7.81 × 10- 05). SMR analyses supported that genetically proxied HMGCR inhibition had causal effects on RA in whole blood (OR = 0.48, 95%CI: 0.29, 0.82, P = 6.86 × 10- 03) and skeletal muscle sites (OR = 0.75, 95%CI: 0.56, 0.99, P = 4.48 × 10- 02). After controlling for blood pressure, body mass index (BMI), smoking and drinking alchohol, HMGCR suppression showed a direct causal effect on a lower risk of RA (OR = 0.33, 95%CI: 0.40, 0.96, P = 0.042).

CONCLUSIONS

Our study reveals causal links of genetically proxied HMGCR inhibition (lipid-lowering drug targets) and HMGCR expression inhibition with a decreased risk of RA, suggesting that HMGCR may serve as candidate drug targets for the treatment and prevention of RA.

Unraveling the role of plasma proteins in dementia: insights from two cohort studies in the UK, with causal evidence from Mendelian randomization

Population-based proteomics offer a groundbreaking avenue to predict dementia onset. This study employed a proteome-wide, data-driven approach to investigate protein-dementia associations in 229 incident all-cause dementia (ACD) among 3,249 participants from the English Longitudinal Study of Ageing (ELSA) over a median 9.8-year follow-up, then validated in 1,506 incident ACD among 52,745 individuals from the UK Biobank (UKB) over median 13.7 years. NEFL and RPS6KB1 were robustly associated with incident ACD; MMP12 was associated with vascular dementia in ELSA. Additional markers EDA2R and KIM1 (HAVCR1) were identified from sensitivity analyses. Combining NEFL and RPS6KB1 with other factors yielded high predictive accuracy (area under the curve (AUC)=0.871) for incident ACD. Replication in the UKB confirmed associations between identified proteins with various dementia subtypes. Results from reverse Mendelian Randomization also supported the role of several proteins as early dementia biomarkers. These findings underscore proteomics' potential in identifying novel risk screening targets for dementia.

Robust use of phenotypic heterogeneity at drug target genes for mechanistic insights: Application of cis-multivariable Mendelian randomization to GLP1R gene region

Phenotypic heterogeneity at genomic loci encoding drug targets can be exploited by multivariable Mendelian randomization to provide insight into the pathways by which pharmacological interventions may affect disease risk. However, statistical inference in such investigations may be poor if overdispersion heterogeneity in measured genetic associations is unaccounted for. In this work, we first develop conditional F statistics for dimension-reduced genetic associations that enable more accurate measurement of phenotypic heterogeneity. We then develop a novel extension for two-sample multivariable Mendelian randomization that accounts for overdispersion heterogeneity in dimension-reduced genetic associations. Our empirical focus is to use genetic variants in the GLP1R gene region to understand the mechanism by which GLP1R agonism affects coronary artery disease (CAD) risk. Colocalization analyses indicate that distinct variants in the GLP1R gene region are associated with body mass index and type 2 diabetes (T2D). Multivariable Mendelian randomization analyses that were corrected for overdispersion heterogeneity suggest that bodyweight lowering rather than T2D liability lowering effects of GLP1R agonism are more likely contributing to reduced CAD risk. Tissue-specific analyses prioritized brain tissue as the most likely to be relevant for CAD risk, of the tissues considered. We hope the multivariable Mendelian randomization approach illustrated here is widely applicable to better understand mechanisms linking drug targets to diseases outcomes, and hence to guide drug development efforts.

Allergic Diseases and Chronic Adenotonsillar Diseases: A Mendelian Randomization Study

OBJECTIVE

The existing epidemiological evidence regarding the intricate relationship between allergic diseases and chronic adenotonsillar diseases (CATD) remains inconclusive. Herein, the objective of our study is to explore the causal association using Mendelian randomization (MR).

METHODS

Employing data from large genome-wide association studies, a comprehensive two-sample bidirectional MR study was conducted. The studied traits encompassed allergic rhinitis (cases n = 9707, controls n = 331173), allergic asthma (cases n = 8525, controls n = 193857), allergic conjunctivitis (cases n = 18321, controls n = 324178), atopic dermatitis (cases n = 11964, controls n = 306909), and CATD (cases n = 38983, controls n = 258553). All the patients were of European descent and participants in cohort studies. The primary analysis was executed using inverse-variance-weighted MR. Furthermore, six additional MR methods (MR-Egger, weighted median, simple mode, weighted mode, MR pleiotropy residual sum and outlier, MR robust adjusted profile score) were employed to ensure the reliability and detect potential horizontal pleiotropy within the results. The estimates obtained from the MR analysis were factored into the overall effect calculation.

RESULTS

Genetically anticipated outcomes demonstrated a significant association between CATD risk and allergic rhinitis (OR = 1.141, p = 6.30E-06), allergic asthma (OR = 1.115, p = 8.31E-05), allergic conjunctivitis (OR = 1.197, p = 8.69E-07), and a suggestive association with atopic dermatitis (OR = 1.053, p = 0.040). However, no substantial correlation was observed in the reverse direction.

CONCLUSIONS

Findings of our study provide evidence supporting a causal role of allergic diseases in the development of CATD, whereas the converse relationship does not appear to hold true.

LEVEL OF EVIDENCE

3 Laryngoscope, 134:2653-2658, 2024.

Refining the impact of genetic evidence on clinical success

The cost of drug discovery and development is driven primarily by failure1, with only about 10% of clinical programmes eventually receiving approval2-4. We previously estimated that human genetic evidence doubles the success rate from clinical development to approval5. In this study we leverage the growth in genetic evidence over the past decade to better understand the characteristics that distinguish clinical success and failure. We estimate the probability of success for drug mechanisms with genetic support is 2.6 times greater than those without. This relative success varies among therapy areas and development phases, and improves with increasing confidence in the causal gene, but is largely unaffected by genetic effect size, minor allele frequency or year of discovery. These results indicate we are far from reaching peak genetic insights to aid the discovery of targets for more effective drugs.

Evaluation of Plasma Biomarkers for Causal Association With Peripheral Artery Disease

BACKGROUND

Hundreds of biomarkers for peripheral artery disease (PAD) have been reported in the literature; however, the observational nature of these studies limits causal inference due to the potential of reverse causality and residual confounding. We sought to evaluate the potential causal impact of putative PAD biomarkers identified in human observational studies through genetic causal inference methods.

METHODS

Putative circulating PAD biomarkers were identified from human observational studies through a comprehensive literature search based on terms related to PAD using PubMed, Cochrane, and Embase. Genetic instruments were generated from publicly available genome-wide association studies of circulating biomarkers. Two-sample Mendelian randomization was used to test the association of genetically determined biomarker levels with PAD using summary statistics from a genome-wide association study of 31 307 individuals with and 211 753 individuals without PAD in the Veterans Affairs Million Veteran Program and replicated in data from FinnGen comprised of 11 924 individuals with and 288 638 individuals without PAD.

RESULTS

We identified 204 unique circulating biomarkers for PAD from the observational literature, of which 173 were genetically instrumented using genome-wide association study results. After accounting for multiple testing (false discovery rate, <0.05), 10 of 173 (5.8%) biomarkers had significant associations with PAD. These 10 biomarkers represented categories including plasma lipoprotein regulation, lipid homeostasis, and protein-lipid complex remodeling. Observational literature highlighted different pathways including inflammatory response, negative regulation of multicellular organismal processes, and regulation of response to external stimuli.

CONCLUSIONS

Integrating human observational studies and genetic causal inference highlights several key pathways in PAD pathophysiology. This work demonstrates that a substantial portion of biomarkers identified in observational studies are not well supported by human genetic evidence and emphasizes the importance of triangulating evidence to understand PAD pathophysiology. Although the identified biomarkers offer insights into atherosclerotic development in the lower limb, their specificity to PAD compared with more widespread atherosclerosis requires further study.