Proteome-wide Mendelian randomization implicates nephronectin as an actionable mediator of the effect of obesity on COVID-19 severity

Genetic insights into the association between serum cytokines and frozen shoulder risk: A bidirectional mendelian randomization study

BACKGROUND

Although existing studies have indicated a connection between chronic low-grade inflammation and the onset of frozen shoulder (FS), the precise causal relationship between distinct circulating inflammatory factors and FS has yet to be thoroughly evaluated. In this study, we employed a bidirectional two-sample Mendelian randomization (MR) analysis to investigate the potential causal relationship between systemic cytokines and FS.

METHODS

A genome-wide association dataset comprising 41 serum cytokines from 8,293 individuals of Finnish descent was utilized, along with FS data from the UK Biobank included 10,104 FS cases and 451,099 controls. The primary MR method was the inverse variance weighted approach, and four additional MR techniques (MR-Egger, weighted median, simple mode, and weighted mode) were also employed to support and validate the findings. Heterogeneity and horizontal pleiotropy assessments were assessed using Cochrane's Q and MR-Egger intercept tests. Moreover, a series of sensitivity analyses were conducted to strengthen the accuracy and credibility of these findings.

RESULTS

Based on the IVW method, genetically predicted increasing levels of growth regulated oncogene alpha (GROa) (OR=1.08, 95 % CI 1.02-1.13, P=0.005), interferon gamma-induced protein 10 (IP-10) (OR=1.09, 95 % CI 1.02-1.17, P=0.010), regulated on activation, C-C Motif Chemokine Ligand 5 (CCL5) (OR=1.11, 95 % CI 1.03-1.20, P=0.007) were suggestively associated with an increased risk of FS. Reverse MR analysis revealed no significant causal effect of FS on the 41 systemic inflammatory factors. No heterogeneity or horizontal pleiotropy was observed in our analysis.

CONCLUSION

This study established a causal association between 41 systemic inflammatory factors and FS, indicating that elevated levels of GROa, IP-10 and CCL5 were associated with a higher risk of FS. Further research is warranted to explore the potential of these biomarkers as early predictors and therapeutic targets for FS.

Mendelian randomization demonstrates a causal link between peripheral circulating acylcarnitines and intracranial aneurysms

Intracranial aneurysm (IA) is the most prevalent type of cerebral vascular disease causing life-threatening subarachnoid hemorrhages (SAH). A long-term vascular structure remodeling is considered as the main pathophysiological feature of IAs. However, the causal factors triggering the pathophysiological process are not clear. Recently, the abnormalities of peripheral circulating proteins and metabolites have been found in IAs patients and associated with the ruptures. We comprehensively investigated the potential causal relationship between blood metabolites and proteins and IAs using the mendelian randomization (MR) analysis. We applied two-sample MR to explore the potential causal association between peripheral circulating metabolites (191 blood metabolites) and proteins (1398 proteins) and IAs using data from the FinnGen study and the GWAS datasets published by Bakker et al. We identified palmitoylcarnitine, stearoylcarnitine and 2-tetradecenoylcarnitine as causal contributors of IAs and ruptures. Further two-step mediation MR analysis suggested that hypertension as one of the contributors of IAs and ruptures mediated the causal relationship between palmitoylcarnitine, stearoylcarnitine and 2-tetradecenoylcarnitine and IAs. Together, our study demonstrates that blood metabolic palmitoylcarnitine, stearoylcarnitine and 2-tetradecenoylcarnitine are causally linked to the formation and rupture of IAs. Hypertension partially mediates the causal effects.

Genetics of chronic respiratory disease

Chronic respiratory diseases, such as chronic obstructive pulmonary disease (COPD), asthma and interstitial lung diseases are frequently occurring disorders with a polygenic basis that account for a large global burden of morbidity and mortality. Recent large-scale genetic epidemiology studies have identified associations between genetic variation and individual respiratory diseases and linked specific genetic variants to quantitative traits related to lung function. These associations have improved our understanding of the genetic basis and mechanisms underlying common lung diseases. Moreover, examining the overlap between genetic associations of different respiratory conditions, along with evidence for gene-environment interactions, has yielded additional biological insights into affected molecular pathways. This genetic information could inform the assessment of respiratory disease risk and contribute to stratified treatment approaches.

Therapeutic targets for age-related macular degeneration: proteome-wide Mendelian randomization and colocalization analyses

Background

Currently, effective therapeutic drugs for age-related macular degeneration (AMD) are urgently needed, and it is crucial to explore new treatment targets. The proteome is indispensable for exploring disease targets, so we conducted a Mendelian randomization (MR) of the proteome to identify new targets for AMD and its related subtypes.

Methods

The plasma protein level data used in this study were obtained from two large-scale studies of protein quantitative trait loci (pQTL), comprising 35,559 and 54,219 samples, respectively. The expression quantitative trait loci (eQTL) data were sourced from eQTLGen and GTEx Version 8. The discovery set for AMD data and subtypes was derived from the FinnGen study, consisting of 9,721 AMD cases and 381,339 controls, 5,239 wet AMD cases and 273,920 controls, and 6,651 dry AMD cases and 272,504 controls. The replication set for AMD data was obtained from the study by Winkler TW et al., comprising 14,034 cases and 91,234 controls. Summary Mendelian randomization (SMR) analysis was employed to assess the association between QTL data and AMD and its subtypes, while colocalization analysis was performed to determine whether they share causal variants. Additionally, chemical exploration and molecular docking were utilized to validate potential drugs targeting the identified proteins.

Results

SMR and colocalization analysis jointly identified risk-associated proteins for AMD and its subtypes, including 5 proteins (WARS1, BRD2, IL20RB, TGFB1, TNFRSF10A) associated with AMD, 2 proteins (WARS1, IL20RB) associated with Dry-AMD, and 9 proteins (COL10A1, WARS1, VTN, SDF2, LBP, CD226, TGFB1, TNFRSF10A, CSF2) associated with Wet-AMD. The results revealed potential therapeutic chemicals, and molecular docking indicated a good binding between the chemicals and protein structures.

Conclusion

Proteome-wide MR have identified risk-associated proteins for AMD and its subtypes, suggesting that these proteins may serve as potential therapeutic targets worthy of further clinical investigation.

Shared genetic aetiology of respiratory diseases: a genome-wide multitraits association analysis

OBJECTIVE

This study aims to explore the common genetic basis between respiratory diseases and to identify shared molecular and biological mechanisms.

METHODS

This genome-wide pleiotropic association study uses multiple statistical methods to systematically analyse the shared genetic basis between five respiratory diseases (asthma, chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, lung cancer and snoring) using the largest publicly available genome wide association studies summary statistics. The missions of this study are to evaluate global and local genetic correlations, to identify pleiotropic loci, to elucidate biological pathways at the multiomics level and to explore causal relationships between respiratory diseases. Data were collected from 27 November 2022 to 30 March 2023 and analysed from 14 April 2023 to 13 July 2023.

MAIN OUTCOMES AND MEASURES

The primary outcomes are shared genetic loci, pleiotropic genes, biological pathways and estimates of genetic correlations and causal effects.

RESULTS

Significant genetic correlations were found for 10 paired traits in 5 respiratory diseases. Cross-Phenotype Association identified 12 400 significant potential pleiotropic single-nucleotide polymorphism at 156 independent pleiotropic loci. In addition, multitrait colocalisation analysis identified 15 colocalised loci and a subset of colocalised traits. Gene-based analyses identified 432 potential pleiotropic genes and were further validated at the transcriptome and protein levels. Both pathway enrichment and single-cell enrichment analyses supported the role of the immune system in respiratory diseases. Additionally, five pairs of respiratory diseases have a causal relationship.

CONCLUSIONS AND RELEVANCE

This study reveals the common genetic basis and pleiotropic genes among respiratory diseases. It provides strong evidence for further therapeutic strategies and risk prediction for the phenomenon of respiratory disease comorbidity.

Gut microbiota and cognitive performance: A bidirectional two-sample Mendelian randomization

PURPOSE

Previous studies have suggested a potential association between gut microbiota and neurological and psychiatric disorders. However, the causal relationship between gut microbiota and cognitive performance remains uncertain.

METHODS

A two-sample Mendelian randomization (MR) study used SNPs linked to gut microbiota (n = 18,340) and cognitive performance (n = 257,841) from recent GWAS data. Inverse-variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode were employed. Heterogeneity was assessed via Cochran's Q test for IVW. Results were shown with funnel plots. Outliers were detected through leave-one-out method. MR-PRESSO and MR-Egger intercept tests were conducted to address horizontal pleiotropy influence.

LIMITATIONS

Limited to European populations, generic level, and potential confounding factors.

RESULTS

IVW analysis revealed detrimental effects on cognitive perfmance associated with the presence of genus Blautia (P = 0.013, 0.966[0.940-0.993]), Catenibacterium (P = 0.035, 0.977[0.956-0.998]), Oxalobacter (P = 0.043, 0.979[0.960-0.999]). Roseburia (P < 0.001, 0.935[0.906-0.965]), in particular, remained strongly negatively associated with cognitive performance after Bonferroni correction. Conversely, families including Bacteroidaceae (P = 0.043, 1.040[1.001-1.081]), Rikenellaceae (P = 0.047, 1.026[1.000-1.053]), along with genera including Paraprevotella (P = 0.044, 1.020[1.001-1.039]), Ruminococcus torques group (P = 0.016, 1.062[1.011-1.115]), Bacteroides (P = 0.043, 1.040[1.001-1.081]), Dialister (P = 0.027, 1.039[1.004-1.074]), Paraprevotella (P = 0.044, 1.020[1.001-1.039]) and Ruminococcaceae UCG003 (P = 0.007, 1.040[1.011-1.070]) had a protective effect on cognitive performance.

CONCLUSIONS

Our results suggest that interventions targeting specific gut microbiota may offer a promising avenue for improving cognitive function in diseased populations. The practical application of these findings has the potential to enhance cognitive performance, thereby improving overall quality of life.

Circulating Metabolite Abundances Associated With Risks of Bipolar Disorder, Schizophrenia, and Depression: A Mendelian Randomization Study

BACKGROUND

Preventive measures and treatments for psychiatric disorders are limited. Circulating metabolites are potential candidates for biomarker and therapeutic target identification, given their measurability and essential roles in biological processes.

METHODS

Leveraging large-scale genome-wide association studies, we conducted Mendelian randomization analyses to assess the associations between circulating metabolite abundances and the risks of bipolar disorder, schizophrenia, and depression. Genetic instruments were selected for 94 metabolites measured in the Canadian Longitudinal Study on Aging cohort (N = 8299). We repeated Mendelian randomization analyses based on the UK Biobank, INTERVAL, and EPIC (European Prospective Investigation into Cancer)-Norfolk studies.

RESULTS

After validating Mendelian randomization assumptions and colocalization evidence, we found that a 1 SD increase in genetically predicted circulating abundances of eicosapentaenoate and docosapentaenoate was associated with odds ratios of 0.72 (95% CI, 0.65-0.79) and 0.63 (95% CI, 0.55-0.72), respectively, for bipolar disorder. Genetically increased Ω-3 unsaturated fatty acids abundance and Ω-3-to-total fatty acids ratio, as well as genetically decreased Ω-6-to-Ω-3 ratio, were negatively associated with the risk of bipolar disorder in the UK Biobank. Genetically increased circulating abundances of 3 N-acetyl-amino acids were associated with an increased risk of schizophrenia with a maximum odds ratio of 1.31 (95% CI, 1.18-1.44) per 1 SD increase. Furthermore, a 1 SD increase in genetically predicted circulating abundance of hypotaurine was associated with an odds ratio of 0.85 (95% CI, 0.78-0.93) for depression.

CONCLUSIONS

The biological mechanisms that underlie Ω-3 unsaturated fatty acids, NAT8-catalyzed N-acetyl-amino acids, and hypotaurine warrant exploration to identify new biomarkers and potential therapeutic targets.

SharePro: an accurate and efficient genetic colocalization method accounting for multiple causal signals

MOTIVATION

Colocalization analysis is commonly used to assess whether two or more traits share the same genetic signals identified in genome-wide association studies (GWAS), and is important for prioritizing targets for functional follow-up of GWAS results. Existing colocalization methods can have suboptimal performance when there are multiple causal variants in one genomic locus.

RESULTS

We propose SharePro to extend the COLOC framework for colocalization analysis. SharePro integrates linkage disequilibrium (LD) modeling and colocalization assessment by grouping correlated variants into effect groups. With an efficient variational inference algorithm, posterior colocalization probabilities can be accurately estimated. In simulation studies, SharePro demonstrated increased power with a well-controlled false positive rate at a low computational cost. Compared to existing methods, SharePro provided stronger and more consistent colocalization evidence for known lipid-lowering drug target proteins and their corresponding lipid traits. Through an additional challenging case of the colocalization analysis of the circulating abundance of R-spondin 3 GWAS and estimated bone mineral density GWAS, we demonstrated the utility of SharePro in identifying biologically plausible colocalized signals.

AVAILABILITY AND IMPLEMENTATION

SharePro for colocalization analysis is written in Python and openly available at https://github.com/zhwm/SharePro_coloc.

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.

SGLT2 inhibition, plasma proteins, and heart failure: a proteome-wide Mendelian Randomization and colocalization study

Objective

To investigate the causal contributions of Sodium-glucose cotransporter 2 (SGLT2) inhibition on Heart Failure (HF) and identify the circulating proteins that mediate SGLT2 inhibition's effects on HF.

Methods

Applying a two-sample, two-step Mendelian Randomization (MR) analysis, we aimed to estimate: (1) the causal impact of SGLT2 inhibition on HF; (2) the causal correlation of SGLT2 inhibition on 4,907 circulating proteins; (3) the causal association of SGLT2 inhibition-driven plasma proteins on HF. Genetic variants linked to SGLT2 inhibition derived from the previous studies. The 4,907 circulating proteins were derived from the deCODE study. Genetic links to HF were obtained through the Heart Failure Molecular Epidemiology for Therapeutic Targets (HERMES) consortium.

Results

SGLT2 inhibition demonstrated a lower risk of HF (odds ratio [OR] = 0.44, 95% CI [0.26, 0.76], P = 0.003). Among 4,907 circulating proteins, we identified leucine rich repeat transmembrane protein 2 (LRRTM2), which was related to both SGLT2 inhibition and HF. Mediation analysis revealed that the impact of SGLT2 inhibition on HF operates indirectly through LRRTM2 [β = -0.20, 95% CI (-0.39, -0.06), P = 0.02] with a mediation proportion of 24.6%. Colocalization analysis provided support for the connections between LRRTM2 and HF.

Conclusion

The study indicated a causative link between SGLT2 inhibition and HF, with plasma LRRTM2 potentially serving as a mediator.

Computer gaming alters resting-state brain networks, enhancing cognitive and fluid intelligence in players: evidence from brain imaging-derived phenotypes-wide Mendelian randomization

The debate on whether computer gaming enhances players' cognitive function is an ongoing and contentious issue. Aiming to delve into the potential impacts of computer gaming on the players' cognitive function, we embarked on a brain imaging-derived phenotypes (IDPs)-wide Mendelian randomization (MR) study, utilizing publicly available data from a European population. Our findings indicate that computer gaming has a positive impact on fluid intelligence (odds ratio [OR] = 6.264, P = 4.361 × 10-10, 95% confidence interval [CI] 3.520-11.147) and cognitive function (OR = 3.322, P = 0.002, 95% CI 1.563-7.062). Out of the 3062 brain IDPs analyzed, only one phenotype, IDP NET100 0378, was significantly influenced by computer gaming (OR = 4.697, P = 1.10 × 10-5, 95% CI 2.357-9.361). Further MR analysis suggested that alterations in the IDP NET100 0378 caused by computer gaming may be a potential factor affecting fluid intelligence (OR = 1.076, P = 0.041, 95% CI 1.003-1.153). Our MR study lends support to the notion that computer gaming can facilitate the development of players' fluid intelligence by enhancing the connectivity between the motor cortex in the resting-state brain and key regions such as the left dorsolateral prefrontal cortex and the language center.

Causal Relationships Between Screen Use, Reading, and Brain Development in Early Adolescents

The rise of new media has greatly changed the lifestyles, leading to increased time on these platforms and less time spent reading. This shift has particularly profound impacts on early adolescents, who are in a critical stage of brain development. Previous studies have found associations between screen use and mental health, but it remains unclear whether screen use is the direct cause of the outcomes. Here, the Adolescent Brain Cognitive Development (ABCD) dataset is utlized to examine the causal relationships between screen use and brain development. The results revealed adverse causal effects of screen use on language ability and specific behaviors in early adolescents, while reading has positive causal effects on their language ability and brain volume in the frontal and temporal regions. Interestingly, increased screen use is identified as a result, rather than a cause, of certain behaviors such as rule-breaking and aggressive behaviors. Furthermore, the analysis uncovered an indirect influence of screen use, mediated by changes in reading habits, on brain development. These findings provide new evidence for the causal influences of screen use on brain development and highlight the importance of monitoring media use and related habit change in children.

Multi-omic insight into the molecular networks of mitochondrial dysfunction in the pathogenesis of inflammatory bowel disease

BACKGROUND

Mitochondrial dysfunction has been linked to the development of inflammatory bowel disease (IBD), but the genetic pathophysiology was not fully elucidated. We employed Mendelian randomization and colocalization analyses to investigate the associations between mitochondrial-related genes and IBD via integrating multi-omics.

METHODS

Summary-level data of mitochondrial gene methylation, expression and protein abundance levels were obtained from corresponding methylation, expression and protein quantitative trait loci studies, respectively. We obtained genetic associations with IBD and its two subtypes from the Inflammatory Bowel Disease Genetics Consortium (discovery), the UK Biobank (replication), and the FinnGen study (replication). We performed summary-data-based Mendelian randomization analysis to assess the associations of mitochondrial gene-related molecular features with IBD. Colocalization analysis was further conducted to assess whether the identified signal pairs shared a causal genetic variant.

FINDINGS

After integrating the multi-omics data between mQTL-eQTL and eQTL-pQTL, we identified two mitochondrial genes, i.e., PARK7 and ACADM, with tier 1 evidence for their associations with IBD and ulcerative colitis (UC). PDK1 and FISI genes were associated with UC risk with tier 2 and tier 3 evidence, respectively. The methylation of cg05467918 in ACADM was associated with lower expression of ACADM, which fits with the positive effect of cg05467918 methylation on UC risk. Consistently, the inverse associations between gene methylation and gene expression were also observed in PARK7 (cg10385390) and PDK1 (cg17679246), which were corroborated with the protective role in UC. At circulating protein level, genetically predicted higher levels of PARK7 (OR 0.36, 95% CI 0.25-0.52) and HINT1 (OR 0.47, 95% CI 0.30-0.74) were inversely associated with IBD risk; genetically predicted higher level of HINT1 was associated with a decreased risk of Crohn's disease (CD) (OR 0.26, 95% CI 0.14-0.49) and a higher level of ACADM (OR 0.67, 95% CI 0.55-0.83), PDK1 (OR 0.63, 95% CI 0.49-0.81), FIS1 (OR 0.63, 95% CI 0.47-0.83) was associated with a decreased risk of UC.

INTERPRETATION

We found that the mitochondrial PARK7 gene was putatively associated with IBD risk, and mitochondrial FIS1, PDK1, and ACADM genes were associated with UC risk with evidence from multi-omics levels. This study identified mitochondrial genes in relation to IBD, which may enhance the understanding of the pathogenic mechanisms of IBD development.

FUNDING

XL is supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001) and Healthy Zhejiang One Million People Cohort (K-20230085).

Proteomic insights into the associations between obesity, lifestyle factors, and coronary artery disease

BACKGROUND

We aimed to investigate the protein pathways linking obesity and lifestyle factors to coronary artery disease (CAD).

METHODS

Summary-level genome-wide association statistics of CAD were obtained from the CARDIoGRAMplusC4D consortium (60,801 cases and 123,504 controls) and the FinnGen study (R8, 39,036 cases and 303,463 controls). Proteome-wide Mendelian randomization (MR) analysis was conducted to identify CAD-associated blood proteins, supplemented by colocalization analysis to minimize potential bias caused by linkage disequilibrium. Two-sample MR analyses were performed to assess the associations of genetically predicted four obesity measures and 13 lifestyle factors with CAD risk and CAD-associated proteins' levels. A two-step network MR analysis was conducted to explore the mediating effects of proteins in the associations between these modifiable factors and CAD.

RESULTS

Genetically predicted levels of 41 circulating proteins were associated with CAD, and 17 of them were supported by medium to high colocalization evidence. PTK7 (protein tyrosine kinase-7), RGMB (repulsive guidance molecule BMP co-receptor B), TAGLN2 (transgelin-2), TIMP3 (tissue inhibitor of metalloproteinases 3), and VIM (vimentin) were identified as promising therapeutic targets. Several proteins were found to mediate the associations between some modifiable factors and CAD, with PCSK9, C1S, AGER (advanced glycosylation end product-specific receptor), and MST1 (mammalian Ste20-like kinase 1) exhibiting highest frequency among the mediating networks.

CONCLUSIONS

This study suggests pathways explaining the associations of obesity and lifestyle factors with CAD from alterations in blood protein levels. These insights may be used to prioritize therapeutic intervention for further study.

The Role of Polyunsaturated Fatty Acids in Osteoarthritis: Insights from a Mendelian Randomization Study

The prior observational research on the impact of polyunsaturated fatty acid (PUFA) supplementation on osteoarthritis (OA) patients had yielded inclusive outcomes. This study utilized the Mendelian randomization (MR) approach to explore potential causal relationships between PUFAs and OA. The MR study was performed using GWAS summary statistics for PUFAs, encompassing omega-3 and omega-6 fatty acids, and for knee OA (KOA) and hip OA (HOA). The primary inverse-variance-weighted (IVW) method and two supplementary MR approaches were used to establish robust causality. Heterogeneity and horizontal pleiotropy were assessed using Cochrane's Q and MR-Egger intercept tests. Additionally, a range of sensitivity analyses were conducted to strengthen the precision and reliability of the results. The IVW method indicated a potential genetic association between omega-3 fatty acids and KOA risk (odd ratio (OR) = 0.94, 95% confidence interval (CI): 0.89-1.00, p = 0.048). No significant correlation was found between omega-3 levels and HOA. Moreover, genetically predicted higher levels of omega-6 fatty acids were associated with a decreased risk of KOA (OR = 0. 93, 95% CI: 0.86-1.00, p = 0.041) and HOA (OR = 0.89, 95% CI: 0.82-0.96; p = 0.003). The MR-Egger intercept evaluation showed no horizontal pleiotropy affecting the MR analysis (all p  >  0.05). Our findings supported the causal relationship between PUFAs and OA susceptibility and offered a novel insight that high omega-6 fatty acids may reduce the risk of KOA and HOA. These results underscore the importance of maintaining optimal levels of PUFAs, particularly omega-6 fatty acids, in individuals with a genetic predisposition to OA. Future research is necessary to validate these findings and elucidate the underlying mechanisms involved.

Alternative splicing in lung influences COVID-19 severity and respiratory diseases

Alternative splicing generates functional diversity in isoforms, impacting immune response to infection. Here, we evaluate the causal role of alternative splicing in COVID-19 severity and susceptibility by applying two-sample Mendelian randomization to cis-splicing quantitative trait loci and the results from COVID-19 Host Genetics Initiative. We identify that alternative splicing in lung, rather than total expression of OAS1, ATP11A, DPP9 and NPNT, is associated with COVID-19 severity. MUC1 and PMF1 splicing is associated with COVID-19 susceptibility. Colocalization analyses support a shared genetic mechanism between COVID-19 severity with idiopathic pulmonary fibrosis at the ATP11A and DPP9 loci, and with chronic obstructive lung diseases at the NPNT locus. Last, we show that ATP11A, DPP9, NPNT, and MUC1 are highly expressed in lung alveolar epithelial cells, both in COVID-19 uninfected and infected samples. These findings clarify the importance of alternative splicing in lung for COVID-19 and respiratory diseases, providing isoform-based targets for drug discovery.

Colocalization of expression transcripts with COVID-19 outcomes is rare across cell states, cell types and organs

Identifying causal genes at GWAS loci can help pinpoint targets for therapeutic interventions. Expression studies can disentangle such loci but signals from expression quantitative trait loci (eQTLs) often fail to colocalize-which means that the genetic control of measured expression is not shared with the genetic control of disease risk. This may be because gene expression is measured in the wrong cell type, physiological state, or organ. We tested whether Mendelian randomization (MR) could identify genes at loci influencing COVID-19 outcomes and whether the colocalization of genetic control of expression and COVID-19 outcomes was influenced by cell type, cell stimulation, and organ. We conducted MR of cis-eQTLs from single cell (scRNA-seq) and bulk RNA sequencing. We then tested variables that could influence colocalization, including cell type, cell stimulation, RNA sequencing modality, organ, symptoms of COVID-19, and SARS-CoV-2 status among individuals with symptoms of COVID-19. The outcomes used to test colocalization were COVID-19 severity and susceptibility as assessed in the Host Genetics Initiative release 7. Most transcripts identified using MR did not colocalize when tested across cell types, cell state and in different organs. Most that did colocalize likely represented false positives due to linkage disequilibrium. In general, colocalization was highly variable and at times inconsistent for the same transcript across cell type, cell stimulation and organ. While we identified factors that influenced colocalization for select transcripts, identifying 33 that mediate COVID-19 outcomes, our study suggests that colocalization of expression with COVID-19 outcomes is partially due to noisy signals even after following quality control and sensitivity testing. These findings illustrate the present difficulty of linking expression transcripts to disease outcomes and the need for skepticism when observing eQTL MR results, even accounting for cell types, stimulation state and different organs.

From target discovery to clinical drug development with human genetics

The substantial investments in human genetics and genomics made over the past three decades were anticipated to result in many innovative therapies. Here we investigate the extent to which these expectations have been met, excluding cancer treatments. In our search, we identified 40 germline genetic observations that led directly to new targets and subsequently to novel approved therapies for 36 rare and 4 common conditions. The median time between genetic target discovery and drug approval was 25 years. Most of the genetically driven therapies for rare diseases compensate for disease-causing loss-of-function mutations. The therapies approved for common conditions are all inhibitors designed to pharmacologically mimic the natural, disease-protective effects of rare loss-of-function variants. Large biobank-based genetic studies have the power to identify and validate a large number of new drug targets. Genetics can also assist in the clinical development phase of drugs-for example, by selecting individuals who are most likely to respond to investigational therapies. This approach to drug development requires investments into large, diverse cohorts of deeply phenotyped individuals with appropriate consent for genetically assisted trials. A robust framework that facilitates responsible, sustainable benefit sharing will be required to capture the full potential of human genetics and genomics and bring effective and safe innovative therapies to patients quickly.

Genetic predisposition to subjective well-being, depression, and suicide in relation to COVID-19 susceptibility and severity

BACKGROUND

Epidemiological studies have reported associations between subjective well-being (SWB), depression, and suicide with COVID-19 illness, but the causality has not been established. We performed a two-sample Mendelian randomization (MR) analysis to investigate the causal link between SWB, depression, suicide and COVID-19 susceptibility and severity.

METHODS

Summary statistics for SWB (298,420 cases), depression (113,769 cases) and suicide (52,208 cases) were obtained from three large-scale GWAS. Data on the associations between the Single Nucleotide Polymorphisms (SNPs) and COVID-19 (159,840 cases), hospitalized COVID-19 (44,986 cases), and severe COVID-19 (18,152 cases) were collected from the COVID-19 host genetics initiative. The causal estimate was calculated by the Inverse Variance Weighted, MR Egger and Weighted Median methods. Sensitivity tests were used to evaluate the validity of the causal relationship.

RESULTS

Our results showed that genetically predicted SWB (OR = 0.98, 95 % CI: 0.86-1.10, P = 0.69), depression (OR = 0.76, 95 % CI: 0.54-1.06, P = 0.11), and suicide (OR = 0.99, 95 % CI: 0.96-1.02, P = 0.56) were not causally related to COVID-19 susceptibility. Similarly, we did not find a potential causal relationship between SWB, depression, suicide and COVID-19 severity.

CONCLUSIONS

This indicated that positive or negative emotions would not make COVID-19 better or worse, and strategies that attempted to use positive emotions to improve COVID-19 symptoms may be useless. Improving knowledge about the SARS-CoV-2 and timely medical intervention to reduce panic during a pandemic is one of the effective measures to deal with the current decrease in well-being and increase in depression and suicide rates.