Rare variant associations with plasma protein levels in the UK Biobank

A systematic exploration of unexploited genes for oxidative stress in Parkinson's disease

Human disease-associated gene data are accessible through databases, including the Open Targets Platform, DisGeNET, miRTex, RNADisease, and PubChem. However, missing data entries in such databases are anticipated because of curational errors, biases, and text-mining failures. Additionally, the extensive research on human diseases has led to challenges in registering comprehensive data. The lack of essential data in databases hinders knowledge sharing and should be addressed. Therefore, we propose an analysis pipeline to explore missing entries of unexploited genes in the human disease-associated gene databases. Using this pipeline for genes in Parkinson's disease with oxidative stress revealed two unexploited genes: nuclear protein 1 (NUPR1) and ubiquitin-like with PHD and ring finger domains 2 (UHRF2). This methodology enhances the identification of underrepresented disease-associated genes, facilitating easier access to potential human disease-related functional genes. This study aims to identify unexploited genes for further research and does not include independent experimental validation.

Using Data-Driven Algorithms with Large-Scale Plasma Proteomic Data to Discover Novel Biomarkers for Diagnosing Depression

Given recent technological advances in proteomics, it is now possible to quantify plasma proteomes in large cohorts of patients to screen for biomarkers and to guide the early diagnosis and treatment of depression. Here we used CatBoost machine learning to model and discover biomarkers of depression in UK Biobank data sets (depression n = 4,479, healthy control n = 19,821). CatBoost was employed for model construction, with Shapley Additive Explanations (SHAP) being utilized to interpret the resulting model. Model performance was corroborated through 5-fold cross-validation, and its diagnostic efficacy was evaluated based on the area under the receiver operating characteristic (AUC) curve. A total of 45 depression-related proteins were screened based on the top 20 important features output by the CatBoost model in six data sets. Of the nine diagnostic models for depression, the performance of the traditional risk factor model was improved after the addition of proteomic data, with the best model having an average AUC of 0.764 in the test sets. KEGG pathway analysis of 45 screened proteins showed that the most significant pathway involved was the cytokine-cytokine receptor interaction. It is feasible to explore diagnostic biomarkers of depression using data-driven machine learning methods and large-scale data sets, although the results require validation.

Phenotypical and biochemical characterization of murine psoriasiform and fibrotic skin disease models in Stabilin-deficient mice

Stabilin-1 (Stab1) and Stabilin-2 (Stab2) are scavenger receptors expressed by liver sinusoidal endothelial cells (LSECs). The Stabilin-mediated scavenging function is responsible for regulating the molecular composition of circulating blood in mammals. Stab1 and Stab2 have been shown to influence fibrosis in liver and kidneys and to modulate inflammation in atherosclerosis. In this context, circulating and localized TGFBi and POSTN are differentially controlled by the Stabilins as their receptors. To assess Stab1 and Stab2 functions in inflammatory and fibrotic skin disease, topical Imiquimod (IMQ) was used to induce psoriasis-like skin lesions in mice and Bleomycin (BLM) was applied subcutaneously to induce scleroderma-like effects in the skin. The topical treatment with IMQ, as expected, led to psoriasis-like changes in the skin of mice, including increased epidermal thickness and significant weight loss. Clinical severity was reduced in Stab2-deficient compared to Stab1-deficient mice. We did not observe differential effects in the skin of Stabilin-deficient mice after bleomycin injection. Interestingly, treatment with IMQ led to a significant increase of Stabilin ligand TGFBi plasma levels in Stab2-/- mice, treatment with BLM resulted in a significant decrease in TGFBi levels in Stab1-/- mice. Overall, Stab1 and Stab2 deficiency resulted in minor alterations of the disease phenotypes accompanied by alterations of circulating ligands in the blood in response to the disease models. Stabilin-mediated clearance of TGFBi was altered in these disease processes. Taken together our results suggest that Stabilin deficiency-associated plasma alterations may interfere with preclinical disease severity and treatment responses in patients.

Ribosomal DNA copy number variation associates with hematological profiles and renal function in the UK Biobank

The phenotypic impact of genetic variation of repetitive features in the human genome is currently understudied. One such feature is the multi-copy 47S ribosomal DNA (rDNA) that codes for rRNA components of the ribosome. Here, we present an analysis of rDNA copy number (CN) variation in the UK Biobank (UKB). From the first release of UKB whole-genome sequencing (WGS) data, a discovery analysis in White British individuals reveals that rDNA CN associates with altered counts of specific blood cell subtypes, such as neutrophils, and with the estimated glomerular filtration rate, a marker of kidney function. Similar trends are observed in other ancestries. A range of analyses argue against reverse causality or common confounder effects, and all core results replicate in the second UKB WGS release. Our work demonstrates that rDNA CN is a genetic influence on trait variance in humans.

Identifying proteomic risk factors for cancer using prospective and exome analyses of 1463 circulating proteins and risk of 19 cancers in the UK Biobank

The availability of protein measurements and whole exome sequence data in the UK Biobank enables investigation of potential observational and genetic protein-cancer risk associations. We investigated associations of 1463 plasma proteins with incidence of 19 cancers and 9 cancer subsites in UK Biobank participants (average 12 years follow-up). Emerging protein-cancer associations were further explored using two genetic approaches, cis-pQTL and exome-wide protein genetic scores (exGS). We identify 618 protein-cancer associations, of which 107 persist for cases diagnosed more than seven years after blood draw, 29 of 618 were associated in genetic analyses, and four had support from long time-to-diagnosis ( > 7 years) and both cis-pQTL and exGS analyses: CD74 and TNFRSF1B with NHL, ADAM8 with leukemia, and SFTPA2 with lung cancer. We present multiple blood protein-cancer risk associations, including many detectable more than seven years before cancer diagnosis and that had concordant evidence from genetic analyses, suggesting a possible role in cancer development.

Harnessing the power of proteomics in precision diabetes medicine

Precision diabetes medicine (PDM) aims to reduce errors in prevention programmes, diagnosis thresholds, prognosis prediction and treatment strategies. However, its advancement and implementation are difficult due to the heterogeneity of complex molecular processes and environmental exposures that influence an individual's disease trajectory. To address this challenge, it is imperative to develop robust screening methods for all areas of PDM. Innovative proteomic technologies, alongside genomics, have proven effective in precision cancer medicine and are showing promise in diabetes research for potential translation. This narrative review highlights how proteomics is well-positioned to help improve PDM. Specifically, a critical assessment of widely adopted affinity-based proteomic technologies in large-scale clinical studies and evidence of the benefits and feasibility of using MS-based plasma proteomics is presented. We also present a case for the use of proteomics to identify predictive protein panels for type 2 diabetes subtyping and the development of clinical prediction models for prevention, diagnosis, prognosis and treatment strategies. Lastly, we discuss the importance of plasma and tissue proteomics and its integration with genomics (proteogenomics) for identifying unique type 2 diabetes intra- and inter-subtype aetiology. We conclude with a call for action formed on advancing proteomics technologies, benchmarking their performance and standardisation across sites, with an emphasis on data sharing and the inclusion of diverse ancestries in large cohort studies. These efforts should foster collaboration with key stakeholders and align with ongoing academic programmes such as the Precision Medicine in Diabetes Initiative consortium.

Drug-target Mendelian randomization analysis supports lowering plasma ANGPTL3, ANGPTL4, and APOC3 levels as strategies for reducing cardiovascular disease risk

Aims

APOC3, ANGPTL3, and ANGPTL4 are circulating proteins that are actively pursued as pharmacological targets to treat dyslipidaemia and reduce the risk of atherosclerotic cardiovascular disease. Here, we used human genetic data to compare the predicted therapeutic and adverse effects of APOC3, ANGPTL3, and ANGPTL4 inactivation.

Methods and results

We conducted drug-target Mendelian randomization analyses using variants in proximity to the genes associated with circulating protein levels to compare APOC3, ANGPTL3, and ANGPTL4 as drug targets. We obtained exposure and outcome data from large-scale genome-wide association studies and used generalized least squares to correct for linkage disequilibrium-related correlation. We evaluated five primary cardiometabolic endpoints and screened for potential side effects across 694 disease-related endpoints, 43 clinical laboratory tests, and 11 internal organ MRI measurements. Genetically lowering circulating ANGPTL4 levels reduced the odds of coronary artery disease (CAD) [odds ratio, 0.57 per s.d. protein (95% CI 0.47-0.70)] and Type 2 diabetes (T2D) [odds ratio, 0.73 per s.d. protein (95% CI 0.57-0.94)]. Genetically lowering circulating APOC3 levels also reduced the odds of CAD [odds ratio, 0.90 per s.d. protein (95% CI 0.82-0.99)]. Genetically lowered ANGPTL3 levels via common variants were not associated with CAD. However, meta-analysis of protein-truncating variants revealed that ANGPTL3 inactivation protected against CAD (odds ratio, 0.71 per allele [95%CI, 0.58-0.85]). Analysis of lowered ANGPTL3, ANGPTL4, and APOC3 levels did not identify important safety concerns.

Conclusion

Human genetic evidence suggests that therapies aimed at reducing circulating levels of ANGPTL3, ANGPTL4, and APOC3 reduce the risk of CAD. ANGPTL4 lowering may also reduce the risk of T2D.

Protein-truncating variants in BSN are associated with severe adult-onset obesity, type 2 diabetes and fatty liver disease

Obesity is a major risk factor for many common diseases and has a substantial heritable component. To identify new genetic determinants, we performed exome-sequence analyses for adult body mass index (BMI) in up to 587,027 individuals. We identified rare loss-of-function variants in two genes (BSN and APBA1) with effects substantially larger than those of well-established obesity genes such as MC4R. In contrast to most other obesity-related genes, rare variants in BSN and APBA1 were not associated with normal variation in childhood adiposity. Furthermore, BSN protein-truncating variants (PTVs) magnified the influence of common genetic variants associated with BMI, with a common variant polygenic score exhibiting an effect twice as large in BSN PTV carriers than in noncarriers. Finally, we explored the plasma proteomic signatures of BSN PTV carriers as well as the functional consequences of BSN deletion in human induced pluripotent stem cell-derived hypothalamic neurons. Collectively, our findings implicate degenerative processes in synaptic function in the etiology of adult-onset obesity.

The transition from genomics to phenomics in personalized population health

Modern health care faces several serious challenges, including an ageing population and its inherent burden of chronic diseases, rising costs and marginal quality metrics. By assessing and optimizing the health trajectory of each individual using a data-driven personalized approach that reflects their genetics, behaviour and environment, we can start to address these challenges. This assessment includes longitudinal phenome measures, such as the blood proteome and metabolome, gut microbiome composition and function, and lifestyle and behaviour through wearables and questionnaires. Here, we review ongoing large-scale genomics and longitudinal phenomics efforts and the powerful insights they provide into wellness. We describe our vision for the transformation of the current health care from disease-oriented to data-driven, wellness-oriented and personalized population health.

Association of circulating inflammatory proteins with type 2 diabetes mellitus and its complications: a bidirectional Mendelian randomization study

Background

Increasing evidence indicates that immune response underlies the pathology of type 2 diabetes (T2D). Nevertheless, the specific inflammatory regulators involved in this pathogenesis remain unclear.

Methods

We systematically explored circulating inflammatory proteins that are causally associated with T2D via a bidirectional Mendelian randomization (MR) study and further investigated them in prevalent complications of T2D. Genetic instruments for 91 circulating inflammatory proteins were derived from a genome-wide association study (GWAS) that enrolled 14,824 predominantly European participants. Regarding the summary-level GWASs of type 2 diabetes, we adopted the largest meta-analysis of European population (74,124 cases vs. 824,006 controls) and a prospective nested case-cohort study in Europe (9,978 cases vs. 12,348 controls). Summary statistics for five complications of T2D were acquired from the FinnGen R9 repository. The inverse variance-weighted method was applied as the primary method for causal inference. MR-Egger, weighted median and maximum likelihood methods were employed as supplementary analyses. Results from the two T2D studies were combined in a meta-analysis. Sensitivity analyses and phenotype-wide association studies (PheWAS) were performed to detect heterogeneity and potential horizontal pleiotropy in the study.

Results

Genetic evidence indicated that elevated levels of TGF-α (OR = 1.16, 95% CI = 1.15-1.17) and CX3CL1 (OR = 1.30, 95% CI = 1.04-1.63) promoted the occurrence of T2D, and increased concentrations of FGF-21 (OR = 0.87, 95% CI = 0.81-0.93) and hGDNF (OR = 0.96, 95% CI = 0.95-0.98) mitigated the risk of developing T2D, while type 2 diabetes did not exert a significant influence on said proteins. Elevated levels of TGF-α were associated with an increased risk of ketoacidosis, neurological complications, and ocular complications in patients with T2D, and increased concentrations of FGF-21 were potentially correlated with a diminished risk of T2D with neurological complications. Higher levels of hGDNF were associated with an increased risk of T2D with peripheral vascular complications, while CX3CL1 did not demonstrate a significant association with T2D complications. Sensitivity analyses and PheWAS further ensure the robustness of our findings.

Conclusion

This study determined four circulating inflammatory proteins that affected the occurrence of T2D, providing opportunities for the early prevention and innovative therapy of type 2 diabetes and its complications.

Search for chromosomal instability aiding variants reveal naturally occurring kinetochore gene variants that perturb chromosome segregation

Chromosomal instability (CIN) is a hallmark of cancers, and CIN-promoting mutations are not fully understood. Here, we report 141 chromosomal instability aiding variant (CIVa) candidates by assessing the prevalence of loss-of-function (LoF) variants in 135 chromosome segregation genes from over 150,000 humans. Unexpectedly, we observe both heterozygous and homozygous CIVa in Astrin and SKA3, two evolutionarily conserved kinetochore and microtubule-associated proteins essential for chromosome segregation. To stratify harmful versus harmless variants, we combine live-cell microscopy and controlled protein expression. We find the naturally occurring Astrin p.Q1012∗ variant is harmful as it fails to localize normally and induces chromosome misalignment and missegregation, in a dominant negative manner. In contrast, the Astrin p.L7Qfs∗21 variant generates a shorter isoform that localizes and functions normally, and the SKA3 p.Q70Kfs∗7 variant allows wild-type SKA complex localisation and function, revealing distinct resilience mechanisms that render these variants harmless. Thus, we present a scalable framework to predict and stratify naturally occurring CIVa, and provide insight into resilience mechanisms that compensate for naturally occurring CIVa.

Identification and validation of prognostic and immunotherapeutic responses in esophageal squamous carcinoma based on hypoxia phenotype-related genes

The study aimed to investigate the clinical significance of the interaction between hypoxia and the immune system in esophageal squamous cell carcinoma (ESCC) microenvironment. A comprehensive evaluation of 13 hypoxia phenotype-related genes (HPRs) was conducted using data from TCGA-ESCC and two GEO cohorts. Three distinct HPRclusters were identified, and the HPRscore was established as an independent prognostic factor (p = 0.001), with higher scores indicating poorer prognosis. The HPRscore was validated in various immunotherapy cohorts, demonstrating its efficacy in evaluating immunotherapy and chemotherapy outcomes. Additionally, phenome-wide association study (PheWAS) analysis showed that PKP1 had no significant correlation with other traits at the gene level. PKP1 was identified as a potential prognostic marker for ESCC, with upregulated expression observed in ESCC patients. In vitro experiments showed that the knockdown of PKP1 inhibited ESCC cell proliferation and migration. These findings suggest that the novel HPRscore and PKP1 may serve as prognostic tools and therapeutic targets for ESCC patients.

Plasma proteomic profiles predict future dementia in healthy adults

The advent of proteomics offers an unprecedented opportunity to predict dementia onset. We examined this in data from 52,645 adults without dementia in the UK Biobank, with 1,417 incident cases and a follow-up time of 14.1 years. Of 1,463 plasma proteins, GFAP, NEFL, GDF15 and LTBP2 consistently associated most with incident all-cause dementia (ACD), Alzheimer's disease (AD) and vascular dementia (VaD), and ranked high in protein importance ordering. Combining GFAP (or GDF15) with demographics produced desirable predictions for ACD (area under the curve (AUC) = 0.891) and AD (AUC = 0.872) (or VaD (AUC = 0.912)). This was also true when predicting over 10-year ACD, AD and VaD. Individuals with higher GFAP levels were 2.32 times more likely to develop dementia. Notably, GFAP and LTBP2 were highly specific for dementia prediction. GFAP and NEFL began to change at least 10 years before dementia diagnosis. Our findings strongly highlight GFAP as an optimal biomarker for dementia prediction, even more than 10 years before the diagnosis, with implications for screening people at high risk for dementia and for early intervention.

Deficiency of Stabilin-1 in the Context of Hepatic Melanoma Metastasis

BACKGROUND

This study analyzed the role of Stabilin-1 on hepatic melanoma metastasis in preclinical mouse models.

METHODS

In Stabilin-1-/- mice (Stab1 KO), liver colonization of B16F10 luc2 and Wt31 melanoma was investigated. The numbers, morphology, and vascularization of hepatic metastases and the hepatic microenvironment were analyzed by immunofluorescence.

RESULTS

While hepatic metastasis of B16F10 luc2 or Wt31 melanoma was unaltered between Stab1 KO and wildtype (Ctrl) mice, metastases of B16F10 luc2 tended to be smaller in Stab1 KO. The endothelial differentiation of both types of liver metastases was similar in Stab1 KO and Ctrl. No differences in initial tumor cell adhesion and retention to the liver vasculature were detected in the B16F10 luc2 model. Analysis of the immune microenvironment revealed a trend towards higher levels of CD45+Gr-1+ cells in Stab1 KO as compared to Ctrl in the B16F10 luc2 model. Interestingly, significantly higher levels of POSTN were found in the matrix of hepatic metastases of Wt31, while liver metastases of B16F10 luc2 showed a trend towards increased deposition of RELN.

CONCLUSIONS

Hepatic melanoma metastases show resistance to Stabilin-1 targeting approaches. This suggests that anti-Stab1 therapies should be considered with respect to the tumor entity or target organs.