Phenome-wide Mendelian randomization analysis reveals multiple health comorbidities of coeliac disease

Yuan, Shuai; Jiang, Fangyuan; Chen, Jie; Lebwohl, Benjamin; Green, Peter H.R.; Leffler, Daniel; Larsson, Susanna C.; Li, Xue; Ludvigsson, Jonas F.

doi:10.1016/j.ebiom.2024.105033

Cited by 13 publications

(3 citation statements)

References 69 publications

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“…Therefore, further understanding the roles of these proteins in the onset and progression of T1D, as well as how existing T1D medications influence protein–protein interactions, will pave the way for novel drug development. MR phenome-wide association studies could delve deeper into the causal associations between the identified protein targets and common diseases, thus identifying their potential beneficial indications and side effects [ 20 ]. This methodology could demonstrate the safety and reliability of the targets, thereby maximizing their therapeutic efficacy.…”

Section: Discussionmentioning

confidence: 99%

Novel Protein Biomarkers and Therapeutic Targets for Type 1 Diabetes and Its Complications: Insights from Summary-Data-Based Mendelian Randomization and Colocalization Analysis

Zou,

Yang

2024

Pharmaceuticals

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Millions of patients suffer from type 1 diabetes (T1D) and its associated complications. Nevertheless, the pursuit of a cure for T1D has encountered significant challenges, with a crucial impediment being the lack of biomarkers that can accurately predict the progression of T1D and reliable therapeutic targets for T1D. Hence, there is an urgent need to discover novel protein biomarkers and therapeutic targets, which holds promise for targeted therapy for T1D. In this study, we extracted summary-level data on 4907 plasma proteins from 35,559 Icelanders and 2923 plasma proteins from 54,219 UK participants as exposures. The genome-wide association study (GWAS) summary statistics on T1D and T1D with complications were obtained from the R9 release results from the FinnGen consortium. Summary-data-based Mendelian randomization (SMR) analysis was employed to evaluate the causal associations between the genetically predicted levels of plasma proteins and T1D-associated outcomes. Colocalization analysis was utilized to investigate the shared genetic variants between the exposure and outcome. Moreover, transcriptome analysis and a protein–protein interaction (PPI) network further illustrated the expression patterns of the identified protein targets and their interactions with the established targets of T1D. Finally, a Mendelian randomization phenome-wide association study evaluated the potential side effects of the identified core protein targets. In the primary SMR analysis, we identified 72 potential protein targets for T1D and its complications, and nine of them were considered crucial protein targets. Within the group were five risk targets and four protective targets. Backed by evidence from the colocalization analysis, the protein targets were classified into four tiers, with MANSC4, CTRB1, SIGLEC5 and MST1 being categorized as tier 1 targets. Delving into the DrugBank database, we retrieved 11 existing medications for T1D along with their therapeutic targets. The PPI network clarified the interactions among the identified potential protein targets and established ones. Finally, the Mendelian randomization phenome-wide association study corroborated MANSC4 as a reliable target capable of mitigating the risk of various forms of diabetes, and it revealed the absence of adverse effects linked to CTRB1, SIGLEC5 and MST1. This study unveiled many protein biomarkers and therapeutic targets for T1D and its complications. Such advancements hold great promise for the progression of drug development and targeted therapy for T1D.

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Section: Discussionmentioning

confidence: 99%

Novel Protein Biomarkers and Therapeutic Targets for Type 1 Diabetes and Its Complications: Insights from Summary-Data-Based Mendelian Randomization and Colocalization Analysis

Zou,

Yang

2024

Pharmaceuticals

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“…For example, our ESPRESSO (Epidemiology Strengthened by histoPathology Reports in Sweden) study suggests a small but significant excess mortality from CVD in people with coeliac disease [5]. However, the association between coeliac disease and risk of CVD has not been identified in Mendelian randomisation (MR) analysis [10,11]. Likewise, conflicting data have been found for the association between coeliac disease and type 2 diabetes.…”

Section: Introductionmentioning

confidence: 99%

Coeliac disease and type 2 diabetes risk: a nationwide matched cohort and Mendelian randomisation study

Yuan,

Leffler,

Lebwohl

et al. 2024

Diabetologia

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Aims/hypothesis While the association between coeliac disease and type 1 diabetes is well documented, the association of coeliac disease with type 2 diabetes risk remains undetermined. We conducted a nationwide cohort and Mendelian randomisation analysis to investigate this link. Methods This nationwide matched cohort used data from the Swedish ESPRESSO cohort including 46,150 individuals with coeliac disease and 219,763 matched individuals in the comparator group selected from the general population, followed up from 1969 to 2021. Data from 9053 individuals with coeliac disease who underwent a second biopsy were used to examine the association between persistent villous atrophy and type 2 diabetes. Multivariable Cox regression was employed to estimate the associations. In Mendelian randomisation analysis, 37 independent genetic variants associated with clinically diagnosed coeliac disease at p<5×10−8 were used to proxy genetic liability to coeliac disease. Summary-level data for type 2 diabetes were obtained from the DIAGRAM consortium (80,154 cases) and the FinnGen study (42,593 cases). Results Over a median 15.7 years’ follow-up, there were 6132 (13.3%) and 30,138 (13.7%) incident cases of type 2 diabetes in people with coeliac disease and comparator individuals, respectively. Those with coeliac disease were not at increased risk of incident type 2 diabetes with an HR of 1.00 (95% CI 0.97, 1.03) compared with comparator individuals. Persistent villous atrophy was not associated with an increased risk of type 2 diabetes compared with mucosal healing among participants with coeliac disease (HR 1.02, 95% CI 0.90, 1.16). Genetic liability to coeliac disease was not associated with type 2 diabetes in DIAGRAM (OR 1.01, 95% CI 0.99, 1.03) or in FinnGen (OR 1.01, 95% CI 0.99–1.04). Conclusions/interpretation Coeliac disease was not associated with type 2 diabetes risk. Graphical Abstract

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“…The UK Biobank (UKB), rich in multi-omic data, stands as an ideal platform for such endeavors and has been widely used for sequencing studies of human diseases and traits 7 – 12 . Prior investigations within the UKB, primarily through GWAS, have focused on genetic risk factors 20 , 21 , ethnic disparities 22 , identification of IMD therapeutic targets 23 – 25 , associated comorbidities 26 , 27 , and their unique or overlapping genetic landscape 28 . However, WES studies of IMDs in the UKB have been sparse.…”

Section: Introductionmentioning

confidence: 99%

Large-scale whole-exome sequencing analyses identified protein-coding variants associated with immune-mediated diseases in 350,770 adults

Yang,

Ou,

et al. 2024

Nat Commun

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The genetic contribution of protein-coding variants to immune-mediated diseases (IMDs) remains underexplored. Through whole exome sequencing of 40 IMDs in 350,770 UK Biobank participants, we identified 162 unique genes in 35 IMDs, among which 124 were novel genes. Several genes, including FLG which is associated with atopic dermatitis and asthma, showed converging evidence from both rare and common variants. 91 genes exerted significant effects on longitudinal outcomes (interquartile range of Hazard Ratio: 1.12-5.89). Mendelian randomization identified five causal genes, of which four were approved drug targets (CDSN, DDR1, LTA, and IL18BP). Proteomic analysis indicated that mutations associated with specific IMDs might also affect protein expression in other IMDs. For example, DXO (celiac disease-related gene) and PSMB9 (alopecia areata-related gene) could modulate CDSN (autoimmune hypothyroidism-, psoriasis-, asthma-, and Graves’ disease-related gene) expression. Identified genes predominantly impact immune and biochemical processes, and can be clustered into pathways of immune-related, urate metabolism, and antigen processing. Our findings identified protein-coding variants which are the key to IMDs pathogenesis and provided new insights into tailored innovative therapies.

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Phenome-wide Mendelian randomization analysis reveals multiple health comorbidities of coeliac disease

Cited by 13 publications

References 69 publications

Novel Protein Biomarkers and Therapeutic Targets for Type 1 Diabetes and Its Complications: Insights from Summary-Data-Based Mendelian Randomization and Colocalization Analysis

Novel Protein Biomarkers and Therapeutic Targets for Type 1 Diabetes and Its Complications: Insights from Summary-Data-Based Mendelian Randomization and Colocalization Analysis

Coeliac disease and type 2 diabetes risk: a nationwide matched cohort and Mendelian randomisation study

Large-scale whole-exome sequencing analyses identified protein-coding variants associated with immune-mediated diseases in 350,770 adults

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