Aims/hypothesis: The aim of this study was to use Mendelian randomisation (MR) to identify the causal risk factors for type 2 diabetes. Methods: We first conducted a review of meta-analyses and review articles to pinpoint possible risk factors for type 2 diabetes. Around 170 possible risk factors were identified of which 97 risk factors with available genetic instrumental variables were included in MR analyses. To reveal more risk factors that were not included in our MR analyses, we conducted a review of published MR studies of type 2 diabetes. For our MR analyses, we used summary-level data from the DIAbetes Genetics Replication And Meta-analysis consortium (74,124 type 2 diabetes cases and 824,006 controls of European ancestry). Potential causal associations were replicated using the FinnGen consortium (11,006 type 2 diabetes cases and 82,655 controls of European ancestry). The inverse-variance weighted method was used as the main analysis. Multivariable MR analysis was used to assess whether the observed associations with type 2 diabetes were mediated by BMI. We used the Benjamini–Hochberg method that controls false discovery rate for multiple testing. Results: We found evidence of causal associations between 34 exposures (19 risk factors and 15 protective factors) and type 2 diabetes. Insomnia was identified as a novel risk factor (OR 1.17 [95% CI 1.11, 1.23]). The other 18 risk factors were depression, systolic BP, smoking initiation, lifetime smoking, coffee (caffeine) consumption, plasma isoleucine, valine and leucine, liver alanine aminotransferase, childhood and adulthood BMI, body fat percentage, visceral fat mass, resting heart rate, and four plasma fatty acids. The 15 exposures associated with a decreased risk of type 2 diabetes were plasma alanine, HDL- and total cholesterol, age at menarche, testosterone levels, sex hormone binding globulin levels (adjusted for BMI), birthweight, adulthood height, lean body mass (for women), four plasma fatty acids, circulating 25-hydroxyvitamin D and education years. Eight associations remained after adjustment for adulthood BMI. We additionally identified 21 suggestive risk factors (p < 0.05), such as alcohol consumption, breakfast skipping, daytime napping, short sleep, urinary sodium, and certain amino acids and inflammatory factors. Conclusions/interpretation: The present study verified several previously reported risk factors and identified novel potential risk factors for type 2 diabetes. Prevention strategies for type 2 diabetes should be considered from multiple perspectives on obesity, mental health, sleep quality, education level, birthweight and smoking. Graphical

Background: The proteome is a major source of therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) study to identify candidate protein markers and therapeutic targets for colorectal cancer (CRC). Methods: Protein quantitative trait loci (pQTLs) were derived from seven published genome-wide association studies (GWASs) on plasma proteome, and summary-level data were extracted for 4853 circulating protein markers. Genetic associations with CRC were obtained from a large-scale GWAS meta-analysis (16,871 cases and 26,328 controls), the FinnGen cohort (4957 cases and 304,197 controls), and the UK Biobank (9276 cases and 477,069 controls). Colocalization and summary-data-based MR (SMR) analyses were performed sequentially to verify the causal role of candidate proteins. Single cell-type expression analysis, protein-protein interaction (PPI), and druggability evaluation were further conducted to detect the specific cell type with enrichment expression and prioritize potential therapeutic targets. Results: Collectively, genetically predicted levels of 13 proteins were associated with CRC risk. Elevated levels of two proteins (GREM1, CHRDL2) and decreased levels of 11 proteins were associated with an increased risk of CRC, among which four (GREM1, CLSTN3, CSF2RA, CD86) were prioritized with the most convincing evidence. These protein-coding genes are mainly expressed in tissue stem cells, epithelial cells, and monocytes in colon tumor tissue. Two interactive pairs of proteins (GREM1 and CHRDL2; MMP2 and TIMP2) were identified to be involved in osteoclast differentiation and tumorigenesis pathways; four proteins (POLR2F, CSF2RA, CD86, MMP2) have been targeted for drug development on autoimmune diseases and other cancers, with the potentials of being repurposed as therapeutic targets for CRC. Conclusions: This study identified several protein biomarkers to be associated with CRC risk and provided new insights into the etiology and promising targets for the development of screening biomarkers and therapeutic drugs for CRC.

Identifying new drug targets for inflammatory bowel disease (IBD) is urgently needed. The proteome is a major source of therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) and colocalization analyses to identify possible targets for IBD. Summary-level data of 4907 circulating protein levels were extracted from a large-scale protein quantitative trait loci study including 35,559 individuals. Genetic associations with IBD and its subtypes were obtained from the Inflammatory Bowel Disease Genetics Consortium (25,024 cases and 34,915 controls), the FinnGen study (7206 cases and 253,199 controls), and the UK Biobank study (7045 cases and 449,282 controls). MR analysis was conducted to estimate the associations between protein and IBD risk. The colocalization analysis was used to examine whether the identified proteins and IBD shared casual variants. Genetically predicted levels of 3, and 5 circulating proteins were associated with IBD and ulcerative colitis (UC), respectively. With high supporting evidence of colocalization, genetically predicted MST1 (macrophage stimulating 1) and HGFAC (hepatocyte growth factor activator) levels were inversely associated with IBD risks. The associations of STAT3 (signal transducer and activator of transcription 3), MST1, CXCL5 (C-X-C motif chemokine ligand 5), and ITPKA (inositol-trisphosphate 3-kinase A) with the risk of UC were supported by colocalization analysis. The proteome-wide MR investigation identified many proteins associated with the risk of IBD. MST1, HGFAC, STAT3, ITPKA, and CXCL5 deserve further investigation as potential therapeutic targets for IBD. SCL is supported by research grants from the Swedish Research Council for Health, Working Life and Welfare (Forte; grant no. 2018-00123) and the Swedish Research Council (Vetenskapsrådet; grant no. 2019-00977). XYW is supported by research grants from the National Natural Science Foundation of China (81970494) and Key Project of Research and Development Plan of Hunan Province (2019SK2041). XL is supported by research grants from the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001).

Obesity, type 2 diabetes, and lifestyle factors (cigarette smoking, alcohol drinking, and coffee consumption) have been associated with the risk of developing gallstone disease in observational studies, but whether these associations are causal is undetermined. We conducted a Mendelian randomization study to assess these associations. Genetic instruments associated with the exposures at the genome-wide significance (p<5×10-8) level were selected from corresponding genome-wide associations studies (n=224 459 to 1 232 091 individuals). Summary-level data for gallstone disease were obtained from the UK Biobank (10 520 cases and 350 674 non-cases) and FinnGen consortium (11 675 cases and 121 348 non-cases). Univariable and multivariable Mendelian randomization analyses were conducted. Results from UK Biobank and FinnGen were combined using fixed-effects meta-analysis. The odds ratios were 1.63 (95% confidence interval (CI), 1.49, 1.79) for one standard deviation (SD) increase in body mass index, 1.81 (95% CI, 1.60, 2.05) for one SD increase in waist circumference, 1.13 (95% CI, 1.09, 1.17) for one unit increase in the log-odds ratio of type 2 diabetes and 1.25 (95% CI, 1.16, 1.34) for one SD increase in prevalence of smoking initiation. The associations for body mass index and type 2 diabetes persisted after mutual adjustment. Genetically predicted coffee consumption was inversely associated with gallstone disease after adjustment for body mass index and smoking (odds ratio per 50% increase 0.44, 95% CI, 0.21, 0.91). There was no association with alcohol consumption. This study supports independent causal roles of obesity, type 2 diabetes, and smoking in gallstone disease.

We conduct proteome-wide Mendelian randomization and colocalization analyses to decipher the associations of blood proteins with the risk of type 2 diabetes and diabetic complications. Genetic data on plasma proteome are obtained from 54,306 UK Biobank participants and 35,559 Icelanders. Summary-level data on type 2 diabetes are obtained from the DIAGRAM (DIAbetes Genetics Replication And Meta-analysis consortium) consortium (74,124 cases) and FinnGen study (33,043 cases). Data on 10 diabetic complications are obtained from FinnGen and corresponding studies. Among 1,886 proteins, genetically predicted levels of 47 plasma proteins are associated with type 2 diabetes. Eleven of these proteins have strong support of colocalization. Seventeen proteins are associated with at least one diabetic complication, although a few have colocalization support. HLA-DRA, AGER, HSPA1A, and HSPA1B are associated with most microvascular complications. This study reveals causal proteins for the onset of type 2 diabetes and diabetic complications, which enhances the understanding of molecular etiology and development of therapeutics.

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. 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. 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. 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. 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).