Controls Of European Descent Research Articles

The causal relationship between CSF metabolites and GBM: a two-sample mendelian randomization analysis

BackgroundGlioblastoma multiforme (GBM) is a highly aggressive primary malignant brain tumor characterized by rapid progression, poor prognosis, and high mortality rates. Understanding the relationship between cerebrospinal fluid (CSF) metabolites and GBM is crucial for identifying potential biomarkers and pathways involved in the pathogenesis of this devastating disease.MethodsIn this study, Mendelian randomization (MR) analysis was employed to investigate the causal relationship between 338 CSF metabolites and GBM. The data for metabolites were obtained from a genome-wide association study summary dataset based on 291 individuals, and the GBM data was derived from FinnGen included 91 cases and 174,006 controls of European descent. The Inverse Variance Weighted method was utilized to estimate the causal effects. Supplementary comprehensive assessments of causal effects between CSF metabolites and GBM were conducted using MR-Egger regression, Weighted Median, Simple Mode, and Weighted Mode methods. Additionally, tests for heterogeneity and pleiotropy were performed.ResultsThrough MR analysis, a total of 12 identified metabolites and 2 with unknown chemical properties were found to have a causal relationship with GBM. 1-palmitoyl-2-stearoyl-gpc (16:0/18:0), 7-alpha-hydroxy-3-oxo-4-cholestenoate, Alpha-tocopherol, Behenoyl sphingomyelin (d18:1/22:0), Cysteinylglycine, Maleate, Uracil, Valine, X-12,101, X-12,104 and Butyrate (4:0) are associated with an increased risk of GBM. N1-methylinosine, Stachydrine and Succinylcarnitine (c4-dc) are associated with decreased GBM risk.ConclusionIn conclusion, this study sheds light on the intricate interplay between CSF metabolites and GBM, offering novel perspectives on disease mechanisms and potential treatment avenues. By elucidating the role of CSF metabolites in GBM pathogenesis, this research contributes to the advancement of diagnostic capabilities and targeted therapeutic interventions for this aggressive brain tumor. Further exploration of these findings may lead to improved management strategies and better outcomes for patients with GBM.

Improving prediction models of amyotrophic lateral sclerosis (ALS) using polygenic, pre-existing conditions, and survey-based risk scores in the UK Biobank.

Amyotrophic lateral sclerosis (ALS) causes profound impairments in neurological function, and a cure for this devastating disease remains elusive. This study aimed to identify pre-disposing genetic, phenotypic, and exposure-related factors for amyotrophic lateral sclerosis using multi-modal data and assess their joint predictive potential. Utilizing data from the UK (United Kingdom) Biobank, we analyzed an unrelated set of 292 ALS cases and 408,831 controls of European descent. Two polygenic risk scores (PRS) are constructed: "GWAS Hits PRS" and "PRS-CS," reflecting oligogenic and polygenic ALS risk profiles, respectively. Time-restricted phenome-wide association studies (PheWAS) were performed to identify pre-existing conditions increasing ALS risk, integrated into phenotypic risk scores (PheRS). A poly-exposure score ("PXS") captures the influence of environmental exposures measured through survey questionnaires. We evaluate the performance of these scores for predicting ALS incidence and stratifying risk, adjusting for baseline demographic covariates. Both PRSs modestly predicted ALS diagnosis but with increased predictive power when combined (covariate-adjusted receiver operating characteristic [AAUC] = 0.584 [0.525, 0.639]). PheRS incorporated diagnoses 1year before ALS onset (PheRS1) modestly discriminated cases from controls (AAUC = 0.515 [0.472, 0.564]). The "PXS" did not significantly predict ALS. However, a model incorporating PRSs and PheRS1 improved the prediction of ALS (AAUC = 0.604 [0.547, 0.667]), outperforming a model combining all risk scores. This combined risk score identified the top 10% of risk score distribution with a fourfold higher ALS risk (95% CI [2.04, 7.73]) versus those in the 40%-60% range. By leveraging UK Biobank data, our study uncovers pre-disposing ALS factors, highlighting the improved effectiveness of multi-factorial prediction models to identify individuals at highest risk for ALS.

The effect of inflammatory cytokines on the risk of hypertrophic scar: a mendelian randomization study.

Hypertrophic scar (HS) results from burns or trauma, causing aesthetic and functional issues. However, observational studies have linked inflammatory cytokines to HS, but the causal pathways involved are unclear. We aimed to determine how circulating inflammatory cytokines contribute to HS formation. Two-sample Mendelian randomization (MR) was used to identify genetic variants associated with hypertrophic scar in a comprehensive, publicly available genome-wide association study (GWAS) involving 766 patients and 207,482 controls of European descent. Additionally, data on 91 plasma proteins were drawn from a GWAS summary involving 14,824 healthy participants. Causal relationships between exposures and outcomes were investigated primarily using the inverse variance weighted (IVW) method. Furthermore, a suite of sensitivity analyses, including MR‒Egger and weighted median approaches, were concurrently employed to fortify the robustness of the conclusive findings. Finally, reverse MR analysis was conducted to evaluate the plausibility of reverse causation between hypertrophic scar and the cytokines identified in our study. In inflammatory cytokines, there was evidence of inverse associations of osteoprotegerin(OPG) levels(OR = 0.59, 95% CI = 0.41 ∼ 0.85, p = 0.01), and leukemia inhibitory factor(LIF) levels(OR = 0.51, 95% CI = 0.32 ∼ 0.82, p = 0.01) are a nominally negative association with hypertrophic scar risk, while CUB domain-domain-containing protein 1(CDCP1) level(OR = 0.59, 95% CI = 0.41 ∼ 0.85, p = 0.01) glial cell line-derived neurotrophic factor(GDNF) levels(OR = 1.42, 95% CI = 1.03 ∼ 1.96, p = 0.01) and programmed cell death 1 ligand 1(PD-L1) levels(OR = 1.47, 95% CI = 1.92 ∼ 2.11, p = 0.04) showed a positive association with hypertrophic scar risk. These associations were similar in the sensitivity analyses. According to our MR findings, OPG and LIF have a protective effect on hypertrophic scar, while CDCP1, GDNF, and PD-L1 have a risk-increasing effect on Hypertrophic scar. Our study adds to the current knowledge on the role of specific inflammatory biomarker pathways in hypertrophic scar. Further validation is needed to assess the potential of these cytokines as pharmacological or lifestyle targets for hypertrophic scar prevention and treatment.

Undetected Association Between Fatty Acids and Dementia with Lewy Bodies: A Bidirectional Two-Sample Mendelian Randomization Study.

Although observational studies indicated connections between fatty acids (FAs) and Alzheimer's disease and dementia, uncertainty persists regarding how these relationships extend to dementia with Lewy bodies (DLB). To explore the potential causal relationships between FAs and the development of DLB, thus clarifying these associations using genetic instruments to infer causality. We applied a two-sample Mendelian randomization (MR) and multivariable Mendelian randomization (MVMR) approach. Genetic data were obtained from a DLB cohort, comprising 2,591 cases and 4,027 controls of European descent. Eight FAs, including linoleic acid, docosahexaenoic acid, monounsaturated fatty acid, omega-3 fatty acid, omega-6 fatty acid, polyunsaturated fatty acid, saturated fatty acid, and total fatty acid, were procured from a comprehensive GWAS of metabolic biomarkers of UK Biobank, conducted by Nightingale Health in 2020 (met-d), involving 114,999 individuals. Our analysis included inverse-variance weighted, MR-Egger, weighted-median, simple mode, and weighted-mode MR estimates. Cochran's Q-statistics, MR-PRESSO, and MR-Egger intercept test were used to quantify the heterogeneity and horizontal pleiotropy of instrumental variables. Only linoleic acid showed a significant genetic association with the risk of developing DLB in the univariate MR. The odds ratio for linoleic acid was 1.337 with a 95% confidence interval of 1.019-1.756 (pIVW = 0.036). Results from the MVMR showed that no FAs were associated with the incidence of DLB. The results did not support the hypothesis that FAs could reduce the risk of developing DLB. However, elucidating the relationship between FAs and DLB risk holds potential implications for informing dietary recommendations and therapeutic approaches in DLB.

Exploring genetic association of systemic iron status and risk with incidence of diabetic neuropathy

BackgroundDiabetic neuropathy (DN), a frequent complication in individuals with diabetes mellitus (DM), is hypothesized to have a correlation with systemic iron status, though the nature of this relationship remains unclear. This study employs two-sample Mendelian randomization (MR) analysis to explore this potential genetic association.MethodsWe used genetic instruments significant associated with iron status including serum iron, ferritin, transferrin, and transferrin saturation, derived from an extensive Genome-Wide Association Study (GWAS) undertaken by the Genetics of Iron Status Consortium, involving a cohort of 48,972 European ancestry individuals. Summary statistics for DN were collected from a public GWAS, including 1,415 patients and 162,201 controls of European descent. Our MR analysis used the inverse-variance-weighted (IVW) method, supplemented by MR-Egger, weighted-median (WM) methods, Cochran’s Q test, MR-Egger intercept analysis, MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) method, and leave-one-out analysis to ensure robustness and consistency of the findings.ResultsNo genetic causal relationship was found between iron status markers and DN (all IVW p value > 0.05). Interestingly, a causative effect of DN on ferritin (IVW: OR = 0.943, 95% CI = 0.892–0.996, p = 0.035) and transferrin saturation (IVW: OR = 0.941, 95% CI = 0.888–0.998, p = 0.044) emerged. Sensitivity analyses confirmed the absence of significant heterogeneity and horizontal pleiotropy.ConclusionWhile systemic iron status was not found to be causally related to DN, our findings suggest that DN may increase the risk of iron deficiency. These results provide further evidence supporting iron supplementation in patients with DN.

The Contribution of Mosaic Chromosomal Alterations to Schizophrenia

BackgroundMosaic chromosomal alterations are implicated in neuropsychiatric disorders, but the contribution to schizophrenia (SCZ) risk for somatic copy number variations (sCNVs) emerging in early developmental stages has not been fully established. MethodsWe analyzed blood-derived genotype arrays from 9715 patients with SCZ and 28,822 control participants of Chinese descent using a computational tool (MoChA) based on long-range chromosomal information to detect mosaic chromosomal alterations. We focused on probable early developmental sCNVs through stringent filtering. We assessed the burden of sCNVs across varying cell fraction cutoffs, as well as the frequency with which genes were involved in sCNVs. We integrated this data with the PGC (Psychiatric Genomics Consortium) dataset, which comprises 12,834 SCZ cases and 11,648 controls of European descent, and complemented it with genotyping data from postmortem brain tissue of 936 participants (449 cases and 487 controls). ResultsPatients with SCZ had a significantly higher somatic losses detection rate than control participants (1.00% vs. 0.52%; odds ratio = 1.91; 95% CI, 1.47–2.49; two-sided Fisher’s exact test, p = 1.49 × 10−6). Further analysis indicated that the odds ratios escalated proportionately (from 1.91 to 2.78) with the increment in cell fraction cutoffs. Recurrent sCNVs associated with SCZ (odds ratio > 8; Fisher’s exact test, p < .05) were identified, including notable regions at 10q21.1 (ZWINT), 3q26.1 (SLITRK3), 1q31.1 (BRINP3) and 12q21.31-21.32 (MGAT4C and NTS) in the Chinese cohort, and some regions were validated with PGC data. Cross-tissue validation pinpointed somatic losses at loci like 1p35.3-35.2 and 19p13.3-13.2. ConclusionsThe study highlights the significant impact of mosaic chromosomal alterations on SCZ, suggesting their pivotal role in the disorder’s genetic etiology.

Evidence supported by Mendelian randomization: impact on inflammatory factors in knee osteoarthritis.

Prior investigations have indicated associations between Knee Osteoarthritis (KOA) and certain inflammatory cytokines, such as the interleukin series and tumor necrosis factor-alpha (TNFα). To further elaborate on these findings, our investigation utilizes Mendelian randomization to explore the causal relationships between KOA and 91 inflammatory cytokines. This two-sample Mendelian randomization utilized genetic variations associated with KOA from a large, publicly accessible Genome-Wide Association Study (GWAS), comprising 2,227 cases and 454,121 controls of European descent. The genetic data for inflammatory cytokines were obtained from a GWAS summary involving 14,824 individuals of European ancestry. Causal relationships between exposures and outcomes were primarily investigated using the inverse variance weighted method. To enhance the robustness of the research results, other methods were combined to assist, such as weighted median, weighted model and so on. Multiple sensitivity analysis, including MR-Egger, MR-PRESSO and leave one out, was also carried out. These different analytical methods are used to enhance the validity and reliability of the final results. The results of Mendelian randomization indicated that Adenosine Deaminase (ADA), Fibroblast Growth Factor 5(FGF5), and Hepatocyte growth factor (HFG) proteins are protective factors for KOA (IVWADA: OR = 0.862, 95% CI: 0.771-0.963, p = 0.008; IVWFGF5: OR = 0.850, 95% CI: 0.764-0.946, p = 0.003; IVWHFG: OR = 0.798, 95% CI: 0.642-0.991, p = 0.042), while Tumor necrosis factor (TNFα), Colony-stimulating factor 1(CSF1), and Tumor necrosis factor ligand superfamily member 12(TWEAK) proteins are risk factors for KOA. (IVWTNFα: OR = 1.319, 95% CI: 1.067-1.631, p = 0.011; IVWCSF1: OR = 1.389, 95% CI: 1.125-1.714, p = 0.002; IVWTWEAK: OR = 1.206, 95% CI: 1.016-1.431, p = 0.032). The six proteins identified in this study demonstrate a close association with the onset of KOA, offering valuable insights for future therapeutic interventions. These findings contribute to the growing understanding of KOA at the microscopic protein level, paving the way for potential targeted therapeutic approaches.

Abstract 7002: RNA m6A modification and lung cancer risk: An epitranscriptome-wide association study

Abstract N6-Methyladenosine (m6A), the most prevalent epitranscriptomic modification in eukaryotic mRNA, determines the fate of target RNAs. Key m6A regulators have been elucidated to be essential for lung cancer cell proliferation. However, the relationship between individual m6A markers and lung cancer risk remains inadequately explored. We conducted an epitranscriptome-wide association study (EpiTWAS) to investigate genetically predicted m6A in association with lung cancer risk. Genetic and m6A data of 30 lung, 12 heart, 28 muscle, and 50 brain tissues from 87 donors predominantly of European ancestry were obtained from Genotype-Tissue Expression (GTEx). For each m6A marker, we built a single-tissue model via elastic net, focusing on lung tissue, and a cross-tissue model through the unified test for molecular signatures (UTMOST) approach, capturing genetic influences on m6A shared by lung and other tissues. SPrediXcan was used to apply these models to data of genome-wide association studies (GWAS) among 38,422 lung cancer cases and 677,930 controls of European descent from International Lung Cancer Consortium (ILCCO), UK Biobank, and FinnGen. For m6A markers significantly associated with lung cancer risk at false discovery rate (FDR)&amp;lt;0.05, we assessed the differential expression of proteins encoded by their target mRNAs in lung cancer versus adjacent normal tissues (200 pairs), using data from Clinical Proteomic Tumor Analysis Consortium (CPTAC). Of the 38,841 high-quality m6A markers in 11,715 genes analyzed, prediction models were built for 6,809 m6A markers in 4,548 genes with performance of R&amp;gt;0.1 (P&amp;lt;0.05), ~85.2% (5,801) of which were single-tissue models. Among these, 28 m6A markers in 26 genes were significantly associated with overall lung cancer risk (FDR&amp;lt;0.05). Notably, 12 (~43%) of these markers in 12 loci are &amp;gt;2 megabases away from any of GWAS-identified lung cancer risk variants. When conditioning on nearby GWAS signals, these 12 associations did not change materially, whereas 15 of the remaining 16 associations lost statistical significance. Analyses by lung cancer histology and smoking status revealed no significant heterogeneity among the 28 associations but identified eight additional m6A markers significantly (FDR&amp;lt;0.05) associated with the risk of adenocarcinoma (n=2), squamous cell carcinoma (n=3), and overall lung cancer among ever- (n=2) or never-smokers (n=1). Of the 33 target RNAs of those 36 m6A markers, 30 encode proteins and 22 of these proteins displayed a significant tumor-normal differential expression at fold change &amp;gt;1.5 and FDR&amp;lt;0.05 in CPTAC lung tissue data. Our study demonstrates the ability of EpiTWAS to decipher GWAS loci and uncover signals potentially missed by GWAS. Our results imply that certain m6A markers may impact lung cancer risk by modulating mRNA translation, underscoring the need for further research to fully unravel the role of m6A in lung cancer etiology. Citation Format: Yaohua Yang, Yaxin Chen, Yawen Qi, Hongmo Liu, Guochong Jia, Jie Ping, Xiao-Ou Shu, Wei Zheng, Weimin Li, Jirong Long, Qiuyin Cai. RNA m6A modification and lung cancer risk: An epitranscriptome-wide association study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7002.

Mendelian randomization analysis to elucidate the causal relationship between small molecule metabolites and ovarian cancer risk

BackgroundSmall molecule metabolites are potential biomarkers for ovarian cancer. However, the causal relationship between small molecule metabolites and ovarian cancer remains unclear.MethodsSingle nucleotide polymorphisms (SNPs) correlated with 53 distinct small molecule metabolites were identified as instrumental variables (IVs) from comprehensive genome-wide association studies. Aggregate data encompassing 25,509 cases of ovarian cancer and 40,941 controls of European descent were procured from the Ovarian Cancer Association Consortium. To evaluate causative associations, four Mendelian randomization techniques—including inverse-variance weighted, weighted median, maximum likelihood, and MR-Egger regression—were employed.ResultsIn total, 242 SNPs were delineated as IVs for the small molecule metabolites under consideration. A significant association with the overarching risk of ovarian cancer was observed for six distinct metabolites. Hexadecenoylcarnitine and methioninesulfoxide were associated with a 32% and 31% reduced risk, respectively. Fifteen metabolites were linked to subtype ovarian cancers. For instance, both methionine sulfoxide and tetradecanoyl carnitine exhibited an inverse association with the risk of clear cell and high-grade serous ovarian cancers. Conversely, tryptophan demonstrated a 1.72-fold elevated risk for endometrioid ovarian cancer.ConclusionThis study identified several metabolites with putative causal effects on ovarian cancer risk using Mendelian randomization analysis. The findings provide insight into the etiological role of small molecule metabolites and highlight potential early detection biomarkers for ovarian cancer. Subsequent investigations are imperative to corroborate these findings and elucidate the underlying pathophysiological mechanisms.

Cannabis use and the risk of primary open-angle glaucoma: a Mendelian randomization study

Several observational studies have investigated the association between cannabis use and intraocular pressure, but its association with primary open-angle glaucoma (POAG) remains unclear. In this study, we leveraged human genetic data to assess through Mendelian randomization (MR) whether cannabis use affects POAG. We used five single-nucleotide polymorphisms (SNPs) associated with lifetime cannabis use (P-value < 5 × 10–8) from a genome-wide association study (GWAS) (N = 184,765) by the International Cannabis Consortium, 23andMe, and UK Biobank and eleven SNPs associated with cannabis use disorder (P-value < 5 × 10–7) from a GWAS meta-analysis of (17,068 cases and 357,219 controls of European descent) from Psychiatric Genomics Consortium Substance Use Disorders working group, Lundbeck Foundation Initiative for Integrative Psychiatric Research, and deCode. We associated the selected five SNPs from the GWAS of lifetime cannabis use and the eleven SNPs from the GWAS of cannabis use disorder, with the largest to date GWAS meta-analysis of POAG (16,677 cases and 199,580 controls). MR analysis suggested no evidence for a causal association of lifetime cannabis use and cannabis use disorder with POAG (odds ratio (OR) of outcome per doubling of the odds of exposure (95% confidence interval): 1.04 (0.88; 1.23) for lifetime cannabis use and 0.97 (0.92; 1.03) for cannabis use disorder). Sensitivity analyses to address pleiotropy and weak instrument bias yielded similar estimates to the primary analysis. In conclusion, our results do not support a causal association between cannabis use and POAG.

Integrating genomics and proteomics data to identify candidate plasma biomarkers for lung cancer risk among European descendants.

Plasma proteins are potential biomarkers for complex diseases. We aimed to identify plasma protein biomarkers for lung cancer. We investigated genetically predicted plasma levels of 1130 proteins in association with lung cancer risk among 29,266 cases and 56,450 controls of European descent. For proteins significantly associated with lung cancer risk, we evaluated associations of genetically predicted expression of their coding genes with the risk of lung cancer. Nine proteins were identified with genetically predicted plasma levels significantly associated with overall lung cancer risk at afalse discovery rate (FDR) of <0.05. Proteins C2, MICA, AIF1, and CTSH were associated with increased lung cancer risk, while proteins SFTPB, HLA-DQA2, MICB, NRP1, and GMFG were associated with decreased lung cancer risk. Stratified analyses by histological types revealed the cross-subtype consistency of these nine associations and identified an additional protein, ICAM5, significantly associated with lung adenocarcinoma risk (FDR < 0.05). Coding genes of NRP1 and ICAM5 proteinsare located at two loci that have never been reported by previous GWAS. Genetically predicted blood levels of genes C2, AIF1, and CTSH were associated with lung cancer risk, in directions consistent with those shown in protein-level analyses. Identification of novel plasma protein biomarkers provided new insights into the biology of lung cancer.

Associations between adiposity, diabetes, lifestyle factors and the risk of gliomas.

Despite numerous observational studies linking adiposity, diabetes, and lifestyle factors with gliomas, the causal associations between them remain uncertain. This study aimed to use two-sample Mendelian randomization (MR) analysis to investigate whether these associations are causal. Specifically, independent genetic variants in body mass index (BMI), waist circumference (WC), type 2 diabetes (T2D), smoking, alcohol, and coffee consumption were extracted from the published genome-wide association studies (GWASs) with genome-wide significance. The corresponding summary-level data for gliomas were available from a GWAS of 1,856 cases and 4,955 controls of European descent from the GliomaScan consortium. Additionally, glioma pathogenesis-related protein 1 data were used for validation, and Radial MR analysis was conducted to examine the potential outlier single-nucleotide polymorphisms (SNPs). One standard deviation (SD) increase in BMI had an odds ratio (OR) of 1.392 (95% confidence interval (CI), 0.935-2.071) for gliomas, while one SD increase in WC had an OR of 0.967 (95% CI, 0.547-1.710). For T2D, a one-unit increase in log-transformed OR had an OR of 0.923 (95% CI, 0.754-1.129). The prevalence of smoking initiation had an OR of 1.703 (95% CI, 0.871-3.326) for gliomas, while the prevalence of alcohol intake frequency had an OR of 0.806 (95% CI, 0.361-1.083), and the prevalence of coffee intake had an OR of 0.268 (95% CI, 0.033-2.140) for gliomas. This study provides evidence that adiposity, T2D, smoking, alcohol drinking, and coffee intake do not play causal roles in the development of gliomas. The findings highlight the importance of reconsidering causal relationships in epidemiological research to better understand the risk factors and prevention strategies for gliomas.

Sleep traits, fat accumulation, and glycemic traits in relation to gastroesophageal reflux disease: A Mendelian randomization study.

Sleep traits, fat accumulation, and glycemic traits are associated with gastroesophageal reflux disease (GERD) in observational studies. However, whether their associations are causal remains unknown. We performed a Mendelian randomization (MR) study to determine these causal relationships. Independent genetic variants associated with insomnia, sleep duration, short sleep duration, body fat percentage, visceral adipose tissue (VAT) mass, type 2 diabetes, fasting glucose, and fasting insulin at the genome-wide significance level were selected as instrumental variables. Summary-level data for GERD were derived from a genome-wide association meta-analysis including 78,707 cases and 288,734 controls of European descent. Inverse variance weighted (IVW) was used for the main analysis, with weighted median and MR-Egger as complements to IVW. Sensitivity analyses were performed using Cochran's Q test, MR-Egger intercept test, and leave-one-out analysis to estimate the stability of the results. The MR study showed the causal relationships of genetically predicted insomnia (odds ratio [OR] = 1.306, 95% confidence interval [CI] 1.261 to 1.352; p = 2.24 × 10-51), short sleep duration (OR = 1.304, 95% CI: 1.147 to 1.483, p = 4.83 × 10-5), body fat percentage (OR = 1.793, 95% CI 1.496 to 2.149; p = 2.68 × 10-10), and visceral adipose tissue (OR = 2.090, 95% CI 1.963 to 2.225; p = 4.42 × 10-117) with the risk of GERD. There was little evidence for causal associations between genetically predicted glycemic traits and GERD. In multivariable analyses, genetically predicted VAT accumulation, insomnia, and decreased sleep duration were associated with an increased risk of GERD. This study suggests the possible roles of insomnia, short sleep, body fat percentage, and visceral adiposity in the development of GERD.

Inflammatory bowel disease and risk of coronary heart disease : AMendelian randomization study.

Inflammatory bowel disease (IBD), including ulcerative colitis (UC) and Crohn's disease (CD), has been reported to be associated with an increased risk of coronary heart disease (CHD); however, the causal link between IBD and CHD is unclear. We performed Mendelian randomization (MR) analysis to investigate the association between genetically predicted IBD and CHD risk. Exposure summary data were obtained from genome-wide association studies (GWAS) with cohorts of IBD (12,882cases and 21,770 controls), UC (6968cases and 20,464 controls), and CD (5956cases and 14,927 controls) of European descent to identify single nucleotide polymorphisms (SNPs) as instrumental variables. Outcome summary data were obtained from ameta-analysis of 22GWAS including 22,233cases and 64,762 controls of European descent. To estimate MR, four methods were used, including inverse variance-weighted (IVW), MR-Egger, simple mode, and weighted median methods. Sensitivity analysis was also performed. The Bonferroni method was used to correct the bias of multiple testing. Three sets of SNPs (69SNPs of IBD, 40SNPs of UC, and 58SNPs of CD) were used to estimate the causal effect between genetically predicted IBD and CHD. Using the IVW method, we found that no causal relationship between genetically predicted IBD and CHD after Bonferroni correction, and there was no causal relationship between UC/CD and the development of CHD. No evidence of significant heterogeneity and pleiotropy was found. The results of this study suggested that genetically predicted IBD may have no causal effect on CHD risk in apopulation with European ancestry.

Genetically Predicted Circulating Concentrations of Alanine and Alanine Aminotransferase Were Associated with Prostate Cancer Risk.

Prostate cancer is one of the leading malignancies in men worldwide. Previous observational studies have linked amino acids and transaminase with altered risk of prostate cancer. However, whether these associations were causal remained unclear. Therefore, we conducted a Mendelian randomization (MR) to assess their potential causal associations. Summary-level data for prostate cancer were obtained from a meta-analysis of genome-wide association studies (GWAS) including 79,148 prostate cancer cases and 61,106 controls of European descent. Instrumental variables (IVs) of amino acids and alanine aminotransferase (ALT) were obtained from a GWAS of 86,507 European individuals and a GWAS of 312,572 participants from the UK Biobank, respectively. MR analyses were performed using inverse-variance-weighted (IVW), likelihood-based, MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test and MR-Egger regression. Genetically predicted circulating concentrations of alanine were associated with an increased risk of prostate cancer (odds ratio (OR): 1.16, 95% confidence interval (CI): 1.01-1.33, P=0.037 by IVW). Consistently, genetically predicted ALT was inversely associated with the risk of prostate cancer (OR: 0.43, 95% CI: 0.27-0.68, P=3.28×10-4 by IVW). MR-Egger regression did not indicate evidence of directional pleiotropy and sensitivity analyses yielded consistent associations. Our study revealed that genetically predicted circulating alanine and ALT levels were associated with an altered risk of prostate cancer, suggesting their potential roles in the development of prostate cancer. Whether targeting alanine, ALT or its downstream effectors are helpful in reducing prostate cancer incidence warrants further investigation.

Adiposity, diabetes, lifestyle factors and risk of gastroesophageal reflux disease: a Mendelian randomization study

Adiposity, diabetes, and lifestyle factors are linked to gastroesophageal reflux disease (GERD) in observational studies. We conducted a two-sample Mendelian randomization analysis to determine whether those associations are causal. Independent genetic variants associated with body mass index (BMI), waist circumference (with and without adjustment for BMI), type 2 diabetes, smoking, and alcohol, coffee and caffeine consumption at the genome-wide significance level were selected as instrumental variables. Summary-level data for GERD were available from a genome-wide association meta-analysis of 71,522 GERD cases and 261,079 controls of European descent from the UK Biobank and QSkin Sun and Health studies. The odds ratio (OR) of GERD was 1.49 (95% confidence interval (CI), 1.40–1.60) for one standard deviation (SD) increase in BMI, 1.07 (95% CI, 1.04–1.10) for one-unit increase in log-transformed OR of type 2 diabetes, and 1.41 (95% CI, 1.31–1.52) for one SD increase in prevalence of smoking initiation. There were suggestive associations with GERD for higher genetically predicted waist circumference (OR per one SD increase, 1.14, 95% CI, 1.02–1.26) and caffeine consumption (OR per 80 mg increase, 1.08, 95% CI, 1.02–1.15). Genetically predicted waist circumference adjusted for BMI, alcohol or coffee consumption was not associated GERD. This study suggests causal roles of adiposity, diabetes, and smoking, and a possible role of high caffeine consumption in the development of GERD.

Hepcidin-regulating iron metabolism genes and pancreatic ductal adenocarcinoma: a pathway analysis of genome-wide association studies

Epidemiological studies have suggested positive associations for iron and red meat intake with risk of pancreatic ductal adenocarcinoma (PDAC). Inherited pathogenic variants in genes involved in the hepcidin-regulating iron metabolism pathway are known to cause iron overload and hemochromatosis. The objective of this study was to determine whether common genetic variation in the hepcidin-regulating iron metabolism pathway is associated with PDAC. We conducted a pathway analysis of the hepcidin-regulating genes using single nucleotide polymorphism (SNP) summary statistics generated from 4 genome-wide association studies in 2 large consortium studies using the summary data-based adaptive rank truncated product method. Our population consisted of 9253 PDAC cases and 12,525 controls of European descent. Our analysis included 11 hepcidin-regulating genes [bone morphogenetic protein 2 (BMP2), bone morphogenetic protein 6 (BMP6), ferritin heavy chain 1 (FTH1), ferritin light chain (FTL), hepcidin (HAMP), homeostatic iron regulator (HFE), hemojuvelin (HJV), nuclear factor erythroid 2-related factor 2 (NRF2), ferroportin 1 (SLC40A1), transferrin receptor 1 (TFR1), and transferrin receptor 2 (TFR2)] and their surrounding genomic regions (±20 kb) for a total of 412 SNPs. The hepcidin-regulating gene pathway was significantly associated with PDAC (P=0.002), with the HJV, TFR2, TFR1, BMP6, and HAMP genes contributing the most to the association. Our results support that genetic susceptibility related to the hepcidin-regulating gene pathway is associated with PDAC risk and suggest a potential role of iron metabolism in pancreatic carcinogenesis. Further studies are needed to evaluate effect modification by intake of iron-rich foods on this association.

Mendelian randomization analyses reveal novel drug targets for anorexia nervosa

Among all psychiatric disorders, anorexia nervosa (AN) has the highest mortality rate. However, there is still no pharmacological therapy for AN. The human plasma proteome may be a great cornerstone for the development of new drugs against AN. Here we performed a Mendelian randomization (MR) analysis to identify causal risk proteins for AN. Exposure data were extracted from a large genome-wide association study (GWAS) of 2994 plasma proteins in 3301 subjects of European descent, while outcome data were obtained from another GWAS of AN (16,992 cases and 55,525 controls of European descent). MR analyses were performed using the inverse-variance weighted (IVW) method and other sensitivity analysis methods. Using single nucleotide polymorphisms as instruments, this study suggested that high TXNDC12 levels were associated with a higher risk of AN (IVW Odd's ratio [OR]: 1.12; 95% confidence interval [CI]: 1.08–1.16; P = 2.35 × 10−10), while another protein ADH1B showed the opposite effect (IVW OR: 0.89; 95% CI: 0.85–0.93; P = 2.99 × 10−7). The causal associations were robust in multivariable models, genome-wide significant models, and with additional MR methods. No pleiotropy was observed. Our findings suggest that TXNDC12 was associated with a high risk of AN, while AHD1B was associated with a low risk of AN. They might both have implications in AN by regulating the brain dopamine reward system. In combination with existing knowledge on AN, these proteins may be novel drug targets for AN treatment.

Abstract 882: Associations of genetically predicted blood protein biomarkers with pancreatic ductal adenocarcinoma risk: A study using comprehensive protein genetic prediction models

Abstract Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with few known risk factors and biomarkers. Identification of biomarkers is critical for understanding the pathogenesis of this deadly cancer and identifying high-risk individuals for close surveillance. Several blood protein biomarkers have been linked to PDAC in previous studies, but these studies have assessed only a limited number of protein biomarkers usually in small set(s) of samples. To identify novel circulating protein biomarkers of PDAC, we studied 8,275 cases and 6,723 controls of European descent from the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium. Leveraging genome and plasma proteome data of 2,841 healthy European descendants included in the INTERVAL study, we established models using four methods (best linear unbiased predictor, elastic net, LASSO, and top1) to predict protein levels based on genetic variants. For each protein, of the four sets of models developed, the model showing the highest prediction performance (R2) was retained. We selected 2,164 built protein models with a prediction performance (R2) of &amp;gt;0.01 for association analyses with PDAC risk. We observed associations between predicted concentrations of 14 proteins and PDAC risk at a false discovery rate of &amp;lt; 0.05, including those of eight proteins that showed a significant association after Bonferroni correction (2.31 × 10-5). These include Histo-blood group ABO system transferase encoded by ABO, which has been previously implicated as a potential target gene of PDAC risk variant identified in GWAS. Besides eight proteins that were previously reported in our earlier study using protein quantitative trait loci as instruments, we identified six novel proteins which have not been identified in previous studies. Six of the identified proteins showed positive associations and eight showed inverse associations (P-values from 2.62 × 10-4 to 5.71 × 10-21). In conclusion, we identified 14 protein biomarker candidates for PDAC risk, which if validated in future studies, may contribute to the etiological understanding of PDAC development. Citation Format: Dalia Ghoneim, Jingjing Zhu, Jihwan Ha, Praveen Surendran, Qizhi Cathy Yao, Tao Liu, Sarah Fahle, Adam Butterworth, Chong Wu, Lang Wu. Associations of genetically predicted blood protein biomarkers with pancreatic ductal adenocarcinoma risk: A study using comprehensive protein genetic prediction models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 882.

Cannabis Use, Pulmonary Function, and Lung Cancer Susceptibility: A Mendelian Randomization Study

IntroductionBecause of widespread use, understanding the pulmonary effects of cannabis use is important; but its role independent from tobacco smoking is yet to be elucidated. We used Mendelian randomization (MR) to assess the effect of genetic liability to lifetime cannabis use and cannabis use disorder on pulmonary function and lung cancer. MethodsWe used four single nucleotide polymorphisms associated with lifetime cannabis use (p value <5 × 10−8) from a genome-wide association study (GWAS) of 184,765 individuals of European descent from the International Cannabis Consortium, 23andme, and U.K. Biobank as instrumental variables. Seven single nucleotide polymorphisms (p value <5 × 10−8) were selected as instruments for cannabis use disorder from a GWAS meta-analysis of 17,068 European ancestry cases and 357,219 controls of European descent from Psychiatric Genomics Consortium Substance Use Disorders working group, Lundbeck Foundation Initiative for Integrative PsychiatricResearch, and deCode. To assess lung function, GWAS included 79,055 study participants of the SpiroMeta Consortium, and for lung cancer GWAS from the International Lung Cancer Consortium contained 29,266 cases and 56,450 controls. ResultsMR revealed that genetic liability to lifetime cannabis use was associated with increased risk of squamous cell carcinoma (OR = 1.22, 95%, confidence interval = 1.07–1.39, p value = 0.003, q value = 0.025). Pleiotropy-robust methods and positive and negative control analyses did not indicate bias in the primary analysis. ConclusionsThe findings of this MR analysis suggest evidence for a potential causal association between genetic liability for cannabis use and the risk of squamous cell carcinoma. Triangulating MR and observational studies and addressing orthogonal sources of bias are necessary to confirm this finding.