| 1. |
- Jiang, Fangyuan, et al.
(författare)
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Association between antibiotic use during early life and early-onset colorectal cancer risk overall and according to polygenic risk and FUT2 genotypes
- 2023
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Ingår i: International Journal of Cancer. - : John Wiley & Sons. - 0020-7136 .- 1097-0215. ; 153:9, s. 1602-1611
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Tidskriftsartikel (refereegranskat)abstract
- Early-onset colorectal cancer (EOCRC) has been increasing worldwide. Potential risk factors may have occurred in childhood or adolescence. We investigated the associations between early-life factors and EOCRC risk, with a particular focus on long-term or recurrent antibiotic use (LRAU) and its interaction with genetic factors. Data on the UK Biobank participants recruited between 2006 and 2010 and followed up to February 2022 were used. We used logistic regression to estimate adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) of the associations between LRAU during early life and EOCRC risk overall and by polygenic risk score (constructed by 127 CRC-related genetic variants) and Fucosyltransferase 2 (FUT2), a gut microbiota regulatory gene. We also assessed the associations for early-onset colorectal adenomas, as precursor lesion of CRC, to examine the effect of LRAU during early-life and genetic factors on colorectal carcinogenesis. A total of 113 256 participants were included in the analysis, with 165 EOCRC cases and 719 EOCRA cases. LRAU was nominally associated with increased risk of early-onset CRC (OR = 1.48, 95% CI = 1.01-2.17, P = .046) and adenomas (OR = 1.40, 95% CI = 1.17-1.68, P < .001). When stratified by genetic polymorphisms of FUT2, LRAU appeared to confer a comparatively greater risk for early-onset adenomas among participants with rs281377 TT genotype (OR = 1.10, 95% CI = 0.79-1.52, P = .587, for CC genotype; OR = 1.75, 95% CI = 1.16-2.64, P = .008, for TT genotype; Pinteraction = .089). Our study suggested that LRAU during early life is associated with increased risk of early-onset CRC and adenomas, and the association for adenomas is predominant among individuals with rs281377 TT/CT genotype. Further studies investigating how LRAU contributes together with genetic factors to modify EOCRC risk, particularly concerning the microbiome-related pathway underlying colorectal carcinogenesis, are warranted.
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| 2. |
- Repetto, Linda, et al.
(författare)
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Genetic mechanisms of 184 neuro-related proteins in human plasma.
- 2023
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Ingår i: medRxiv : the preprint server for health sciences. - : Cold Spring Harbor Laboratory.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Understanding the genetic basis of neuro-related proteins is essential for dissecting the disease etiology of neuropsychiatric disorders and other complex traits and diseases. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-related proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-related traits as well as complex diseases such as hypertension, high cholesterol, immune-related disorders, and psychiatric disorders. Integrating with established drug information, we validated 13 combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets for diseases and comorbidities. This consortium effort provides a large-scale proteogenomic resource for biomedical research.
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| 3. |
- Repetto, Linda, et al.
(författare)
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Unraveling Neuro-Proteogenomic Landscape and Therapeutic Implications for Human Behaviors and Psychiatric Disorders.
- 2023
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Ingår i: Nature Portfolio. - : Research Square Platform LLC.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioral traits and the disease etiology of neuropsychiatric disorders. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-related proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-related traits such as sleeping, smoking, feelings, alcohol intake, mental health, and psychiatric disorders. Integrating with established drug information, we validated 13 out of 13 matched combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets. This consortium effort provides a large-scale proteogenomic resource for biomedical research on human behaviors and other neuro-related phenotypes.
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| 4. |
- Yang, Zhijian, et al.
(författare)
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Genetic Landscape of the ACE2 Coronavirus Receptor
- 2022
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Ingår i: Circulation. - : Ovid Technologies (Wolters Kluwer Health). - 0009-7322 .- 1524-4539. ; 30:SUPPL 1, s. 36-36
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Tidskriftsartikel (refereegranskat)abstract
- Background: SARS-CoV-2, the causal agent of COVID-19, enters human cells using the ACE2 (angiotensin-converting enzyme 2) protein as a receptor. ACE2 is thus key to the infection and treatment of the coronavirus. ACE2 is highly expressed in the heart and respiratory and gastrointestinal tracts, playing important regulatory roles in the cardiovascular and other biological systems. However, the genetic basis of the ACE2 protein levels is not well understood.Methods: We have conducted the largest genome-wide association meta-analysis of plasma ACE2 levels in >28 000 individuals of the SCALLOP Consortium (Systematic and Combined Analysis of Olink Proteins). We summarize the cross-sectional epidemiological correlates of circulating ACE2. Using the summary statistics-based high-definition likelihood method, we estimate relevant genetic correlations with cardiometabolic phenotypes, COVID-19, and other human complex traits and diseases. We perform causal inference of soluble ACE2 on vascular disease outcomes and COVID-19 severity using mendelian randomization. We also perform in silico functional analysis by integrating with other types of omics data.Results: We identified 10 loci, including 8 novel, capturing 30% of the heritability of the protein. We detected that plasma ACE2 was genetically correlated with vascular diseases, severe COVID-19, and a wide range of human complex diseases and medications. An X-chromosome cis-protein quantitative trait loci-based mendelian randomization analysis suggested a causal effect of elevated ACE2 levels on COVID-19 severity (odds ratio, 1.63 [95% CI, 1.10-2.42]; P=0.01), hospitalization (odds ratio, 1.52 [95% CI, 1.05-2.21]; P=0.03), and infection (odds ratio, 1.60 [95% CI, 1.08-2.37]; P=0.02). Tissue- and cell type-specific transcriptomic and epigenomic analysis revealed that the ACE2 regulatory variants were enriched for DNA methylation sites in blood immune cells.Conclusions: Human plasma ACE2 shares a genetic basis with cardiovascular disease, COVID-19, and other related diseases. The genetic architecture of the ACE2 protein is mapped, providing a useful resource for further biological and clinical studies on this coronavirus receptor.
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| 5. |
- Zhang, Yazhou, et al.
(författare)
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A Dual Channel Cyber-Physical Transportation Network for Detecting Traffic Incidents and Driver Emotion
- 2023
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Ingår i: IEEE transactions on consumer electronics. - New York, NY : IEEE. - 0098-3063 .- 1558-4127. ; 70:1, s. 1766-1774
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Tidskriftsartikel (refereegranskat)abstract
- Intelligent traffic incident detection provides benefits such as minimizing traffic accidents and fuel consumption, reducing congestion, and enhancing transportation safety. Hence, traffic incident detection has been an active research area in customer-centric intelligent transportation systems (ITS). Given that a driver’s negative emotions (e.g. anger, nervousness) are often a main cause of traffic incidents, we argue there is a close relationship between traffic incident detection and driver emotion recognition. We propose a Dual channel Dual attention Graph Attention neTworks, termed DDGAT. Specifically, the traffic channel builds a sequential-based graph, where words are nodes and their co-occurrences are edges. In contrast, the emotion channel builds a syntactic-based graph with words as nodes and semantic dependencies as edges. The first attention mechanism automatically learns the importance of neighbors in different layers for different tasks. The second attention produces the attentive graph representation for both tasks. Experiments on two benchmarking datasets including GIIE and Twitter, show the effectiveness of the proposed model over state-of-the-art baselines in terms of micro F1 and H@1, with significant improvements of 3.5%, 3.2%, 2.0%, and 1.7%. © 2023 IEEE
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