Investigating the relationship between depression and breast cancer: observational and genetic analyses
暂无分享,去创建一个
J. Smoller | P. Kraft | Jiayuan Li | Xia Jiang | Wenqiang Zhang | Ben Zhang | Xueyao Wu | Y. Hao | Xunying Zhao | Jinyu Xiao | Li Zhang | Minghan Xu
[1] Peizhan Chen,et al. Major depression disorder may causally associate with the increased breast cancer risk: Evidence from two‐sample mendelian randomization analyses , 2022, Cancer medicine.
[2] M. Meaney,et al. A sex-specific genome-wide association study of depression phenotypes in UK Biobank , 2022, Molecular Psychiatry.
[3] Y. Mao,et al. Causal relationship between genetically predicted depression and cancer risk: a two-sample bi-directional mendelian randomization , 2022, BMC Cancer.
[4] A. Bhattacharjee,et al. Identification of key gene signatures for the overall survival of ovarian cancer , 2022, Journal of Ovarian Research.
[5] Shan Jiang,et al. GRAP2 is a prognostic biomarker and correlated with immune infiltration in lung adenocarcinoma , 2022, Journal of clinical laboratory analysis.
[6] D. Menon,et al. Unique diagnostic signatures of concussion in the saliva of male athletes: the Study of Concussion in Rugby Union through MicroRNAs (SCRUM) , 2021, British Journal of Sports Medicine.
[7] A. Jemal,et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries , 2021, CA: a cancer journal for clinicians.
[8] O. Andreassen,et al. The genetic architecture of human cortical folding , 2021, bioRxiv.
[9] Tae Young Lee,et al. The Role of Estrogen Receptors and Their Signaling across Psychiatric Disorders , 2020, International journal of molecular sciences.
[10] L. Liang,et al. Investigating asthma heterogeneity through shared and distinct genetics: Insights from genome-wide cross-trait analysis , 2020, Journal of Allergy and Clinical Immunology.
[11] Manuel A. R. Ferreira,et al. Age-of-onset information helps identify 76 genetic variants associated with allergic disease , 2020, PLoS genetics.
[12] O. Cases,et al. Cubilin, the intrinsic factor-vitamin B12 receptor in development and disease. , 2020, Current medicinal chemistry.
[13] J. Potash,et al. Minimal phenotyping yields genome-wide association signals of low specificity for major depression , 2020, Nature Genetics.
[14] John P. Rice,et al. Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression , 2020, Biological Psychiatry.
[15] Jack A. Taylor,et al. Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses , 2019, bioRxiv.
[16] D. Yablonski. Bridging the Gap: Modulatory Roles of the Grb2-Family Adaptor, Gads, in Cellular and Allergic Immune Responses , 2019, Front. Immunol..
[17] Max A. Little,et al. Genome-wide association study identifies genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates , 2019, Nature Communications.
[18] Y. Fang,et al. Integrative analyses of major histocompatibility complex loci in the genome-wide association studies of major depressive disorder , 2019, Neuropsychopharmacology.
[19] Dajiang J. Liu,et al. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use , 2018, Nature Genetics.
[20] Ji-Joon Song,et al. ANKRD9 is associated with tumor suppression as a substrate receptor subunit of ubiquitin ligase. , 2018, Biochimica et biophysica acta. Molecular basis of disease.
[21] Terrell Holloway,et al. HDAC2-dependent Antipsychotic-like Effects of Chronic Treatment with the HDAC Inhibitor SAHA in Mice , 2018, Neuroscience.
[22] Juan M. Astorga,et al. Breast Cancer and Its Relationship with the Microbiota , 2018, International journal of environmental research and public health.
[23] Jonathan P. Beauchamp,et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals , 2018, Nature Genetics.
[24] G. Alexander,et al. Genome-wide association study of habitual physical activity in over 377,000 UK Biobank participants identifies multiple variants including CADM2 and APOE , 2017, bioRxiv.
[25] B. Neale,et al. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases , 2018, Nature Genetics.
[26] Samuel E. Jones,et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry , 2018, bioRxiv.
[27] Warren W. Kretzschmar,et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression , 2017, Nature Genetics.
[28] Astrid Gall,et al. Ensembl 2018 , 2017, Nucleic Acids Res..
[29] Bogdan Pasaniuc,et al. Local genetic correlation gives insights into the shared genetic architecture of complex traits , 2016, bioRxiv.
[30] Gary D Bader,et al. Association analysis identifies 65 new breast cancer risk loci , 2017, Nature.
[31] T. Hsia,et al. Patients with uterine leiomyoma exhibit a high incidence but low mortality rate for breast cancer , 2017, Oncotarget.
[32] S. McWeeney,et al. REST corepressors RCOR1 and RCOR2 and the repressor INSM1 regulate the proliferation–differentiation balance in the developing brain , 2017, Proceedings of the National Academy of Sciences.
[33] M. Maes,et al. Depression in Cancer : the many biobehavioural pathways driving tumor progression , 2016 .
[34] Helen E. Parkinson,et al. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog) , 2016, Nucleic Acids Res..
[35] K. Rock,et al. Present Yourself! By MHC Class I and MHC Class II Molecules. , 2016, Trends in immunology.
[36] Cheng Quan,et al. 3DSNP: a database for linking human noncoding SNPs to their three-dimensional interacting genes , 2016, Nucleic Acids Res..
[37] G. Davey Smith,et al. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator , 2016, Genetic epidemiology.
[38] Yifeng Du,et al. Reproducibility of quantitative real-time PCR assay in microRNA expression profiling and comparison with microarray analysis in narcolepsy , 2015, SpringerPlus.
[39] K. Czene,et al. The Heritability of Breast Cancer among Women in the Nordic Twin Study of Cancer , 2015, Cancer Epidemiology, Biomarkers & Prevention.
[40] T. Lehtimäki,et al. Integrative approaches for large-scale transcriptome-wide association studies , 2015, Nature Genetics.
[41] Joseph K. Pickrell,et al. Detection and interpretation of shared genetic influences on 42 human traits , 2015, Nature Genetics.
[42] A. Moustafa,et al. The Cerebellum and Psychiatric Disorders , 2015, Front. Public Health.
[43] M. Daly,et al. An Atlas of Genetic Correlations across Human Diseases and Traits , 2015, Nature Genetics.
[44] G. Davey Smith,et al. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression , 2015, International journal of epidemiology.
[45] N. Timpson,et al. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors , 2015, European Journal of Epidemiology.
[46] P. Elliott,et al. UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age , 2015, PLoS medicine.
[47] S. Thompson,et al. Multivariable Mendelian Randomization: The Use of Pleiotropic Genetic Variants to Estimate Causal Effects , 2015, American journal of epidemiology.
[48] Xiaofeng Zhu,et al. Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension. , 2015, American journal of human genetics.
[49] M. Daly,et al. Genetic and Epigenetic Fine-Mapping of Causal Autoimmune Disease Variants , 2014, Nature.
[50] David C. Glahn,et al. Common genetic variants and gene expression associated with white matter microstructure in the human brain , 2014, NeuroImage.
[51] S. Nathanson,et al. Pathogenesis, prevention, diagnosis and treatment of breast cancer. , 2014, World journal of clinical oncology.
[52] P. Hogarth,et al. ZSWIM1: a novel biomarker in T helper cell differentiation. , 2014, Immunology letters.
[53] Peter Johansson,et al. Depression and cardiovascular disease: a clinical review. , 2014, European heart journal.
[54] Xiaowei Hu,et al. Identification of Aberrantly Expressed miRNAs in Gastric Cancer , 2014, Gastroenterology research and practice.
[55] S. Purcell,et al. Pleiotropy in complex traits: challenges and strategies , 2013, Nature Reviews Genetics.
[56] C. Wallace,et al. Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics , 2013, PLoS genetics.
[57] S. Natsugoe,et al. Clinical implication of HLA class I expression in breast cancer , 2011, BMC Cancer.
[58] M. Karin,et al. Expanding TRAF function: TRAF3 as a tri-faced immune regulator , 2011, Nature Reviews Immunology.
[59] Libing Song,et al. Knockdown of FLOT1 Impairs Cell Proliferation and Tumorigenicity in Breast Cancer through Upregulation of FOXO3a , 2011, Clinical Cancer Research.
[60] Ali M. Ardekani,et al. The Role of MicroRNAs in Human Diseases , 2010, Avicenna journal of medical biotechnology.
[61] Xiaoying Wu,et al. Expression and functions of the repressor element 1 (RE‐1)‐silencing transcription factor (REST) in breast cancer , 2010, Journal of cellular biochemistry.
[62] V. Pascual,et al. Assessing the human immune system through blood transcriptomics , 2010, BMC Biology.
[63] F. Oswald,et al. Expression of the Grb2-related RET adapter protein Grap-2 in human medullary thyroid carcinoma. , 2009, Cancer letters.
[64] A. Luder,et al. Amnionless (AMN) mutations in Imerslund–Gräsbeck syndrome may be associated with disturbed vitamin B12 transport into the CNS , 2008, Journal of Inherited Metabolic Disease.
[65] F. Buntinx,et al. A meta-analysis on depression and subsequent cancer risk , 2007, Clinical practice and epidemiology in mental health : CP & EMH.
[66] Manuel A. R. Ferreira,et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.
[67] S. Ebrahim,et al. 'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease? , 2003, International journal of epidemiology.
[68] P. Sullivan,et al. Genetic epidemiology of major depression: review and meta-analysis. , 2000, The American journal of psychiatry.
[69] T. Dinan,et al. Gutted! Unraveling the Role of the Microbiome in Major Depressive Disorder. , 2020, Harvard review of psychiatry.
[70] R. Marioni,et al. Edinburgh Research Explorer Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways , 2022 .
[71] Y. Gan,et al. Depression and the risk of breast cancer: a meta-analysis of cohort studies. , 2015, Asian Pacific journal of cancer prevention : APJCP.
[72] George Davey Smith,et al. Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology , 2008, Statistics in medicine.
[73] Hilde van der Togt,et al. Publisher's Note , 2003, J. Netw. Comput. Appl..