- See Also
-
Links
- “Predicting Political Beliefs With Polygenic Scores for Cognitive Performance and Educational Attainment”, Edwards et al 2024
- “Causal Interpretations of Family GWAS in the Presence of Heterogeneous Effects”, Veller et al 2023
- “Exploring Pleiotropy in Mendelian Randomization Analyses: What Are Genetic Variants Associated With ‘Cigarette Smoking Initiation’ Really Capturing?”, Reed et al 2023
- “Mendelian Randomization Supports Causality between Overweight Status and Accelerated Aging”, Chen et al 2023
- “Causal Relevance of Different Blood Pressure Traits on Risk of Cardiovascular Diseases: GWAS and Mendelian Randomization in 100,000 Chinese Adults”, Pozarickij et al 2023
- “Causal Association of Genetically Determined Circulating Vitamin D Metabolites and Calcium With Multiple Sclerosis in Participants of European Descent”, Zhang et al 2023
- “Leveraging Family Data to Design Mendelian Randomization That Is Provably Robust to Population Stratification”, LaPierre et al 2023
- “Effect of Basal Metabolic Rate on Lifespan: a Sex-Specific Mendelian Randomization Study”, Ng & Schooling 2023
- “Korea4K: Whole Genome Sequences of 4,157 Koreans With 107 Phenotypes Derived from Extensive Health Check-Ups”, Jeon et al 2022
- “Quantifying the Causal Impact of Biological Risk Factors on Healthcare Costs”, Lee et al 2022
- “Correction for Participation Bias in the UK Biobank Reveals Non-Negligible Impact on Genetic Associations and Downstream Analyses”, Schoeler et al 2022
- “Genome-Wide Association Study Meta-Analysis of Suicide Attempt in 43,871 Cases Identifies Twelve Genome-Wide Statistically-Significant Loci”, Docherty et al 2022
- “Multi-Ancestry GWAS of Major Depression Aids Locus Discovery, Fine-Mapping, Gene Prioritization, and Causal Inference”, Meng et al 2022
- “MRSL: A Phenome-Wide Causal Discovery Algorithm Based on GWAS Summary Data”, Hou et al 2022
- “The Contribution of Mate-Choice, Couple Convergence and Confounding to Assortative Mating”, Sjaarda & Kutalik 2022
- “Genome-Wide Association Study of Occupational Attainment As a Proxy for Cognitive Reserve”, Ko et al 2022
- “Sleep Duration and Brain Structure—Phenotypic Associations and Genotypic Covariance”, Fjell et al 2022
- “Mendelian Randomization of Genetically Independent Aging Phenotypes Identifies LPA and VCAM1 As Biological Targets for Human Aging”, Timmers et al 2022
- “Educational Attainment, Health Outcomes and Mortality: a Within-Sibship Mendelian Randomization Study”, Howe et al 2022
- “Polynomial Mendelian Randomization Reveals Widespread Non-Linear Causal Effects in the UK Biobank”, Sulc et al 2021
- “A Selection Pressure Landscape for 870 Human Polygenic Traits”, Song et al 2021
- “Genetically Proxied Diurnal Preference, Sleep Timing, and Risk of Major Depressive Disorder”, Daghlas et al 2021
- “The Relationship between Cannabis and Schizophrenia: a Genetically Informed Perspective”, Johnson et al 2021
- “Causal Relationships between Genetically Determined Metabolites and Human Intelligence: a Mendelian Randomization Study”, Yang et al 2021
- “Disentangling Sex Differences in the Shared Genetic Architecture of Post-Traumatic Stress Disorder, Traumatic Experiences, and Social Support With Body Size and Composition”, Carvalho et al 2021
- “Evidence for Shared Genetics between Physical Activity, Sedentary Behavior and Adiposity-Related Traits”, Schnurr et al 2020
- “A Genetic Perspective on the Association between Exercise and Mental Health in the Era of Genome-Wide Association Studies”, Geus 2020
- “Discovery of Rare Variants Associated With Blood Pressure Regulation through Meta-Analysis of 1.3 Million Individuals”, Surendran et al 2020
- “Genetic Predictors of Educational Attainment and Intelligence Test Performance Predict Voter Turnout”, Aarøe et al 2020
- “Use of Genetically Informed Methods to Clarify the Nature of the Association Between Cannabis Use and Risk for Schizophrenia”, Gillespie & Kendler 2020
- “Amyloid, Tau and Risk of Alzheimer’s Disease: a Mendelian Randomization Study”, Yeung et al 2020
- “An Exposure-Wide and Mendelian Randomization Approach to Identifying Modifiable Factors for the Prevention of Depression”, Choi et al 2020
- “Genome-Wide Meta-Analysis of Problematic Alcohol Use in 435,563 Individuals Yields Insights into Biology and Relationships With Other Traits”, Zhou et al 2020
- “Comprehensive Genomic Analysis of Dietary Habits in UK Biobank Identifies Hundreds of Genetic Associations”, Cole et al 2020
- “Mendelian Randomization Accounting for Correlated and Uncorrelated Pleiotropic Effects Using Genome-Wide Summary Statistics”, Morrison et al 2020
- “The Interplay between Host Genetics and the Gut Microbiome Reveals Common and Distinct Microbiome Features for Human Complex Diseases”, Xu et al 2019
- “Genetic Analysis Identifies Molecular Systems and Biological Pathways Associated With Household Income”, Hill et al 2019
- “Genome-Wide Association Study Identifies Genetic Loci for Self-Reported Habitual Sleep Duration Supported by Accelerometer-Derived Estimates”, Dashti et al 2019
- “Cannabis Use, Depression and Self-Harm: Phenotypic and Genetic Relationships”, Hodgson et al 2019
- “Schizophrenia Risk and Reproductive Success: a Mendelian Randomization Study”, Lawn et al 2019
- “Distinguishing Genetic Correlation from Causation across 52 Diseases and Complex Traits”, O’Connor & Price 2018
- “Using Genetic Data to Strengthen Causal Inference in Observational Research”, Pingault et al 2018
- “The Landscape of Pervasive Horizontal Pleiotropy in Human Genetic Variation Is Driven by Extreme Polygenicity of Human Traits and Diseases”, Jordan et al 2018
- “GWAS in 446,118 European Adults Identifies 78 Genetic Loci for Self-Reported Habitual Sleep Duration Supported by Accelerometer-Derived Estimates”, Dashti et al 2018
- “Meta-Analysis of Genome-Wide Association Studies for Height and Body Mass Index in ∼700,000 Individuals of European Ancestry”, Yengo et al 2018
- “A Genetic Perspective on the Relationship between Eudaimonic and Hedonic Well-Being”, Baselmans & Bartels 2018
- “Genome-Wide Analysis of Insomnia (N = 1,331,010) Identifies Novel Loci and Functional Pathways”, Jansen et al 2018
- “Detection of Widespread Horizontal Pleiotropy in Causal Relationships Inferred from Mendelian Randomization between Complex Traits and Diseases”, Verbanck et al 2018
- “GWAS of Lifetime Cannabis Use Reveals New Risk Loci, Genetic Overlap With Psychiatric Traits, and a Causal Influence of Schizophrenia”, Pasman et al 2018
- “Genome-Wide Association Meta-Analysis in 269,867 Individuals Identifies New Genetic and Functional Links to Intelligence”, Savage et al 2018
- “Meta-Analysis of Genome-Wide Association Studies for Height and Body Mass Index in ∼700000 Individuals of European Ancestry”, Yengo et al 2018
- “Fitness, Physical Activity, and Cardiovascular Disease: Longitudinal and Genetic Analyses in the UK Biobank Study”, Tikkanen et al 2017
- “Extending the MR-Egger Method for Multivariable Mendelian Randomization to Correct for Both Measured and Unmeasured Pleiotropy”, Rees et al 2017
- “Genomic Analyses for Age at Menarche Identify 389 Independent Signals and Indicate BMI-Independent Effects of Puberty Timing on Cancer Susceptibility”, Day et al 2016
- “Physical and Neurobehavioral Determinants of Reproductive Onset and Success”, Day et al 2016
- “Height, Body Mass Index, and Socioeconomic Status: Mendelian Randomization Study in UK Biobank”, Tyrrell 2016
- “Mendelian Randomization With Invalid Instruments: Effect Estimation and Bias Detection through Egger Regression (MR-Egger)”, Bowden et al 2015
- “Mendelian Randomization: Can Genetic Epidemiology Help Redress the Failures of Observational Epidemiology?”, Ebrahim & Smith 2007
- “Clustered Environments and Randomized Genes: A Fundamental Distinction between Conventional and Genetic Epidemiology”, Smith et al 2007
- “A Cautionary Note on the Use of Mendelian Randomization to Infer Causation in Observational Epidemiology”, Bochud et al 2007
- “Genetic Epidemiology and Public Health: Hope, Hype, and Future Prospects”, Smith et al 2005
- “What Can Mendelian Randomization Tell Us about Modifiable Behavioral and Environmental Exposures?”, Smith & Ebrahim 2005
- “A Primer on Why Microbiome Research Is Hard”
- Sort By Magic
- Wikipedia
- Miscellaneous
- Bibliography
See Also
Links
“Predicting Political Beliefs With Polygenic Scores for Cognitive Performance and Educational Attainment”, Edwards et al 2024
“Causal Interpretations of Family GWAS in the Presence of Heterogeneous Effects”, Veller et al 2023
Causal interpretations of family GWAS in the presence of heterogeneous effects
“Exploring Pleiotropy in Mendelian Randomization Analyses: What Are Genetic Variants Associated With ‘Cigarette Smoking Initiation’ Really Capturing?”, Reed et al 2023
“Mendelian Randomization Supports Causality between Overweight Status and Accelerated Aging”, Chen et al 2023
Mendelian Randomization supports causality between overweight status and accelerated aging
“Causal Relevance of Different Blood Pressure Traits on Risk of Cardiovascular Diseases: GWAS and Mendelian Randomization in 100,000 Chinese Adults”, Pozarickij et al 2023
“Causal Association of Genetically Determined Circulating Vitamin D Metabolites and Calcium With Multiple Sclerosis in Participants of European Descent”, Zhang et al 2023
“Leveraging Family Data to Design Mendelian Randomization That Is Provably Robust to Population Stratification”, LaPierre et al 2023
“Effect of Basal Metabolic Rate on Lifespan: a Sex-Specific Mendelian Randomization Study”, Ng & Schooling 2023
Effect of basal metabolic rate on lifespan: a sex-specific Mendelian Randomization study
“Korea4K: Whole Genome Sequences of 4,157 Koreans With 107 Phenotypes Derived from Extensive Health Check-Ups”, Jeon et al 2022
“Quantifying the Causal Impact of Biological Risk Factors on Healthcare Costs”, Lee et al 2022
Quantifying the causal impact of biological risk factors on healthcare costs
“Correction for Participation Bias in the UK Biobank Reveals Non-Negligible Impact on Genetic Associations and Downstream Analyses”, Schoeler et al 2022
“Genome-Wide Association Study Meta-Analysis of Suicide Attempt in 43,871 Cases Identifies Twelve Genome-Wide Statistically-Significant Loci”, Docherty et al 2022
“Multi-Ancestry GWAS of Major Depression Aids Locus Discovery, Fine-Mapping, Gene Prioritization, and Causal Inference”, Meng et al 2022
“MRSL: A Phenome-Wide Causal Discovery Algorithm Based on GWAS Summary Data”, Hou et al 2022
MRSL: A phenome-wide causal discovery algorithm based on GWAS summary data
“The Contribution of Mate-Choice, Couple Convergence and Confounding to Assortative Mating”, Sjaarda & Kutalik 2022
The contribution of mate-choice, couple convergence and confounding to assortative mating
“Genome-Wide Association Study of Occupational Attainment As a Proxy for Cognitive Reserve”, Ko et al 2022
Genome-wide association study of occupational attainment as a proxy for cognitive reserve
“Sleep Duration and Brain Structure—Phenotypic Associations and Genotypic Covariance”, Fjell et al 2022
Sleep duration and brain structure—phenotypic associations and genotypic covariance
“Mendelian Randomization of Genetically Independent Aging Phenotypes Identifies LPA and VCAM1 As Biological Targets for Human Aging”, Timmers et al 2022
“Educational Attainment, Health Outcomes and Mortality: a Within-Sibship Mendelian Randomization Study”, Howe et al 2022
“Polynomial Mendelian Randomization Reveals Widespread Non-Linear Causal Effects in the UK Biobank”, Sulc et al 2021
Polynomial Mendelian Randomization reveals widespread non-linear causal effects in the UK Biobank
“A Selection Pressure Landscape for 870 Human Polygenic Traits”, Song et al 2021
A selection pressure landscape for 870 human polygenic traits
“Genetically Proxied Diurnal Preference, Sleep Timing, and Risk of Major Depressive Disorder”, Daghlas et al 2021
Genetically Proxied Diurnal Preference, Sleep Timing, and Risk of Major Depressive Disorder
“The Relationship between Cannabis and Schizophrenia: a Genetically Informed Perspective”, Johnson et al 2021
The relationship between cannabis and schizophrenia: a genetically informed perspective
“Causal Relationships between Genetically Determined Metabolites and Human Intelligence: a Mendelian Randomization Study”, Yang et al 2021
“Disentangling Sex Differences in the Shared Genetic Architecture of Post-Traumatic Stress Disorder, Traumatic Experiences, and Social Support With Body Size and Composition”, Carvalho et al 2021
“Evidence for Shared Genetics between Physical Activity, Sedentary Behavior and Adiposity-Related Traits”, Schnurr et al 2020
“A Genetic Perspective on the Association between Exercise and Mental Health in the Era of Genome-Wide Association Studies”, Geus 2020
“Discovery of Rare Variants Associated With Blood Pressure Regulation through Meta-Analysis of 1.3 Million Individuals”, Surendran et al 2020
“Genetic Predictors of Educational Attainment and Intelligence Test Performance Predict Voter Turnout”, Aarøe et al 2020
Genetic predictors of educational attainment and intelligence test performance predict voter turnout
“Use of Genetically Informed Methods to Clarify the Nature of the Association Between Cannabis Use and Risk for Schizophrenia”, Gillespie & Kendler 2020
“Amyloid, Tau and Risk of Alzheimer’s Disease: a Mendelian Randomization Study”, Yeung et al 2020
Amyloid, tau and risk of Alzheimer’s disease: a Mendelian Randomization study
“An Exposure-Wide and Mendelian Randomization Approach to Identifying Modifiable Factors for the Prevention of Depression”, Choi et al 2020
“Genome-Wide Meta-Analysis of Problematic Alcohol Use in 435,563 Individuals Yields Insights into Biology and Relationships With Other Traits”, Zhou et al 2020
“Comprehensive Genomic Analysis of Dietary Habits in UK Biobank Identifies Hundreds of Genetic Associations”, Cole et al 2020
“Mendelian Randomization Accounting for Correlated and Uncorrelated Pleiotropic Effects Using Genome-Wide Summary Statistics”, Morrison et al 2020
“The Interplay between Host Genetics and the Gut Microbiome Reveals Common and Distinct Microbiome Features for Human Complex Diseases”, Xu et al 2019
“Genetic Analysis Identifies Molecular Systems and Biological Pathways Associated With Household Income”, Hill et al 2019
“Genome-Wide Association Study Identifies Genetic Loci for Self-Reported Habitual Sleep Duration Supported by Accelerometer-Derived Estimates”, Dashti et al 2019
“Cannabis Use, Depression and Self-Harm: Phenotypic and Genetic Relationships”, Hodgson et al 2019
Cannabis use, depression and self-harm: phenotypic and genetic relationships
“Schizophrenia Risk and Reproductive Success: a Mendelian Randomization Study”, Lawn et al 2019
Schizophrenia risk and reproductive success: a Mendelian Randomization study
“Distinguishing Genetic Correlation from Causation across 52 Diseases and Complex Traits”, O’Connor & Price 2018
Distinguishing genetic correlation from causation across 52 diseases and complex traits
“Using Genetic Data to Strengthen Causal Inference in Observational Research”, Pingault et al 2018
Using genetic data to strengthen causal inference in observational research
“The Landscape of Pervasive Horizontal Pleiotropy in Human Genetic Variation Is Driven by Extreme Polygenicity of Human Traits and Diseases”, Jordan et al 2018
“GWAS in 446,118 European Adults Identifies 78 Genetic Loci for Self-Reported Habitual Sleep Duration Supported by Accelerometer-Derived Estimates”, Dashti et al 2018
“Meta-Analysis of Genome-Wide Association Studies for Height and Body Mass Index in ∼700,000 Individuals of European Ancestry”, Yengo et al 2018
“A Genetic Perspective on the Relationship between Eudaimonic and Hedonic Well-Being”, Baselmans & Bartels 2018
A genetic perspective on the relationship between eudaimonic and hedonic well-being
“Genome-Wide Analysis of Insomnia (N = 1,331,010) Identifies Novel Loci and Functional Pathways”, Jansen et al 2018
Genome-wide Analysis of Insomnia (N = 1,331,010) Identifies Novel Loci and Functional Pathways
“Detection of Widespread Horizontal Pleiotropy in Causal Relationships Inferred from Mendelian Randomization between Complex Traits and Diseases”, Verbanck et al 2018
“GWAS of Lifetime Cannabis Use Reveals New Risk Loci, Genetic Overlap With Psychiatric Traits, and a Causal Influence of Schizophrenia”, Pasman et al 2018
“Genome-Wide Association Meta-Analysis in 269,867 Individuals Identifies New Genetic and Functional Links to Intelligence”, Savage et al 2018
“Meta-Analysis of Genome-Wide Association Studies for Height and Body Mass Index in ∼700000 Individuals of European Ancestry”, Yengo et al 2018
“Fitness, Physical Activity, and Cardiovascular Disease: Longitudinal and Genetic Analyses in the UK Biobank Study”, Tikkanen et al 2017
“Extending the MR-Egger Method for Multivariable Mendelian Randomization to Correct for Both Measured and Unmeasured Pleiotropy”, Rees et al 2017
“Genomic Analyses for Age at Menarche Identify 389 Independent Signals and Indicate BMI-Independent Effects of Puberty Timing on Cancer Susceptibility”, Day et al 2016
“Physical and Neurobehavioral Determinants of Reproductive Onset and Success”, Day et al 2016
Physical and neurobehavioral determinants of reproductive onset and success
“Height, Body Mass Index, and Socioeconomic Status: Mendelian Randomization Study in UK Biobank”, Tyrrell 2016
Height, body mass index, and socioeconomic status: Mendelian Randomization study in UK Biobank
“Mendelian Randomization With Invalid Instruments: Effect Estimation and Bias Detection through Egger Regression (MR-Egger)”, Bowden et al 2015
“Mendelian Randomization: Can Genetic Epidemiology Help Redress the Failures of Observational Epidemiology?”, Ebrahim & Smith 2007
“Clustered Environments and Randomized Genes: A Fundamental Distinction between Conventional and Genetic Epidemiology”, Smith et al 2007
“A Cautionary Note on the Use of Mendelian Randomization to Infer Causation in Observational Epidemiology”, Bochud et al 2007
“Genetic Epidemiology and Public Health: Hope, Hype, and Future Prospects”, Smith et al 2005
Genetic epidemiology and public health: hope, hype, and future prospects
“What Can Mendelian Randomization Tell Us about Modifiable Behavioral and Environmental Exposures?”, Smith & Ebrahim 2005
What can Mendelian Randomization tell us about modifiable behavioral and environmental exposures?
“A Primer on Why Microbiome Research Is Hard”
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genome-phenotype
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Bibliography
-
2024-edwards.pdf: “Predicting Political Beliefs With Polygenic Scores for Cognitive Performance and Educational Attainment”, -
https://www.nature.com/articles/s43587-021-00159-8: “Mendelian Randomization of Genetically Independent Aging Phenotypes Identifies LPA and VCAM1 As Biological Targets for Human Aging”, -
2021-song.pdf: “A Selection Pressure Landscape for 870 Human Polygenic Traits”, -
2021-johnson.pdf: “The Relationship between Cannabis and Schizophrenia: a Genetically Informed Perspective”, -
https://www.nature.com/articles/s41467-019-08917-4: “Genome-Wide Association Study Identifies Genetic Loci for Self-Reported Habitual Sleep Duration Supported by Accelerometer-Derived Estimates”,