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Sun W, Wu X, Yang H, Yuan S, Chen J, Fang Y, Zhang X. Identifying causal associations between women's reproductive traits and risk of schizophrenia: a multivariate validated two-sample Mendelian randomization analysis. BMC Psychiatry 2024; 24:161. [PMID: 38395764 PMCID: PMC10893634 DOI: 10.1186/s12888-024-05614-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 02/15/2024] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND A significant association between women's reproductive traits and the risk of schizophrenia (SCZ) has been discovered, but the causalities remain unclear. We designed a two-sample univariate Mendelian randomization (MR) study using female-specific SNPs collected from a large-scale genome-wide association study as a genetic tool to explore the causal effect of female reproductive traits on the risk of SCZ, and conducted a multivariate MR study to re-validate the above findings. METHODS From extensive genome-wide association studies (GWAS) of people with European ancestry (n = 176,881 to 418,758 individuals), summary-level data on five female reproductive variables were extracted. Summary-level information on SCZ was taken from a GWAS meta-analysis involving 320,404 people with European ancestry. The inverse variance weighting estimations for both univariable MR (UVMR) and multivariable MR (MVMR) were presented as the primary results. MR-Egger, weighted median, simple mode, and weighted mode regression methods for UVMR, and MVMR-Egger, MVMR-Lasso, and MVMR-median methods for MVMR were used for sensitivity analyses. RESULTS The UVMR produced compelling proof for a connection between genetically predicted later age at first sexual intercourse (AFS) (OR, 0.632; 95% CI, 0.512-0.777; P < 0.01) and decreased SCZ risk. Pleiotropy analysis of the AFS-SCZ association confirmed the robustness of the MR results (P > 0.05). Consistent, substantial causal effects of AFS (OR, 0.592; 95%CI, 0.407-0.862; P < 0.01) on the risk of SCZ were demonstrated after adjusting for body mass index, years of schooling, and smoking initiation using MVMR. CONCLUSIONS Our findings provide convincing evidence that early AFS is a risk factor for SCZ. SCZ risk may be decreased by raising awareness of reproductive healthcare for women.
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Affiliation(s)
- Wenxi Sun
- Suzhou Guangji Hospital, Suzhou, Jiangsu Province; Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, Jiangsu Province, China
| | - Xiaohui Wu
- Clinical Research Center & Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Haidong Yang
- Department of Psychiatry, The Fourth People's Hospital of Lianyungang, The Affiliated KangDa College of Nanjing Medical University, Lianyungang, 222003, People's Republic of China
| | - Shiting Yuan
- Suzhou Guangji Hospital, Suzhou, Jiangsu Province; Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, Jiangsu Province, China
| | - Jun Chen
- Clinical Research Center & Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Yiru Fang
- Clinical Research Center & Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
- Department of Psychiatry & Affective Disorders Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Xiaobin Zhang
- Suzhou Guangji Hospital, Suzhou, Jiangsu Province; Affiliated Guangji Hospital of Soochow University, Suzhou, 215137, Jiangsu Province, China.
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Liu A, Akimova ET, Ding X, Jukarainen S, Vartiainen P, Kiiskinen T, Koskelainen S, Havulinna AS, Gissler M, Lombardi S, Fall T, Mills MC, Ganna A. Evidence from Finland and Sweden on the relationship between early-life diseases and lifetime childlessness in men and women. Nat Hum Behav 2024; 8:276-287. [PMID: 38110509 PMCID: PMC10896715 DOI: 10.1038/s41562-023-01763-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 10/18/2023] [Indexed: 12/20/2023]
Abstract
The percentage of people without children over their lifetime is approximately 25% in men and 20% in women. Individual diseases have been linked to childlessness, mostly in women, yet we lack a comprehensive picture of the effect of early-life diseases on lifetime childlessness. We examined all individuals born in 1956-1968 (men) and 1956-1973 (women) in Finland (n = 1,035,928) and Sweden (n = 1,509,092) to the completion of their reproductive lifespan in 2018. Leveraging nationwide registers, we associated sociodemographic and reproductive information with 414 diseases across 16 categories, using a population and matched-pair case-control design of siblings discordant for childlessness (71,524 full sisters and 77,622 full brothers). The strongest associations were mental-behavioural disorders (particularly among men), congenital anomalies and endocrine-nutritional-metabolic disorders (strongest among women). We identified new associations for inflammatory and autoimmune diseases. Associations were dependent on age at onset and mediated by singlehood and education. This evidence can be used to understand how disease contributes to involuntary childlessness.
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Affiliation(s)
- Aoxing Liu
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
| | - Evelina T Akimova
- Leverhulme Centre for Demographic Science, Nuffield Department of Population Health, and Nuffield College, University of Oxford, Oxford, UK
| | - Xuejie Ding
- Leverhulme Centre for Demographic Science, Nuffield Department of Population Health, and Nuffield College, University of Oxford, Oxford, UK
| | - Sakari Jukarainen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Pekka Vartiainen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Tuomo Kiiskinen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Sara Koskelainen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Mika Gissler
- Finnish Institute for Health and Welfare, Helsinki, Finland
- Research Centre for Child Psychiatry and Invest Research Flagship, University of Turku, Turku, Finland
- Academic Primary Health Care Centre, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | | | - Tove Fall
- Molecular Epidemiology, Department of Medical Sciences, and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Melinda C Mills
- Leverhulme Centre for Demographic Science, Nuffield Department of Population Health, and Nuffield College, University of Oxford, Oxford, UK.
- Department of Economics, Econometrics and Finance, Faculty of Economics and Business, University of Groningen, Groningen, the Netherlands.
- Department of Genetics, University Medical Centre Groningen, Groningen, the Netherlands.
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
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3
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Zhuo C, Chen L, Wang Q, Cai H, Lin Z, Pan H, Wu M, Jin Y, Jin H, Zheng L. Association of age at first sexual intercourse and lifetime number of sexual partners with cardiovascular diseases: a bi-directional Mendelian randomization study. Front Cardiovasc Med 2023; 10:1267906. [PMID: 38146444 PMCID: PMC10749299 DOI: 10.3389/fcvm.2023.1267906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 11/03/2023] [Indexed: 12/27/2023] Open
Abstract
Background Limited studies have explored the association between sexual factors [age at first sexual intercourse (AFS) and lifetime number of sexual partners (LNSP)] and cardiovascular diseases (CVDs), leaving the causality inconclusive. Methods We performed a bi-directional Mendelian randomization (MR) study to investigate the causality between sexual factors and CVDs, including coronary artery disease, myocardial infarction, atrial fibrillation (AF), heart failure (HF), and ischemic stroke (IS). Single-nucleotide polymorphisms (SNPs) for sexual factors were extracted from the UK Biobank. Statistics for each CVD were derived from two different databases. MR estimates were calculated per outcome database and were combined through meta-analysis. Several complementary sensitivity analyses were also performed. Results The primary analysis suggested that AFS was causally associated with the risk of CVDs; the odds ratios (ORs) ranged from 0.686 [95% confidence interval (CI), 0.611-0.770] for HF to 0.798 (95% CI, 0.719-0.886) for AF. However, the association between AFS and IS (OR, 0.844; 95% CI, 0.632-1.126) was not consistent in the meta-analysis after excluding SNPs related to confounders. Moreover, non-significant associations were found between LNSP and CVDs. Reverse direction MR analysis showed that CVDs were not associated with sexual factors. Conclusions Genetic evidence suggested that AFS was causally associated with the risk of CVDs except for IS, whereas non-significant association of LNSP with CVDs was detected. Further investigation into AFS could be warranted in preventing the progression of CVDs.
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Affiliation(s)
- Chengui Zhuo
- Department of Cardiology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China
| | - Lei Chen
- Department of Cardiology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China
| | - Qiqi Wang
- Zhejiang Provincial Center for Drug and Medical Device Procurement, Hangzhou, China
| | - Haipeng Cai
- Department of Cardiology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China
| | - Zujin Lin
- Department of Cardiology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China
| | - Huili Pan
- Department of Cardiology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China
| | - Meicui Wu
- Department of Cardiology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China
| | - Yuxiang Jin
- Department of Cardiology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China
| | - Hong Jin
- Department of Cardiology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China
| | - Liangrong Zheng
- Department of Cardiology and Atrial Fibrillation Center, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
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4
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Wu D, Liu B, Xian W, Yang Y, Li J, Hong S, Li Y, Xiao H. New insight into the causal relationship between Graves' disease liability and drug eruption: a Mendelian randomization study. Front Immunol 2023; 14:1267814. [PMID: 38077385 PMCID: PMC10703291 DOI: 10.3389/fimmu.2023.1267814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Accepted: 11/06/2023] [Indexed: 12/18/2023] Open
Abstract
Background Graves' disease (GD) and drug eruption are closely associated and frequently observed in the clinical setting. However, it remains unclear whether a causal relationship exists between these two conditions. The aim of the study is to investigate whether GD is causal to drug eruptions using two-sample Mendelian randomization. Methods We launched a two-sample MR to investigate whether GD is causal to drug eruption using Genome-wide association study (GWAS) summary data from Biobank Japan and FinnGen. Genetic variants were used as instrumental variables to avoid confounding bias. Statistical methods including inverse variance weighted (IVW), weighted median, MR-Egger, and MR-PRESSO were conducted to identify the robustness of the causal effect. Results Genetically predicted GD may increase the risk of drug eruption by 30.3% (OR=1.303, 95% CI 1.119-1.516, p<0.001) in the Asian population. In European populations, GD may increase the generalized drug eruption by 15.9% (OR=1.159, 95%CI 0.982-1.367, p=0.080). Conclusions We found GD is potentially causal to drug eruption. This finding expanded the view of the frequently observed co-existence of GD and adverse drug reactions involving the skin. The mechanism remains for further investigation.
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Affiliation(s)
- Dide Wu
- Department of Endocrinology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Boyuan Liu
- Department of Endocrinology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wei Xian
- Department of Endocrinology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yuxin Yang
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Jinjian Li
- Department of Endocrinology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Shubin Hong
- Department of Endocrinology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yanbing Li
- Department of Endocrinology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Haipeng Xiao
- Department of Endocrinology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
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Yu Y, Hou L, Wu Y, Yu Y, Liu X, Wu S, He Y, Ge Y, Wei Y, Qian F, Luo Q, Feng Y, Cheng X, Yu T, Li H, Xue F. Causal associations between female reproductive behaviors and psychiatric disorders: a lifecourse Mendelian randomization study. BMC Psychiatry 2023; 23:799. [PMID: 37915018 PMCID: PMC10621101 DOI: 10.1186/s12888-023-05203-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 09/18/2023] [Indexed: 11/03/2023] Open
Abstract
BACKGROUND The timings of reproductive life events have been examined to be associated with various psychiatric disorders. However, studies have not considered the causal pathways from reproductive behaviors to different psychiatric disorders. This study aimed to investigate the nature of the relationships between five reproductive behaviors and twelve psychiatric disorders. METHODS Firstly, we calculated genetic correlations between reproductive factors and psychiatric disorders. Then two-sample Mendelian randomization (MR) was conducted to estimate the causal associations among five reproductive behaviors, and these reproductive behaviors on twelve psychiatric disorders, using genome-wide association study (GWAS) summary data from genetic consortia. Multivariable MR was then applied to evaluate the direct effect of reproductive behaviors on these psychiatric disorders whilst accounting for other reproductive factors at different life periods. RESULTS Univariable MR analyses provide evidence that age at menarche, age at first sexual intercourse and age at first birth have effects on one (depression), seven (anxiety disorder, ADHD, bipolar disorder, bipolar disorder II, depression, PTSD and schizophrenia) and three psychiatric disorders (ADHD, depression and PTSD) (based on p<7.14×10-4), respectively. However, after performing multivariable MR, only age at first sexual intercourse has direct effects on five psychiatric disorders (Depression, Attention deficit or hyperactivity disorder, Bipolar disorder, Posttraumatic stress disorder and schizophrenia) when accounting for other reproductive behaviors with significant effects in univariable analyses. CONCLUSION Our findings suggest that reproductive behaviors predominantly exert their detrimental effects on psychiatric disorders and age at first sexual intercourse has direct effects on psychiatric disorders.
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Affiliation(s)
- Yifan Yu
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
| | - Lei Hou
- Beijing International Center for Mathematical Research, Peking University, Beijing, People's Republic of China
| | - Yutong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
| | - Yuanyuan Yu
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
| | - Xinhui Liu
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
| | - Sijia Wu
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
| | - Yina He
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
| | - Yilei Ge
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
| | - Yun Wei
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
| | - Fengtong Qian
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
| | - Qingxin Luo
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
| | - Yue Feng
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
| | - Xiaojing Cheng
- Shandong Mental Health Center, Shandong Province, Jinan, China
| | - Tiangui Yu
- Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China.
| | - Hongkai Li
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China.
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China.
| | - Fuzhong Xue
- Department of Epidemiology and Health Statistics, School of Public Health, , Cheeloo College of Medicine, Shandong University, 44 Wenhua West Road, Jinan, Shandong Province, China.
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China.
- Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China.
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6
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Wootton RE, Lawn RB, Magnus MC, Treur JL, Corfield EC, Njølstad PR, Andreassen OA, Lawlor DA, Munafò MR, Håberg SE, Davey Smith G, Reichborn-Kjennerud T, Magnus P, Havdahl A. Associations between health behaviours, fertility and reproductive outcomes: triangulation of evidence in the Norwegian Mother, Father and Child Cohort Study (MoBa). BMC Med 2023; 21:125. [PMID: 37013617 PMCID: PMC10071662 DOI: 10.1186/s12916-023-02831-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 03/13/2023] [Indexed: 04/05/2023] Open
Abstract
BACKGROUND Guidance to improve fertility includes reducing alcohol and caffeine consumption, achieving healthy weight-range and stopping smoking. Advice is informed by observational evidence, which is often biased by confounding. METHODS This study primarily used data from a pregnancy cohort, the Norwegian Mother, Father and Child Cohort Study. First, we conducted multivariable regression of health behaviours (alcohol and caffeine consumption, body-mass index (BMI), and smoking) on fertility outcomes (e.g. time to conception) and reproductive outcomes (e.g. age at first birth) (n = 84,075 females, 68,002 males), adjusting for birth year, education and attention-deficit and hyperactive-impulsive (ADHD) traits. Second, we used individual-level Mendelian randomisation (MR) to explore possible causal effects of health behaviours on fertility/reproductive outcomes (n = 63,376 females, 45,460 males). Finally, we performed summary-level MR for available outcomes in UK Biobank (n = 91,462-1,232,091) and controlled for education and ADHD liability using multivariable MR. RESULTS In multivariable regression analyses, higher BMI associated with fertility (longer time to conception, increased odds of infertility treatment and miscarriage), and smoking was associated with longer time to conception. In individual-level MR analyses, there was strong evidence for effects of smoking initiation and higher BMI on younger age at first birth, of higher BMI on increased time to conception, and weak evidence for effects of smoking initiation on increased time to conception. Age at first birth associations were replicated in summary-level MR analysis; however, effects attenuated using multivariable MR. CONCLUSIONS Smoking behaviour and BMI showed the most consistent associations for increased time to conception and a younger age at first birth. Given that age at first birth and time to conception are positively correlated, this suggests that the mechanisms for reproductive outcomes are distinct to the mechanisms acting on fertility outcomes. Multivariable MR suggested that effects on age at first birth might be explained by underlying liability to ADHD and education.
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Affiliation(s)
- Robyn E Wootton
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway.
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
- School of Psychological Science, University of Bristol, Bristol, UK.
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway.
| | - Rebecca B Lawn
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Jorien L Treur
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Elizabeth C Corfield
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Pål R Njølstad
- Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo University Hospital, Oslo, Norway
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Marcus R Munafò
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ted Reichborn-Kjennerud
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Alexandra Havdahl
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
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Abstract
The field of psychopathology is in a transformative phase, and is witnessing a renewed surge of interest in theoretical models of mental disorders. While many interesting proposals are competing for attention in the literature, they tend to focus narrowly on the proximate level of analysis and lack a broader understanding of biological function. In this paper, we present an integrative framework for mental disorders built on concepts from life history theory, and describe a taxonomy of mental disorders based on its principles, the fast-slow-defense model (FSD). The FSD integrates psychopathology with normative individual differences in personality and behavior, and allows researchers to draw principled distinctions between broad clusters of disorders, as well as identify functional subtypes within current diagnostic categories. Simulation work demonstrates that the model can explain the large-scale structure of comorbidity, including the apparent emergence of a general "p factor" of psychopathology. A life history approach also provides novel integrative insights into the role of environmental risk/protective factors and the developmental trajectories of various disorders.
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Abstract
Mendelian randomization (MR) is a method of studying the causal effects of modifiable exposures (i.e., potential risk factors) on health, social, and economic outcomes using genetic variants associated with the specific exposures of interest. MR provides a more robust understanding of the influence of these exposures on outcomes because germline genetic variants are randomly inherited from parents to offspring and, as a result, should not be related to potential confounding factors that influence exposure-outcome associations. The genetic variant can therefore be used as a tool to link the proposed risk factor and outcome, and to estimate this effect with less confounding and bias than conventional epidemiological approaches. We describe the scope of MR, highlighting the range of applications being made possible as genetic data sets and resources become larger and more freely available. We outline the MR approach in detail, covering concepts, assumptions, and estimation methods. We cover some common misconceptions, provide strategies for overcoming violation of assumptions, and discuss future prospects for extending the clinical applicability, methodological innovations, robustness, and generalizability of MR findings.
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Affiliation(s)
- Rebecca C Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, United Kingdom
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol BS1 3NU, United Kingdom
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9
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A selection pressure landscape for 870 human polygenic traits. Nat Hum Behav 2021; 5:1731-1743. [PMID: 34782732 DOI: 10.1038/s41562-021-01231-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 09/28/2021] [Indexed: 02/05/2023]
Abstract
Characterizing the natural selection of complex traits is important for understanding human evolution and both biological and pathological mechanisms. We leveraged genome-wide summary statistics for 870 polygenic traits and attempted to quantify signals of selection on traits of different forms in European ancestry across four periods in human history and evolution. We found that 88% of these traits underwent polygenic change in the past 2,000-3,000 years. Recent selection was associated with ancient selection signals in the same trait. Traits related to pigmentation, body measurement and nutritional intake exhibited strong selection signals across different time scales. Our findings are limited by our use of exclusively European data and the use of genome-wide association study data, which identify associations between genetic variants and phenotypes that may not be causal. In sum, we provide an overview of signals of selection on human polygenic traits and their characteristics across human evolution, based on a European subset of human genetic diversity. These findings could serve as a foundation for further populational and medical genetic studies.
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10
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Tudball MJ, Bowden J, Hughes RA, Ly A, Munafò MR, Tilling K, Zhao Q, Davey Smith G. Mendelian randomisation with coarsened exposures. Genet Epidemiol 2021; 45:338-350. [PMID: 33527565 PMCID: PMC8603937 DOI: 10.1002/gepi.22376] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 10/16/2020] [Accepted: 12/16/2020] [Indexed: 01/24/2023]
Abstract
A key assumption in Mendelian randomisation is that the relationship between the genetic instruments and the outcome is fully mediated by the exposure, known as the exclusion restriction assumption. However, in epidemiological studies, the exposure is often a coarsened approximation to some latent continuous trait. For example, latent liability to schizophrenia can be thought of as underlying the binary diagnosis measure. Genetically driven variation in the outcome can exist within categories of the exposure measurement, thus violating this assumption. We propose a framework to clarify this violation, deriving a simple expression for the resulting bias and showing that it may inflate or deflate effect estimates but will not reverse their sign. We then characterise a set of assumptions and a straight‐forward method for estimating the effect of SD increases in the latent exposure. Our method relies on a sensitivity parameter which can be interpreted as the genetic variance of the latent exposure. We show that this method can be applied in both the one‐sample and two‐sample settings. We conclude by demonstrating our method in an applied example and reanalysing two papers which are likely to suffer from this type of bias, allowing meaningful interpretation of their effect sizes.
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Affiliation(s)
- Matthew J Tudball
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jack Bowden
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,College of Medicine and Health, University of Exeter, Exeter, UK
| | - Rachael A Hughes
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Amanda Ly
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Marcus R Munafò
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,School of Psychological Science, University of Bristol, Bristol, UK
| | - Kate Tilling
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Qingyuan Zhao
- Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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11
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Ni G, Amare AT, Zhou X, Mills N, Gratten J, Lee SH. The genetic relationship between female reproductive traits and six psychiatric disorders. Sci Rep 2019; 9:12041. [PMID: 31427629 PMCID: PMC6700195 DOI: 10.1038/s41598-019-48403-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Accepted: 07/31/2019] [Indexed: 12/31/2022] Open
Abstract
Female reproductive behaviours have important implications for evolutionary fitness and health of offspring. Here we used the second release of UK Biobank data (N = 220,685) to evaluate the association between five female reproductive traits and polygenic risk scores (PRS) projected from genome-wide association study summary statistics of six psychiatric disorders (N = 429,178). We found that the PRS of attention-deficit/hyperactivity disorder (ADHD) were strongly associated with age at first birth (AFB) (genetic correlation of -0.68 ± 0.03), age at first sexual intercourse (AFS) (-0.56 ± 0.03), number of live births (NLB) (0.36 ± 0.04) and age at menopause (-0.27 ± 0.04). There were also robustly significant associations between the PRS of eating disorder (ED) and AFB (0.35 ± 0.06), ED and AFS (0.19 ± 0.06), major depressive disorder (MDD) and AFB (-0.27 ± 0.07), MDD and AFS (-0.27 ± 0.03) and schizophrenia and AFS (-0.10 ± 0.03). These associations were mostly explained by pleiotropic effects and there was little evidence of causal relationships. Our findings can potentially help improve reproductive health in women, hence better child outcomes. Our findings also lend partial support to the evolutionary hypothesis that causal mutations underlying psychiatric disorders have positive effects on reproductive success.
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Affiliation(s)
- Guiyan Ni
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, 5000, Australia
- School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia
| | - Azmeraw T Amare
- South Australian Academic Health Science and Translation centre, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, South Australia, Australia
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia
| | - Xuan Zhou
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, 5000, Australia
| | - Natalie Mills
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia
| | - Jacob Gratten
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
- Mater Research Institute, University of Queensland, Brisbane, Queensland, 4072, Australia
| | - S Hong Lee
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, 5000, Australia.
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12
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Lawn RB, Sallis HM, Taylor AE, Wootton RE, Davey Smith G, Davies NM, Hemani G, Fraser A, Penton-Voak IS, Munafò MR. Comment on the Relationship Between Common Variant Schizophrenia Liability and Number of Offspring in the UK Biobank. Am J Psychiatry 2019; 176:573-574. [PMID: 31256616 DOI: 10.1176/appi.ajp.2019.19010071] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Rebecca B Lawn
- Medical Research Council Integrative Epidemiology Unit (Lawn, Sallis, Wootton, Davey Smith, Davies, Hemani, Fraser, Munafò), School of Psychological Science (Lawn, Sallis, Wootton, Penton-Voak, Munafò), and Bristol Medical School (Sallis, Taylor, Davey Smith, Davies, Fraser), University of Bristol, Bristol, United Kingdom; National Institute for Health Research Biomedical Research Center, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, United Kingdom (Taylor)
| | - Hannah M Sallis
- Medical Research Council Integrative Epidemiology Unit (Lawn, Sallis, Wootton, Davey Smith, Davies, Hemani, Fraser, Munafò), School of Psychological Science (Lawn, Sallis, Wootton, Penton-Voak, Munafò), and Bristol Medical School (Sallis, Taylor, Davey Smith, Davies, Fraser), University of Bristol, Bristol, United Kingdom; National Institute for Health Research Biomedical Research Center, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, United Kingdom (Taylor)
| | - Amy E Taylor
- Medical Research Council Integrative Epidemiology Unit (Lawn, Sallis, Wootton, Davey Smith, Davies, Hemani, Fraser, Munafò), School of Psychological Science (Lawn, Sallis, Wootton, Penton-Voak, Munafò), and Bristol Medical School (Sallis, Taylor, Davey Smith, Davies, Fraser), University of Bristol, Bristol, United Kingdom; National Institute for Health Research Biomedical Research Center, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, United Kingdom (Taylor)
| | - Robyn E Wootton
- Medical Research Council Integrative Epidemiology Unit (Lawn, Sallis, Wootton, Davey Smith, Davies, Hemani, Fraser, Munafò), School of Psychological Science (Lawn, Sallis, Wootton, Penton-Voak, Munafò), and Bristol Medical School (Sallis, Taylor, Davey Smith, Davies, Fraser), University of Bristol, Bristol, United Kingdom; National Institute for Health Research Biomedical Research Center, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, United Kingdom (Taylor)
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit (Lawn, Sallis, Wootton, Davey Smith, Davies, Hemani, Fraser, Munafò), School of Psychological Science (Lawn, Sallis, Wootton, Penton-Voak, Munafò), and Bristol Medical School (Sallis, Taylor, Davey Smith, Davies, Fraser), University of Bristol, Bristol, United Kingdom; National Institute for Health Research Biomedical Research Center, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, United Kingdom (Taylor)
| | - Neil M Davies
- Medical Research Council Integrative Epidemiology Unit (Lawn, Sallis, Wootton, Davey Smith, Davies, Hemani, Fraser, Munafò), School of Psychological Science (Lawn, Sallis, Wootton, Penton-Voak, Munafò), and Bristol Medical School (Sallis, Taylor, Davey Smith, Davies, Fraser), University of Bristol, Bristol, United Kingdom; National Institute for Health Research Biomedical Research Center, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, United Kingdom (Taylor)
| | - Gibran Hemani
- Medical Research Council Integrative Epidemiology Unit (Lawn, Sallis, Wootton, Davey Smith, Davies, Hemani, Fraser, Munafò), School of Psychological Science (Lawn, Sallis, Wootton, Penton-Voak, Munafò), and Bristol Medical School (Sallis, Taylor, Davey Smith, Davies, Fraser), University of Bristol, Bristol, United Kingdom; National Institute for Health Research Biomedical Research Center, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, United Kingdom (Taylor)
| | - Abigail Fraser
- Medical Research Council Integrative Epidemiology Unit (Lawn, Sallis, Wootton, Davey Smith, Davies, Hemani, Fraser, Munafò), School of Psychological Science (Lawn, Sallis, Wootton, Penton-Voak, Munafò), and Bristol Medical School (Sallis, Taylor, Davey Smith, Davies, Fraser), University of Bristol, Bristol, United Kingdom; National Institute for Health Research Biomedical Research Center, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, United Kingdom (Taylor)
| | - Ian S Penton-Voak
- Medical Research Council Integrative Epidemiology Unit (Lawn, Sallis, Wootton, Davey Smith, Davies, Hemani, Fraser, Munafò), School of Psychological Science (Lawn, Sallis, Wootton, Penton-Voak, Munafò), and Bristol Medical School (Sallis, Taylor, Davey Smith, Davies, Fraser), University of Bristol, Bristol, United Kingdom; National Institute for Health Research Biomedical Research Center, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, United Kingdom (Taylor)
| | - Marcus R Munafò
- Medical Research Council Integrative Epidemiology Unit (Lawn, Sallis, Wootton, Davey Smith, Davies, Hemani, Fraser, Munafò), School of Psychological Science (Lawn, Sallis, Wootton, Penton-Voak, Munafò), and Bristol Medical School (Sallis, Taylor, Davey Smith, Davies, Fraser), University of Bristol, Bristol, United Kingdom; National Institute for Health Research Biomedical Research Center, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, United Kingdom (Taylor)
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