Major depressive disorder and cardiometabolic diseases: a bidirectional Mendelian randomisation study.
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SUBMITTER: Tang B
PROVIDER: S-EPMC7286869 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature
Publications
Major depressive disorder and cardiometabolic diseases: a bidirectional Mendelian randomisation study.
Tang Bowen B Yuan Shuai S Xiong Ying Y He Qiqiang Q Larsson Susanna C SC
Diabetologia 20200408 7
<h4>Aims/hypothesis</h4>Observational studies have shown a bidirectional association between major depressive disorder (MDD) and cardiometabolic diseases. We conducted a two-sample bidirectional Mendelian randomisation (MR) study to assess the causal associations of MDD with type 2 diabetes, coronary artery disease (CAD) and heart failure and vice versa.<h4>Methods</h4>We extracted summary-level data for MDD, type 2 diabetes, CAD and heart failure from corresponding published large genome-wide a ...[more]
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Project description:AIMS/HYPOTHESIS:Abnormal serum IGF-1 levels are associated with an increased risk of type 2 diabetes and cardiovascular disease. However, the causal role of IGF-1 levels within the normal range in cardiometabolic disease remains unclear. We employed Mendelian randomisation to explore the associations between genetically predicted serum IGF-1 levels and cardiometabolic diseases. METHODS:Serum IGF-1 levels were predicted using 416 SNPs associated with IGF-1 levels among 358,072 individuals in UK Biobank. Genetic association estimates for the outcomes were obtained from consortia of type 2 diabetes (74,124 cases, 824,006 controls), coronary artery disease (60,801 cases, 123,504 controls), heart failure (47,309 cases, 930,014 controls), atrial fibrillation (65,446 cases, 522,744 controls), and ischaemic stroke (60,341 cases, 454,450 controls). RESULTS:Genetic predisposition to elevated serum IGF-1 levels was associated with higher risk of type 2 diabetes and coronary artery disease. The OR (95% CI) per SD increment in IGF-1 level was 1.14 (1.05, 1.24) for type 2 diabetes and 1.09 (1.02, 1.16) for coronary artery disease. The association between IGF-1 and coronary artery disease was attenuated after adjustment for type 2 diabetes (OR 1.06 [95% CI 1.00, 1.13]), suggesting that the association may be partly mediated via type 2 diabetes. There was limited evidence of associations between IGF-1 levels and heart failure, atrial fibrillation and ischaemic stroke. CONCLUSIONS/INTERPRETATION:This study found evidence that increased IGF-1 levels may be causally associated with higher risk of type 2 diabetes. Graphical abstract.
| S-EPMC7406523 | biostudies-literature
Project description:Major depressive disorder (MDD) exhibits numerous clinical, epidemiological, and molecular features that are consistent with partially inherited and partially acquired epigenetic misregulation. We performed microarray based DNA modification study of MDD, utilizing affected and unaffected samples from white blood cells from monozygotic twins discordant for MDD, post-mortem prefrontal cortex tissues, and sperm samples. We performed DNA methylome analysis on white blood cells from monozygotic twins discordant for depression (n=200), pre-frontal cortex (n=71), and germline samples (n=33) from affected individuals and controls (total n=304). DNA samples were enriched for unmodified fraction of the genome using DNA-modification sensitive restriction enzyme digestion followed by adaptor-mediated PCR. The enriched fractions were labelled with a fluorescent dye (Cy5) and hybridized onto the array with a common reference pool (Cy3) generated from individuals unrelated to this study.
2012-04-27 | E-GEOD-37579 | biostudies-arrayexpress
Project description:ObjectiveTo explore the causal relationships between sleep, major depressive disorder (MDD), and Alzheimer disease (AD).MethodsWe conducted bidirectional 2-sample Mendelian randomization analyses. Genetic associations were obtained from the largest genome-wide association studies currently available in UK Biobank (n = 446,118), Psychiatric Genomics Consortium (n = 18,759), and International Genomics of Alzheimer's Project (n = 63,926). We used the inverse variance-weighted Mendelian randomization method to estimate causal effects and weighted median and Mendelian randomization-Egger for sensitivity analyses to test for pleiotropic effects.ResultsWe found that higher risk of AD was significantly associated with being a "morning person" (odds ratio [OR] 1.01, p = 0.001), shorter sleep duration (self-reported: β = -0.006, p = 1.9 × 10-4; accelerometer based: β = -0.015, p = 6.9 × 10-5), less likely to report long sleep (β = -0.003, p = 7.3 × 10-7), earlier timing of the least active 5 hours (β = -0.024, p = 1.7 × 10-13), and a smaller number of sleep episodes (β = -0.025, p = 5.7 × 10-14) after adjustment for multiple comparisons. We also found that higher risk of AD was associated with lower risk of insomnia (OR 0.99, p = 7 × 10-13). However, we did not find evidence that these abnormal sleep patterns were causally related to AD or for a significant causal relationship between MDD and risk of AD.ConclusionWe found that AD may causally influence sleep patterns. However, we did not find evidence supporting a causal role of disturbed sleep patterns for AD or evidence for a causal relationship between MDD and AD.
| S-EPMC7682841 | biostudies-literature
Project description:Recent advances in data analysis methods based on principles of Mendelian Randomisation, such as Egger regression and the weighted median estimator, add to the researcher's ability to infer cause-effect links from observational data. Now is the time to gauge the potential of these methods within specific areas of biomedical research. In this paper, we choose a study in metabolomics as an illustrative testbed. We apply Mendelian Randomisation methods in the analysis of data from the DILGOM (Dietary, Lifestyle and Genetic determinants of Obesity and Metabolic syndrome) study, in the context of an effort to identify molecular pathways of cardiovascular disease. In particular, our illustrative analysis addresses the question whether body mass, as measured by body mass index (BMI), exerts a causal effect on the concentrations of a collection of 137 cardiometabolic markers with different degrees of atherogenic power, such as the (highly atherogenic) lipoprotein metabolites with very low density (VLDLs) and the (protective) high density lipoprotein metabolites.We found strongest evidence of a positive BMI effect (that is, evidence that an increase in BMI causes an increase in the metabolite concentration) on those metabolites known to represent strong risk factors for coronary artery disease, such as the VLDLs, and evidence of a negative effect on protective biomarkers.The methods discussed represent a useful scientific tool, although they assume the validity of conditions that are (at best) only partially verifiable. This paper provides a rigorous account of such conditions. The results of our analysis provide a proof-of-concept illustration of the potential usefulness of Mendelian Randomisation in genomic biobank studies aiming to dissect the molecular causes of disease, and to identify candidate pharmacological targets.
| S-EPMC6069804 | biostudies-other
Project description:BackgroundEarlier puberty is widely linked with future obesity and cardiometabolic disease. We examined whether age at puberty onset likely influences adiposity and cardiometabolic traits independent of childhood adiposity.Methods and findingsOne-sample Mendelian randomisation (MR) analyses were conducted on up to 3,611 white-European female and male offspring from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort recruited at birth via mothers between 1 April 1991 and 31 December 1992. Time-sensitive exposures were age at menarche and age at voice breaking. Outcomes measured at age 18 y were body mass index (BMI), dual-energy X-ray absorptiometry-based fat and lean mass indices, blood pressure, and 230 cardiometabolic traits derived from targeted metabolomics (150 concentrations plus 80 ratios from nuclear magnetic resonance [NMR] spectroscopy covering lipoprotein subclasses of cholesterol and triglycerides, amino acids, inflammatory glycoproteins, and others). Adjustment was made for pre-pubertal BMI measured at age 8 y. For negative control MR analyses, BMI and cardiometabolic trait measures taken at age 8 y (before puberty, and which therefore cannot be an outcome of puberty itself) were used. For replication analyses, 2-sample MR was conducted using summary genome-wide association study data on up to 322,154 adults for post-pubertal BMI, 24,925 adults for post-pubertal NMR cardiometabolic traits, and 13,848 children for pre-pubertal obesity (negative control). Like observational estimates, 1-sample MR estimates in ALSPAC using 351 polymorphisms for age at menarche (explaining 10.6% of variance) among 2,053 females suggested that later age at menarche (per year) was associated with -1.38 kg/m2 of BMI at age 18 y (or -0.34 SD units, 95% CI -0.46, -0.23; P = 9.77 × 10-09). This coefficient attenuated 10-fold upon adjustment for BMI at age 8 y, to -0.12 kg/m2 (or -0.03 SDs, 95% CI -0.13, 0.07; P = 0.55). Associations with blood pressure were similar, but associations across other traits were small and inconsistent. In negative control MR analyses, later age at menarche was associated with -0.77 kg/m2 of pre-pubertal BMI measured at age 8 y (or -0.39 SDs, 95% CI -0.50, -0.29; P = 6.28 × 10-13), indicating that variants influencing menarche also influence BMI before menarche. Cardiometabolic trait associations were weaker and less consistent among males and both sexes combined. Higher BMI at age 8 y (per 1 kg/m2 using 95 polymorphisms for BMI explaining 3.4% of variance) was associated with earlier menarche among 2,648 females (by -0.26 y, 95% CI -0.37, -0.16; P = 1.16 × 10-06), likewise among males and both sexes combined. In 2-sample MR analyses using 234 polymorphisms and inverse variance weighted (IVW) regression, each year later age at menarche was associated with -0.81 kg/m2 of adult BMI (or -0.17 SD units, 95% CI -0.21, -0.12; P = 4.00 × 10-15). Associations were weaker with cardiometabolic traits. Using 202 polymorphisms, later menarche was associated with lower odds of childhood obesity (IVW-based odds ratio = 0.52 per year later, 95% CI 0.48, 0.57; P = 6.64 × 10-15). Study limitations include modest sample sizes for 1-sample MR, lack of inference to non-white-European populations, potential selection bias through modest completion rates of puberty questionnaires, and likely disproportionate measurement error of exposures by sex. The cardiometabolic traits examined were heavily lipid-focused and did not include hormone-related traits such as insulin and insulin-like growth factors.ConclusionsOur results suggest that puberty timing has a small influence on adiposity and cardiometabolic traits and that preventive interventions should instead focus on reducing childhood adiposity.
| S-EPMC6112630 | biostudies-literature
Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD. In total, 33 MDD patients and 34 healthy controls were analyzed using basal gene expression in whole blood, and gene expression from whole blood that was stimulated with LPS for 5-6 h, using microarrays. Patients were arbitrarily selected from all patients to serve as primary cohort (nMDD = 21 (MDD01-MDD21); nControls = 21 (Con01-Con21)), or replication cohort (nMDD = 12 (MDD22-MDD35); nControls = 13 (Con22-Con37)) using microarrays. This submission does not include Samples CON21_LPS or CON30_LPS.
2011-10-04 | E-GEOD-19738 | biostudies-arrayexpress
Project description:OBJECTIVES:To investigate whether the association between subjective wellbeing (subjective happiness and life satisfaction) and cardiometabolic health is causal. DESIGN:Two sample, bidirectional mendelian randomisation study. SETTING:Genetic data taken from various cohorts comprised of the general population (mostly individuals of European ancestry, plus a small proportion of other ancestries); follow-up analysis included individuals from the United Kingdom. PARTICIPANTS:Summary data were used from previous genome wide association studies (number of participants ranging from 83?198 to 339?224), which investigated traits related to cardiovascular or metabolic health, had the largest sample sizes, and consisted of the most similar populations while minimising sample overlap. A follow-up analysis included 337?112 individuals from the UK Biobank (54% female (n=181?363), mean age 56.87 years (standard deviation 8.00) at recruitment). MAIN OUTCOME MEASURES:Subjective wellbeing and 11 measures of cardiometabolic health (coronary artery disease; myocardial infarction; total, high density lipoprotein, and low density lipoprotein cholesterol; diastolic and systolic blood pressure; body fat; waist to hip ratio; waist circumference; and body mass index). RESULTS:Evidence of a causal effect of body mass index on subjective wellbeing was seen; each 1 kg/m2 increase in body mass index caused a -0.045 (95% confidence interval -0.084 to -0.006, P=0.02) standard deviation reduction in subjective wellbeing. Follow-up analysis of this association in an independent sample from the UK Biobank provided strong evidence of an effect of body mass index on satisfaction with health (?=-0.035 unit decrease in health satisfaction (95% confidence interval -0.043 to -0.027) per standard deviation increase in body mass index, P<0.001). No clear evidence of a causal effect was seen between subjective wellbeing and the other cardiometabolic health measures, in either direction. CONCLUSIONS:These results suggest that a higher body mass index is associated with a lower subjective wellbeing. A follow-up analysis confirmed this finding, suggesting that the effect in middle aged people could be driven by satisfaction with health. Body mass index is a modifiable determinant, and therefore, this study provides further motivation to tackle the obesity epidemic because of the knock-on effects of higher body mass index on subjective wellbeing.
| S-EPMC6155050 | biostudies-literature
Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD.
2011-10-05 | GSE19738 | GEO
Project description:ImportanceAlopecia areata (AA) is an autoimmune disease characterized by hair loss that can impose a substantial psychological burden on patients, including major depressive disorder (MDD), yet many patients report mental health symptoms prior to the onset of AA. As such, there may be an association between MDD and AA that acts in both directions.ObjectiveTo assess the bidirectional association between MDD and AA.Design, setting, and participantsThis population-based retrospective cohort study included patients 10 to 90 years of age registered with The Health Improvement Network in general practices in the United Kingdom between January 1, 1986, and May 16, 2012. Statistical analysis was conducted from August 17, 2017, to April 23, 2018. To assess the risk of AA, the following 2 cohorts were defined: patients with an incident diagnosis of MDD (exposure) and a reference general population cohort. To assess the risk of MDD, the following 2 cohorts were defined: patients with an incident diagnosis of AA (exposure) and a reference general population cohort. Person-time was partitioned into unexposed and exposed time in the exposure cohorts.Main outcomes and measuresIn the analysis of the risk of AA, development of incident AA during follow-up was considered the main outcome measure. In the analysis of the risk of MDD, development of incident MDD during follow-up was considered the primary outcome measure.ResultsIn the analysis of the risk of AA, 405 339 patients who developed MDD (263 916 women and 141 423 men; median age, 36.7 years [interquartile range, 26.6-50.5 years]) and 5 738 596 patients who did not develop MDD (2 912 201 women and 2 826 395 men; median age, 35.8 years [interquartile range, 25.3-52.6 years]) were followed up for 26 years. After adjustment for covariates, MDD was found to increase the risk of subsequently developing AA by 90% (hazard ratio, 1.90; 95% CI, 1.67-2.15; P < .001). Antidepressants demonstrated a protective effect on the risk of AA (hazard ratio, 0.57; 95% CI, 0.53-0.62; P < .001). In the analysis of the risk of MDD, 6861 patients who developed AA (3846 women and 3015 men; median age, 31.5 years [interquartile range, 18.2 years]) and 6 137 342 patients who did not develop AA (3 172 371 women and 2 964 971 men; median age, 35.9 years [interquartile range, 27.0 years]) were followed up for 26 years. After adjustment for covariates, AA was found to increase the risk of subsequently developing MDD by 34% (hazard ratio, 1.34; 95% CI, 1.23-1.46; P < .001).Conclusions and relevanceThese temporal analyses suggest that, while patients with AA are at risk for subsequently developing MDD, having MDD also appears to be a significant risk factor for development of AA, with antidepressant use confounding this risk.
| S-EPMC6459092 | biostudies-literature
Project description:Major depressive disorder (MDD) exhibits numerous clinical and molecular features that are consistent with putative epigenetic misregulation. Despite growing interest in epigenetic studies of psychiatric diseases, the methodologies guiding such studies have not been well defined. We performed DNA modification analysis in white blood cells from monozygotic twins discordant for MDD, in brain prefrontal cortex, and germline (sperm) samples from affected individuals and control subjects (total N = 304) using 8.1K CpG island microarrays and fine mapping. In addition to the traditional locus-by-locus comparisons, we explored the potential of new analytical approaches in epigenomic studies. In the microarray experiment, we detected a number of nominally significant DNA modification differences in MDD and validated selected targets using bisulfite pyrosequencing. Some MDD epigenetic changes, however, overlapped across brain, blood, and sperm more often than expected by chance. We also demonstrated that stratification for disease severity and age may increase the statistical power of epimutation detection. Finally, a series of new analytical approaches, such as DNA modification networks and machine-learning algorithms using binary and quantitative depression phenotypes, provided additional insights on the epigenetic contributions to MDD. Mapping epigenetic differences in MDD (and other psychiatric diseases) is a complex task. However, combining traditional and innovative analytical strategies may lead to identification of disease-specific etiopathogenic epimutations.
2012-04-28 | GSE37579 | GEO