Project description:Migraine frequently co-occurs with depression. Using a large sample of Australian twin pairs, we aimed to characterize the extent to which shared genetic factors underlie these two disorders. Migraine was classified using three diagnostic measures, including self-reported migraine, the ID migraine™ screening tool, or migraine without aura (MO) and migraine with aura (MA) based on International Headache Society (IHS) diagnostic criteria. Major depressive disorder (MDD) and minor depressive disorder (MiDD) were classified using the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria. Univariate and bivariate twin models, with and without sex-limitation, were constructed to estimate the univariate and bivariate variance components and genetic correlation for migraine and depression. The univariate heritability of broad migraine (self-reported, ID migraine, or IHS MO/MA) and broad depression (MiDD or MDD) was estimated at 56% (95% confidence interval [CI]: 53-60%) and 42% (95% CI: 37-46%), respectively. A significant additive genetic correlation (r G = 0.36, 95% CI: 0.29-0.43) and bivariate heritability (h 2 = 5.5%, 95% CI: 3.6-7.8%) was observed between broad migraine and depression using the bivariate Cholesky model. Notably, both the bivariate h 2 (13.3%, 95% CI: 7.0-24.5%) and r G (0.51, 95% CI: 0.37-0.69) estimates significantly increased when analyzing the more narrow clinically accepted diagnoses of IHS MO/MA and MDD. Our results indicate that for both broad and narrow definitions, the observed comorbidity between migraine and depression can be explained almost entirely by shared underlying genetically determined disease mechanisms.
Project description:ObjectiveTo investigate the co-occurrence of migraine and depression and assess whether shared genetic factors may underlie both diseases.MethodsSubjects were 2,652 participants of the Erasmus Rucphen Family genetic isolate study. Migraine was diagnosed using a validated 3-stage screening method that included a telephone interview. Symptoms of depression were assessed using the Center for Epidemiologic Studies Depression scale and the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). The contribution of shared genetic factors in migraine and depression was investigated by comparing heritability estimates for migraine with and without adjustment for symptoms of depression, and by comparing the heritability scores of depression between migraineurs and controls.ResultsWe identified 360 migraine cases: 209 had migraine without aura (MO) and 151 had migraine with aura (MA). Odds ratios for depression in patients with migraine were 1.29 (95% confidence interval [CI] 0.98-1.70) for MO and 1.70 (95% CI 1.28-2.24) for MA. Heritability estimates were significant for all migraine (0.56), MO (0.77), and MA (0.96), and decreased after adjustment for symptoms of depression or use of antidepressant medication, in particular for MA. Comparison of the heritability scores for depression between patients with migraine and controls showed a genetic correlation between HADS-D score and MA.ConclusionsThere is a bidirectional association between depression and migraine, in particular migraine with aura, which can be explained, at least partly, by shared genetic factors.
Project description:BackgroundMigraine is a common primary headache that has a significant impact on patients' quality of life. The co-occurrence of migraine and depression is frequent, resulting in more complex symptoms and a poorer prognosis. The evidence suggests that depression and migraine comorbidity share a polygenic genetic background.ObjectiveThe aim of this study is to identify related genetic variants that contribute to genetic susceptibility to migraine with and without depression in a Chinese cohort.MethodsIn this case-control study, 263 individuals with migraines and 223 race-matched controls were included. Eight genetic polymorphism loci selected from the GWAS were genotyped using Sequenom's MALDI-TOF iPLEX platform.ResultsIn univariate analysis, ANKDD1B rs904743 showed significant differences in genotype and allele distribution between migraineurs and controls. Furthermore, a machine learning approach was used to perform multivariate analysis. The results of the Random Forest algorithm indicated that ANKDD1B rs904743 was a significant risk factor for migraine susceptibility in China. Additionally, subgroup analysis by the Boruta algorithm showed a significant association between this SNP and migraine comorbid depression. Migraineurs with depression have been observed to have worse scores on the Beck Anxiety Inventory (BAI) and the Migraine Disability Assessment Scale (MIDAS).ConclusionThe study indicates that there is an association between ANKDD1B rs904743 and susceptibility to migraine with and without depression in Chinese patients.
Project description:Clonal hematopoiesis (CH)-age-related expansion of mutated hematopoietic clones-can differ in frequency and cellular fitness by CH type (e.g., mutations in driver genes (CHIP), gains/losses and copy-neutral loss of chromosomal segments (mCAs), and loss of sex chromosomes). Co-occurring CH raises questions as to their origin, selection, and impact. We integrate sequence and genotype array data in up to 482,378 UK Biobank participants to demonstrate shared genetic architecture across CH types. Our analysis suggests a cellular evolutionary trade-off between different types of CH, with LOY occurring at lower rates in individuals carrying mutations in established CHIP genes. We observed co-occurrence of CHIP and mCAs with overlap at TET2, DNMT3A, and JAK2, in which CHIP precedes mCA acquisition. Furthermore, individuals carrying overlapping CH had high risk of future lymphoid and myeloid malignancies. Finally, we leverage shared genetic architecture of CH traits to identify 15 novel loci associated with leukemia risk.
Project description:BackgroundsResearch on shared decision-making (SDM) has mainly focused on decisions about treatment (e.g., medication or surgical procedures). Little is known about the decision-making process for the numerous other decisions in consultations.ObjectivesWe assessed to what extent patients are actively involved in different decision types in medical specialist consultations and to what extent this was affected by medical specialist, patient, and consultation characteristics.DesignAnalysis of video-recorded encounters between medical specialists and patients at a large teaching hospital in the Netherlands.ParticipantsForty-one medical specialists (28 male) from 18 specialties, and 781 patients.Main measureTwo independent raters classified decisions in the consultations in decision type (main or other) and decision category (diagnostic tests, treatment, follow-up, or other advice) and assessed the decision-making behavior for each decision using the Observing Patient Involvement (OPTION)5 instrument, ranging from 0 (no SDM) to 100 (optimal SDM). Scheduled and realized consultation duration were recorded.Key resultIn the 727 consultations, the mean (SD) OPTION5 score for the main decision was higher (16.8 (17.1)) than that for the other decisions (5.4 (9.0), p < 0.001). The main decision OPTION5 scores for treatment decisions (n = 535, 19.2 (17.3)) were higher than those for decisions about diagnostic tests (n = 108, 14.6 (16.8)) or follow-up (n = 84, 3.8 (8.1), p < 0.001). This difference remained significant in multilevel analyses. Longer consultation duration was the only other factor significantly associated with higher OPTION5 scores (p < 0.001).ConclusionMost of the limited patient involvement was observed in main decisions (versus others) and in treatment decisions (versus diagnostic, follow-up, and advice). SDM was associated with longer consultations. Physicians' SDM training should help clinicians to tailor promotion of patient involvement in different types of decisions. Physicians and policy makers should allow sufficient consultation time to support the application of SDM in clinical practice.
Project description:BackgroundPrevious epidemiological and other studies have shown an association between major depressive disorder (MDD) and migraine. However, the causal relationship between them remains unclear. Therefore, this study aimed to investigate the causal relationship between MDD and migraine using a bidirectional, two-sample Mendelian randomization (MR) approach.MethodsData on MDD and migraine, including subtypes with aura migraine (MA) and without aura migraine (MO), were gathered from a publicly available genome-wide association study (GWAS). Single nucleotide polymorphisms (SNPs) utilized as instrumental variables (IVs) were then screened by adjusting the intensity of the connection and removing linkage disequilibrium. To explore causal effects, inverse variance weighting (IVW) was used as the primary analysis method, with weighted median, MR-Egger, simple mode, and weighted mode used as supplementary analytic methods. Furthermore, heterogeneity and pleiotropy tests were carried out. Cochran's Q-test with IVW and MR-Egger was used to assess heterogeneity. Pleiotropy testing was carried out using the MR-Egger intercept and MR-PRESSO analysis methods. A leave-one-out analysis was also used to evaluate the stability of the findings. Finally, we used migraine (MA and MO) levels to deduce reverse causality with MDD risk.ResultsRandom effects IVW results were (MDD-Migraine: odds ratio (OR), 1.606, 95% confidence interval (CI), 1.324-1.949, p = 1.52E-06; MDD-MA: OR, 1.400, 95%CI, 1.067-1.8378, p = 0.015; MDD-MO: OR, 1.814, 95%CI, 1.277-2.578, p = 0.0008), indicating a causal relationship between MDD levels and increased risk of migraine (including MA and MO). In the inverse MR analysis, the findings were all negative, while in sensitivity analyses, the results were robust except for the study of MA with MDD.ConclusionOur study confirms a causal relationship between MDD levels and increased risk of migraine, MA, and MO. There was little evidence in the reverse MR analysis to suggest a causal genetic relationship between migraine (MA and MO) and MDD risk levels.
Project description:Genome-wide association studies (GWAS) have identified several common genetic variants influencing major depression and general cognitive abilities, but little is known about whether the two share any of their genetic aetiology. Here we investigate shared genomic architectures between major depression (MD) and general intelligence (INT) with the MiXeR statistical tool and their overlapping susceptibility loci with conjunctional false discovery rate (conjFDR), which evaluate the level of overlap in genetic variants and improve the power for gene discovery between two phenotypes. We analysed GWAS data on MD (n = 480,359) and INT (n = 269,867) to characterize polygenic architecture and identify genetic loci shared between these phenotypes. Despite non-significant genetic correlation (rg = -0.0148, P = 0.50), we observed large polygenic overlap and identified 92 loci shared between MD and INT at conjFDR < 0.05. Among the shared loci, 69 and 64 are new for MD and INT, respectively. Our study demonstrates polygenic overlap between these phenotypes with a balanced mixture of effect.
Project description:Spatial Protein Quality Control (sPQC) sequesters misfolded proteins into specific, organelle-associated inclusions within the cell to control their toxicity. To approach the role of sPQC in cellular fitness, neurodegenerative diseases and aging, we report on the construction of Hsp100-based systems in budding yeast cells, which can artificially target protein aggregates to non-canonical locations. We demonstrate that aggregates of mutant huntingtin (mHtt), the disease-causing agent of Huntington's disease can be artificially targeted to daughter cells as well as to eisosomes and endosomes with this approach. We find that the artificial removal of mHtt inclusions from mother cells protects them from cell death suggesting that even large mHtt inclusions may be cytotoxic, a trait that has been widely debated. In contrast, removing inclusions of endogenous age-associated misfolded proteins does not significantly affect the lifespan of mother cells. We demonstrate also that this approach is able to manipulate mHtt inclusion formation in human cells and has the potential to be useful as an alternative, complementary approach to study the role of sPQC, for example in aging and neurodegenerative disease.
Project description:We performed high-throughput snATAC-seq using the 10X Genomics Chromium platform on archived post-mortem dorsolateral prefrontal cortex (BA9) tissue in MDD subjects who died by suicide and neurotypical control subjects to identify cell-type specific differentially accessible chromatin regions. We further combined snATAC-seq with previously generated snRNA-seq data from the same subjects to generate high-resolution multi-modal accessibility and expression atlas of cortical cells. This identified accessible chromatin regions potentially regulating expression of genes. Further, MDD-associated genetic risk variants were examined for their allele-specific effects on chromatin accessibility and transcription factors binding sites in cell type speciifc manner, elucdiating target risk genes and pathways associated with MDD.
Project description:Bacteria have adaptive immunity against viruses (phages) in the form of CRISPR-Cas immune systems. Currently, 6 types of CRISPR-Cas systems are known and the molecular study of three of these has revealed important molecular differences. It is unknown if and how these molecular differences change the outcome of phage infection and the evolutionary pressure the CRISPR-Cas systems faces. To determine the importance of these molecular differences, we model a phage outbreak entering a population defending exclusively with a type I/II or a type III CRISPR-Cas system. We show that for type III CRISPR-Cas systems, rapid phage extinction is driven by the probability to acquire at least one resistance spacer. However, for type I/II CRISPR-Cas systems, rapid phage extinction is characterized by an a threshold-like behaviour: any acquisition probability below this threshold leads to phage survival whereas any acquisition probability above it, results in phage extinction. We also show that in the absence of autoimmunity, high acquisition rates evolve. However, when CRISPR-Cas systems are prone to autoimmunity, intermediate levels of acquisition are optimal during a phage outbreak. As we predict an optimal probability of spacer acquisition 2 factors of magnitude above the one that has been measured, we discuss the origin of such a discrepancy. Finally, we show that in a biologically relevant parameter range, a type III CRISPR-Cas system can outcompete a type I/II CRISPR-Cas system with a slightly higher probability of acquisition.