Dissecting the shared genetic basis of migraine and mental disorders using novel statistical tools

Migraine is three times more prevalent in people with bipolar disorder or depression. The relationship between schizophrenia and migraine is less certain although glutamatergic and serotonergic neurotransmission are implicated in both. A shared genetic basis to migraine and mental disorders has been suggested but previous studies have reported weak or non-significant genetic correlations and five shared risk loci. Using the largest samples to date and novel statistical tools, we aimed to determine the extent to which migraine's polygenic architecture overlaps with bipolar disorder, depression and schizophrenia beyond genetic correlation, and to identify shared genetic loci. Summary statistics from genome-wide association studies were acquired from large-scale consortia for migraine (n cases = 59 674; n controls = 316 078), bipolar disorder (n cases = 20 352; n controls = 31 358), depression (n cases = 170 756; n controls = 328 443) and schizophrenia (n cases = 40 675, n controls = 64 643). We applied the bivariate causal mixture model to estimate the number of disorder-influencing variants shared between migraine and each mental disorder, and the conditional/conjunctional false discovery rate method to identify shared loci. Loci were functionally characterized to provide biological insights. Univariate MiXeR analysis revealed that migraine was substantially less polygenic (2.8 K disorder-influencing variants) compared to mental disorders (8100-12 300 disorder-influencing variants). Bivariate analysis estimated that 800 (SD = 300), 2100 (SD = 100) and 2300 (SD = 300) variants were shared between bipolar disorder, depression and schizophrenia, respectively. There was also extensive overlap with intelligence (1800, SD = 300) and educational attainment (2100, SD = 300) but not height (1000, SD = 100). We next identified 14 loci jointly associated with migraine and depression and 36 loci jointly associated with migraine and schizophrenia, with evidence of consistent genetic effects in independent samples. No loci were associated with migraine and bipolar disorder. Functional annotation mapped 37 and 298 genes to migraine and each of depression and schizophrenia, respectively, including several novel putative migraine genes such as L3MBTL2, CACNB2 and SLC9B1. Gene-set analysis identified several putative gene sets enriched with mapped genes including transmembrane transport in migraine and schizophrenia. Most migraine-influencing variants were predicted to influence depression and schizophrenia, although a minority of mental disorder-influencing variants were shared with migraine due to the difference in polygenicity. Similar overlap with other brain-related phenotypes suggests this represents a pool of 'pleiotropic' variants that influence vulnerability to diverse brain-related disorders and traits. We also identified specific loci shared between migraine and each of depression and schizophrenia, implicating shared molecular mechanisms and highlighting candidate migraine genes for experimental validation.Peer reviewe

The limited usefulness of real-time 3-dimensional echocardiography in obtaining normal reference ranges for right ventricular volumes

<p>Abstract</p> <p>Background</p> <p>To obtain normal reference ranges and intraobserver variability for right ventricular (RV) volume indexes (VI) and ejection fraction (EF) from apical recordings with real-time 3-dimensional echocardiography (RT3DE), and similarly for RV area indexes (AI) and area fraction (AF) with 2-dimensional echocardiography (2DE).</p> <p>Methods</p> <p>166 participants; 79 males and 87 females aged between 29–79 years and considered free from clinical and subclinical cardiovascular disease. Normal ranges are defined as 95% reference values and reproducibility as coefficients of variation (CV) for repeated measurements.</p> <p>Results</p> <p>None of the apical recordings with RT3DE and 2DE included the RV outflow tract. Upper reference values were 62 ml/m²for RV end-diastolic (ED) VI and 24 ml/m²for RV end-systolic (ES) VI. Lower normal reference value for RVEF was 41%. The respective reference ranges were 17 cm²/m²for RVEDAI, 11 cm²/m²for RVESAI and 27% for RVAF. Males had higher upper normal values for RVEDVI, RVESVI and RVEDAI, and a lower limit than females for RVEF and RVAF. Weak but significant negative correlations between age and RV dimensions were found with RT3DE, but not with 2DE. CVs for repeated measurements ranged between 10% and 14% with RT3DE and from 5% to 14% with 2DE.</p> <p>Conclusion</p> <p>Although the normal ranges for RVVIs and RVAIs presented in this study reflect RV inflow tract dimensions only, the data presented may still be regarded as a useful tool in clinical practice, especially for RVEF and RVAF.</p

Flow propagation velocity is not a simple index of diastolic function in early filling. A comparative study of early diastolic strain rate and strain rate propagation, flow and flow propagation in normal and reduced diastolic function

BACKGROUND: Strain Rate Imaging shows the filling phases of the left ventricle to consist of a wave of myocardial stretching, propagating from base to apex. The propagation velocity of the strain rate wave is reduced in delayed relaxation. This study examined the relation between the propagation velocity of strain rate in the myocardium and the propagation velocity of flow during early filling. METHODS: 12 normal subjects and 13 patients with treated hypertension and normal systolic function were studied. Patients and controls differed significantly in diastolic early mitral flow measurements, peak early diastolic tissue velocity and peak early diastolic strain rate, showing delayed relaxation in the patient group. There were no significant differences in EF or diastolic diameter. RESULTS: Strain rate propagation velocity was reduced in the patient group while flow propagation velocity was increased. There was a negative correlation (R = -0.57) between strain rate propagation and deceleration time of the mitral flow E-wave (R = -0.51) and between strain rate propagation and flow propagation velocity and there was a positive correlation (R = 0.67) between the ratio between peak mitral flow velocity / strain rate propagation velocity and flow propagation velocity. CONCLUSION: The present study shows strain rate propagation to be a measure of filling time, but flow propagation to be a function of both flow velocity and strain rate propagation. Thus flow propagation is not a simple index of diastolic function in delayed relaxation

Assessment of cardiac remodeling in asymptomatic mitral regurgitation for surgery timing: a comparative study of echocardiography and magnetic resonance imaging

<p>Abstract</p> <p>Background</p> <p>Early surgery is recommended for asymptomatic severe mitral regurgitation (MR), because of increased postoperative left ventricular (LV) dysfunction in patients with late surgery. On the other hand, recent reports emphasized a "watchful waiting" process for the determination of the proper time of mitral valve surgery. In our study, we compared magnetic resonance imaging (MRI) and transthoracic echocardiography to evaluate the LV and left atrial (LA) remodeling; for better definitions of patients that may benefit from early valve surgery.</p> <p>Methods</p> <p>Twenty-one patients with moderate to severe asymptomatic MR were evaluated by echocardiography and MRI. LA and LV ejection fractions (EFs) were calculated by echocardiography and MRI. Pulmonary veins (PVs) were measured from vein orifices in diastole and systole from the tangential of an imaginary circle that completed LA wall. Right upper PV indices were calculated with the formula; (Right upper PV diastolic diameter- Right upper PV systolic diameter)/Right upper PV diastolic diameter.</p> <p>Results</p> <p>In 9 patients there were mismatches between echocardiography and MRI measurements of LV EF. LV EFs were calculated ≥60% by echocardiography, meanwhile < 60% by MRI in these 9 patients. Severity of MR evaluated by effective regurgitant orifice area (EROA) didn't differ with preserved and depressed EFs by MRI (p > 0.05). However, both right upper PV indices (0.16 ± 0.06 vs. 0.24 ± 0.08, p: 0.024) and LA EFs (0.19 ± 0.09 vs. 0.33 ± 0.14, p: 0.025) were significantly decreased in patients with depressed EFs when compared to patients with normal EFs.</p> <p>Conclusions</p> <p>MRI might be preferred when small changes in functional parameters like LV EF, LA EF, and PV index are of clinical importance to disease management like asymptomatic MR patients that we follow up for appropriate surgery timing.</p

EFFECTIVENESS OF SWITCHING BETWEEN TNF INHIBITORS IN ANKYLOSING SPONDYLITIS (AS): DATA FROM THE NOR-DMARD REGISTER

Pathophysiology and treatment of rheumatic disease

Response and Drug Survival of 1st TNF-Inhibitor in 440 Patients with Psoriatic Arthritis - What Is the Role of Co-Medication with Methotrexate?

Pathophysiology and treatment of rheumatic disease

Effectiveness of switching between TNF inhibitors in ankylosing spondylitis: data from the NOR-DMARD register

Objective To assess the effectiveness of switching to a second tumour necrosis factor inhibitor (TNFi) in patients with ankylosing spondylitis (AS). Methods Data were extracted from an ongoing longitudinal observational multicentre study in Norway. This study included anti-TNF naive patients with AS starting treatment with a TNFi as well as treatment with a second TNFi in these same patients. Effectiveness data and 2-year drug survival were compared between switchers and non-switchers and within switchers (first and second TNFi). Results 514 anti-TNF naive patients with AS were included; 77 patients switched to a second TNFi while 437 patients did not switch. The percentages of non-switchers using etanercept, infliximab or adalimumab were 53%, 32% and 15%, and the percentages of first and second TNFi in the switchers were 42%, 53% and 5% and 40%, 23% and 36%, respectively. The reason for switching was insufficient response (IR) in 30, adverse events (AEs) in 44 and not reported in 3 patients. Baseline disease activity was similar between the groups. Three-month BASDAI 50 and ASAS 40 responses were achieved by 49% and 38% of non-switchers, by 25% and 30% of switchers after the first TNFi and by 28% and 31% after the second TNFi. The 3-month disease activity level was higher for switchers on the second TNFi than for non-switchers. Drug withdrawal rate was higher during the second TNFi among switchers than for non-switchers (p = 0.001). No difference was found in the effectiveness of the second TNFi between switchers due to IR and AE. Conclusion This study confirms that switching to a second TNFi can be effective in AS and can be as useful as in rheumatoid arthritis, although overall effectiveness seems to be somewhat lower than in non-switchers.Pathophysiology and treatment of rheumatic disease