Hormonal circadian rhythms in patients with congenital adrenal hyperplasia: identifying optimal monitoring times and novel disease biomarkers

Objectives: The treatment goal in congenital adrenal hyperplasia (CAH) is to replace glucocorticoids while avoiding androgen excess and iatrogenic Cushing's syndrome. However, there is no consensus on how to monitor disease control. Our main objectives were to evaluate hormonal circadian rhythms and use these profiles to identify optimal monitoring times and novel disease biomarkers in CAH adults on intermediate- and long-acting glucocorticoids. Design: This was an observational, cross-sectional study at the National Institutes of Health Clinical Center in 16 patients with classic CAH. Methods: Twenty-four-hour serum sampling for ACTH, 17-hydroxyprogesterone (17OHP), androstenedione (A4), androsterone, DHEA, testosterone, progesterone and 24-h urinary pdiol and 5β-pdiol was carried out. Bayesian spectral analysis and cosinor analysis were performed to detect circadian rhythmicity. The number of hours to minimal (TminAC) and maximal (TmaxAC) adrenocortical hormone levels after dose administration was calculated. Results: A significant rhythm was confirmed for ACTH (r2, 0.95; P<0.001), 17OHP (r2, 0.70; P=0.003), androstenedione (r2, 0.47; P=0.043), androsterone (r2, 0.80; P<0.001), testosterone (r2, 0.47; P=0.042) and progesterone (r2, 0.64; P=0.006). The mean (S.D.) TminAC and TmaxAC for 17OHP and A4 were: morning prednisone (4.3 (2.3) and 9.7 (3.5) h), evening prednisone (4.5 (2.0) and 10.3 (2.4) h), and daily dexamethasone (9.2 (3.5) and 16.4 (7.2) h). AUC0–24 h progesterone, androsterone and 24-h urine pdiol were significantly related to 17OHP. Conclusion: In CAH patients, adrenal androgens exhibit circadian rhythms influenced by glucocorticoid replacement. Measurement of adrenocortical hormones and interpretation of results should take into account the type of glucocorticoid and time of dose administration. Progesterone and backdoor metabolites may provide alternative disease biomarkers

The genetics of the mood disorder spectrum:genome-wide association analyses of over 185,000 cases and 439,000 controls

Background Mood disorders (including major depressive disorder and bipolar disorder) affect 10-20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Despite their diagnostic distinction, multiple approaches have shown considerable sharing of risk factors across the mood disorders. Methods To clarify their shared molecular genetic basis, and to highlight disorder-specific associations, we meta-analysed data from the latest Psychiatric Genomics Consortium (PGC) genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; non-overlapping N = 609,424). Results Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More genome-wide significant loci from the PGC analysis of major depression than bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell-types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment – positive in bipolar disorder but negative in major depressive disorder. Conclusions The mood disorders share several genetic associations, and can be combined effectively to increase variant discovery. However, we demonstrate several differences between these disorders. Analysing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum

Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders

Multiplex families with a high prevalence of a psychiatric disorder are often examined to identify rare genetic variants with large effect sizes. In the present study, we analysed whether the risk for bipolar disorder (BD) in BD multiplex families is influenced by common genetic variants. Furthermore, we investigated whether this risk is conferred mainly by BD-specific risk variants or by variants also associated with the susceptibility to schizophrenia or major depression. In total, 395 individuals from 33 Andalusian BD multiplex families (166 BD, 78 major depressive disorder, 151 unaffected) as well as 438 subjects from an independent, BD case/control cohort (161 unrelated BD, 277 unrelated controls) were analysed. Polygenic risk scores (PRS) for BD, schizophrenia (SCZ), and major depression were calculated and compared between the cohorts. Both the familial BD cases and unaffected family members had higher PRS for all three psychiatric disorders than the independent controls, with BD and SCZ being significant after correction for multiple testing, suggesting a high baseline risk for several psychiatric disorders in the families. Moreover, familial BD cases showed significantly higher BD PRS than unaffected family members and unrelated BD cases. A plausible hypothesis is that, in multiplex families with a general increase in risk for psychiatric disease, BD development is attributable to a high burden of common variants that confer a specific risk for BD. The present analyses demonstrated that common genetic risk variants for psychiatric disorders are likely to contribute to the high incidence of affective psychiatric disorders in the multiplex families. However, the PRS explained only part of the observed phenotypic variance, and rare variants might have also contributed to disease development.</p