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- W4308957035 abstract "The recent published article by Elefante et al. (2022), which examined, in a retrospective chart review, the association between late-onset depression (LOD) and risk of developing bipolar disorder (BD), is of great interest with important implications for the field as people are living longer and healthier lives. This retrospective study included 57 adults [mean age (SD) = 73.9 (4.7)] experiencing a major depressive episode of at least moderate severity with a mean follow-up period of more than 3 years; the study was divided into two groups: LOD (>60 years of age) and typical onset of depression (TOD) (<60 years of age). The authors reported a trend association of a higher conversion rate to BD from LOD in comparison to TOD (44% vs. 20%, P = 0.09) and a significantly shorter conversion time for the LOD group (hazard ratio = 3.7; P = 0.04). These observations are in accordance with previous literature and encourage further research into the LOD phenotype. The significant challenges of quantifying risk of conversion to BD with an episode of depression, in the absence of operationalized clinical criteria or validated biomarkers, has diagnostic and therapeutic implications. Several explanations likely contribute to the diagnostic difficulties encountered such as the high prevalence of depression as the index first episode and the common clinical course of recurrent episodes of depression preceding the hallmark manic episode. Additionally, subthreshold mania/hypomania (i.e. mixed symptoms) could be missed or not diagnosed in patients with major depressive disorder (MDD). For example, Fiedorowicz et al. (2011) examining more than 500 hundred patients with major depression from the National Institute of Mental Health Collaborative Depression Study (mean prospective follow-up = 17.5 years) found that hypomanic symptoms, in particular, decreased need for sleep, energy, and goal-oriented productivity even of mild severity were associated with a subsequent progression to BD. Similarly, the BRIDGE study that included more than 5600 patients with an episode of major depression (16% with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision bipolar diagnosis) identified an additional 31% of patients who met criteria for bipolar spectrum when mood and energy criteria were modified (either, not both) and duration were waived (Angst et al., 2011). Certainly, a contributing factor, now more broadly recognized with DSM5 and recognized with the Elefante study, is the presence of mixed features in major depression (Elefante et al., 2022). The association of age of illness onset and mood predominance is complex, and not unidirectional. In a cohort of patients with BD (N = 505) systematically followed for more than 4 years, the proportion of time spent manic(hypo) declined with older onset-age, whereas depression increased significantly (Miola et al., 2022). This, in turn, may contribute to the challenges of recognizing mania(hypo) in LOD phenotype. There has been great interest in identifying features or longitudinal risk factors that differentially diagnose the major mood disorders. Clinical features suggestive of BD have included earlier onset and multiple episodes of depression, psychosis, greater prevalence of family history of mood disorders, subthreshold hypomanic or mixed symptoms, family history of BD, and the greater number of suicide attempts (Dudek et al., 2010; Nestsiarovich et al., 2021). Longitudinal studies such as the seminal work of the Zurich cohort by Angst et al. (2005), which evaluated the time course and risk factors to diagnostic conversion for more than 20 years reported a 50% rate switch to BD type I (32%) and BD type II (18%) with average per year risk of conversion of approximately of 1% for bipolar type I and 0.5% for bipolar type II. Interestingly, the authors also suggested the contribution of a LOD phenotype as a risk factor, in addition to female sex and family history of mania (Angst et al., 2005). Elefante et al. (2022) reported that 36 patients (63.2%) received serotonin noradrenaline reuptake inhibitors (SNRIs) and 21 patients (36.8%) tricyclics. However, treatment duration, dose, or switch between antidepressant classes was not reported. Considering the high rate of antidepressant nonresponse and treatment resistance in BD, the relationship between nonresponse and diagnostic conversion is an important area for research. For example, Li et al. (2012) in a large prospective study (mean follow-up of 8 years) reported an association between antidepressant nonresponse and diagnostic conversion from unipolar to BD; specifically, when the authors examined two cohorts of patients with MDD, they found that the ‘difficult to treat group’ had a higher conversion rate to BD than ‘easier to treat’ group; in each cohort antidepressant use history strongly associated with diagnostic conversion. Antidepressant pharmacotherapy remains common for both mood disorders despite strikingly disparate clinical evidence bases in BD compared with MDD (Pacchiarotti et al., 2013; Dell’Osso et al., 2020). Different molecules have been suggested to have lower incidence rates of treatment-emergent switch such as serotonin reuptake inhibitors and bupropion compared with SNRIs and tricyclics (Vieta et al., 2002; Post et al., 2006). Thus, general treatment guidelines suggest, if needed, the use of antidepressant solely in combination with mood stabilizers for a limited period of time (Frye et al., 2000; Pacchiarotti et al., 2013). When to prescribe antidepressants and to what extent of time, dosage, and combination is an urgent clinical concern, which remains unanswered. An interesting point raised by Elefante et al. (2022) is the appearance of hypomanic/mixed episodes in the context of LOD due to vascular and neurodegenerative changes; this diagnostic conversion aligns with bipolar VI subtype described by Akiskal and Benazzi, 2005. It would be important to better understand the percentage of patients in each of the comparison groups who have had associated neurological conditions (stroke, vascular disease, and traumatic brain injury). For example, Zanetti et al. (2007) has highlighted the possible association of brain MRI white matter intensities, prototypical of vasculopathy, and the emergence of a late onset mania. These findings would further encourage future age of illness onset phenotyping studies and their association with imaging-based biomarkers and potential clinical significance with prospective treatment outcome. Most of the genetic or heritability studies have focused on early-onset depression with few studies examining LOD phenotype or its association with other psychiatric disorders. Data from the UK Biobank cohort (N = 94 154) suggested that early age of onset of major depression was heritable and had genetic overlap with not only MDD, but also autism-spectrum disorder, schizophrenia, BD, and anorexia nervosa (Harder et al., 2022). Additionally, Coleman et al. (2020) suggested 15 novel loci for mood disorders emphasizing a greater genetic similarity of BD type II to MDD supporting a genetic mood spectrum, which seem to align with the earlier clinical descriptions (Akiskal and Benazzi, 2005). Elefante et al. (2022) stresses the need to further study the genetic contribution and overlapping symptoms between unipolar and bipolar depressive episodes, especially considering early versus late onset. Perhaps the diagnostic controversies between early versus LOD and transition towards BD could be analyzed in a similar fashion as the mania phenotypes described by the French National EPIMAN II Mille Cohort (Azorin, 2012), which identified four clusters of classic mania, psychotic mania, depressive mania, and dual mania with its specific sociodemographic and clinical characteristics. This study remarks the importance of age of onset and environmental stress models as contributing factors to the course and severity of illness. Improving phenotypic characterization of the affective subgroups by considering a combination of clinical risk factors, including age of onset, prodromal symptomatology, and genetic and neuroimaging findings could lead to new stratification-risk models, which would hopefully optimize diagnostic and therapeutic clinical endeavors. Acknowledgements Conflicts of interest N.A.N.’s research was supported by National Institute of General Medical Sciences of the National Institutes of Health under award number T32 GM008685. A.M. has no conflicts of interest. M.A.F. reports grant support from Assurex Health, Mayo Foundation, Medibio. Consultant (Mayo) - Actify Neurotherapies, Allergan, Intra-Cellular Therapies, Inc., Janssen, Myriad, Neuralstem Inc., Takeda, Teva Pharmaceuticals. He reports CME/Travel/Honoraria from the American Physician Institute, CME Outfitters, Global Academy for Medical Education." @default.
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- W4308957035 date "2022-11-11" @default.
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- W4308957035 title "Examining age of onset phenotype in the spectrum of mood disorders" @default.
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