Major depressive disorder (MDD) is a heterogeneous and disabling illness in which the depressive episode may occur alongside other psychiatric disorders and may present with distinct DSM-5 specifiers. Comorbid anxiety, obsessive-compulsive symptoms, alcohol use, psychotic symptoms and personality disorders can complicate recognition, increase symptom burden and influence treatment planning. Population and clinical studies have repeatedly found that depression co-occurs with anxiety and substance-use disorders, although estimates vary with setting, diagnostic interview, time frame and case mix [1-5]. In India, community surveys have documented a substantial burden of depressive disorders and important gaps in treatment access [2,3]. In a tertiary-care cohort, the distribution of comorbid diagnoses may therefore differ from community estimates because patients with more severe illness are more likely to seek or require specialist care. DSM-5 specifiers describe clinically relevant features of a major depressive episode, including anxious distress, mixed features, melancholic or atypical features, psychotic features, catatonia, peripartum onset and seasonal pattern. These descriptors are not mutually exclusive. The anxious-distress specifier is particularly relevant to psychiatric comorbidity: validation studies found that it commonly co-occurs with anxiety disorders, including generalized anxiety disorder (GAD) and panic disorder, and may add information about clinical course beyond a separate anxiety diagnosis [5-8,19,22]. Mixed features may overlap with activation or externalizing presentations, while psychotic depression is associated with a distinct clinical course and high clinical risk [15-18]. However, evidence linking individual specifiers to specific comorbid disorders is less extensive than the evidence that MDD itself is frequently comorbid. Results also vary by how both the specifier and comorbidity are assessed. Indian clinical data describing psychiatric comorbidities alongside DSM-5 MDD specifiers remain limited. Estimating the frequency of individual diagnoses and examining their relationship with specifier-defined presentations can help clinicians plan comprehensive assessment, identify patients who may require additional diagnostic clarification, and avoid treating symptom clusters as interchangeable with independent disorders. The present study used structured diagnostic assessment in adults with MDD attending inpatient and outpatient psychiatric services at a teaching-hospital setting in Davangere. It described the observed psychiatric comorbidity profile and DSM-5 specifier distribution, then examined the available associations between selected comorbid diagnoses and specifiers. AIM To estimate Psychiatric comorbidities and examine their association with DSM-5 specifiers among patients with Major depressive disorder. OBJECTIVES 1. To estimate the frequency and distribution of psychiatric comorbidities in patients with major depressive disorder. 2. To describe the frequency and distribution of DSM-5 specifiers in the study cohort. 3. To assess the reported associations between psychiatric comorbidities and individual DSM-5 specifiers.

Source of data The source population consisted of patients diagnosed with major depressive disorder according to DSM-5 criteria who attended the psychiatric inpatient and outpatient services of teaching hospitals attached to JJM Medical College, Davangere. The analysis used the data reported for 210 consenting patients in the source thesis. Study design The study was conducted as a hospital-based, cross-sectional descriptive study. Eligible participants were recruited by purposive sampling. Study location The study was carried out in the Department of Psychiatry and associated inpatient and outpatient services of teaching hospitals attached to JJM Medical College, Davangere, Karnataka, India. Study duration The study was conducted from December 2019 to September 2021. Sample size The source thesis stated that the sample size was calculated using the single-proportion formula: The source thesis included 210 participants. Its stated sample-size formula was n=Z^2 (p(1-p))/d^2 It specified Z = 1.96, expected prevalence p = 0.16, and absolute precision d = 0.10. Substitution gives n = (1.96² × 0.16 × 0.84) / 0.10² = 51.6, or approximately 152 participants. The enrolled sample was 210 in this study. Inclusion criteria Patients of either sex aged 18-75 years who met DSM-5 criteria for MDD and provided informed consent were included. Exclusion criteria Patients with a severe general medical condition that made an interview infeasible, intellectual disability, or a previously diagnosed psychiatric disorder were excluded, as stated in the source protocol. Procedure and methodology After written informed consent, sociodemographic and clinical details were recorded using a study proforma. MDD was confirmed using DSM-5 diagnostic criteria and applicable specifiers were assigned using the DSM-5 criteria. Psychiatric comorbidities were assessed using the Mini International Neuropsychiatric Interview (MINI), and suicidality was assessed with the MINI suicidality module. For the comorbidity analysis, manic or hypomanic episodes and non-affective psychotic disorders were tabulated descriptively but their associations with mixed-features and psychotic-features specifiers were not analyzed separately because these symptom domains as overlapping. Statistical methods Categorical variables were summarized as frequencies and percentages. Proportions and 95% confidence intervals in the manuscript tables were recalculated from the available counts using the Wilson score method. The source thesis reported use of Pearson chi-square tests for associations, Pearson correlation for selected overlap analyses, and IBM SPSS Statistics version 28. A p-value below 0.05 was considered statistically significant. Data collection Data were collected prospectively during clinical interviews by the study team using the consent form, sociodemographic proforma, DSM-5 criteria, HAM-D, MINI and MINI suicidality module. Institutional Ethics Committee approval was taken.

The analysis included 210 patients with MDD. Multiple DSM-5 specifiers could occur in the same participant. Table 1. Sociodemographic and depression-severity profile (N=210) Characteristic n (%) 95% CI for proportion (%) Age 18-35 years 107 (51.0%) 44.2-57.6 Age 36-55 years 78 (37.1%) 30.9-43.9 Age >55 years 25 (11.9%) 8.2-17.0 Female 136 (64.8%) 58.1-70.9 Male 74 (35.2%) 29.1-41.9 Rural residence 129 (61.4%) 54.7-67.8 Urban residence 81 (38.6%) 32.2-45.3 The cohort was predominantly aged 18-35 years, female and rural-residing. Severe or very severe depression was recorded in 194 participants (92.4%; 95% CI 88.0-95.3%). These are descriptive estimates from a single cohort; no between-group hypothesis test was applicable. Table 2. Psychiatric comorbidities reported among patients with MDD (N=210) Comorbidity n (%) 95% CI (%) Any psychiatric comorbidity 163 (77.6%) 71.5-82.7 No psychiatric comorbidity 47 (22.4%) 17.3-28.5 Generalized anxiety disorder (GAD) 60 (28.6%) 22.9-35.0 Alcohol use disorder (AUD) 30 (14.3%) 10.2-19.7 Non-affective psychotic disorder 21 (10.0%) 6.6-14.8 Obsessive-compulsive disorder (OCD) 20 (9.5%) 6.2-14.3 Social anxiety disorder 16 (7.6%) 4.7-12.0 Manic/hypomanic episodes 8 (3.8%) 1.9-7.3 Panic disorder 4 (1.9%) 0.7-4.8 Antisocial personality disorder (ASPD) 4 (1.9%) 0.7-4.8 Any psychiatric comorbidity was reported in 163/210 participants (77.6%; 95% CI 71.5-82.7%). GAD was the most frequently listed diagnosis (60/210, 28.6%; 95% CI 22.9-35.0%), followed by AUD (14.3%), non-affective psychotic disorder (10.0%) and OCD (9.5%). Table 3. Prevalence of DSM-5 specifiers in the MDD cohort (N=210) DSM-5 specifier n (%) 95% CI (%) Anxious distress 173 (82.4%) 76.7-86.9 Psychotic features 109 (51.9%) 45.2-58.6 Melancholic features 43 (20.5%) 15.6-26.4 Catatonic features 16 (7.6%) 4.7-12.0 Peripartum onset 13 (6.2%) 3.7-10.3 Atypical features 12 (5.7%) 3.3-9.7 Mixed features 8 (3.8%) 1.9-7.3 Seasonal pattern 4 (1.9%) 0.7-4.8 Anxious distress was the most frequently reported specifier (173/210, 82.4%; 95% CI 76.7-86.9%), followed by psychotic features (51.9%) and melancholic features (20.5%). Specifiers were permitted to overlap, so percentages do not sum to 100%. Table 4. Source-reported associations between DSM-5 specifiers and selected psychiatric comorbidities DSM-5 specifier Panic disorder p Social anxiety p GAD p OCD p AUD p ASPD p Anxious distress 0.556 0.674 0.001 0.334 0.690 0.352 Mixed features 0.212 0.015 0.652 0.463 0.096 0.001 Melancholic features 0.870 0.470 0.039 1.000 1.000 0.383 Atypical features 0.754 0.929 0.750 0.385 0.014 0.668 Psychotic features 0.028 0.063 0.085 0.858 0.535 0.093 Peripartum onset 0.707 0.041 0.026 0.816 0.129 0.654 Catatonic features 0.201 0.023 0.062 0.034 0.065 0.142 Seasonal pattern 0.312 0.123 0.111 0.125 0.127 0.215 The source used chi-square tests. Reported significant associations were anxious distress with GAD (p=0.001); mixed features with social anxiety (p=0.015) and ASPD (p=0.001); melancholic features with GAD (p=0.039); atypical features with AUD (p=0.014); psychotic features with panic disorder (p=0.028); and peripartum onset with social anxiety (p=0.041) and GAD (p=0.026). The study suggests that catatonic and seasonal specifiers had no significant comorbidity associations. Manic/hypomanic and non-affective psychotic disorders were not included in this association matrix because the thesis treated them as overlapping with mixed and psychotic specifiers.

This hospital-based sample showed substantial psychiatric comorbidity: 77.6% of participants were reported to have at least one comorbid diagnosis, while 22.4% had none. GAD was the most common diagnosis, followed by alcohol use disorder, non-affective psychosis and OCD. The high proportion is consistent with the broad literature describing frequent psychiatric co-occurrence in MDD, although estimates vary considerably with recruitment setting and diagnostic ascertainment. Hasin et al. [4] found that DSM-5 MDD was associated with a range of other psychiatric diagnoses in a nationally representative US sample, with especially strong associations for GAD. The NESDA synthesis by ter Meulen et al. [9] similarly reported that comorbidity was common among people with depressive and anxiety disorders and was related to greater chronicity, functional impairment and poorer outcome. The cross-sectional OCD findings of Dold et al.[21] also illustrate that co-occurrence rates depend on sampling and definitions. These studies support routine diagnostic assessment beyond depressive symptoms alone. GAD was present in 28.6% of the present cohort. This frequency should not be compared directly with population-based or multicentre estimates because MINI use, tertiary-care case mix, active symptom burden and exclusion criteria differed across studies [4,9,20]. The observed link between anxious distress and GAD (p=0.001) is clinically plausible. McIntyre et al. [5], Zimmerman et al. [6] and Rosellini et al. [22] found that DSM-5 anxious distress clustered with anxiety symptoms and anxiety disorders, especially GAD and panic disorder. Dold etal.[20] also described clinically relevant differences in patients with comorbid anxiety disorders. Gaspersz et al. [7,8] further showed that anxious distress carried information about subsequent clinical outcomes in MDD. The present source results align with that pattern, but missing cross-tabulation counts prevent estimation of the strength or precision of the association. Alcohol use disorder was reported in 14.3% of participants, and the source table reported an association between AUD and atypical features (p=0.014). Hunt et al. [10] synthesized community and clinical studies and found that comorbid substance-use disorders, particularly alcohol use disorder, occurred regularly in MDD. Lai et al. [11] also described substantial overlap between mood, anxiety and substance-use disorders in epidemiological surveys. Those pooled estimates cannot be directly compared with a single-center cohort, but they reinforce the need to ask about alcohol and other substances when evaluating MDD. The atypical-feature association should be treated as exploratory because the relevant cross-tabulation counts, expected cell frequencies and adjusted estimates were not reported. The source reported that mixed features were associated with social anxiety (p=0.015) and ASPD (p=0.001), while melancholic features were associated with GAD (p=0.039). DSM-5 specifier studies have emphasized that these presentations overlap with broader symptom dimensions and are sensitive to operational definitions. Hasin et al. [4] documented substantial variation in prevalence and correlates of anxious and mixed-feature MDD, and Na et al. [15] found that prevalence estimates for mixed features varied across methods. Since the mixed-feature subgroup in this cohort was small (n=8), a few participants could materially change the observed association; sparse-cell bias and multiple comparisons are important concerns. No adjustment for the number of associations tested was available. Psychotic features were recorded in 51.9% of the prevalence table, and panic disorder was associated with this specifier in the source analysis (p=0.028). Psychotic depression is a distinct clinical presentation, and systematic reviews have described its epidemiology and serious adverse outcomes [16-18]. The high psychotic-feature frequency in this study may reflect a selected tertiary-care population, local case mix, or differences in the threshold used to record a specifier. Moreover, the thesis excluded non-affective psychotic disorder from the specifier association analysis because of conceptual overlap, although it counted 21 such diagnoses in the comorbidity prevalence table. This operational decision should be clarified before interpreting or reproducing the findings. Peripartum onset was associated with social anxiety (p=0.041) and GAD (p=0.026) in the source results. These findings are based on only 13 patients and are vulnerable to unstable estimates. More broadly, the presence of overlapping psychiatric diagnoses can identify patients whose assessment and treatment require attention to multiple symptom domains. Reviews of MDD comorbidity and psychological treatment evidence emphasize that co-occurring disorders can affect functioning, prognosis and treatment needs [13,14]. The current data are descriptive and cannot establish whether comorbidity preceded the depressive episode or arose during it. The study had clinically useful strengths: DSM-5 criteria were used to assign MDD specifiers, and structured instruments were used to assess severity and comorbidity. However, its analytic reporting is incomplete. Several prevalence counts differ from association denominators; source percentages are occasionally inconsistent with counts; the stated sample-size calculation does not reproduce the enrolled sample; and the association results give p-values without the contingency tables, test statistics or confidence intervals. Thus, the findings identify potentially relevant patterns but do not support claims about adjusted or causal relationships. National mental-health studies in India [2,3] provide important epidemiologic context, but local hospital estimates should not be generalized to community populations. Replication using participant-level data, prespecified comparisons, effect estimates and correction or cautious interpretation for multiple testing is warranted.

Psychiatric comorbidity was frequent in this 210-patient MDD cohort, with GAD the most commonly listed diagnosis. Anxious distress was the leading DSM-5 specifier, followed by psychotic and melancholic features. The source analysis reported several comorbidity-specifier associations, including anxious distress with GAD, mixed features with social anxiety and ASPD, melancholic features with GAD, atypical features with AUD, psychotic features with panic disorder, and peripartum onset with social anxiety and GAD. LIMITATIONS • The hospital-based cross-sectional design and purposive sampling limited generalizability and did not establish temporal or causal relationships.

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