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In populations exposed to substantial structural adversity, it remains unclear whether inflammatory and metabolic biomarker differences reflect adversity exposure itself or cluster around specific depressive phenotypes.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>Data were drawn from the S\u00e3o Paulo Megacity Mental Health Survey, a population- based study in which 5,037 household residents underwent structured psychiatric interviews. Among 770 participants assessed as having clinically significant symptoms (SCID-I), individuals with chronic physical illnesses, hs-CRP &gt;20 mg\/L, or missing data were excluded, yielding an analytic sample of 653. Latent class analysis of 16 DSM-IV depressive symptoms was used to identify symptom-derived phenotypes. Multinomial logistic regression tested associations between latent classes and immune-metabolic biomarkers, including hs-CRP, lipid fractions, fasting glucose, and triglycerides, adjusting for age, sex, education, smoking, and BMI.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>A four-class solution identified asymptomatic (44.56%), mild-moderate (19.14%), atypical-like (16.69%), and melancholic-like (19.60%) classes. The two high-severity classes diverged by neurovegetative features: atypical-like depression was characterised by weight gain, hypersomnia, and psychomotor retardation, whereas melancholic-like depression was characterised by weight loss, insomnia, and psychomotor agitation. hs-CRP was highest in the atypical-like class and lowest in the melancholic-like class despite similar symptom severity. After BMI adjustment, elevated hs-CRP in the atypical-like class attenuated, whereas lower hs- CRP in the melancholic-like class persisted. Other metabolic markers did not robustly differentiate classes after adjustment.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Immune-metabolic differences in depression do not simply follow symptom severity. In this S\u00e3o Paulo cohort, higher and lower hs-CRP profiles clustered around distinct latent depressive phenotypes, supporting biologically heterogeneous depressive presentations within a socially exposed urban population.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Highlights<\/jats:title>\n                  <jats:list list-type=\"bullet\">\n                    <jats:list-item>\n                      <jats:p>Latent class analysis (LCA) of 16 DSM-IV symptoms identified four symptom-derived classes: asymptomatic, mild\u2013moderate, atypical-like, and melancholic-like.<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>The two high-severity classes diverged primarily by neurovegetative features: weight gain\/hypersomnia versus weight loss\/insomnia.<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>hs-CRP was highest in the atypical-like class and lowest in the melancholic-like class.<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>Elevated hs-CRP in the atypical-like class attenuated after BMI adjustment, whereas lower hs-CRP in the melancholic-like class persisted after BMI adjustment.<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>Findings suggest that immune-metabolic differences in depression may cluster around symptom-derived phenotypes rather than severity alone.<\/jats:p>\n                    <\/jats:list-item>\n                  <\/jats:list>\n                <\/jats:sec>","DOI":"10.64898\/2026.07.15.26358135","type":"posted-content","created":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T22:55:13Z","timestamp":1784242513000},"source":"Crossref","is-referenced-by-count":0,"title":["Immune disturbances cluster around 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