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Cardiovascular morbidity and mortality are high in persons with severe mental illness. Psychotropic medications, particularly second-generation antipsychotics (SGA), and also adverse health behaviors are mediators of adverse cardiometabolic health outcomes in persons with severe mental illness. Identifying and addressing specific risk factors early and aggressively is key to improving health outcomes in these patients; yet studies addressing the above problems are limited. We therefore evaluated 39 patients with schizophrenia, schizoaffective, or bipolar disorder on SGA in a comprehensive cardiometabolic, lifestyle, and mental health screening program. Data were analyzed using SPSS version 24. As previously reported, the majority of screened patients had prediabetes (PD) or diabetes mellitus (DM), 74% per oral Glucose Tolerance Testing (oGTT), 56% per HbA1c criteria. Pulse rates, insulin resistance indices (Homeostatic Model Assessment of Insulin Resistance, HOMA IR, and Matsuda) were significantly different between patients classified as normal or with PD/DM, using either oGTT or HbA1c criteria. However, patients with PD/DM per HbA1c, but not oGTT criterium, also had higher waist/hip ratios (p=0.01), triglyceride (p=0.01) and hsCRP levels (p=0.04) as well as lower HDL levels (p=0.04). We then determined whether dietary habits (by UK Diabetes and Diet Questionnaire, UKDDQ), mood (by Patient Health Questionnaire, PHQ-9) and/or physical activity (average daily step count) were associated with unfavorable, and potentially modifiable cardiometabolic biomarkers (fasting, 2h-oGTT plasma glucose, serum insulin, triglycerides, HDL, LDL, HbA1c, hsCRP and adiponectin). We find that fasting plasma glucose and triglyceride levels significantly correlated with UKDDQ scores (fasting plasma glucose: r=0.34, p=0.03, fasting triglyceride levels: r=0.37, p=0.02); a trend was observed for higher insulin resistance indices (HOMA IR) being associated with higher UKDDQ scores (r=0.31, p=0.06). We also confirm a strong negative correlation of the average daily step count with hsCRP levels (r=-0.62, p Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m., Sunday, June 12, 2022 1:06 p.m. - 1:11 p.m.

The rates of obesity and type 2 diabetes (T2D) are much higher in patients with chronic mental illness compared to the general population1. Second-generation antipsychotic medications (SGA) are clearly contributory to these adverse metabolic phenotypes2. Thus, annual monitoring of fasting plasma glucose (FPG) levels is recommended to screen for T2D in patients on SGA3. Of note, FPG, and also HbA1c, have poor sensitivities in detecting T2D early, with nearly 50% of cases being missed using either of the above tests when compared to oral Glucose Tolerance Testing (oGTT,4). We thus screened patients with schizophrenia, schizoaffective or bipolar disorder on SGA per oGTT. We hypothesized that we would identify more patients with T2D per oGTT compared to FPG or HbA1c testing alone. To identify risk factors for T2D, we also assessed BMI, waist/hip ratio, blood pressure, dietary habits (UKDDQ = UK Diabetes and Diet Questionnaire), physical activity records (3d pedometer records), measures of psychopathology, cognition (PHQ-9 = Patient Health Questionnaire, SLUMS = Saint Louis University Mental Status exam) as well as HOMA IR (Homeostatic Model Assessment of Insulin Resistance), Matsuda index and lipid profile. Data were analyzed using SPSS, comparing normal and prediabetic patients to patients with T2D (per oGTT criteria). Thus far, we screened 22 patients per oGTT and newly identified 5 patients with T2D (23%), only one patient had T2D per HbA1c criterion, 4 were identified per elevated FPG, 3 patients had elevated 2h plasma glucose levels. Patients with T2D had significantly lower Matsuda indices (p

Introduction: Obesity and diabetes are much more common in patients with mental illnesses compared to the general population; and both, antipsychotic as well as antidepressant medications have been associated with adverse metabolic outcomes. A retrospective data analysis of patients seen in our diabetes clinic revealed that patients on AntiPsychotic Medications (APM) particularly benefited from GLP (Glucagon-Like Peptide) analogues compared to alternative regimens. In addition to HbA1c reductions, patients on GLP analogues lost about 7 kg weight after one year; patients on alternative diabetes regimens gained 2 kg (1). Furthermore, HbA1c reductions were blunted in patients who were on APM andAntiDepressant Medications (ADM), but NOT if treated with GLP analogues. Patients on APM and ADM had significantly larger HbA1c reductions after therapy with a GLP analogue compared to alternative regimens (1). HYPOTHESIS: We hypothesized that patients on ADM ALONE might similarly benefit from GLP analogues, both in terms of weight as well as glycemic control. RESULTS: We conducted a retrospective chart review of patients on ADM seen in our diabetes clinic between 2016-2018. So far, 20 patients were included into this retrospective analysis. Ten were on GLP analogues (cases), ten were on alternative antidiabetic agents (controls). Cases and controls did not significantly differ in age, sex, height and weight at the time of referral. Within one year, a reduction in HbA1c (mean±SE) was noted in both groups (-1.19±0.86% for cases, -0.6±0.67% for controls) with a trend towards a larger HbA1 reduction in the cases, i.e. patients treated with a GLP analogue (p=0.1). In addition, patients on GLP analogues lost 2.87±3.15kg weight, control patients lost 0.71±0.95kg (p=0.5). CONCLUSIONS: In summary, GLP analogues promote both glycemic and weight control in diabetic patients on ADM; they may be superior to alternative antidiabetic regimens. Additional, prospective studies are needed to confirm and validate these promising trends. REFERENCES: Perlis L, Miedlich SU. GLP analogues are superior for diabetes and weight control in patients on antipsychotic plus/minus antidepressant medications. Diabetes 2018 Jul; 67 (Supplement 1): 2294-PUB.

Introduction: The majority of cases with postmenopausal hyperandrogenism have a benign etiology such as ovarian hyperthecosis, hilus cell hyperplasia, ovarian or adrenal tumors. Determining adrenal versus ovarian OR tumorous versus nontumorous causes of hyperandrogenism can be tricky. Here we report two very different cases associated with ovarian hyperthecosis. Case 1: The 73 year old obese female with a history of prediabetes, hysterectomy and breast cancer presented with severe hirsutism and virilization over 5 years. Testosterone levels per LC/MS were between 200-350 ng/dL and rose further during a 2d LDDST (Low Dose Dexamethasone Suppression Test), while cortisol and DHEA-S suppressed appropriately. Imaging was negative for an adrenal or ovarian mass. Based on the biochemical data, we suspected a tumorous ovarian source of androgen excess despite negative imaging findings. The patient underwent salpingo-oophorectomy which revealed small bilateral steroid cell tumors (0.7-0.9 cm) in the setting of bilateral focal hyperthecosis and hilus cell hyperplasia. Postoperative testosterone levels fell to 14 ng/dL. Case 2: The 53 year old obese female with a history of diabetes and PCOS presented with progressive male pattern hair loss, acne and acanthosis nigricans over 3-5 years. Her testosterone levels per LC/MS were between 100-150 ng/dL. During LDDST, cortisol and DHEA-S suppressed appropriately, testosterone increased further. Imaging was again negative for an adrenal or ovarian mass. Following this workup, the patient was treated with a GnRH analogue which resulted in complete testosterone suppression, regression of acanthosis nigricans and scalp hair regrowth. She later underwent salpingo-oophorectomy which showed only a few scattered, minute clusters of luteinizing theca cells in both ovaries, no tumor was identified. Lessons: These cases illustrate that imaging often fails to detect small ovarian tumors, stressing the need for additional diagnostic markers such as LDDST. Based on their case series, Kaltsas et al. suggested that lack of testosterone suppression during LDDST ruled out a nontumorous androgen source (1). However, this was not true for case 2 presented here: Testosterone remained non-suppressed during LDDST, yet she did not have an androgen-producing tumor, but mild hyperthecosis. Notably, her testosterone levels were 150 ng/dL PLUS absent testosterone suppression during LDDST might be suggestive of androgen-producing tumors. Furthermore, therapy with GnRH can be an alternative to surgery in cases with ovarian hyperandrogenism. References: Kaltsas GA, Isidori AM, Kola BP, et al. The value of the low-dose dexamethasone suppression test in the differential diagnosis of hyperandrogenism in women. JCEM 2003; 88(6): 2634-2643.