Anxiety Amplifies Plasma Oxytocin Levels in Older Individuals with type 2 Diabetes. Findings from the Cross-Sectional KORA-Age Study.

Anxiety Amplifies Plasma Oxytocin Levels in Older Individuals with type 2 Diabetes. 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Findings from the Cross-Sectional KORA-Age Study. Hamimatunnisa Johar, Seryan Atasoy, Linmiao Jiang, Martin Bidlingmaier, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-266249/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Purpose Beyond its role in parturition, lactation, and emotion regulation, oxytocin (OXT) plays an important role in metabolism and energy homeostasis, although evidence is still limited. We investigated the association between endogenous OXT levels and type 2 diabetes mellitus (T2DM) and whether anxiety may modify its association. Methods A cross-sectional analysis was conducted in 1006 participants aged 65-93 years (mean=75.9, SD ± 6.6) from the population-based KORA-Age study. Multivariable generalized linear regression analyses were performed to examine the association between non-extracted plasma OXT levels and T2DM with adjustments for potential confounders. Results Across the OXT tertile groups, no substantial differences between sociodemographic, lifestyle, cardiometabolic or psychosocial factors were found except for multimorbidity. The differences between the OXT tertile groups with respect to obesity status were on the borderline of statistical significance (P=0.05). However, a significant statistical interaction between T2DM and anxiety on OXT levels was found ( p = 0.03). In T2DM individuals with anxiety, substantially higher plasma OXT levels (Least Squares (LS) mean = 340.82 pg/ml, 95% CI 231.12-502.59) were observed compared to those without anxiety (217.08 pg/ml, 95% CI 190.93 – 247.99) ( p =0.02). No significant association between T2DM and OXT levels in individuals without anxiety was found. Conclusion OXT levels were significantly elevated in T2DM subjects, particularly among older individuals with anxiety. The modifying role of anxiety highlights that anxiogenic stimuli may be associated with enhanced OXT signalling, particularly in subjects who suffer from T2DM as a severe pathological feature of dysregulated metabolism. Endocrinology & Metabolism oxytocin type 2 diabetes anxiety ageing Figures Figure 1 Introduction Oxytocin (OXT), a popular hypothalamic neuropeptide known as the “prosocial hormone”, is well recognized for its positive functions in parturition, lactation, mother-infant bonding, sexuality, attachment, interpersonal trust, and emotion regulation [ 1 ]. Impairments in psychosocial domains, such as anxiety disorders, schizophrenia, and depression, may also have an impact on endogenous OXT levels [ 1 ]. Recently, increasing evidence indicates that OXT may also play a positive role in regulating metabolism by modulating eating behavior, body fat, body weight, energy expenditure, and glucose homeostasis [ 2 ]. OXT receptors have been found on pancreatic α and β cells, suggesting a potential link between OXT and type 2 diabetes mellitus (T2DM) [ 3 ]. A double-blinded crossover study on 29 healthy men found that intranasal OXT administration could acutely enhance glucose tolerance and β cell responsivity [ 4 ]. Another randomized pilot clinical trial with 24 patients reported effectively reversed prediabetic changes over 8 weeks of continuous intranasal OXT treatment [ 5 ]. Although these intervention studies showed beneficial effects of OXT on T2DM-related metabolic profiles, how T2DM may affect endogenous OXT levels is still poorly understood. While previous studies in young to middle-aged adults have found an association between lower OXT levels and T2DM [ 6 – 11 ], others have reported conflicting findings with higher levels of OXT in metabolic disorders [ 12 – 14 ]. Furthermore, most studies investigating the association between OXT and T2DM are small-sized and stem from sex-specific young populations. To date, only one study in an older men population has shown an association between elevated OXT levels and metabolic syndrome [ 14 ]. In older subjects suffering from metabolic syndrome, a compensatory mechanism of OXT may operate to maintain metabolic homeostasis where aging-related deficits develop [ 15 ]. As circulating levels of OXT tend to decline with age in animal models [ 16 ], there are possible age-by-sex related differences in circulatory OXT in humans [ 17 ], leading to mixed findings. Therefore, further research to explain these conflicting results and how T2DM may impact OXT secretion in old aged are warranted. Symptoms of anxiety are frequently observed in T2DM individuals with prevalence ranges from 14–41% in various populations [ 18 ]. Given that OXT is a profound anxiolytic factor of the brain [ 19 ], and anxiety amplifies the progression of prediabetes to T2DM onset [ 20 ], it is crucial to find out how anxiety may impact the OXT-T2DM relationship. The potential involvement of anxiety may provide some useful insights into the psychoneuroendocrinological coping mechanism of the body to deal with chronic metabolic disease conditions like T2DM. Therefore, we aimed to examine in a representative elderly population-based study: (i) the association of T2DM and plasma OXT levels and (ii) the potential modifying role of anxiety on this association. Materials And Methods Study Design and Participants Data for this study were obtained from the 2008–2009 baseline assessment of the KORA-Age study, a population-based longitudinal study designed to determine the prevalence of multimorbidity, functioning, and successful aging [ 21 ]. The KORA-Age study is a follow-up of all participants aged 65 years or older on 31 December 2008, who participated in at least one of the MONICA/KORA (Monitoring of Trends and Determinants in Cardiovascular Diseases/Cooperative Health Research in the Region of Augsburg) Surveys S1-S4 conducted between 1984–2001 among inhabitants of Augsburg and its two surrounding counties in southern Germany. All eligible participants of the KORA-Age study (n = 5991) who were alive and reachable received a postal health questionnaire (response rate 76.2%, n = 4565), followed by a standardized telephone interview (response rate 68.9%, n = 4127). Furthermore, a gender- and age-stratified random subsample of the KORA-Age cohort (53.8% of eligible participants, n = 1079) underwent an extensive medical examination, including a non-fasting blood draw and a face-to-face interview. After the exclusion of participants with missing information on plasma OXT (n = 66), diabetes status (n = 2) and non-psychosocial covariates (n = 5) in this subsample, our study has a sample size of 1006 participants. A drop-out analysis of the excluded participants revealed no significant age, sex and education level differences. This study was approved by the Ethics Committee of the Bavarian Medical Association, and written informed consents were provided by all the participants. Outcome – Plasma OXT Level Non-extracted plasma OXT level was measured from a non-fasting venous blood sample of each participant during the physical examination at the study centre using OXT Enzyme Immunoassay (Assay Designs, Ann Arbor, MI), as previously described [ 22 ]. Samples were collected in chilled EDTA tubes with 500 KIU/ml aprotinin, centrifuged within 30 min, and stored at -80℃ to minimize preanalytical sample degradation. All the samples were analyzed within 2 months using the same batch of reagents. The detection limits of the assay range from 15 to 2000 pg/ml. Intra-assay coefficients of variability are below 15%, and inter-assay coefficients of variability are 15.4%, 18.5% and 17.9% at concentrations of 234, 416 and 1930 pg/ml, respectively. The plasma OXT concentrations showed a right-skewed distribution. For the descriptive analyses, the distributions of plasma OXT were split by the tertiles, and subjects were stratified into those with low, medium or high levels. Exposure – T2DM T2DM was determined by the participant’s report in the self-administered questionnaire, and each case was verified by assessing the participant’s medical history, records from physicians, information from previous MONICA/KORA surveys, as well as the use of antidiabetic medication. Covariates Low education was defined as less than 12 years of education. A current smoker was defined as someone smoking cigarettes regularly or occasionally. Alcohol consumption was classified into two categories: consuming alcohol more than once per week, or not. Participants were considered as physically active during leisure time if they regularly participated in sports for at least 1 hour/week in either summer or winter, and inactive else. Obesity was defined as Body Mass Index (BMI) greater than 30, where BMI was calculated as weight (kg) / height 2 (m). Hypertension was defined as blood pressure ≥ 140/90 mmHg or current use of antihypertensive medication. Dyslipidemia was defined as the ratio of total cholesterol (TC) to high density lipoprotein cholesterol (HDL-C) TC/HDL-C ≥ 5.0, where TC and HDL-C in mmol/L were measured by enzymatic methods (CHOD-PAP, Boehringer Mannheim, Germany). HbA1c was quantified with a reverse-phase cation-exchange HPLC method using a Menarini–Arkray Analyzer HA-8160 (Menarini Diagnostics, Florence, Italy) in mmol/mol and %. HbA1c levels ≥ 6.5% was considered as hyperglycemia and 2 disease conditions according to the Charlson Comorbidity Index [ 23 ]. Depressive symptoms were measured by the 15-item German version of the Geriatric Depression Scale (GDS 15), with a score ≥ 10 or taking antidepressants indicating depression [ 24 ]. Anxiety symptoms were assessed using the Generalized Anxiety Disorder-7 (GAD-7) Questionnaires, where anxiety was defined by a score of 10 or higher [ 25 ]. Perceived stress from a stressful life event experienced in the past year, if any, was assessed in a personal interview rated on 5-point Likert Scale, where scale 4-quite a lot and scale 5-severely were categorized as suffering from heavy/severe stress [ 22 ]. Social network was assessed by the Beckman social network index score and classified into high (score 3–4) and low (score 1–2) social network [ 26 ]. Statistical Analysis The plasma OXT concentrations showed a right-skewed distribution and, therefore, were logarithmically transformed to approximate a normal distribution. Descriptive data of sociodemographic, lifestyle, clinical, and psychosocial characteristics were stratified by tertiles of log-transformed plasma OXT levels. The 𝜒 2 test for categorical variables and the Kruskal-Wallis test for continuous variables were used to compare the differences across the OXT tertile groups. Categorical variables were expressed as frequencies (n), and age was reported as means with standard deviations (± SD). Multivariable generalized linear regression (GLM) models were applied to assess the association between T2DM (exposure) and plasma OXT levels (outcome) with 5 different models adjustment. Model 1 was a crude model adjusted only for age and sex. Model 2 was further adjusted for educational level as a sociodemographic confounder. Model 3 and model 4 were additionally adjusted for established lifestyle (smoking, alcohol consumption, physical activity) and metabolic risk factors (obesity, hypertension, dyslipidemia, multimorbidity) of T2DM. Model 5 was performed on a smaller subgroup of participants (N = 961) with complete information for depression, anxiety, perceived stress, and social network status to consider the influence of psychosocial factors on the association. We also reanalyzed the association of OXT levels and T2DM by an additional adjustment for HbA1c levels in the crude and full model. Additional sensitivity analyses were performed to consider the interaction effect of sex and T2DM on OXT levels by including the sex X T2DM interaction term in all the models. The influence of anxiety in the association between T2DM and OXT was examined by introducing an interaction term to the crude and fully-adjusted logistic regression model. In the case of significant interaction, the regression analyses were further stratified by anxiety. The influence of obesity or glycemic status was assessed via the introduction of an interaction term of HbA1c levels*T2DM. Age and sex-adjusted least-square means (LS-means) of log-transformed plasma OXT levels and 95% confidence intervals were calculated from generalized linear models for the total study population and stratified by anxiety status. The model fits were sufficient as indicated by acceptable adjusted R-square and Root MSE statistics values throughout the GLM models. No multicollinearity among covariates was detected as assessed with the Variance Inflation Factor (VIF) with a cut-off of VIF > 2. All the statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA). The significance level was set at 0.05. The reporting of this study followed the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) guidelines. Results A total of 1006 participants (489 women and 517 men) of KORA-Age were included in our study, with an age range of 65–93 (mean 75.9, SD ± 6.6) years. Table 1 presents the study characteristics according to tertiles of the OXT level. No substantial differences between sociodemographic, lifestyle or cardiometabolic factors across the OXT tertile groups were found except for multimorbidity. The differences between the OXT tertile groups with respect to obesity status were on the borderline of statistical significance (P = 0.05). Of note, no significant differences between OXT tertile groups and anxiety were observed. Table 1 Characteristics of study population stratified by tertiles of plasma OXT levels in means (± standard deviation) or N (%) (N = 1006) Plasma OXT level Low (n = 336, 33.40%) Middle (n = 334, 33.20%) High (n = 336, 33.40%) p Sociodemographic factors Age 75.74 (± 6.81) 76.16 (± 6.43) 75.86 (± 6.68) 0.698 Male 170 (50.60%) 176 (52.69%) 171 (50.89%) 0.841 Low Education 242 (72.02%) 238 (71.26%) 250 (74.40%) 0.635 Lifestyle factors Smoking 10 (2.98%) 20 (5.99%) 17 (5.06%) 0.167 High Alcohol Consumption 161 (47.92%) 155 (46.41%) 149 (44.35%) 0.648 Physically inactive 162 (48.21%) 147 (44.01%) 158 (47.02%) 0.532 Clinical factors Obesity 100 (29.76%) 115 (34.43%) 87 (25.89%) 0.054 T2DM 46 (26.6%) 65 (37.6%) 62 (35.8%) 0.136 HbA1c (%) 5.72 (0.56) 5.75 (0.58) 5.72 (0.59) 0.750 HbA1c (mmol/mol) 38.99 (6.11) 39.35 (6.37) 38.94 (6.46) 0.755 Hypertension 251 (74.70%) 258 (77.25%) 244 (72.62%) 0.385 Dyslipidaemia 46 (13.69%) 62 (18.56%) 54 (16.07%) 0.230 Multimorbidity 197 (58.63%) 228 (68.26%) 217 (64.58%) 0.032 Psychosocial factors N = 321 (33.3%) N = 322 (33.4%) N = 321 (33.3%) Depression 23 (7.17%) 19 (5.90%) 23 (7.17%) 0.761 Anxiety 22 (6.85%) 22 (6.83%) 27 (8.41%) 0.680 Great/Severe Stress 52 (16.20%) 60 (18.63%) 60 (18.69%) 0.642 Low Social Network 209 (65.11%) 204 (63.35%) 208 (64.80%) 0.884 P values: Kruskal-wallis test for continuous variables and 𝜒 2 test for categorical variables. OXT levels were higher in participants with T2DM (age and sex-adjusted LS-mean = 224.78, 95% CI: 200, 189–211 pg/ml) compared to those without T2DM (199.74, 199–254 pg/ml) ( p = 0.08). T2DM participants were more likely to be older, have lower education levels, have BMI ≥ 30 kg/m², consume less alcohol, have hypertension and multimorbidity, and suffer more from stressful life events ( Supplementary Table 1 ). Multivariable linear regression analyses on the association of plasma OXT levels and T2DM were employed with adjustments for sociodemographic, lifestyle, metabolic, and psychosocial factors, as displayed in Table 2 . T2DM was associated with higher levels of plasma OXT; however, only with borderline statistical significance (Model 1: ß = 0.13, SE = 0.07, p = 0.07). Adjustments for all potential confounders further reduced the strength of association into non-significance (Model 5: ß = 0.11, SE = 0.07, p = 0.13). Table 2 ß estimates, standard errors (SE) and P -values for the association between T2DM and plasma OXT levels (pg/ml) of the KORA-Age participants (N = 1006) ß SE p Model 1 0.13 0.07 0.07 Model 2 0.12 0.07 0.08 Model 3 0.13 0.07 0.09 Model 4 0.12 0.07 0.12 Model 5 (n = 961) 0.11 0.08 0.13 Model 1: generalized linear model adjusted for age and sex Model 2: Model 1 + education level Model 3: Model 2 + smoking status, alcohol consumption, physical activity Model 4: Model 3 + obesity, hypertension, dyslipidemia, multimorbidity Model 5: Model 4 + anxiety, depression, perceived stress, social network Additional analytical models demonstrated, however, that a significant interaction between T2DM and anxiety on OXT levels was observed in multivariable linear regression models adjusted for age and sex ( p = 0.03). A significant interaction indicates that the association between T2DM and OXT levels is modified by the presence of anxiety. Therefore, stratified analyses were performed on the study population grouped by individuals having anxiety symptoms. As displayed in Fig. 1 , elevated plasma OXT levels were observed in T2DM individuals with anxiety ( p = 0.008) but not in those without anxiety ( p > 0.05) (LSMeans for T2DM participants, with anxiety: 340.82 pg/ml, 95% CI 231.12–502.59; without anxiety: 217.08 pg/ml, 95% CI 190.93–247.99). In multivariable linear regression models, neither the strength nor the significance of the association was substantially altered by further adjustments for concurrent risk factors (anxiety: ß = 0.62, SE = 0.24, p = 0.01; no anxiety: ß = 0.05, SE = 0.08, p = 0.50) (Table 3 ). No significant interaction of T2DM by sex on plasma OXT levels ( p > 0.05) was found. Table 3 ß estimates, standard errors (SE) and P -values of the association between T2DM and plasma OXT levels stratified by anxiety (n = 961). ß SE p No Model 1 0.06 0.08 0.43 Anxiety Model 2 0.05 0.08 0.47 (N = 891) Model 3 0.05 0.08 0.50 Model 4 0.04 0.08 0.58 Model 5 0.05 0.08 0.50 Anxiety Model 1 0.58 0.22 0.01 (N = 70) Model 2 0.59 0.22 0.01 Model 3 0.58 0.23 0.01 Model 4 0.56 0.23 0.02 Model 5 0.62 0.24 0.01 Model 1: generalized linear model adjusted for age and sex. Model 2: Model 1 + education level Model 3: Model 2 + smoking status, alcohol consumption, physical activity. Model 4: Model 3 + obesity, hypertension, dyslipidemia, multimorbidity. Model 5: Model 4 + depression, perceived stress, social network. Discussion In a sample of community-dwelling older people of 64–93 years, we found a borderline significant association between T2DM and elevated plasma OXT levels which was further diminished after adjustment for concurrent risk factors. However, driven by a significant interaction between T2DM and anxiety on OXT levels, indicating a potential modifying role of anxiety on the T2DM-OXT link, we revealed a substantially 44% higher mean level of OXT in T2DM subjects with anxiety compared to their non-T2DM counterparts with anxiety. Notably, a significant association between T2DM and OXT levels in subjects without anxiety was not found. While increasing evidence points to positive effects of OXT in attenuating metabolic risks [ 2 , 27 ] as well as its profound anxiolytic behavioral effect [ 28 ], our findings seem to be counterintuitive at first sight. However, the findings of heightened levels of OXT in T2DM subjects with anxiety do not come unexpectedly: both the impact of OXT on fear and anxiety, and its role in the metabolic regulation has yielded contradictory findings. Concerning human social behavior, OXT is widely acknowledged as a candidate molecule to facilitate fear extinction and anxiolysis [ 29 ] and, thus, is emerging as a target for mood treatment approaches [ 30 ]. However, opposing experimental data are available. Grillon et al. (2012) exposed healthy subjects to an electrical startle experiment and evidenced that OXT increased anxiety to unpredictable threat [ 31 ]. Likewise, Eckstein et al. subjected 97 healthy male probands to a Pavlovian fear learning experiment and disclosed that OXT enhanced CNS responses to social stimuli during fear conditioning, provoking increased vigilance and heightened alertness to threat [ 32 ]. Peters et al. (2014) showed that chronic intra-cereberoventricular infusion of high doses of OXT in male mice induces an anxiogenic phenotype while a low dose of OXT prevents hyperanxiety [ 33 ]. Thus, the specific nature, dosage, and timing of OXT are key aspects in orchestrating OXT responses and, instead of acting unidirectional, may result in both anxiolytic and anxiogenic behavioral effects [ 34 ]. A low dose of OXT administration is likely to alleviate the effects of stress, while a chronic high dose of OXT may increase anxiety-like behavior [ 34 ]. Furthermore, chronic administration of OXT increases adreno-corticotropic hormone (ACTH) and corticosterone levels, indicating a potentiating effect of OXT on the hypothalamic-pituitary-adrenal (HPA) axis stress reactivity [ 35 , 36 ]. Of note, the positive association between T2DM and OXT levels in subjects with anxiety remained strong even after adjustment for potentially important influential lifestyle factors (e.g. physical activity, smoking and alcohol consumption). This suggests a robust association of anxiety in T2DM patients independent from unfavorable lifestyle habits and highlights chronic anxiety as a clinically relevant phenotype [ 37 ]. Comparable to its role in affect regulation, a functional dichotomy of OXT is also apparent in metabolic regulation: On the one hand, evidence indicated that high OXT levels were positively associated with T2DM and obesity [ 38 , 12 , 39 , 14 , 13 ], reflecting the role of OXT as a signal of energy availability [ 3 ]. High OXT levels may appropriately signal the need to reduce caloric intake and increase energy expenditure [ 3 ]. On the other hand, conflicting evidence comes from studies showing low endogenous OXT levels in people with obesity (Fu-Man et al., 2019; Maestrini et al., 2018) or T2DM (Eisenberg et al., 2018; Qian et al., 2014; Yuan et al., 2016). In the present investigation, we assert a weak association between high OXT levels and T2DM. Most studies showing low OXT levels in T2DM subjects were conducted in samples of newly diagnosed or uncontrolled T2DM patients. In the present study, the majority of T2DM subjects (77%, n = 133) were under ongoing treatment. In a sensitivity analysis that considered only T2DM participants under treatment, we found that the results of our analyses remained unaltered (data are not shown). To date, there is no clear understanding of sexual dimorphism related to the OXT regulation. Although sexual dimorphism has been recognized in the OXT system [ 40 ], both genders seem to be involved in the OXT-regulated energy homeostasis [ 41 , 42 ]. The present study adds to the conflicting evidence by showing that neither sex differences nor interaction of T2DM by sex influences OXT levels. Our data also demonstrate that endogenous plasma OXT levels were unaffected by increasing age, supporting a previous report that showed OXT response during the insulin tolerance test had similar patterns and magnitudes in all groups [ 43 ]. However, it is also likely that the increase in OXT levels of older T2DM subjects could be a compensatory mechanism for the maintenance of metabolic homeostasis where age-related metabolic impairments may have already developed. Study strengths and limitations This present study was conducted in a large population-based sample of older subjects from the KORA-Age study. The random sampling of the study population, the low loss to follow-up rate, and the strict quality assessment ensured the quality of the data. The substantially larger sample size of this study compared to other relevant studies to date made it easier to draw firm conclusions based on analytical results. The study design involved extensive assessments of psychological tests and biomarkers, providing the possibility to consider potential modifying factors and to produce robust results adjusting for covariates. The current study contributes to the understanding of endogenous OXT-T2DM association in an older population. Limitations exist in this study. First, due to its cross-sectional design, we could not infer causality on the anxiety driven association between increased OXT levels and T2DM, and the findings from our study may not be generalizable to other populations. Second, the OXT levels of participants were measured from a single blood sample which may not accurately represent the average metabolic status of an individual. However, in this epidemiologic setting, the quality of the data was ensured by highly standardized procedures and a very strict quality assessment. The non-extracted plasma OXT enzyme immunoassay method used in our study may yield levels of higher magnitude than traditional radioimmunoassays because the samples may contain interfering substances [ 3 ]. Therefore, we acknowledge that OXT levels from immunoassays are measuring OXT immunoreactive products, not absolute values of OXT, preventing comparisons of absolute OXT levels between studies. However, the optimal method measuring endogenous OXT is still in active development, and “discrepancies between methods (i.e., extracted or unextracted) are not necessarily an indicator that some methods are valid whereas others are not” [ 44 ]. Furthermore, previous reports have shown a robust correlation between extracted and unextracted serum oxytocin levels [ 45 ], as well as associations between non-extracted OXT levels with body dysmorphic disorder (BDD) [ 46 ] or relationship distress [ 47 ], providing evidence for biologic relevance in these sample preparations. Therefore, in the current study, we valued the non-extracted plasma OXT enzyme immunoassay for comparing relative levels of peripheral OXT in participants with T2DM without T2DM. Conclusion The present investigation demonstrates that both T2DM status and sustained symptoms of anxiety in this old aged population contribute to a strong combined effect leading to a significantly elevated OXT level. Thus, anxiogenic stimuli significantly activate the body’s OXT system, however, only in subjects who additionally suffer from T2DM as a severe pathological feature of dysregulated metabolism. The clinical consequences of this finding actually remain unclear, however, it may be speculated that this particular OXT signaling network may be achieved to influence psychosocial adaptations with an impact on lifestyle behaviors related to energy regulation and metabolism. Declarations Funding This study was supported by grants from the German Federal Ministry of Education and Research (BMBF) to MB (FKZ 01ET1003D) and the German Center for Diabetes Research (Deutsche Zentrum für Diabetesforschung). The KORA research platform was initiated and financed by the Helmholtz Zentrum München-German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research and by the State of Bavaria. The KORA-Age project was financed by the German Federal Ministry of Education and Research [BMBF FKZ 01ET0713] as part of the ‘Health in Old Age’ program. Conflict of Interest Statement The authors have no relevant financial or non-financial interests to disclose. Availability of data and material The informed consent given by KORA study participants does not cover data posting in public databases. However, data are available upon request from KORA/KORA-gen (https://epi.helmholtz-muenchen.de/) by means of a project agreement. Requests should be sent to [email protected] and are subject to approval by the KORA Board. Code availability Statistical codes are available from the corresponding author on request. Author Contributions KHL and MB designed the study. HJ and LJ conducted literature searches and performed statistical analyses. HJ and LK wrote the first draft of the manuscript. SA and KHL provided critical feedback, proofread and approved the final manuscript. MB and JK proofread and approved the final manuscript. Ethics approval The study was approved by the Ethics Committee of the Bavarian Medical Association, and written informed consents were provided by all the participants. Consent to participate Informed consent was obtained from all individual participants included in the study. Consent for publication The authors affirm that human research participants provided informed consent for publication. 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BMC Med Res Methodol 10 (1), 36 (2010). doi:10.1186/1471-2288-10-36 Emeny, R.T., Huber, D., Bidlingmaier, M., Reincke, M., Klug, G., Ladwig, K.-H.: Oxytocin-induced coping with stressful life events in old age depends on attachment: Findings from the cross-sectional KORA Age study. Psychoneuroendocrinology 56 , 132-142 (2015). doi:https://doi.org/10.1016/j.psyneuen.2015.03.014 Charlson, M.E., Pompei, P., Ales, K.L., MacKenzie, C.R.: A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 40 (5), 373-383 (1987). doi:https://doi.org/10.1016/0021-9681(87)90171-8 Sheikh, J.I., Yesavage, J.A.: A knowledge assessment test for geriatric psychiatry. Hosp Community Psychiatry 36 (11), 1160-1161 (1985). Spitzer, R.L., Kroenke, K., Williams, J.B., Lowe, B.: A brief measure for assessing generalized anxiety disorder: the GAD-7. 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Psychopharmacology 236 (1), 339-354 (2019). doi:10.1007/s00213-018-5030-5 Meyer-Lindenberg, A., Domes, G., Kirsch, P., Heinrichs, M.: Oxytocin and vasopressin in the human brain: social neuropeptides for translational medicine. Nature Reviews Neuroscience 12 (9), 524-538 (2011). doi:10.1038/nrn3044 Grillon, C., Krimsky, M., Charney, D.R., Vytal, K., Ernst, M., Cornwell, B.: Oxytocin increases anxiety to unpredictable threat. Mol Psychiatry 18 , 958 (2012). doi:10.1038/mp.2012.156 Eckstein, M., Scheele, D., Patin, A., Preckel, K., Becker, B., Walther, A., Domschke, K., Grinevich, V., Maier, W., Hurlemann, R.: Oxytocin Facilitates Pavlovian Fear Learning in Males. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 41 (2015). doi:10.1038/npp.2015.245 Peters, S., Slattery, D.A., Uschold-Schmidt, N., Reber, S.O., Neumann, I.D.: Dose-dependent effects of chronic central infusion of oxytocin on anxiety, oxytocin receptor binding and stress-related parameters in mice. Psychoneuroendocrinology 42 , 225-236 (2014). doi:10.1016/j.psyneuen.2014.01.021 Peters, S., Slattery, D.A., Uschold-Schmidt, N., Reber, S.O., Neumann, I.D.: Dose-dependent effects of chronic central infusion of oxytocin on anxiety, oxytocin receptor binding and stress-related parameters in mice. Psychoneuroendocrinology 42 , 225-236 (2014). doi:https://doi.org/10.1016/j.psyneuen.2014.01.021 Taylor, S.E., Gonzaga, G.C., Klein, L.C., Hu, P., Greendale, G.A., Seeman, T.E.: Relation of oxytocin to psychological stress responses and hypothalamic-pituitary-adrenocortical axis activity in older women. Psychosom med 68 (2), 238-245 (2006). doi:10.1097/01.psy.0000203242.95990.74 Ondrejcakova, M., Bakos, J., Garafova, A., Kovacs, L., Kvetnansky, R., Jezova, D.: Neuroendocrine and cardiovascular parameters during simulation of stress-induced rise in circulating oxytocin in the rat. Stress 13 (4), 315-323 (2010). doi:10.3109/10253891003596822 Akour, A., Kasabri, V., Boulatova, N., Bustanji, Y., Naffa, R., Hyasat, D., Khawaja, N., Bustanji, H., Zayed, A., Momani, M.: Levels of metabolic markers in drug-naive prediabetic and type 2 diabetic patients. Acta Diabetol 54 (2), 163-170 (2017). doi:10.1007/s00592-016-0926-1 Stock, S., Granstrom, L., Backman, L., Matthiesen, A.S., Uvnas-Moberg, K.: Elevated plasma levels of oxytocin in obese subjects before and after gastric banding. Int J Obes 13 (2), 213-222 (1989). Schorr, M., Marengi, D.A., Pulumo, R.L., Yu, E., Eddy, K.T., Klibanski, A., Miller, K.K., Lawson, E.A.: Oxytocin and Its Relationship to Body Composition, Bone Mineral Density, and Hip Geometry Across the Weight Spectrum. J Clin Endocrinol Metab 102 (8), 2814-2824 (2017). doi:10.1210/jc.2016-3963 Macdonald, K.: Sex, Receptors, and Attachment: A Review of Individual Factors Influencing Response to Oxytocin. Front Neurosci 6 (194) (2013). doi:10.3389/fnins.2012.00194 Plessow, F., Marengi, D.A., Perry, S.K., Felicione, J.M., Franklin, R., Holmes, T.M., Holsen, L.M., Makris, N., Deckersbach, T., Lawson, E.A.: Effects of Intranasal Oxytocin on the Blood Oxygenation Level-Dependent Signal in Food Motivation and Cognitive Control Pathways in Overweight and Obese Men. Neuropsychopharmacology 43 (3), 638-645 (2018). doi:10.1038/npp.2017.226 Striepens, N., Schroter, F., Stoffel-Wagner, B., Maier, W., Hurlemann, R., Scheele, D.: Oxytocin enhances cognitive control of food craving in women. Hum Brain Mapp 37 (12), 4276-4285 (2016). doi:10.1002/hbm.23308 Chiodera, P., Volpi, R., Capretti, L., Caiazza, A., Marchesi, M., Caffari, G., Rossi, G., Coiro, V.: Oxytocin response to challenging stimuli in elderly men. Regul Pept 51 (2), 169-176 (1994). MacLean, E.L., Wilson, S.R., Martin, W.L., Davis, J.M., Nazarloo, H.P., Carter, C.S.: Challenges for measuring oxytocin: The blind men and the elephant? Psychoneuroendocrinology 107 , 225-231 (2019). doi:10.1016/j.psyneuen.2019.05.018 Lawson, E.A., Ackerman, K.E., Estella, N.M., Guereca, G., Pierce, L., Sluss, P.M., Bouxsein, M.L., Klibanski, A., Misra, M.: Nocturnal oxytocin secretion is lower in amenorrheic athletes than nonathletes and associated with bone microarchitecture and finite element analysis parameters. Eur J Endocrinol 168 (3), 457-464 (2013). doi:10.1530/eje-12-0869 Fang, A., Jacoby, R.J., Beatty, C., Germine, L., Plessow, F., Wilhelm, S., Lawson, E.A.: Serum oxytocin levels are elevated in body dysmorphic disorder and related to severity of psychopathology. Psychoneuroendocrinology 113 , 104541-104541 (2020). doi:10.1016/j.psyneuen.2019.104541 Taylor, S.E., Saphire-Bernstein, S., Seeman, T.E.: Are plasma oxytocin in women and plasma vasopressin in men biomarkers of distressed pair-bond relationships? Psychol Sci 21 (1), 3-7 (2010). doi:10.1177/0956797609356507 Supplementary Files Supplementarytable1oxytocinT2DManxietyendocrine.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 01 Mar, 2021 Editor assigned by journal 26 Feb, 2021 First submitted to journal 21 Feb, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-266249","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":14530981,"identity":"3c281233-946d-4fc6-a661-2a9392dff2e0","order_by":0,"name":"Hamimatunnisa Johar","email":"","orcid":"","institution":"Helmholtz Zentrum München Deutsches Forschungszentrum für Umwelt und Gesundheit: Helmholtz Zentrum Munchen Deutsches Forschungszentrum fur Gesundheit und 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Ladwig","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIie3RMUsDMRTA8RcKdXnS9fSO5ivk6FDKif0cbspBbrm5uJnpuvgBLP0ijgkPOtV2FW5pFyfB1aVoEq24pHQUzH84wh0/Xh4HEIv9wRIAppkCBHeArj2cKPehc4jAnsAXQTqOwJ7YV+VhcjZ92mj2eJENexr0+4QyfvW2OH+Goh8iKVZCs6XEkdJg7leEeVt20xqqQYj0QQLtGkJhFOjTpsV87gndqBDpvdhdmg8Udmmzc2RGntyFSJpIRzSKBQC5KTzpeHIdXP/BTylRLJmibGXHYTkoalHloSnJWrINay7HYk1m+zqRYz4127a+LXhoyq++/47Q/nkE+ImHLhSLxWL/tk+qzlUWsLckQQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-0221-311X","institution":"Klinikum rechts der Isar der Technischen Universität München: Klinikum rechts der Isar der Technischen Universitat Munchen","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Karl","middleName":"Heinz","lastName":"Ladwig","suffix":""}],"badges":[],"createdAt":"2021-02-22 09:33:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-266249/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-266249/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":6813392,"identity":"1a9eee6c-5a3e-46a4-b827-c999dd6ad775","added_by":"auto","created_at":"2021-03-10 20:15:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":16079,"visible":true,"origin":"","legend":"Age and sex-adjusted least-squares means (LS-means) of log-transformed plasma OXT levels (95% CI) by T2DM status, stratified by anxiety status (N=961).","description":"","filename":"OnlineFig1Endocrine.png","url":"https://assets-eu.researchsquare.com/files/rs-266249/v1/f55096fdb040a0b2a5b14376.png"},{"id":13677715,"identity":"66c9eeca-b2a6-4396-b114-635f3e72deb0","added_by":"auto","created_at":"2021-09-17 11:36:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":440225,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-266249/v1/fb5f5d79-ede3-432e-9b03-84a9d3ce7995.pdf"},{"id":6813393,"identity":"9297e9de-94d2-4c67-8bb4-df3fa7d27697","added_by":"auto","created_at":"2021-03-10 20:15:20","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":37977,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable1oxytocinT2DManxietyendocrine.docx","url":"https://assets-eu.researchsquare.com/files/rs-266249/v1/61a4d8fd00cb4899e05b8b68.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eAnxiety Amplifies Plasma Oxytocin Levels in Older Individuals with type 2 Diabetes. Findings from the Cross-Sectional KORA-Age Study.\u003c/p\u003e","fulltext":[{"header":"Introduction","content":" \u003cp\u003eOxytocin (OXT), a popular hypothalamic neuropeptide known as the \u0026ldquo;prosocial hormone\u0026rdquo;, is well recognized for its positive functions in parturition, lactation, mother-infant bonding, sexuality, attachment, interpersonal trust, and emotion regulation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Impairments in psychosocial domains, such as anxiety disorders, schizophrenia, and depression, may also have an impact on endogenous OXT levels [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Recently, increasing evidence indicates that OXT may also play a positive role in regulating metabolism by modulating eating behavior, body fat, body weight, energy expenditure, and glucose homeostasis [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOXT receptors have been found on pancreatic α and β cells, suggesting a potential link between OXT and type 2 diabetes mellitus (T2DM) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A double-blinded crossover study on 29 healthy men found that intranasal OXT administration could acutely enhance glucose tolerance and β cell responsivity [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Another randomized pilot clinical trial with 24 patients reported effectively reversed prediabetic changes over 8 weeks of continuous intranasal OXT treatment [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Although these intervention studies showed beneficial effects of OXT on T2DM-related metabolic profiles, how T2DM may affect endogenous OXT levels is still poorly understood. While previous studies in young to middle-aged adults have found an association between lower OXT levels and T2DM [\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], others have reported conflicting findings with higher levels of OXT in metabolic disorders [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Furthermore, most studies investigating the association between OXT and T2DM are small-sized and stem from sex-specific young populations. To date, only one study in an older men population has shown an association between elevated OXT levels and metabolic syndrome [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In older subjects suffering from metabolic syndrome, a compensatory mechanism of OXT may operate to maintain metabolic homeostasis where aging-related deficits develop [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. As circulating levels of OXT tend to decline with age in animal models [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], there are possible age-by-sex related differences in circulatory OXT in humans [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], leading to mixed findings. Therefore, further research to explain these conflicting results and how T2DM may impact OXT secretion in old aged are warranted.\u003c/p\u003e \u003cp\u003eSymptoms of anxiety are frequently observed in T2DM individuals with prevalence ranges from 14\u0026ndash;41% in various populations [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Given that OXT is a profound anxiolytic factor of the brain [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and anxiety amplifies the progression of prediabetes to T2DM onset [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], it is crucial to find out how anxiety may impact the OXT-T2DM relationship. The potential involvement of anxiety may provide some useful insights into the psychoneuroendocrinological coping mechanism of the body to deal with chronic metabolic disease conditions like T2DM. Therefore, we aimed to examine in a representative elderly population-based study: (i) the association of T2DM and plasma OXT levels and (ii) the potential modifying role of anxiety on this association.\u003c/p\u003e "},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Participants\u003c/h2\u003e\u003cp\u003eData for this study were obtained from the 2008\u0026ndash;2009 baseline assessment of the KORA-Age study, a population-based longitudinal study designed to determine the prevalence of multimorbidity, functioning, and successful aging [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. \u003cdiv class=\"Ethics-ToolTip\"\u003eThe KORA-Age study is a follow-up of all participants aged 65 years or older on 31 December 2008, who participated in at least one of the MONICA/KORA (Monitoring of Trends and Determinants in Cardiovascular Diseases/Cooperative Health Research in the Region of Augsburg) Surveys S1-S4 conducted between 1984\u0026ndash;2001 among inhabitants of Augsburg and its two surrounding counties in southern Germany.\u003c/div\u003e All eligible participants of the KORA-Age study (n\u0026thinsp;=\u0026thinsp;5991) who were alive and reachable received a postal health questionnaire (response rate 76.2%, n\u0026thinsp;=\u0026thinsp;4565), followed by a standardized telephone interview (response rate 68.9%, n\u0026thinsp;=\u0026thinsp;4127). Furthermore, a gender- and age-stratified random subsample of the KORA-Age cohort (53.8% of eligible participants, n\u0026thinsp;=\u0026thinsp;1079) underwent an extensive medical examination, including a non-fasting blood draw and a face-to-face interview. After the exclusion of participants with missing information on plasma OXT (n\u0026thinsp;=\u0026thinsp;66), diabetes status (n\u0026thinsp;=\u0026thinsp;2) and non-psychosocial covariates (n\u0026thinsp;=\u0026thinsp;5) in this subsample, our study has a sample size of 1006 participants. A drop-out analysis of the excluded participants revealed no significant age, sex and education level differences. \u003cdiv class=\"Ethics-ToolTip\"\u003eThis study was approved by the Ethics Committee of the Bavarian Medical Association, and written informed consents were provided by all the participants.\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eOutcome \u0026ndash; Plasma OXT Level\u003c/h2\u003e\u003cp\u003eNon-extracted plasma OXT level was measured from a non-fasting venous blood sample of each participant during the physical examination at the study centre using OXT Enzyme Immunoassay (Assay Designs, Ann Arbor, MI), as previously described [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Samples were collected in chilled EDTA tubes with 500 KIU/ml aprotinin, centrifuged within 30 min, and stored at -80℃ to minimize preanalytical sample degradation. All the samples were analyzed within 2 months using the same batch of reagents. The detection limits of the assay range from 15 to 2000 pg/ml. Intra-assay coefficients of variability are below 15%, and inter-assay coefficients of variability are 15.4%, 18.5% and 17.9% at concentrations of 234, 416 and 1930 pg/ml, respectively. The plasma OXT concentrations showed a right-skewed distribution. For the descriptive analyses, the distributions of plasma OXT were split by the tertiles, and subjects were stratified into those with low, medium or high levels.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eExposure \u0026ndash; T2DM\u003c/h2\u003e\u003cp\u003eT2DM was determined by the participant\u0026rsquo;s report in the self-administered questionnaire, and each case was verified by assessing the participant\u0026rsquo;s medical history, records from physicians, information from previous MONICA/KORA surveys, as well as the use of antidiabetic medication.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eCovariates\u003c/h2\u003e\u003cp\u003eLow education was defined as less than 12 years of education. A current smoker was defined as someone smoking cigarettes regularly or occasionally. Alcohol consumption was classified into two categories: consuming alcohol more than once per week, or not. Participants were considered as physically active during leisure time if they regularly participated in sports for at least 1 hour/week in either summer or winter, and inactive else. Obesity was defined as Body Mass Index (BMI) greater than 30, where BMI was calculated as weight (kg) / height\u003csup\u003e2\u003c/sup\u003e (m). Hypertension was defined as blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;140/90 mmHg or current use of antihypertensive medication. Dyslipidemia was defined as the ratio of total cholesterol (TC) to high density lipoprotein cholesterol (HDL-C) TC/HDL-C\u0026thinsp;\u0026ge;\u0026thinsp;5.0, where TC and HDL-C in mmol/L were measured by enzymatic methods (CHOD-PAP, Boehringer Mannheim, Germany). HbA1c was quantified with a reverse-phase cation-exchange HPLC method using a Menarini\u0026ndash;Arkray Analyzer HA-8160 (Menarini Diagnostics, Florence, Italy) in mmol/mol and %. HbA1c levels\u0026thinsp;\u0026ge;\u0026thinsp;6.5% was considered as hyperglycemia and \u0026lt;\u0026thinsp;6.5% as normoglycemia. Multimorbidity was determined by the co-occurrence of \u0026gt;\u0026thinsp;2 disease conditions according to the Charlson Comorbidity Index [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDepressive symptoms were measured by the 15-item German version of the Geriatric Depression Scale (GDS 15), with a score\u0026thinsp;\u0026ge;\u0026thinsp;10 or taking antidepressants indicating depression [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Anxiety symptoms were assessed using the Generalized Anxiety Disorder-7 (GAD-7) Questionnaires, where anxiety was defined by a score of 10 or higher [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Perceived stress from a stressful life event experienced in the past year, if any, was assessed in a personal interview rated on 5-point Likert Scale, where scale 4-quite a lot and scale 5-severely were categorized as suffering from heavy/severe stress [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Social network was assessed by the Beckman social network index score and classified into high (score 3\u0026ndash;4) and low (score 1\u0026ndash;2) social network [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eThe plasma OXT concentrations showed a right-skewed distribution and, therefore, were logarithmically transformed to approximate a normal distribution. Descriptive data of sociodemographic, lifestyle, clinical, and psychosocial characteristics were stratified by tertiles of log-transformed plasma OXT levels. The \u0026#120594;\u003csup\u003e2\u003c/sup\u003e test for categorical variables and the Kruskal-Wallis test for continuous variables were used to compare the differences across the OXT tertile groups. Categorical variables were expressed as frequencies (n), and age was reported as means with standard deviations (\u0026plusmn;\u0026thinsp;SD). Multivariable generalized linear regression (GLM) models were applied to assess the association between T2DM (exposure) and plasma OXT levels (outcome) with 5 different models adjustment. Model 1 was a crude model adjusted only for age and sex. Model 2 was further adjusted for educational level as a sociodemographic confounder. Model 3 and model 4 were additionally adjusted for established lifestyle (smoking, alcohol consumption, physical activity) and metabolic risk factors (obesity, hypertension, dyslipidemia, multimorbidity) of T2DM. Model 5 was performed on a smaller subgroup of participants (N\u0026thinsp;=\u0026thinsp;961) with complete information for depression, anxiety, perceived stress, and social network status to consider the influence of psychosocial factors on the association. We also reanalyzed the association of OXT levels and T2DM by an additional adjustment for HbA1c levels in the crude and full model.\u003c/p\u003e\u003cp\u003eAdditional sensitivity analyses were performed to consider the interaction effect of sex and T2DM on OXT levels by including the sex X T2DM interaction term in all the models. The influence of anxiety in the association between T2DM and OXT was examined by introducing an interaction term to the crude and fully-adjusted logistic regression model. In the case of significant interaction, the regression analyses were further stratified by anxiety. The influence of obesity or glycemic status was assessed via the introduction of an interaction term of HbA1c levels*T2DM.\u003c/p\u003e\u003cp\u003eAge and sex-adjusted least-square means (LS-means) of log-transformed plasma OXT levels and 95% confidence intervals were calculated from generalized linear models for the total study population and stratified by anxiety status. The model fits were sufficient as indicated by acceptable adjusted R-square and Root MSE statistics values throughout the GLM models. No multicollinearity among covariates was detected as assessed with the Variance Inflation Factor (VIF) with a cut-off of VIF\u0026thinsp;\u0026gt;\u0026thinsp;2.\u003c/p\u003e\u003cp\u003eAll the statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA). The significance level was set at 0.05. The reporting of this study followed the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) guidelines.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":" \u003cp\u003eA total of 1006 participants (489 women and 517 men) of KORA-Age were included in our study, with an age range of 65\u0026ndash;93 (mean 75.9, SD\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6) years. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the study characteristics according to tertiles of the OXT level. No substantial differences between sociodemographic, lifestyle or cardiometabolic factors across the OXT tertile groups were found except for multimorbidity. The differences between the OXT tertile groups with respect to obesity status were on the borderline of statistical significance (P\u0026thinsp;=\u0026thinsp;0.05). Of note, no significant differences between OXT tertile groups and anxiety were observed.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of study population stratified by tertiles of plasma OXT levels in means (\u0026plusmn;\u0026thinsp;standard deviation) or N (%) (N\u0026thinsp;=\u0026thinsp;1006)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlasma OXT level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow (n\u0026thinsp;=\u0026thinsp;336, 33.40%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMiddle (n\u0026thinsp;=\u0026thinsp;334, 33.20%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;336, 33.40%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSociodemographic factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.74 (\u0026plusmn;\u0026thinsp;6.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.16 (\u0026plusmn;\u0026thinsp;6.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.86 (\u0026plusmn;\u0026thinsp;6.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.698\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e170 (50.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e176 (52.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e171 (50.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.841\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e242 (72.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e238 (71.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e250 (74.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLifestyle factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (2.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (5.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (5.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh Alcohol Consumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161 (47.92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155 (46.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e149 (44.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.648\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysically inactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e162 (48.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e147 (44.01%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e158 (47.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.532\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (29.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115 (34.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87 (25.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2DM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (26.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65 (37.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (35.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.72 (0.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.75 (0.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.72 (0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c (mmol/mol)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.99 (6.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.35 (6.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.94 (6.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.755\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e251 (74.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e258 (77.25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e244 (72.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidaemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (13.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (18.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54 (16.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.230\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultimorbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197 (58.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e228 (68.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e217 (64.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePsychosocial factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eN\u0026thinsp;=\u0026thinsp;321 (33.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eN\u0026thinsp;=\u0026thinsp;322 (33.4%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eN\u0026thinsp;=\u0026thinsp;321 (33.3%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (7.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (5.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (7.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.761\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (6.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (6.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (8.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.680\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreat/Severe Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (16.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (18.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (18.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.642\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Social Network\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209 (65.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e204 (63.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e208 (64.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.884\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eP\u003c/em\u003e values: Kruskal-wallis test for continuous variables and \u0026#120594;\u003csup\u003e2\u003c/sup\u003e test for categorical variables.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOXT levels were higher in participants with T2DM (age and sex-adjusted LS-mean\u0026thinsp;=\u0026thinsp;224.78, 95% CI: 200, 189\u0026ndash;211 pg/ml) compared to those without T2DM (199.74, 199\u0026ndash;254 pg/ml) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.08). T2DM participants were more likely to be older, have lower education levels, have BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u0026sup2;, consume less alcohol, have hypertension and multimorbidity, and suffer more from stressful life events (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSupplementary Table\u0026nbsp;1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMultivariable linear regression analyses on the association of plasma OXT levels and T2DM were employed with adjustments for sociodemographic, lifestyle, metabolic, and psychosocial factors, as displayed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. T2DM was associated with higher levels of plasma OXT; however, only with borderline statistical significance (Model 1: \u0026szlig; = 0.13, SE\u0026thinsp;=\u0026thinsp;0.07, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.07). Adjustments for all potential confounders further reduced the strength of association into non-significance (Model 5: \u0026szlig; = 0.11, SE\u0026thinsp;=\u0026thinsp;0.07, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.13).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026szlig; estimates, standard errors (SE) and \u003cem\u003eP\u003c/em\u003e-values for the association between T2DM and plasma OXT levels (pg/ml) of the KORA-Age participants (N\u0026thinsp;=\u0026thinsp;1006)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026szlig;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 5 (n\u0026thinsp;=\u0026thinsp;961)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eModel 1: generalized linear model adjusted for age and sex\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eModel 2: Model 1\u0026thinsp;+\u0026thinsp;education level\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eModel 3: Model 2\u0026thinsp;+\u0026thinsp;smoking status, alcohol consumption, physical activity\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eModel 4: Model 3\u0026thinsp;+\u0026thinsp;obesity, hypertension, dyslipidemia, multimorbidity\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eModel 5: Model 4\u0026thinsp;+\u0026thinsp;anxiety, depression, perceived stress, social network\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAdditional analytical models demonstrated, however, that a significant interaction between T2DM and anxiety on OXT levels was observed in multivariable linear regression models adjusted for age and sex (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03). A significant interaction indicates that the association between T2DM and OXT levels is modified by the presence of anxiety. Therefore, stratified analyses were performed on the study population grouped by individuals having anxiety symptoms. As displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, elevated plasma OXT levels were observed in T2DM individuals with anxiety (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008) but not in those without anxiety (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (LSMeans for T2DM participants, with anxiety: 340.82 pg/ml, 95% CI 231.12\u0026ndash;502.59; without anxiety: 217.08 pg/ml, 95% CI 190.93\u0026ndash;247.99). In multivariable linear regression models, neither the strength nor the significance of the association was substantially altered by further adjustments for concurrent risk factors (anxiety: \u0026szlig; = 0.62, SE\u0026thinsp;=\u0026thinsp;0.24, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01; no anxiety: \u0026szlig; = 0.05, SE\u0026thinsp;=\u0026thinsp;0.08, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.50) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). No significant interaction of T2DM by sex on plasma OXT levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) was found.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026szlig; estimates, standard errors (SE) and \u003cem\u003eP\u003c/em\u003e-values of the association between T2DM and plasma OXT levels stratified by anxiety (n\u0026thinsp;=\u0026thinsp;961).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026szlig;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eModel 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnxiety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eModel 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e(N\u0026thinsp;=\u0026thinsp;891)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eModel 3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eModel 4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eModel 5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnxiety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eModel 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e(N\u0026thinsp;=\u0026thinsp;70)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eModel 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eModel 3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eModel 4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eModel 5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel 1: generalized linear model adjusted for age and sex.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel 2: Model 1\u0026thinsp;+\u0026thinsp;education level\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel 3: Model 2\u0026thinsp;+\u0026thinsp;smoking status, alcohol consumption, physical activity.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel 4: Model 3\u0026thinsp;+\u0026thinsp;obesity, hypertension, dyslipidemia, multimorbidity.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel 5: Model 4\u0026thinsp;+\u0026thinsp;depression, perceived stress, social network.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eIn a sample of community-dwelling older people of 64\u0026ndash;93 years, we found a borderline significant association between T2DM and elevated plasma OXT levels which was further diminished after adjustment for concurrent risk factors. However, driven by a significant interaction between T2DM and anxiety on OXT levels, indicating a potential modifying role of anxiety on the T2DM-OXT link, we revealed a substantially 44% higher mean level of OXT in T2DM subjects with anxiety compared to their non-T2DM counterparts with anxiety. Notably, a significant association between T2DM and OXT levels in subjects without anxiety was not found. While increasing evidence points to positive effects of OXT in attenuating metabolic risks [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] as well as its profound anxiolytic behavioral effect [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], our findings seem to be counterintuitive at first sight.\u003c/p\u003e \u003cp\u003eHowever, the findings of heightened levels of OXT in T2DM subjects with anxiety do not come unexpectedly: both the impact of OXT on fear and anxiety, and its role in the metabolic regulation has yielded contradictory findings. Concerning human social behavior, OXT is widely acknowledged as a candidate molecule to facilitate fear extinction and anxiolysis [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and, thus, is emerging as a target for mood treatment approaches [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. However, opposing experimental data are available. Grillon et al. (2012) exposed healthy subjects to an electrical startle experiment and evidenced that OXT increased anxiety to unpredictable threat [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Likewise, Eckstein et al. subjected 97 healthy male probands to a Pavlovian fear learning experiment and disclosed that OXT enhanced CNS responses to social stimuli during fear conditioning, provoking increased vigilance and heightened alertness to threat [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePeters et al. (2014) showed that chronic intra-cereberoventricular infusion of high doses of OXT in male mice induces an anxiogenic phenotype while a low dose of OXT prevents hyperanxiety [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Thus, the specific nature, dosage, and timing of OXT are key aspects in orchestrating OXT responses and, instead of acting unidirectional, may result in both anxiolytic and anxiogenic behavioral effects [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. A low dose of OXT administration is likely to alleviate the effects of stress, while a chronic high dose of OXT may increase anxiety-like behavior [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Furthermore, chronic administration of OXT increases adreno-corticotropic hormone (ACTH) and corticosterone levels, indicating a potentiating effect of OXT on the hypothalamic-pituitary-adrenal (HPA) axis stress reactivity [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOf note, the positive association between T2DM and OXT levels in subjects with anxiety remained strong even after adjustment for potentially important influential lifestyle factors (e.g. physical activity, smoking and alcohol consumption). This suggests a robust association of anxiety in T2DM patients independent from unfavorable lifestyle habits and highlights chronic anxiety as a clinically relevant phenotype [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eComparable to its role in affect regulation, a functional dichotomy of OXT is also apparent in metabolic regulation: On the one hand, evidence indicated that high OXT levels were positively associated with T2DM and obesity [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], reflecting the role of OXT as a signal of energy availability [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. High OXT levels may appropriately signal the need to reduce caloric intake and increase energy expenditure [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. On the other hand, conflicting evidence comes from studies showing low endogenous OXT levels in people with obesity (Fu-Man et al., 2019; Maestrini et al., 2018) or T2DM (Eisenberg et al., 2018; Qian et al., 2014; Yuan et al., 2016). In the present investigation, we assert a weak association between high OXT levels and T2DM. Most studies showing low OXT levels in T2DM subjects were conducted in samples of newly diagnosed or uncontrolled T2DM patients. In the present study, the majority of T2DM subjects (77%, n\u0026thinsp;=\u0026thinsp;133) were under ongoing treatment. In a sensitivity analysis that considered only T2DM participants under treatment, we found that the results of our analyses remained unaltered (data are not shown).\u003c/p\u003e \u003cp\u003eTo date, there is no clear understanding of sexual dimorphism related to the OXT regulation. Although sexual dimorphism has been recognized in the OXT system [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], both genders seem to be involved in the OXT-regulated energy homeostasis [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The present study adds to the conflicting evidence by showing that neither sex differences nor interaction of T2DM by sex influences OXT levels. Our data also demonstrate that endogenous plasma OXT levels were unaffected by increasing age, supporting a previous report that showed OXT response during the insulin tolerance test had similar patterns and magnitudes in all groups [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. However, it is also likely that the increase in OXT levels of older T2DM subjects could be a compensatory mechanism for the maintenance of metabolic homeostasis where age-related metabolic impairments may have already developed.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStudy strengths and limitations\u003c/h2\u003e \u003cp\u003eThis present study was conducted in a large population-based sample of older subjects from the KORA-Age study. The random sampling of the study population, the low loss to follow-up rate, and the strict quality assessment ensured the quality of the data. The substantially larger sample size of this study compared to other relevant studies to date made it easier to draw firm conclusions based on analytical results. The study design involved extensive assessments of psychological tests and biomarkers, providing the possibility to consider potential modifying factors and to produce robust results adjusting for covariates. The current study contributes to the understanding of endogenous OXT-T2DM association in an older population.\u003c/p\u003e \u003cp\u003eLimitations exist in this study. First, due to its cross-sectional design, we could not infer causality on the anxiety driven association between increased OXT levels and T2DM, and the findings from our study may not be generalizable to other populations. Second, the OXT levels of participants were measured from a single blood sample which may not accurately represent the average metabolic status of an individual. However, in this epidemiologic setting, the quality of the data was ensured by highly standardized procedures and a very strict quality assessment. The non-extracted plasma OXT enzyme immunoassay method used in our study may yield levels of higher magnitude than traditional radioimmunoassays because the samples may contain interfering substances [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Therefore, we acknowledge that OXT levels from immunoassays are measuring OXT immunoreactive products, not absolute values of OXT, preventing comparisons of absolute OXT levels between studies. However, the optimal method measuring endogenous OXT is still in active development, and \u0026ldquo;discrepancies between methods (i.e., extracted or unextracted) are not necessarily an indicator that some methods are valid whereas others are not\u0026rdquo; [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Furthermore, previous reports have shown a robust correlation between extracted and unextracted serum oxytocin levels [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], as well as associations between non-extracted OXT levels with body dysmorphic disorder (BDD) [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] or relationship distress [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], providing evidence for biologic relevance in these sample preparations. Therefore, in the current study, we valued the non-extracted plasma OXT enzyme immunoassay for comparing relative levels of peripheral OXT in participants with T2DM without T2DM.\u003c/p\u003e \u003c/div\u003e "},{"header":"Conclusion","content":" \u003cp\u003eThe present investigation demonstrates that both T2DM status and sustained symptoms of anxiety in this old aged population contribute to a strong combined effect leading to a significantly elevated OXT level. Thus, anxiogenic stimuli significantly activate the body\u0026rsquo;s OXT system, however, only in subjects who additionally suffer from T2DM as a severe pathological feature of dysregulated metabolism. The clinical consequences of this finding actually remain unclear, however, it may be speculated that this particular OXT signaling network may be achieved to influence psychosocial adaptations with an impact on lifestyle behaviors related to energy regulation and metabolism.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from the German Federal Ministry of Education and Research (BMBF) to MB (FKZ 01ET1003D) and the German Center for Diabetes Research (Deutsche Zentrum f\u0026uuml;r Diabetesforschung). The KORA research platform was initiated and financed by the Helmholtz Zentrum M\u0026uuml;nchen-German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research and by the State of Bavaria. The KORA-Age project was financed by the German Federal Ministry of Education and Research [BMBF FKZ 01ET0713] as part of the \u0026lsquo;Health in Old Age\u0026rsquo; program.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe informed consent given by KORA study participants does not cover data posting in public databases. However, data are available upon request from KORA/KORA-gen (https://epi.helmholtz-muenchen.de/) by means of a project agreement. Requests should be sent to [email protected] and are subject to approval by the KORA Board.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical codes are available from the corresponding author on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKHL and MB designed the study. HJ and LJ conducted literature searches and performed statistical analyses. HJ and LK wrote the first draft of the manuscript. SA and KHL provided critical feedback, proofread and approved the final manuscript. MB and JK proofread and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003cbr /\u003e\u003c/strong\u003eThe study was approved by the Ethics Committee of the Bavarian Medical Association, and written informed consents were provided by all the participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors affirm that human research participants provided informed consent for publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLee, H.-J., Macbeth, A.H., Pagani, J.H., Young, W.S., 3rd: Oxytocin: the great facilitator of life. 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Psychol Sci \u003cstrong\u003e21\u003c/strong\u003e(1), 3-7 (2010). doi:10.1177/0956797609356507\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"endocrine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"endo","sideBox":"Learn more about [Endocrine](https://www.springer.com/journal/12020)","snPcode":"12020","submissionUrl":"https://submission.nature.com/new-submission/12020/3","title":"Endocrine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"oxytocin, type 2 diabetes, anxiety, ageing","lastPublishedDoi":"10.21203/rs.3.rs-266249/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-266249/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePurpose\u003c/p\u003e\u003cp\u003eBeyond its role in parturition, lactation, and emotion regulation, oxytocin (OXT) plays an important role in metabolism and energy homeostasis, although evidence is still limited. We investigated the association between endogenous OXT levels and type 2 diabetes mellitus (T2DM) and whether anxiety may modify its association.\u003c/p\u003e\u003cp\u003eMethods\u003c/p\u003e\u003cp\u003eA cross-sectional analysis was conducted in 1006 participants aged 65-93 years (mean=75.9, SD ± 6.6) from the population-based KORA-Age study. Multivariable generalized linear regression analyses were performed to examine the association between non-extracted plasma OXT levels and T2DM with adjustments for potential confounders. \u003c/p\u003e\u003cp\u003eResults\u003c/p\u003e\u003cp\u003eAcross the OXT tertile groups, no substantial differences between sociodemographic, lifestyle, cardiometabolic or psychosocial factors were found except for multimorbidity. The differences between the OXT tertile groups with respect to obesity status were on the borderline of statistical significance (P=0.05). However, a significant statistical interaction between T2DM and anxiety on OXT levels was found (\u003cem\u003ep\u003c/em\u003e = 0.03). In T2DM individuals with anxiety, substantially higher plasma OXT levels (Least Squares (LS) mean = 340.82 pg/ml, 95% CI 231.12-502.59) were observed compared to those without anxiety (217.08 pg/ml, 95% CI 190.93 – 247.99) (\u003cem\u003ep\u003c/em\u003e=0.02). No significant association between T2DM and OXT levels in individuals without anxiety was found. \u003c/p\u003e\u003cp\u003eConclusion\u003c/p\u003e\u003cp\u003eOXT levels were significantly elevated in T2DM subjects, particularly among older individuals with anxiety. The modifying role of anxiety highlights that anxiogenic stimuli may be associated with enhanced OXT signalling, particularly in subjects who suffer from T2DM as a severe pathological feature of dysregulated metabolism.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Anxiety Amplifies Plasma Oxytocin Levels in Older Individuals with type 2 Diabetes. Findings from the Cross-Sectional KORA-Age Study.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-03-10 20:15:18","doi":"10.21203/rs.3.rs-266249/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2021-03-02T00:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-02-27T00:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Endocrine","date":"2021-02-22T04:33:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"endocrine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"endo","sideBox":"Learn more about [Endocrine](https://www.springer.com/journal/12020)","snPcode":"12020","submissionUrl":"https://submission.nature.com/new-submission/12020/3","title":"Endocrine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"63a13245-e8bd-4858-af26-b2d9e818636a","owner":[],"postedDate":"March 10th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":2886896,"name":"Endocrinology \u0026 Metabolism"}],"tags":[],"updatedAt":"2021-03-10T20:15:18+00:00","versionOfRecord":[],"versionCreatedAt":"2021-03-10 20:15:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-266249","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-266249","identity":"rs-266249","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}