Clinical Subtypes of Depression Are Associated with Specific Metabolic Parameters and Circadian Endocrine Profiles in Women: The Power Study

Major depressive disorder (MDD) has been associated with adverse medical consequences, including cardiovascular disease and osteoporosis. Patients with MDD may be classified as having melancholic, atypical, or undifferentiated features. The goal of the present study was to assess whether these clinical subtypes of depression have different endocrine and metabolic features and consequently, varying medical outcomes.Premenopausal women, ages 21 to 45 years, with MDD (N = 89) and healthy controls (N = 44) were recruited for a prospective study of bone turnover. Women with MDD were classified as having melancholic (N = 51), atypical (N = 16), or undifferentiated (N = 22) features. Outcome measures included: metabolic parameters, body composition, bone mineral density (BMD), and 24 hourly sampling of plasma adrenocorticotropin (ACTH), cortisol, and leptin.Compared with control subjects, women with undifferentiated and atypical features of MDD exhibited greater BMI, waist/hip ratio, and whole body and abdominal fat mass. Women with undifferentiated MDD characteristics also had higher lipid and fasting glucose levels in addition to a greater prevalence of low BMD at the femoral neck compared to controls. Elevated ACTH levels were demonstrated in women with atypical features of depression, whereas higher mean 24-hour leptin levels were observed in the melancholic subgroup.Pre-menopausal women with various features of MDD exhibit metabolic, endocrine, and BMD features that may be associated with different health consequences.ClinicalTrials.gov NCT00006180

Evolutionary fitness as a function of pubertal age in 22 subsistence-based traditional societies

<p>Abstract</p> <p>Context</p> <p>The age of puberty has fallen over the past 130 years in industrialized, western countries, and this fall is widely referred to as the secular trend for earlier puberty. The current study was undertaken to test two evolutionary theories: (a) the reproductive system maximizes the number of offspring in response to positive environmental cues in terms of energy balance, and (b) early puberty is a trade-off response for high mortality rate and reduced resource availability.</p> <p>Methods</p> <p>Using a sample of 22 natural-fertility societies of mostly tropical foragers, horticulturalists, and pastoralists from Africa, South America, Australia, and Southeastern Asia, this study compares indices of adolescence growth and menarche with those of fertility fitness in these non-industrial, traditional societies.</p> <p>Results</p> <p>The average age at menarche correlated with the first reproduction, but did not correlate with the total fertility rate TFR or reproductive fitness. The age at menarche correlated negatively with their average adult body mass, and the average adult body weight positively correlated with reproductive fitness. Survivorship did not correlate with the age at menarche or age indices of the adolescent growth spurt. The population density correlated positively with the age at first reproduction, but not with menarche age, TFR, or reproductive fitness.</p> <p>Conclusions</p> <p>Based on our analyses, we reject the working hypotheses that reproductive fitness is enhanced in societies with early puberty or that early menarche is an adaptive response to greater mortality risk. Whereas body mass is a measure of resources is tightly associated with fitness, the age of menarche is not.</p

Compliance and persistence with osteoporosis medications: A critical review of the literature

It is widely acknowledged that compliance and persistence with oral osteoporosis medications, particularly with bisphosphonates, is poor. Several excellent reviews have been written on compliance and persistence with osteoporosis medications and have discussed improvements seen with extended dosing intervals. This review begins with studies on extended dosing intervals to examine the limitations of administrative claims data. It also looks at compliance and persistence across multiple medical conditions, examining the importance of prescription fulfillment, intentional choice, causation and possible interventions

Effect of venlafaxine on bone loss associated with ligature-induced periodontitis in Wistar rats

<p>Abstract</p> <p>Background</p> <p>The present study investigated the effects of venlafaxine, an antidepressant drug with immunoregulatory properties on the inflammatory response and bone loss associated with experimental periodontal disease (EPD).</p> <p>Materials and Methods</p> <p>Wistar rats were subjected to a ligature placement around the second upper left molar. The treated groups received orally venlafaxine (10 or 50 mg/kg) one hour before the experimental periodontal disease induction and daily for 10 days. Vehicle-treated experimental periodontal disease and a sham-operated (SO) controls were included. Bone loss was analyzed morphometrically and histopathological analysis was based on cell influx, alveolar bone, and cementum integrity. Lipid peroxidation quantification and immunohistochemistry to TNF-α and iNOS were performed.</p> <p>Results</p> <p>Experimental periodontal disease rats showed an intense bone loss compared to SO ones (SO = 1.61 ± 1.36; EPD = 4.47 ± 1.98 mm, p < 0.001) and evidenced increased cellular infiltration and immunoreactivity for TNF-α and iNOS. Venlafaxine treatment while at low dose (10 mg/kg) afforded no significant protection against bone loss (3.25 ± 1.26 mm), a high dose (50 mg/kg) caused significantly enhanced bone loss (6.81 ± 3.31 mm, p < 0.05). Venlafaxine effectively decreased the lipid peroxidation but showed no significant change in TNF-α or iNOS immunoreactivity.</p> <p>Conclusion</p> <p>The increased bone loss associated with high dose venlafaxine may possibly be a result of synaptic inhibition of serotonin uptake.</p

Proximal correlates of metabolic phenotypes during ‘at-risk' and ‘case' stages of the metabolic disease continuum

Extent: 11p.OBJECTIVE: To examine the social and behavioural correlates of metabolic phenotypes during ‘at-risk’ and ‘case’ stages of the metabolic disease continuum. DESIGN: Cross-sectional study of a random population sample. PARTICIPANTS: A total of 718 community-dwelling adults (57% female), aged 18--92 years from a regional South Australian city. MEASUREMENTS: Total body fat and lean mass and abdominal fat mass were assessed by dual energy x-ray absorptiometry. Fasting venous blood was collected in the morning for assessment of glycated haemoglobin, plasma glucose, serum triglycerides, cholesterol lipoproteins and insulin. Seated blood pressure (BP) was measured. Physical activity and smoking, alcohol and diet (96-item food frequency), sleep duration and frequency of sleep disordered breathing (SDB) symptoms, and family history of cardiometabolic disease, education, lifetime occupation and household income were assessed by questionnaire. Current medications were determined by clinical inventory. RESULTS: 36.5% were pharmacologically managed for a metabolic risk factor or had known diabetes (‘cases’), otherwise were classified as the ‘at-risk’ population. In both ‘at-risk’ and ‘cases’, four major metabolic phenotypes were identified using principal components analysis that explained over 77% of the metabolic variance between people: fat mass/insulinemia (FMI); BP; lipidaemia/lean mass (LLM) and glycaemia (GLY). The BP phenotype was uncorrelated with other phenotypes in ‘cases’, whereas all phenotypes were inter-correlated in the ‘at-risk’. Over and above other socioeconomic and behavioural factors, medications were the dominant correlates of all phenotypes in ‘cases’ and SDB symptom frequency was most strongly associated with FMI, LLM and GLY phenotypes in the ‘at-risk’. CONCLUSION: Previous research has shown FMI, LLM and GLY phenotypes to be most strongly predictive of diabetes development. Reducing SDB symptom frequency and optimising the duration of sleep may be important concomitant interventions to standard diabetes risk reduction interventions. Prospective studies are required to examine this hypothesis.MT Haren, G Misan, JF Grant, JD Buckley, PRC Howe, AW Taylor, J Newbury and RA McDermot

Proximal correlates of metabolic phenotypes during ‘at-risk' and ‘case' stages of the metabolic disease continuum

Extent: 11p.OBJECTIVE: To examine the social and behavioural correlates of metabolic phenotypes during ‘at-risk’ and ‘case’ stages of the metabolic disease continuum. DESIGN: Cross-sectional study of a random population sample. PARTICIPANTS: A total of 718 community-dwelling adults (57% female), aged 18--92 years from a regional South Australian city. MEASUREMENTS: Total body fat and lean mass and abdominal fat mass were assessed by dual energy x-ray absorptiometry. Fasting venous blood was collected in the morning for assessment of glycated haemoglobin, plasma glucose, serum triglycerides, cholesterol lipoproteins and insulin. Seated blood pressure (BP) was measured. Physical activity and smoking, alcohol and diet (96-item food frequency), sleep duration and frequency of sleep disordered breathing (SDB) symptoms, and family history of cardiometabolic disease, education, lifetime occupation and household income were assessed by questionnaire. Current medications were determined by clinical inventory. RESULTS: 36.5% were pharmacologically managed for a metabolic risk factor or had known diabetes (‘cases’), otherwise were classified as the ‘at-risk’ population. In both ‘at-risk’ and ‘cases’, four major metabolic phenotypes were identified using principal components analysis that explained over 77% of the metabolic variance between people: fat mass/insulinemia (FMI); BP; lipidaemia/lean mass (LLM) and glycaemia (GLY). The BP phenotype was uncorrelated with other phenotypes in ‘cases’, whereas all phenotypes were inter-correlated in the ‘at-risk’. Over and above other socioeconomic and behavioural factors, medications were the dominant correlates of all phenotypes in ‘cases’ and SDB symptom frequency was most strongly associated with FMI, LLM and GLY phenotypes in the ‘at-risk’. CONCLUSION: Previous research has shown FMI, LLM and GLY phenotypes to be most strongly predictive of diabetes development. Reducing SDB symptom frequency and optimising the duration of sleep may be important concomitant interventions to standard diabetes risk reduction interventions. Prospective studies are required to examine this hypothesis.MT Haren, G Misan, JF Grant, JD Buckley, PRC Howe, AW Taylor, J Newbury and RA McDermot