Overall summary Frailty results from the lifelong accumulation of damage caused by age- and disease-related impairment of the repair network. The amount of cellular damage needed to alter function is uncertain and determined on an individual basis. Assessing cumulative dysfunction in different systems (hormonal, metabolic, immune, cardiovascular, and skeletal) is crucial as the relationship with frailty is nonlinear and not linked to the severity in one system. When subtle, declining functions reaches an aggregate crucial level, and frailty becomes evident. The frail individual is who, after a mild stressor event, undergoes a larger deterioration, which manifest as functional dependency (hospitalization), and who does not return to baseline homoeostasis (favoring polypharmacy). By implementing precision medicine, retrospective and prospective data collected in five referral centers covering densely populated regions in Italy, will be merged and thoroughly analyzed. This network aims at identifying novel biomarkers, predictors of treatment response, and simplified management for complex multiple endocrine comorbidities. The network will investigate emerging and highly prevalent disorders linked to frailty: the gonadal and adrenal, metabolic, neuroendocrine, skeletal. The network will generate scores and precision-medicine based algorithms for the fragile population, often excluded from clinical trials while absorbing most of healthcare expenditure.

Background Frailty is raising globally. Patients with multiple endocrine and metabolic comorbidities (MEDs) are at high risk for inappropriate prescriptions, with negative effects on health outcomes and costs. Endocrine and metabolic comorbidities often coexist with frailty being the common endpoint in patients requiring intensive medical care (falls, disability, hospitalization, and mortality). Concomitant multiple medications aggravate frailty by increasing the risk of interactions, adverse effects and reduce efficacy. The cost of supporting these high-risk population are no longer sustainable for the National Health System (NHS). The pathophysiology of frailty is poorly understood, but multiple endocrine dysfunctions are often associated. Dysregulation of the hypothalamic-pituitary-gonadal and adrenal axes are often associated with metabolic disease (Type 2 Diabetes Mellitus-T2D) as well as bone diseases. In 2018 data from the European Male Aging Study (EMAS) showed that both androgen and nonandrogenic anabolic hormones were independently associated with change in frailty status. Other studies showed that frailty was independently associated with chronically raised diurnal cortisol. Diabetes and osteoporosis (OP) are commonly associated with a significant health burden, especially in elderly individuals. Diabetes is also associated with a wide spectrum of comorbidities (cardiovascular disease, impairment of bone quality, hypogonadism, reduced quality of life, obesity). OP is a complex disorder whose pathogenesis is due to the interaction of various predisposing genetic and epigenetic factors regulating bone and mineral metabolism and non-skeletal risk factors that could influence the risk of fall. Genome-wide association studies (GWAS), epigenetic factors and circulating micro-RNA have opened new horizons for the discovery of genetic loci and variants associated with OP and fracture risk, identifying replicated genetic loci associated with OP. Circulating microRNA profiles have also a prognostic value making them attractive, blood-based, non-invasive biomarkers for prediction and staging of endocrine diseases. Moreover, evidence suggests that inflammation has a major role in the pathophysiology of frailty through an abnormal, low-grade inflammatory chronic response that is hyper-responsive to stimuli. Several inflammatory cytokines have been independently associated with frailty and a link was demonstrated between immune cell function and steroid hormone levels in the recently published DREAM trial. Response to therapy in T2D is often patient-related especially in frail patients. However specific biomarkers are needed for disease monitoring and prediction of disease progression or therapy response. Finally, pituitary diseases are associated with increased mortality and morbidity. This can be a direct effect of hormonal hypersecretion but also secondary to hypopituitarism (HP) caused by mass effect, or a direct consequence of trauma, as well as an important side effect of the treatment itself on pituitary lesions (novel immune check-point inhibitors). HP is globally under-diagnosed and insidious with tremendous effects on quality of life (QoL) as well. All the above mentioned and several other studies suggest an important role of the endocrine system on the development of frailty. It is very likely that comorbidities and drugs can accelerate the frailty of endocrine and metabolic origin. Finally, as concern inappropriate prescriptions, some algorithms were demonstrated particularly reliable. Combining clinical, epidemiological, social, hospital admissions and drug prescription data, has been proven a valid approach to identify inappropriate prescriptions due to drug ineffectiveness and to evaluate cost of polypharmacy.

Hypothesis and Significance Dysregulation of glucocorticoid secretion and hypogonadism due to primary adrenal or gonadal disorders are independent contributors to frailty and failure to treat effectively cardiovascular, metabolic and bone diseases. Prompt restoration of gonadal and adrenal function, when altered, can reduce the need for multi-drug prescription necessary to target high blood pressure, cardiovascular remodeling, osteoporosis and diabetes mellitus.

Less than 50% of patients with T2D had good glycemic control, understanding the mechanisms of Dipeptidyl peptidase-4 (DPP4) inhibitors and Glucagon-like peptide 1 (GLP1)-receptor agonist therapy is needed to predict the response to treatment. Genetic analysis and circulating microRNA profiling may help choosing the appropriate glucose-lowering drugs in T2D patients.

The high prevalence of pituitary and neuroendocrine disorders has a significant impact on morbidity, mortality and QoL. Tailoring diagnostic and therapeutic strategies will lead to early diagnosis of these diseases and their complications allowing to select the best long-term management.

A correlation between genetic and epigenetic risk of OP and fragility fractures (FF), two major components of frailty, is hypothesized and the investigators aim to identify early the subjects at higher risk and predict their response to anti-fracture drug.

Some complex endocrine disorders require extensive use of healthcare resources. Health Care Utilization (HCU) data offer accurate information on the prevalence, incidence, and duration of drugs use providing a comprehensive picture of the therapeutic habits. Linking prescription and clinical-administrative data could allow this network to investigate the inappropriate prescription patterns and the association with worse clinical outcomes.

Implications of the Study The case load of hospital care, diagnostic procedures and drug costs for non-communicable diseases is exceeding sustainability in all countries with a negative impact on public health system. The exponential rise in costs is due to the ageing of the population, prevalence of chronic disorders, improved acute care and new expensive drugs. Rationalization of expenditures is mandatory. Personalize diagnostic procedures, therapeutic approaches and management of comorbidities in highly prevalent disorders is only the immediately sustainable approach. The endocrine and metabolic disorders offer the ideal model to quantify the advantages of shifting from a non-personalized approached to precision etiological treatment strategies. This can lead to a rapid and substantial decline in cost expenditure in terms of number of hospital access, prescribed investigations, and inappropriate medication use. Expected outcomes is a reduction of NIH cost due to saving in 1) polypharmacy and 2) reduced hospitalization for the greater efficacy of drugs prescribed using and personalized algorithm, 3) reduced side effects due to multiple-drug interactions.