Impact of COVID-19 on the Endocrine System: A Mini-review

The coronavirus disease 2019 (COVID-19) pandemic continues to exert a significant impact on global health care systems, causing devastating mortality and morbidity. As time passes and our understanding of this novel respiratory virus deepens, it is increasingly clear that its effects extend beyond that of the respiratory system. The coronavirus responsible for COVID-19, severe acute respiratory syndrome coronavirus 2, obtains cellular access through the angiotensin-converting enzyme 2 (ACE2) receptor in a process requiring the transmembrane serine protease 2 (TMPRSS2) protein. Both ACE2 and TMPRSS2 are widely expressed in many endocrine glands. This, along with several case reports of thyroid and pituitary disruption in patients with COVID-19, has resulted in significant interest in its impact on the endocrine system. Indeed, as mortality is abated by the increasing availability of effective vaccines, there is increasing focus on the long-term effects on health in COVID-19 survivors. This review summarizes data investigating the effects of COVID-19 on each of the endocrine axes to guide appropriate investigations and optimal management.

A Bayesian optimization approach for rapidly mapping residual network function in stroke

Post-stroke cognitive and linguistic impairments are debilitating conditions, with limited therapeutic options. Domain-general brain networks play an important role in stroke recovery and characterizing their residual function with functional MRI has the potential to yield biomarkers capable of guiding patient-specific rehabilitation. However, this is challenging as such detailed characterization requires testing patients on multitudes of cognitive tasks in the scanner, rendering experimental sessions unfeasibly lengthy. Thus, the current status quo in clinical neuroimaging research involves testing patients on a very limited number of tasks, in the hope that it will reveal a useful neuroimaging biomarker for the whole cohort. Given the great heterogeneity among stroke patients and the volume of possible tasks this approach is unsustainable. Advancing task-based functional MRI biomarker discovery requires a paradigm shift in order to be able to swiftly characterize residual network activity in individual patients using a diverse range of cognitive tasks. Here, we overcome this problem by leveraging neuroadaptive Bayesian optimization, an approach combining real-time functional MRI with machine-learning, by intelligently searching across many tasks, this approach rapidly maps out patient-specific profiles of residual domain-general network function. We used this technique in a cross-sectional study with 11 left-hemispheric stroke patients with chronic aphasia (four female, age ± standard deviation: 59 ± 10.9 years) and 14 healthy, age-matched control subjects (eight female, age ± standard deviation: 55.6 ± 6.8 years). To assess intra-subject reliability of the functional profiles obtained, we conducted two independent runs per subject, for which the algorithm was entirely reinitialized. Our results demonstrate that this technique is both feasible and robust, yielding reliable patient-specific functional profiles. Moreover, we show that group-level results are not representative of patient-specific results. Whereas controls have highly similar profiles, patients show idiosyncratic profiles of network abnormalities that are associated with behavioural performance. In summary, our study highlights the importance of moving beyond traditional 'one-size-fits-all' approaches where patients are treated as one group and single tasks are used. Our approach can be extended to diverse brain networks and combined with brain stimulation or other therapeutics, thereby opening new avenues for precision medicine targeting a diverse range of neurological and psychiatric conditions.

Effects of Glucagon-like Peptide-1 on the Reproductive Axis in Healthy Men

CONTEXT

Glucagon-like peptide-1 (GLP-1) potently reduces food intake and augments glucose-stimulated insulin secretion. Recent animal data suggest that GLP-1 may also influence reproduction. As GLP-1 receptor agonists are currently widely used in clinical practice to treat obesity/type 2 diabetes, it is necessary to determine the effects of GLP-1 on the reproductive system in humans.

OBJECTIVE

To investigate the effects of GLP-1 administration on the reproductive axis in humans.

DESIGN

Single-blind, randomized, placebo-controlled crossover study.

SETTING

Clinical Research Facility, Imperial College Healthcare NHS Trust.

PARTICIPANTS

Eighteen healthy men (mean age 24.7 ± 0.1years, mean BMI 22.1 ± 0.4kg/m2).

INTERVENTION

Eight-hour intravenous infusion of 0.8 pmol/kg/min GLP-1 or rate-matched vehicle infusion.

MAIN OUTCOME MEASURES

Number of luteinizing hormone (LH) pulses, LH, follicle-stimulating hormone (FSH), and testosterone levels.

RESULTS

The number of LH pulses (number of LH pulses/500 min: vehicle 4.2 ± 0.4, GLP-1 4.5 ± 0.3, P = 0.46), LH area under the curve (AUC) (vehicle 1518 ± 88min.IU/L, GLP-1 1524 ± 101min.IU/L, P = 0.95), follicle-stimulating hormone AUC (vehicle 1210 ± 112 min IU/L, GLP-1 1216 ± 112 min IU/L, P = 0.86), and testosterone AUC (vehicle 10893 ± 615 min nmol/L, GLP-1 11088 ± 792 min nmol/L, P = 0.77) did not significantly differ during vehicle and GLP-1 administration. Glucagon-like peptide-1 significantly reduced food intake (vehicle 15.7 ± 1.3 kcal/kg, GLP-1 13.4 ± 1.3 kcal/kg, P = 0.01).

CONCLUSIONS

In contrast to the animal literature, our data demonstrate that acute GLP-1 administration does not affect reproductive hormone secretion in healthy men.