ENDOCRINE SOCIETY
OXFORD
Enhanced Chronic Inflammation and Increased Branched-Chain Amino Acids in Adrenal Disorders: A Cross-Sectional Study
Annop A. Kittithaworn,1 Prerna Dogra, 1,2 Jasmine Saini,10D Eke G. Gruppen,3 Elizabeth Atkinson, 4 Sara Achenbach,4 Kai Yu,10 Karthik Thangamuthu,1 Margery A. Connelly,5
Robin P. F. Dullaart,3,*DD and Irina Bancos1 .* DD
1Division of Endocrinology, Mayo Clinic, Rochester, MN 55905, USA
2Division of Endocrinology, Diabetes and Metabolism, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
3Department of Internal Medicine, University Medical Center Groningen and University of Groningen, Groningen 9700 RB, the Netherlands 4Division of Clinical Trials and Biostatistics, Mayo Clinic, Rochester, MN 55905, USA 5Labcorp, Morrisville, NC 27560, USA
Correspondence: Irina Bancos, MD, Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. Email: Bancos.Irina@mayo.edu; or Robin P. F. Dullaart, MD, Department of Internal Medicine, Division of Endocrinology, University of Groningen and University Medical Center Groningen, P.O. Box 30001, 9700 RB Groningen, the Netherlands. Email: dull.fam@12move.nl.
*These authors contributed equally to this work.
Abstract
Context: Patients with adrenal hormone excess demonstrate increased cardiovascular (CV) risk and mortality.
Objective: We aimed to determine the effect of adrenal disorders on the inflammation marker glycoprotein acetylation (GlycA), total branched- chain amino acids (BCAAs), ketone bodies, and the gut microbiome-derived metabolites trimethylamine N-oxide (TMAO) and betaine.
Methods: We conducted a single-center cross-sectional study of patients with nonfunctioning adenomas (NFAs), mild autonomous cortisol secretion (MACS), primary aldosteronism (PA), Cushing syndrome (CS), pheochromocytoma/paragangliomas (PPGLs), other benign or malignant adrenal masses, and adrenocortical carcinoma (ACC) between January 2015 and July 2022 (n = 802). Referent individuals included participants in the PREVEND (Prevention of Renal and Vascular End-Stage Disease) study (n = 5241). GlycA, BCAAs, ketone bodies, TMAO, and betaine were measured using nuclear magnetic resonance spectroscopy. Multivariable logistic analyses were adjusted for age, sex, body mass index, smoking, hypertension, diabetes mellitus, and statin therapy.
Results: In age- and sex-adjusted comparison to referent individuals, increased GlycA was noted in all patient categories, increased BCAAs in NFA, MACS, CS, PA, and ACC, increased TMAO in patients with other malignant adrenal masses, increased betaine in NFA and MACS, and increased ketone bodies in NFA, CS, and ACC. Essentially similar findings were observed in fully adjusted analysis and after exclusion of participants with diabetes and CV disease.
Conclusion: Patients with functioning and nonfunctioning adrenal masses demonstrated increased GlycA and BCAAs, biomarkers associated with adverse cardiometabolic disorders and mortality. Patients with NFA demonstrated an adverse metabolic profile similar to patients with MACS and CS.
Key Words: MACS, mild autonomous cortisol secretion, Cushing syndrome, inflammation, branched-chain amino acids, nuclear magnetic resonance spectroscopy Abbreviations: ACC, adrenocortical carcinoma; BCAA, branched-chain amino acid; BMI, body mass index; CS, Cushing syndrome; CV, cardiovascular; eGFR, estimated glomerular filtration rate; GlycA, glycoprotein acetylation; hsCRP, high-sensitivity C-reactive protein; IQR, interquartile range; LC-MS/MS, liquid chromatography-tandem mass spectrometry; MACS, mild autonomous cortisol secretion; NFA, nonfunctioning adenoma; NMR, nuclear magnetic resonance; OB, other benign; OM, other malignant; OR, odds ratio; PA, primary aldosteronism; PPGL, pheochromocytoma and paragangliomas; PREVEND, Prevention of Renal and Vascular End-Stage Disease; T2D, type 2 diabetes; TMAO, trimethylamine N-oxide.
Patients with adrenal masses and adrenal hormone excess demonstrate increased cardiovascular (CV) morbidity and mortality (1-7). Patients with malignant adrenal masses, and those with overt hormone excess, such as Cushing syndrome (CS), primary aldosteronism (PA), and pheochromocytomas or paragangliomas (PPGL), are usually treated with surgery, while patients with asymptomatic benign adrenal masses, such as those with mild autonomous cortisol secretion
(MACS) and nonfunctioning adrenal adenomas (NFAs) are usually followed conservatively (8).
Notably, despite the incidental discovery and lack of symp- toms, even patients with MACS and NFA are reported to show accumulation of CV risk factors and CV events (9-11). While the prevalence and incidence of CV morbidity and mortality is higher in patients with MACS when compared to NFA (1, 7, 9, 11), even patients with NFA demonstrate increased
CV risk when compared to patients without adrenal masses (10, 12), although overall mortality may be unchanged (13).
Identifying patients with asymptomatic but relevant ad- renal hormone excess early and before the development of co- existing CV morbidities is challenging. Approximately half of patients with MACS treated with adrenalectomy demonstrate improvement in CV risk factors such as hypertension, dia- betes, and obesity (14). Adrenalectomy is usually reserved for patients with more severe MACS and already established CV comorbidities (15-17). Consequently, long-term conser- vative follow-up of adrenal masses without overt hormone se- cretion may conceivably result in irreversible cardiometabolic damage. For this reason, there is an unmet need for identifying biomarkers that help predict future CV comorbidities and events among patients with an adrenal mass, especially in the context of MACS and NFA.
Several biomarkers have been recently reported to predict CV morbidity in the general population. Glycoprotein acetyl- ation (GlycA) is a composite biomarker of systemic inflamma- tion, which is a key driver of CV disease (CVD). GlycA was reported to predict major adverse CV events, heart failure, in- cident diabetes mellitus, development of microvascular com- plications in type 2 diabetes (T2D), and all-cause mortality (18-23). Total branched-chain amino acids (BCAAs), which include leucine, isoleucine, and valine, is another promising biomarker that was reported to be associated with increased risk of CVD, obesity, hypertension, T2D, and greater carotid intima thickness (24-28). Trimethylamine N-oxide (TMAO, N, N-dimethylmethanamine N-oxide) and betaine (N, N, N-trimethylglycine) are both microbiome-derived biomarkers. TMAO was reported to be associated with endothelial dys- function, nonalcoholic fatty liver disease, coronary artery dis- ease, and peripheral artery disease, and to predict major adverse CV events and overall mortality, whereas high betaine was associated with low diabetes risk (29-31). Ketone bodies were reported not only to be elevated in T2D, acute heart fail- ure, and myocardial infarction but also to be associated with all-cause mortality, incident T2D, and heart failure (32-35).
Recently developed nuclear magnetic resonance (NMR) techniques enable accurate quantification of a set of bio- markers including GlycA, BCAAs, ketone bodies, TMAO, and betaine with sufficient precision, suitable for measure- ment in large clinical studies (36, 37). In the absence of com- prehensive data, our objective was to determine the association of adrenal masses with and without adrenal hor- mone excess with these biomarkers known to be predictive of CV events and mortality.
Materials and Methods
Study Design
Participants included adult patients with adrenal masses and/ or adrenal hormone excess prospectively enrolled at Mayo Clinic, Rochester, Minnesota, and referent individuals in- cluded in the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study carried out among inhabitants of the city of Groningen, the Netherlands.
Patients With Adrenal Masses
Patients with adrenal masses and/or adrenal hormone excess were enrolled consecutively and prospectively from the ad- renal clinic at Mayo Clinic in Rochester, Minnesota, between
January 1, 2015 and July 1, 2022. All patients signed an in- formed consent. This study was approved by the institutional review board (IRB No. 18-009787 and IRB No. 13-005838) and complies with the Declaration of Helsinki.
Patients with adrenal disorders included those with NFA, MACS, CS, PA, PPGL, adrenocortical carcinoma (ACC), oth- er adrenal malignant masses (metastases, lymphomas, sarco- mas), and other benign adrenal masses (myelolipomas, cysts). Diagnosis of MACS, CS, and PA was made according to the most recent guidelines (38, 39). Patients with an incom- plete workup or those on active exogenous glucocorticoid therapy for any reason were excluded. Demographics, smok- ing history, data on present comorbidities (hypertension, dys- lipidemia, diabetes mellitus), body mass index (BMI), history of CV events, and presence of therapy for diabetes, dyslipide- mia, and hypertension were collected for all patients. Fasting EDTA plasma biomaterial was collected in the morning and stored at -80 ℃ within the Mayo Clinic biobank.
Referent Individuals
The PREVEND study investigates vascular and renal damage in a large Dutch population-based cohort comprising inhabi- tants of the city of Groningen (predominantly White ethni- city), as previously described (21, 24, 33, 40, 41). In short, in the period from 1997 to 1998, all inhabitants aged 28 to 75 years were asked to send in a morning urine sample and to fill out a short questionnaire. Pregnant women and individ- uals with type 1 diabetes mellitus were excluded. Urinary al- bumin concentration was assessed in 40 856 (47.8%) responders. Individuals with a urinary albumin concentration greater than or equal to 10 mg L-1 (n = 7768) were invited to participate, of whom 6000 agreed. Furthermore, 3394 ran- domly selected individuals with a urinary albumin concentra- tion of less than 10 mg L-1 were invited and 2592 agreed to participate. These 8592 individuals constitute the initial PREVEND cohort. Of 8592 participants, 6894 participated in the second screening round (2001-2003). NMR biomarkers were available for the present reference data in 5241 partici- pants in the second screening round. The PREVEND study has been approved by the medical ethics committee of the University Medical Center Groningen, the Netherlands (ap- proval No. MEC96/01/022) and was conducted in accordance with the guidelines of the Declaration of Helsinki. All partic- ipants gave written informed consent.
The procedures at each examination in the PREVEND study have been described in detail previously (42, 43). In summary, before the outpatient clinic visit, all participants completed a questionnaire regarding demographics, CV and renal disease history, smoking habits, alcohol consumption, and medication use. Information on medication use was com- bined with information from a pharmacy-dispensing registry, which had complete information on the drugs of more than 95% of participants in the PREVEND study. Blood pressure was measured with an automatic Dinamap XL Model 9300 series device (Johnson-Johnson Medical).
Clinical Measurements and Definition of Comorbidities
BMI was calculated as weight in kilograms divided by height in meters squared. Hypertension was defined as a systolic blood pressure greater than 140 mm Hg or a diastolic blood pressure greater than 90 mm Hg, and/or the use of antihypertensive
drugs. T2D was defined as a fasting serum glucose level greater than 7.0 mmol/L, a nonfasting plasma glucose level greater than 11.1 mmol/L, self-report of a physician diagnosis, and/or the use of glucose-lowering drugs, retrieved from a central phar- macy registry (PREVEND) or medical records (patients). Serum creatinine levels were measured using an enzymatic method (Roche Modular, Roche Diagnostics) for the PREVEND cohort and using an enzymatic colorimetric assay at the Mayo Clinic. The estimated glomerular filtration rate (eGFR) was calculated with the use of creatinine-based Chronic Kidney Disease- Epidemiology Collaboration equation (44).
Nuclear Magnetic Resonance Measurements
EDTA plasma samples from patients and both referent participant cohorts were sent frozen to Labcorp for testing on the Vantera Clinical Analyzer, a fully automated, high- throughput, 400-MHz proton (1H) NMR spectroscopy platform. Plasma concentrations of GlycA, BCAAs, TMAO, betaine, and ketone bodies were quantified as previously described (26, 31, 32, 45, 46). In short, the GlycA NMR signal comes from the methyl group protons of the N-acetylglucosamine moieties located on the bi-, tri-, and tetra-antennary branches of plasma glycoproteins, mainly a1-acid glycoprotein, haptoglobin, a1-antitrypsin, a1-antichymotrypsin, and transferrin. The coefficients of vari- ation for the GlycA assay range from 1.3% to 2.3%. Total BCAA, that is valine, leucine, and isoleucine concentrations com- bined, were measured using a standalone assay that has been op- timized to quantify only the BCAAs concentrations. CVS for interassay and intraassay precision ranged from 1.8% to 6.0%, 1.7% to 5.4%, 4.4% to 9.1%, and 8.8% to 21.3%, for total BCAAs, valine, leucine, and isoleucine, respectively. BCAAs quantified from the same samples using NMR and liquid chro- matography-tandem mass spectrometry (LC-MS/MS) were highly correlated (12=0.97, 0.95, and 0.90 for valine, leucine, and isoleucine). Total ketone bodies were calculated as the sum of ß-hydroxybutyrate, acetoacetate, and acetone. A method com- parison study was performed comparing quantification by NMR to platforms commonly used for determining ketone body con- centrations (LC-MS/MS for ß-hydroxybutyrate and acetoacetate and gas chromatography/MS for acetone). A comparison of plas- ma concentrations using the comparator platforms correlated well by Deming regression with R2 values of 0.996, 0.994, and 0.994 for ß-hydroxybutyrate, acetoacetate, and acetone, respect- ively. For ß-hydroxybutyrate, acetoacetate, and acetone, coeffi- cients of variation for intra-assay and interassay precision were 1.3% to 9.3%, 3.1% to 7.7%, and 3.8% to 9.1%, respectively. TMAO was quantified from one-dimensional (1D) proton (1H) Carr-Purcell-Meiboom-Gill (CPMG) spectra by spectral decon- volution algorithm. The TMAO assay has intra-assay and inter- assay coefficients of variation percentage ranges from 4.3% to 10.3% and 9.8% to 14.5%, respectively. For the TMAO and betaine assays, plasma specimens were mixed with citrate/phos- phate buffer (3:1 v/v) to lower the pH to 5.3, which was necessary to separate the betaine and TMAO signals that otherwise overlap at physiological pH. Betaine assay results are linear over a wide range of concentrations (26.0-1135 umol/L). Coefficients of vari- ation for intra-assay and interassay precision are 4.3% and 5.5%, respectively. Betaine as measured by the NMR assay gives comparable results with LC-MS/MS (R2 = 0.94). Long-term fro- zen stability of most of the measured analytes has been demon- strated in EDTA plasma and serum for up to 12 years when
stored at -80 ℃. For TMAO and betaine, long-term frozen sta- bility was demonstrated in EDTA plasma for up to 2 years and serum for up to 5 years when stored at -80 ℃.
Statistical Analysis
For descriptive statistics, median and interquartile range (IQR) were used to describe continuous variables and compared us- ing the Kruskal-Wallis test, while categorical variables are shown as a number (%) and compared using the chi-square test. Differences in the association of each biomarker measure- ment in between the 9 adrenal disorder groups, compared with the referent population (PREVEND), were measured using lo- gistic regression analysis adjusting for age, sex within model 1, and for age, sex, BMI, smoking, hypertension, T2D, and statin therapy within model 2. Prior to fitting the logistic regression models, the biomarker data was log2 transformed, then stand- ardized by subtracting the mean value and dividing by the SD. Odds ratios (ORs) are expressed with 95% CIs and are inter- preted as the influence of a 1-SD change of the log2- transformed data. Analyses were conducted using the R soft- ware environment, version 4.2.2. Statistical significance was defined as P less than .05.
Results
Patients and Referent Individuals
A total of 802 patients (median age, 57 years, IQR 44-66 years, 499, 62.2% women) were diagnosed with NFA (167, 20.8%), MACS (213, 26.6%), CS (142, 17.7%), PA (130, 16.2%), ACC (39, 4.9%), other malignant adrenal masses (39, 4.9%), other benign adrenal masses (29, 3.6%), and PPGL (43, 5.4%). Referent individuals included 5241 partic- ipants from the PREVEND study (median age, 52 years, IQR 43-63 years, 2632, 50.2% women). As expected, patients with various adrenal disorder subtypes presented with differ- ences in age, sex, BMI, and prevalence of comorbidities (Table 1). In general, patients with adrenal disorders were old- er, with a higher prevalence of obesity, hypertension, T2D, and dyslipidemia, smoked less frequently, and had lower eGFR compared to participants from the PREVEND referent population. The P values for the various adrenal mass categor- ies in comparison with the referent population are shown in Supplementary data (reference No. 24784074) (47).
Biomarkers
Plasma GlycA was elevated in all patient categories when compared to referent participants (Tables 2 and 3, Fig. 1). Age- and sex-adjusted analysis demonstrated that GlycA was highest in patients with adrenal malignancies, CS, and PPGL, followed by MACS, NFA, and PA (see Fig. 1). Patients with MACS and NFA had similar elevations of GlycA, and postdexamethasone cortisol was not associated with GlycA (R = 0.06; P =. 276). After adjusting also for BMI, hypertension, diabetes, smoking, and statin therapy, GlycA remained similarly elevated in all patient groups except for patients with PA (see Table 3). Plasma BCAAs were ele- vated in all patient categories except in those with noncortical adrenal masses (other benign, other malignant, and PPGL) (see Table 3 and Fig. 1). After adjusting for BMI, hyperten- sion, diabetes, smoking, and statin therapy, BCCAs were simi- larly elevated in patients with NFA, MACS, CS, PA, and ACC, without prominent intergroup differences (see Table 3 and
| Benign adrenal disorders | Malignant adrenal disorders | PPGL | Referent individuals (PREVEND cohort) | ||||||
|---|---|---|---|---|---|---|---|---|---|
| NFA | MACS | CS | PA | Other benign | ACC | Other malignant | |||
| n | 167 | 213 | 142 | 130 | 39 | 39 | 29 | 43 | 5241 |
| Women, n (%) | 106 (63.5%) | 140 (65.7%) | 125 (88.0%) | 53 (40.8%) | 19 (48.7%) | 21 (53.8%) | 15 (51.7%) | 20 (46.5%) | 2632 (50.2%) |
| Age, | 60.1 | 61.0 | 46.3 | 53.0 | 51.5 | 54.2 | 63.5 | 55.5 | 52.0 |
| median (IQR), y | (53.0-66.4) | (51.1-69.5) | (34.7-58.4) | (44.1-59.3) | (39.4-66.1) | (40.5-65.6) | (57.5-72.3) | (41.9-65.0) | (43.0-63.0) |
| BMI, | 32.0 | 31.1 | 32.5 | 33.0 | 28.8 | 28.7 | 28.0 | 27.0 | 26.1 |
| median (IQR) | (27.8-37.6) | (26.3-36.0) | (28.1-39.3) | (28.6-36.8) | (24.5-34.5) | (25.3-33.3) | (24.1-36.8) | (23.9-31.0) | (23.7-28.9) |
| SBP, mm Hg | 130 | 132 | 134 | 138 | 124 | 137 | 130 | 130 | 123 |
| median (IQR) | (121-140) | (122-143) | (123-146) | (130-153) | (120-136) | (123-152) | (120-143) | (120-141) | (112-137) |
| DBP, mm Hg | 78 | 80 | 84 | 85 | 82 | 82 | 76 | 80 | 72 |
| median (IQR) | (71-86) | (74-86) | (79-91) | (80-94) | (75-86) | (73-95) | (66-83) | (73-86) | (67-79) |
| Postdexamethasone cortisol, mcg/dL | 1.2 | 3.1 | 13 | 1.1 | 1.1 | 3 | 1.4 | 1.4 | — |
| median (IQR) | (1.0-1.5) | (2.3-5.2) | (6.8-19.3) | (1.0-1.4) | (1.0-1.5) | (2.0-7.6) | (1.0-2.5) | (1.0-1.6) | |
| Hypertension, n (%) | 106 (63.5%) | 174 (81.7%) | 107 (75.4%) | 128 (98.5%) | 21 (53.8%) | 28 (71.8%) | 18 (62.1%) | 36 (83.7%) | 1740 (33.2%) |
| Type 2 diabetes, n (%) | 35 (21.0%) | 63 (29.6%) | 47 (33.1%) | 24 (18.5%) | 3 (7.7%) | 10 (25.6%) | 6 (20.7%) | 9 (20.9%) | 317 (6.0%) |
| Dyslipidemia, n (%) | 118 (70.7%) | 151 (70.9%) | 83 (58.5%) | 86 (66.2%) | 14 (35.9%) | 17 (43.6%) | 12 (41.4%) | 15 (34.9%) | 1578 (30.1%) |
| Statin therapy, n (%) | 51 (30.9%) | 83 (43.0%) | 40 (31.0%) | 47 (44.8%) | 9 (23.1%) | 13 (34.2%) | 8 (27.6%) | 15 (34.9%) | 512 (9.8%) |
| eGFR, mL/min/1.73 m2 | 80 | 80 | 90 | 84 | 91 | 87 | 66 | 88 | 95 |
| median (IQR)) | (65-94) | (66-95) | (72-104) | (68-95) | (73-101) | (68-102) | (55-82) | (70-98) | (84-105) |
| Smoking status | |||||||||
| Never, n (%) | 78 (46.7%) | 95 (44.6%) | 104 (73.2%) | 99 (76.2%) | 22 (56.4%) | 18 (46.2%) | 15 (51.7%) | 26 (60.5%) | 1529 (29.5%) |
| Past smoker, n (%) | 62 (37.1%) | 76 (35.7%) | 21 (14.8%) | 24 (18.5%) | 11 (28.2%) | 15 (38.5%) | 11 (37.9%) | 13 (30.2%) | 2225 (42.9%) |
| Current smoker, n (%) | 27 (16.2%) | 42 (19.7%) | 17 (12.0%) | 7 (5.4%) | 6 (15.4%) | 6 (15.4%) | 3 (10.3%) | 4 (9.3%) | 1431 (27.6%) |
| Cardiovascular events, n (%) | 32 (19.2%) | 48 (22.5%) | 13 (9.2%) | 13 (10%) | 3 (7.7%) | 8 (20.5%) | 2 (6.9%) | 11 (25.6%) | 799 (15.2%) |
Overall P values: P less than or equal to .001 for all variables compared to referent individuals, Supplementary Appendix.
Abbreviations: ACC, adrenocortical carcinoma; BMI, body mass index; CS, Cushing syndrome; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; IQR, interquartile range; MACS, mild autonomous cortisol secretion; NFA, nonfunctioning adenoma; PA, primary aldosteronism; PPGL, pheochromocytoma and paragangliomas; PREVEND, Prevention of Renal and Vascular End-Stage Disease; SBP, systolic blood pressure.
| Benign adrenal disorders | Malignant adrenal disorders | PPGL | Referent individuals | ||||||
|---|---|---|---|---|---|---|---|---|---|
| NFA | MACS | CS | PA | Other benign | ACC | Other malignant | |||
| n | 167 | 213 | 142 | 130 | 39 | 39 | 29 | 43 | 5241 |
| GlycA, umol/L | 430 | 440 | 495 | 408 | 403 | 517 | 505 | 433 | 372 |
| median (IQR) | (379-482) | (390-498) | (434-580) | (366-452) | (345-446) | (397-590) | (423-585) | (394-491) | (336-415) |
| Total BCCA, umol/L | 435 | 427 | 429 | 462 | 399 | 426 | 422 | 421 | 376 |
| median (IQR) | (374-492) | (373-489) | (371-491) | (400-538) | (342-446) | (348-503) | (317-487) | (321-466) | (329-427) |
| ΤΜΑΟ, μΜ | 3 | 3 | 3 | 3 | 3 | 3 | 4 | 3 | 3 |
| median (IQR) | (2-5) | (2-6) | (2-4) | (2-5) | (2-4) | (2-4) | (3-8) | (2-5) | (2-6) |
| Betaine, umol/L | 40 | 38 | 32 | 37 | 38 | 37 | 35 | 36 | 37 |
| median (IQR) | (32-46) | (32-45) | (27-39) | (33-44) | (30-43) | (30-43) | (32-44) | (29-46) | (31-44) |
| Total ketone bodies, | 201 | 174 | 187 | 164 | 181 | 193 | 210 | 197 | 179 |
| umol/L median (IQR) | (149-349) | (134-293) | (138-286) | (127-231) | (139-297) | (158-349) | (160-345) | (131-271) | (139-248) |
Abbreviations: ACC, adrenocortical carcinoma; BCCA, branched-chain amino acid; CS, Cushing syndrome; GlycA, glycoprotein acetylation; IQR, interquartile range; MACS, mild autonomous cortisol secretion; NFA, nonfunctioning adenoma; PA, primary aldosteronism; PPGL, pheochromocytoma and paragangliomas; TMAO, trimethylamine N-oxide.
Fig. 1). Plasma TMAO was elevated only in patients with oth- er malignant adrenal masses in both models (see Table 3 and Fig. 1). Plasma betaine was elevated in patients with NFA and MACS in age- and sex-adjusted and fully adjusted analysis. In fully adjusted analysis betaine was also elevated in PA (see Table 3 and Fig. 1). Plasma ketone bodies were modestly ele- vated in patients with NFA, CS, and ACC after adjustment for age and sex, and in patients with NFA and ACC in fully ad- justed analysis. Ketone bodies were not increased in PPGL pa- tients (see Table 3 and Fig. 1).
We next performed a secondary analysis after excluding patients and referent individuals with T2D and a positive CV history. The results were similar to the analysis of the whole cohort (Supplementary data, reference No. 24784074).
Discussion
In this large cross-sectional study of patients with adrenal dis- orders with and without hormone excess compared to referent participants, we found that patients among all categories of adrenal disorders demonstrate an increase in GlycA in multi- variable logistic regression analysis adjusted for age, sex, BMI, hypertension, diabetes status, current smoking, and statin therapy. After these adjustments, BCAAs were also elevated in most patient categories except those with noncortical ad- renal masses and PPGL. Modest increases in betaine were demonstrated in patients with NFA, MACS, and PA, but there were almost no differences in TMAO and ketone bodies when compared to referent individuals. Similar findings were ob- tained after excluding patients with T2D and established CVD. Taken together, the findings of the present study sup- port the contention that both functioning and nonfunctioning adrenal masses may give rise to enhanced low-grade chronic inflammation and elevated BCAAs, a metabolic abnormality that is associated with insulin resistance and the development of cardiometabolic diseases. Notably, similar increases in GlycA and BCAAs were observed in patients with NFA and MACS, underscoring an adverse metabolic profile in NFA comparable to that of mild cortisol excess.
A main novel finding of our study is that GlycA is elevated not only in adrenal malignancies and CS, but also in patients with NFA, MACS, and PPGL. GlycA is an emerging biomarker of chronic inflammation that has been recently reported to pre- dict T2D, atherosclerotic CVD, all-cause mortality, and re- duced life expectancy (18, 20-23, 31, 40, 41, 46, 48). GlycA measured by NMR spectroscopy is a composite biomarker that senses the glycosylation states of several of the most abundant acute-phase proteins. Its signal comes from N-acetyl methyl groups mostly bound to acute-phase proteins, such as a1-acid glycoprotein (oromucosoid), haptoglobin, a1-antitrypsin, a1-antichymotrypsin, and transferrin. Recent experimental evidence has confirmed that the GlycA NMR sig- nal is linked to N-glycan branching commonly associated with acute-phase reactive proteins involved in inflammation (49). GlycA appears to be governed by SLC39A8, a gene that enco- des a manganese transporter that influences N-glycan branch- ing (49). Plasma GlycA is robustly correlated with high-sensitivity C-reactive protein (hsCRP), which is, in con- trast, not highly glycosylated. Interestingly, the association of GlycA with incident atherosclerotic CVD and new-onset T2D was found to remain after adjustment for hsCRP, findings that can at least in part be explained by the fact that GlycA is less variable within an individual than hsCRP (46). In compari- son, previous reports in (much) smaller patient groups have demonstrated an increase in GlycA in PA but no change after adrenalectomy, equivocal increases in hsCRP in NFA and MACS, and increases in hsCRP in CS and in PPGL (50-56). In addition, a small immunohistochemical study has shown in- creased expression of inflammatory proteins in adrenal mass tissue, in particular in adenomas and PPGL (57).
We also found elevated plasma BCAA concentrations in patients with benign adrenal adenomas with and without hor- mone excess, as well as in ACC in adjusted analyses. Decreased plasma levels of leucine and increased urinary se- cretion of leucine, isoleucine, and valine were found in CS, whereas BCAAs increased after adrenalectomy in PA patients without diabetes initially (55, 58). We found no other reports documenting plasma levels of BCAAs in series of patients with functioning and nonfunctioning adrenal masses.
| Biomarker | Benign adrenal disorders | Malignant adrenal disorders | PPGL | |||||
|---|---|---|---|---|---|---|---|---|
| NFA | MACS | CS | PA | Other benign | ACC | Other malignant | ||
| Age- and sex-adjusted odds ratio (95% CIs) | ||||||||
| GlycA | 2.25 | 2.44 | 4.52 | 1.87 | 1.90 | 4.95 | 4.42 | 2.84 |
| (1.92-2.64) | (2.12-2.82) | (3.80-5.38) | (1.56-2.24) | (1.38-2.62) | (3.83-6.40) | (3.25-6.00) | (2.14-3.77) | |
| Total BCCA | 2.66 | 2.57 | 3.09 | 3.25 | 1.53 | 2.09 | 1.26 | 1.33 |
| (2.24-3.16) | (2.20-2.99) | (2.58-3.70) | (2.70-3.92) | (1.07-2.21) | (1.48-2.95) | (0.82-1.94) | (0.93-190) | |
| TMAO | 1.02 | 1.12 | 1.18 | 1.10 | 0.86 | 0.92 | 1.72 | 0.95 |
| (0.85-1.21) | (0.97-1.30) | (0.99-1.40) | (0.92-1.32) | (0.65-1.21) | (0.67-1.29) | (1.15-2.56) | (0.68-1.31) | |
| Betaine | 1.25 | 1.19 | 1.02 | 1.14 | 1.07 | 1.11 | 1.05 | 1.13 |
| (1.05-1.49) | (1.02-1.39) | (0.87-1.20) | (0.94-1.40) | (0.75-1.52) | (0.77-1.59) | (0.70-1.59) | (0.79-1.62) | |
| Total ketone bodies | 1.26 | 1.05 | 1.27 | 0.84 | 1.16 | 1.52 | 1.30 | 1.06 |
| (1.09-1.46) | (0.92-1.21) | (1.08-1.49) | (0.69-1.03) | (0.85-1.57) | (1.17-1.99) | (0.93-1.82) | (0.78-1.44) | |
| Age-, sex-, BMI-, hypertension-, type 2 diabetes-, smoking-, and statin therapy-adjusted odds ratio (95% CIs) | ||||||||
| GlycA | 1.67 | 1.82 | 3.38 | 1.23 | 1.65 | 4.23 | 3.93 | 2.64 |
| (1.39-2.00) | (1.55-2.13) | (2.75-4.14) | (0.98-1.54) | (1.17-2.32) | (3.23-5.55) | (2.88-5.37) | (1.96-3.55) | |
| Total BCCA | 1.91 | 1.74 | 1.62 | 1.89 | 1.18 | 1.48 | 1.07 | 1.01 |
| (1.58-2.31) | (1.47-2.06) | (1.31-2.00) | (1.51-2.36) | (0.80-1.74) | (1.02-2.14) | (0.68-1.69) | (0.70-1.46) | |
| TMAO | 0.92 | 1.02 | 1.10 | 1.10 | 0.85 | 0.86 | 1.57 | 0.91 |
| (0.77-1.11) | (0.87-1.20) | (0.89-1.36) | (0.88-1.38) | (0.61-1.17) | (0.62-1.21) | (1.06-2.34) | (0.65-1.29) | |
| Betaine | 1.31 | 1.22 | 1.10 | 1.38 | 1.08 | 1.17 | 1.02 | 1.14 |
| (1.08-1.58) | (1.04-1.44) | (0.89-1.35) | (1.12-1.70) | (0.75-1.55) | (0.81-1.68) | (0.67-1.57) | (0.80-1.64) | |
| Total ketone bodies | 1.19 | 0.96 | 1.06 | 0.73 | 1.13 | 1.42 | 1.23 | 1.01 |
| (1.01-1.39) | (0.82-1.12) | (0.87-1.29) | (0.58-0.92) | (0.82-1.55) | (1.08-1.86) | (0.88-1.73) | (0.73-1.40) | |
Abbreviations: ACC, adrenocortical carcinoma; BCCA, branched-chain amino acid; BMI, body mass index; CS, Cushing syndrome; GlycA, glycoprotein acetylation; IQR, interquartile range; MACS, mild autonomous cortisol secretion; NFA, nonfunctioning adenoma; PA, primary aldosteronism; PPGL, pheochromocytoma and paragangliomas; TMAO, trimethylamine N-oxide.
NFA
CS
OB
OM
MACS
PA
ACC
PPGL
GlycA
GlycA
BCAA
BCAA
TMAO
TMAO
Betaine
Betaine
KetBod
KetBod
0.5
1.0
2.0
4.0
8.0
0.5
1.0
2.0
4.0
8.0
OR
OR
Experimental evidence has suggested that elevated circulating BCAAs may be causally implicated in the development of in- sulin resistance and diabetes via a role in mitochondrial over- loading with lipid substrates, contributing to mitochondrial stress, and through impaired insulin action via activation of the mammalian target of rapamycin complex 1 (mTORC1) (59, 60). On the other hand, an early study has shown that acute cortisol excess impairs insulin sensitivity without affect- ing circulating BCAA concentrations (58). More recently, based on genetic evidence, impaired insulin action itself could also contribute to plasma BCAA elevations (61). Associations of elevated BCAAs with insulin resistance, T2D, and metabolic syndrome have been repeatedly demonstrated (26) (62-64), but such cross-sectional findings do not necessarily implicate a pathogenic role of plasma BCAA elevations in the development of new-onset diabetes. However, in support of the possibility that BCAAs are implicated in the pathogenesis of human dia- betes, high plasma BCAA concentrations likely occur long be- fore the development of T2D (65). In the present study, the prevalence of diabetes was very high in patients with function- ing and nonfunctioning adrenal adenomas, ranging from 18.5% in PA to 31% in CS. In contrast, a lower prevalence of 7.7% was observed in patients with other benign adrenal masses, which was approximately similar to that of 6.0% in the referent population. To reduce the probability that the ele- vated plasma BCAA concentrations in patients with function- ing and nonfunctioning adrenal adenomas could be merely attributable to the high diabetes prevalence, we carried out a secondary analysis excluding participants with prevalent dia- betes and CVD, both from the adrenal mass cohort and from the referent population. This analysis still showed higher BCAA levels in patients with NFA, MACS, CS, PA, and ACC (Supplementary data, reference No. 24784074) (47).
To the best of our knowledge, no data are available regarding abnormalities in plasma TMAO and betaine in patients with be- nign adrenal cortical masses, ACC, and PPGL. Gut microbiota metabolize nutrients including choline and L-carnitine to gener- ate trimethylamine (TMA, N, N-dimethylmethanamine), which is converted to TMAO in the liver, and choline to generate beta- ine (N, N, N-trimethylglycine) (66, 67). Betaine is an osmolyte as well as a methyl donor in one-carbon metabolism (68). Betaine may ameliorate oxidative stress and inflammation, like- ly due to its ability to lower homocysteine (69, 70). Although TMAO and betaine may be modestly correlated with each oth- er, TMAO was elevated only in patients with other adrenal ma- lignancies, whereas betaine was elevated in NFA, MACS, and PA in fully adjusted analyses. Whether higher betaine in these patient categories could to some extent mitigate the possible ad- verse effect of chronic inflammation and BCAA levels on cardi- ometabolic outcome remains speculative. Also, the extent to which these changes in circulating betaine and possibly also TMAO and BCAAs reflect alterations in the gut microbiome is still unclear (71, 72).
Plasma ketone bodies were modestly elevated in patients with NFA, CS, and ACC after adjustment for age and sex, and in patients with NFA and ACC in fully adjusted analyses. Ketone bodies were unaltered in PPGL patients. Measurement of ketone bodies was included in the present study in the ex- pectation that catecholamine-induced lipolysis would result in higher ketone body generation (73, 74). The reasons for this lack of increase in ketone bodies in PPGL is unclear but could be due to the use of a-blockers in a considerable number of PPGL patients studied.
Strengths of this study include a large sample size of patients with adrenal masses, consecutive enrollment, comparison with a large, well-characterized referent cohort, and consistent and uni- form prospective data collection. Limitations include those at- tributed to the cross-sectional study design, such as the lack of longitudinal follow-up for incident cardiometabolic risk factors and outcome. As patients were referred to our institution for evaluation and management, selection bias is likely. As PREVEND participants did not have imaging, adrenal inciden- taloma may have been present in around 5% of participants, thus underestimating the differences noted between patients and referent individuals. Patients and referent participants in the present study were predominantly White, and the results of this study may not be applicable to more diverse populations.
In conclusion, patients with adrenal masses demonstrate in- creased GlycA and BCAAs, biomarkers associated with ad- verse cardiometabolic disorders and mortality. Patients with NFA demonstrated an adverse metabolic profile similar to pa- tients with MACS. Future longitudinal studies will need to demonstrate whether elevated plasma levels of GlycA and BCAAs could be used to select patients most likely to benefit from an early surgical approach and to determine the extent to which these biomarkers normalize after surgery.
Funding
This work was partly supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the National Institutes of Health (NIH) USA under award K23DK121888 and R03DK132121 (to I.B). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The NMR-determined biomarkers were measured at Labcorp, Morrisville, North Carolina, 27560, USA, at no cost. The Dutch Kidney Foundation supported the infrastructure of the PREVEND program from 1997 to 2003 (grant E.033). The University Medical Center Groningen supported the infrastructure from 2003 to 2006. The Netherlands Heart Foundation supported studies on lipid metabolism from 2001 to 2005.
Disclosures
I.B. reports advisory board participation/consulting (fees to insti- tution) from HRA Pharma, Corcept, Recordati, Xeris, NovoNordisk, AstraZeneca, Sparrow Pharmaceutics, Neurocrine, Spruce, and Diurnal outside the submitted work, and data monitoring and safety board participation for Adrenas. She also reports funding for investigator-initiated re- search (outside this work) from HRA Pharma and Recordati. The University Medical Center Groningen received research sup- port from Labcorp in the form of a research grant and laboratory assessments to R.P.F.D. M.A.C. is an employee of Labcorp. The remainder of the authors have nothing to disclose.
Data Availability
Some or all data sets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.
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