Abstract
The identification of brown adipose tissue (BAT) as a thermogenic organ in human adults approximately 20 years ago raised the exciting possibility of activating this tissue as a new treatment for obesity and cardiometabolic disease. [18F]Fluoro-2-deoxyglucose (18F-FDG) combined positron emission tomography and computed tomography (PET/CT) scanning is the most commonly used imaging modality to detect and quantify human BAT activity in vivo. This technique exploits the substantial glucose uptake by BAT during thermogenesis as a marker for BAT metabolism. 18F-FDG PET has provided substantial insights into human BAT physiology, including its regulatory pathways and the effect of obesity and cardiometabolic disease on BAT function. The use of alternative PET tracers and the development of novel techniques such as magnetic resonance imaging, supraclavicular skin temperature measurements, contrast-enhanced ultrasound, near-infrared spectroscopy and microdialysis have all added complementary information to improve our understanding of human BAT. However, many questions surrounding BAT physiology remain unanswered, highlighting the need for further research and novel approaches to investigate this tissue. This review critically discusses current techniques to assess human BAT function in vivo, the insights gained from these modalities and their limitations. We also discuss other promising techniques in development that will help dissect the pathways regulating human thermogenesis and determine the therapeutic potential of BAT activation.
Introduction
The prevalence of obesity is rising worldwide, bringing with it significant morbidity and mortality (https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight). While dietary interventions are often initially successful, weight regain is typical after just a few years (Wadden et al. 1989, Knowler et al. 2009), in part as weight loss causes a compensatory reduction in energy expenditure (EE) (Leibel et al. 1995). Current pharmacotherapy for obesity, such as liraglutide or orlistat, primarily targets the reduction of energy intake with limited success (Torgerson et al. 2004, Pi-Sunyer et al. 2015). While newer agents to inhibit food intake hold much promise (Jastreboff et al. 2022), treatments that increase EE could be of substantial benefit, potentially for use in combination with appetite suppressants. This has led to recent interest in activating brown adipose tissue (BAT) which is a thermogenic organ. While white adipose tissue (WAT) is chiefly an organ of energy storage, BAT is highly vascularised and contains abundant mitochondria due to its role in energy dissipation (Zingaretti et al. 2009). Cold activates BAT through sympathetic stimulation, resulting in the release of fatty acids, which subsequently activate a specialised thermogenic protein known as uncoupling protein 1 (UCP1) (Cannon & Nedergaard 2004). UCP1 is located on the inner mitochondrial membrane and generates heat by uncoupling oxidative phosphorylation from ATP synthesis, resulting in a futile cycle of energy lost as heat (Nicholls & Locke 1984) (Fig. 1).
The importance of BAT in cardiometabolic health is well-established in murine models, where it provides protection against diet-induced obesity and improves dyslipidaemia and insulin resistance (Lowell et al. 1993, Liu et al. 2013). In human adults, substantial quantities of BAT were only identified ~20 years ago through [18F]fluoro-2-deoxyglucose (18F-FDG) combined positron emission tomography and computed tomography (PET/CT) scanning (Cohade et al. 2003). Subsequent studies have revealed the positive effects of BAT activation on cardiometabolic health in humans, supporting its potential as a therapeutic target (Iwen et al. 2017, Becher et al. 2021). However, our understanding of human BAT remains limited, in part due to the location of BAT in numerous discrete depots which adds complexity in quantifying BAT activity in vivo (Heaton 1972) (Fig. 1). Furthermore, recent evidence demonstrates key differences between human and murine BAT regulatory pathways; as such, identifying these pathways in humans is vital to determine their therapeutic potential (Ramage et al. 2016, Blondin et al. 2020). To address these challenges, several techniques have been developed to assess human BAT function. BAT activation is measured using surrogate markers such as substrate uptake by BAT, blood flow or heat generation, whereas BAT mass is quantified either by measuring the quantity of ‘active’ BAT during stimulation or by exploiting intrinsic markers such as its fat or mitochondrial content. In this review, we will focus primarily on the insights gained from these techniques, their limitations and the questions which remain unanswered, requiring novel approaches to improve our understanding of human BAT function.
Analysis of human brown adipose tissue biopsies
Early human BAT studies centred around the analysis of adipose tissue biopsies, where discrete BAT locations were identified based on its typical brown adipocyte morphology (Heaton 1972, Huttunen et al. 1981). More recent studies using BAT biopsies have identified the molecular signature of human BAT, UCP1 function and sympathetic innervation, allowing comparisons with murine BAT (Zingaretti et al. 2009, Sharp et al. 2012, Jespersen et al. 2013, Porter et al. 2016). Human BAT biopsies and brown adipocyte cultures have been used to identify regulators of BAT function such as bile acids, glucocorticoids and the β2-adrenergic receptor, revealing key species-specific differences that emphasize the importance of studying BAT in humans (Broeders et al. 2015, Ramage et al. 2016, Blondin et al. 2020). In addition, human brown adipocytes have been used to reveal the circadian rhythm of human BAT by identifying changes in UCP1 and glucose transport (Lee et al. 2016). Importantly, these studies utilising BAT biopsies have revealed key mechanistic insights that are not possible using current in vivo techniques. For example, proteomics analysis of human brown and beige adipocytes recently identified secreted proteins by these cells, revealing novel regulatory pathways and potential crosstalk with other metabolic tissues (Deshmukh et al. 2019, Whitehead et al. 2021). These studies have also identified pathways mediating the deleterious effects of ageing on the differentiation capacity of beige pre-adipocytes (Khanh et al. 2018). While in vitro cultures offer tremendous potential to explore new mechanisms, these cells are studied outside of their microenvironment usually in 2D, without interactions from other cell types such as immune cells or the extracellular matrix, which may introduce bias (Samuelson & Vidal-Puig 2020). Therefore, complementary in vivo techniques to study human BAT are of vital importance.
In vivo techniques to measure human BAT function
PET/CT
18F-FDG
18F-FDG PET/CT scanning is the most commonly used imaging modality to quantify BAT mass and activation, with bilateral 18F-FDG uptake noted in the supraclavicular, axillary, paravertebral and perirenal regions revealing the typical BAT depots present in human adults (Fig. 1) (Chen et al. 2016). 18F-FDG is used routinely in clinical practice and has a half-life of ~110 min and so can be manufactured off-site, allowing these scans to be performed in most imaging centres without an on-site cyclotron. Quantification of BAT is ensured by analysing uptake in voxels with CT measurements of radiodensity (Hounsfield units) within the accepted range for adipose tissue (Chen et al. 2016). Tissue biopsies from these BAT-positive regions revealed multilocular adipocytes with high expression of UCP1, confirming the presence of BAT (Virtanen et al. 2009). Although 18F-FDG uptake does not directly measure BAT thermogenesis, there is substantial evidence that glucose uptake correlates well with other measures of BAT thermogenesis (Yoneshiro et al. 2011, Muzik et al. 2012, Ramage et al. 2016, Koskensalo et al. 2017). Additionally, BAT volume quantified with 18F-FDG has not been substantially different to those visualised using other tracers (Admiraal et al. 2013).
Early studies analysing clinical 18F-FDG PET/CT scans undertaken at room temperature confirmed human BAT to be activated by cold and sympathetic stimulation (Au-Yong et al. 2009, Wang et al. 2011). In addition, detectable 18F-FDG uptake by BAT in adults decreased with increasing age, BMI and fasting glucose (Cypess et al. 2009, van Marken Lichtenbelt et al. 2009). More recent analysis of large datasets support the protective effects of 18F-FDG uptake by human BAT at room temperature against developing type 2 diabetes mellitus (T2DM), hypertension and cardiovascular disease (Becher et al. 2021). Importantly, these cardioprotective benefits were most evident in obese individuals, supporting the therapeutic potential of BAT activation in this group. Clinical 18F-FDG scans at room temperature demonstrated increased uptake in female subjects; however, scans undertaken during cold exposure have not revealed substantial sex-specific differences, highlighting that BAT activation occurs at a higher room temperature in females, potentially due to their lower skeletal muscle mass (Cypess et al. 2009, Chen et al. 2013a, van der Lans et al. 2013). Therefore, dedicated cooling protocols prior to PET imaging are vital to activate BAT to increase the comparability of 18F-FDG PET data across different subjects. Interestingly, in children, the prevalence of detectable BAT at room temperature is similar between sexes and is unaltered by BMI, while detectable BAT mass increased progressively during puberty (Gilsanz et al. 2012).
Three different cooling techniques are generally used to activate BAT: (1) cooling participants with a fixed ambient room temperature, this mild cooling approach aims to activate BAT with minimal muscle shivering; (2) using cooling blankets and suits individualised to 1–2°C above the symptomatic shivering threshold, this approach maximises BAT activation and dramatically increases EE but with substantial thermogenesis from muscle and other tissues; (3) immersing the participant’s arms or legs in cold water or ice, this approach is technically simpler to undertake but difficult to standardise, achieves cooling only of extremities and causes pain-induced sympathetic stimulation (Chen et al. 2016). Participants should be cooled for 1 h prior to and following 18F-FDG injection (Chen et al. 2016) to allow uptake and trapping of 18F-FDG by brown adipocytes. 18F-FDG PET scans during cold exposure have been used extensively to explore human BAT physiology and its regulatory pathways, through the use of various pharmacological agents such as mirabegron, nicotinic acid, bile acids, capsaicin and glucocorticoids (Broeders et al. 2015, Ramage et al. 2016, Blondin et al. 2017b, O’Mara et al. 2020). Nonetheless, there is substantial variation in the prevalence (20–100%) and volume of BAT (~5–350 mL) in humans even in these dedicated studies (Table 1). This is partly attributable to differences in patient demographics (e.g. age, BMI, comorbidities) but also due to variation in cooling protocols and image analysis methodologies (Table 1). Importantly, there are considerable discrepancies in BAT mass between individuals matched for these characteristics, potentially due to other environmental factors such as daily living ambient temperature and dietary differences (Williams & Kolodny 2008, Lee et al. 2014, Richard et al. 2022). In addition, it is likely that there are strong genetic drivers of BAT mass in humans that are yet to be elucidated.
BAT prevalence and volume in human adults from 18F-FDG PET/CT scans during cold exposure.
Study population | Cooling protocol | Threshold values of CT HU and 18F-FDG SUV | Regions of analysis | BAT prevalence (%) | BAT volume (mL) | References | ||
---|---|---|---|---|---|---|---|---|
Sex (M/F) | BMI (kg/m2) | Age (years) | ||||||
Lean/overweight only | ||||||||
10/0 | 23.2 | 24.3 | 16°C, 2 h | Unspecified | All depots | 100 | 130 | (van Marken Lichtenbelt et al. 2009) |
7/20 | 22.8 | 40.2 | 17°C, 2 h | Unspecified | All depots | 70 | 38 | (Orava et al. 2011) |
5/9 | 23.7 | 30 | 16°C, 2 h | −250 < HU < −50, SUV ≥2, >5 mm diameter | All depots | 36 | 22 | (Muzik et al. 2012) |
10/15 | 23.8 | 30.8 | 15.5°C, 2 h | −250 < HU <−50, SUV ≥ 2, >5 mm diameter | All depots | 36 | 25 | (Muzik et al. 2013) |
5/0 | 22 | 21 | 19°C, 24 h | −300 ≤ HU ≤−10, SUV ≥2 | All depots | 100 | 55 | (Lee et al. 2014) |
6/0 | 22 | 22.1 | 16°C, 2 h | −150 ≤ HU ≤ −30, SUV ≥2 | All depots | 100 | 50 | (Ramage et al. 2016) |
12/0 | 23.2 | 22.5 | ICP, 5 h | −300 ≤ HU ≤−10, SUV ≥1.2/LBM% |
All depots | – | 334 | (Leitner et al. 2017) |
6/0 | 22.7 | 21.3 | 16°C, 3 h | −150 ≤ HU ≤−30, SUV ≥2 | All depots | 100 | 117 | (Weir et al. 2018) |
6/18 | 22.1 | 24.4 | ICP water suits, 2 h | −190 ≤ HU ≤−10, SUV ≥1.2/LBM% | All depots | 75 | 70b | (Fraum et al. 2019) |
2/8 | 28 | 24.4 | 19°C, 3 h | SUV ≥1.5 | SCV | 60 | 21.6 | (Thuzar et al. 2019) |
Prevalence and average BAT volume in non-obese individuals | 75 | 86 | ||||||
Overweight/obese only | ||||||||
14/0 | 30.3 | 23.5 | 16°C, 2 h | Unspecified | All depots | 93 | 77 | (van Marken Lichtenbelt et al. 2009) |
11/25 | 34 | 38.1 | 17°C, 2 h | Unspecified | All depots | 31 | 16 | (Orava et al. 2013) |
12/0 | 29 | 44.8 | 19°C water suit, 3½ h | −100 ≤ HU ≤ −10, SUV ≥1 | SCV | 58 | 42 | (Chondronikola et al. 2014) |
18/0 | 29.5 | 46.9 | ICP cooling suit, 6 h | −190 ≤ HU ≤ −30, SUV ≥1.5 | All depots | 56 | 39 | (Chondronikola et al. 2016a ) |
8/0 | 34.8 | 28.8 | ICP, 5 h | −300 ≤ HU ≤ −0 SUV ≥1.2/LBM |
All depots | – | 130 | (Leitner et al. 2017) |
10/0 | 32.2 | 25.5 | 16–17°C, 2 h | Unspecified | All depots | 70 | 12 | (Bahler et al. 2016) |
Pre-gastric banding surgery | ICP using cooling blankets, 2 h | Unspecified | SCV | 20 | 7.1 | (Vijgen et al. 2012) | ||
2/8 | 41.7 | 40 | ||||||
Post-gastric banding surgery | 50 | 42.5 | ||||||
2/8 | 29.8 | 41 | ||||||
Prevalence and average BAT volume in overweight and obese individuals | 55 | 46 | ||||||
All BMI | ||||||||
6/0 | 23.7–31a | 23–42a | Water suit 18°C, 2½ h | −100 ≤ HU ≤ −10, SUV ≥1 | All depots | 100 | 168 | (Ouellet et al. 2012) |
9/7 | 26.4 | 30.9 | 16°C, 2 h | −250 ≤ HU ≤ −10, SUV ≥2 | SCV | 75 | 105 | (Schlögl et al. 2013) |
12/5 | 25.4 | 36 | 19°C, 2 h | Unspecified HU, SUV ≥1.5 | SCV | 65 | 63 | (Jang et al. 2014) |
37/65 | 22 | 25 | ICP water suits, 2 h | −190 ≤ HU ≤ −10, SUV ≥1.2/LBM% | SCV | 80 | 72 | (Sanchez-Delgado et al. 2020) |
Prevalence and average BAT volume in individuals from all weight groups | 70 | 72 | ||||||
Young vs older | ||||||||
Y, 12/0 | 25.4 | 24 | 18°C water suit, 3 h | −150 ≤ HU ≤−30, SUV ≥1.5 | SCV | – | 48c | (Blondin et al. 2015b ) |
O, 7/0 | 26.3 | 59 | 13 | |||||
Y, 14/0 | 22 | 25.5 | 16–17°C, 2 h | Unspecified | All depots | 93 | 125c | (Bahler et al. 2016) |
O, 11/0 | 23.1 | 54 | 55 | 3.4 | ||||
Prevalence and average BAT volume in young vs old individuals | 93 (Y) vs 55 (O) | 86.4 (Y) vs 8 (O) | ||||||
Males vs females | ||||||||
9/0 | 25.1 | 31.1 | 16°C, 2 h | −250 ≤HU ≤−10, SUV ≥2 | SCV | 78 | 77d | (Schlögl et al. 2013) |
0/7 | 28 | 30.7 | 71 | 142 | ||||
14/0 | 20–27a | 28.1 | 19°C, 12 h | SUV ≥2 | SCV | 29 | 50 | (Chen et al. 2013a ) |
0/10 | (Entire group) | 30 | 82 | |||||
19/0 | 27.6 | 22.1 | ICP cooling suit, 2 h | −300 ≤ HU ≤ −10 | SCV | 79 | 113 | (Martinez-Tellez et al. 2017) |
0/28 | 22.4 | 21.9 | SUV ≥1.2/LBM | 89 | 86 | |||
Prevalence and average BAT volume in males vs females | 62 (M) vs 63 (F) | 80 (M) vs 103 (F) | ||||||
Type 2 diabetes | ||||||||
6/0 | 28.6 | 60 | 18°C water suit, 3 h | −150 ≤ HU ≤ −30, SUV ≥1.5 | SCV | – | 4 | (Blondin et al. 2015b) |
Ethnicity | ||||||||
SA, 10/0 | 22.3 | 23.2 | 17°C, 2 h | −250 ≤ HU ≤ −50, SUV≥2 | SCV | 80 | 38 | (Admiraal et al. 2013) |
C, 10/0 | 22.6 | 22.4 | 80 | 16 | ||||
SA, 12/0 | 21.5 | 23.6 | ICP water blankets, 2h | Unspecified HU, SUV ≥2 | All depots | 100 | 187e | (Bakker et al. 2014) |
C, 11/0 | 22 | 24.6 | 91 | 288 | ||||
Prevalence and average BAT volume in different ethnicities | 90 (SA) vs 86 (C) | 113 (SA) vs 152 (C) |
Data are expressed as the mean of each study population unless otherwise indicated by afor range and bfor median. The cooling protocol temperatures are ambient room temperatures unless stated otherwise. Time in hours indicate the cooling duration prior to the 18F-FDG PET scan. In the regions of analysis, SCV is used to denote the combined supraclavicular, cervical and superior mediastinal regions.
cP<0.05 between age groups; dP<0.05 between sexes; eP<0.05 between ethnicity.
C, Caucasian; F, female; HU, Hounsfield units; ICP, individualised cooling protocol; LBM, lean body mass; M, male; O, older; SA, South Asian; SUV, standardised uptake value; Y, young.
While most studies have used static18F-FDG PET, dynamic PET/CT is needed to quantify the rate of 18F-FDG uptake in vivo. Glucose uptake by BAT during cold exposure is substantially greater than skeletal muscle (~80 vs 10 nmol/g tissue/min, respectively), highlighting the substantial metabolic activity of human BAT (Orava et al. 2011, Blondin et al. 2017a ). However, due to the small BAT mass in adult humans, BAT glucose uptake accounts for <1% of total body glucose uptake during cold compared with ~50% for skeletal muscle, suggesting that BAT activation alone is unlikely to substantially alter systemic glucose homeostasis (Blondin et al. 2015a ). This is further emphasised in older individuals with T2DM, a potential group in whom to target treatment, who have reduced BAT mass but increased glucose uptake in skeletal muscle, highlighting a potential compensatory response for reduced BAT activity (Blondin et al. 2015b , Hanssen et al. 2015). These data also highlight the potential interplay between skeletal muscle and BAT in cold-induced thermogenesis, novel techniques though are needed to understand this relationship.
Glucose uptake by BAT increases markedly during BAT thermogenesis and inhibition of BAT lipolysis and thermogenesis reduces BAT glucose uptake, emphasizing the close relationship between glucose uptake and BAT thermogenesis (Virtanen et al. 2009, Blondin et al. 2017a , McNeill et al. 2020). However, there are substantial limitations with 18F-FDG–PET (Table 2), such as the radiation exposure which limits repeated scanning, especially in paediatric studies and the requirement for cold exposure or pharmacological stimulation prior to injection. Importantly, glucose uptake is not a direct measure of BAT thermogenesis and lipids are the primary energy substrate (Blondin et al. 2017a , Weir et al. 2018). The specific metabolic fate of glucose by BAT is not fully understood, although much is released as lactate rather than fully oxidised and cannot be answered by 18F-FDG PET (Weir et al. 2018). Glucose uptake may also be influenced by other factors without altering BAT thermogenesis, with diet noted to have profound effects, which must be considered, particularly in studies comparing different groups (Richard et al. 2022). Insulin resistance may also reduce glucose uptake and confound measurements of BAT thermogenesis (Blondin et al. 2015b ); however, glucocorticoid treatment substantially reduced whole body glucose uptake but increased BAT glucose uptake by ~80%, suggesting that the two are not inextricably linked (Ramage et al. 2016). To overcome some of these limitations, other PET radiotracers have been used to measure human BAT activity.
Characteristics, advantages, disadvantages and the key findings from various PET radiotracers used in BAT imaging.
PET tracer | Mechanism | Advantages | Disadvantages | Key finding(s) | References |
---|---|---|---|---|---|
18F-FDG | Quantifies BAT glucose uptake |
|
|
|
(Becher et al. 2021) |
|
|
|
(Blondin et al. 2020, Ramage et al. 2016) | ||
|
|
|
(Gilsanz et al. 2012) | ||
|
|
|
(Hanssen et al. 2015, Vijgen et al. 2012) | ||
|
|
|
(Blondin et al. 2015a ) | ||
|
|||||
|
|||||
|
|||||
|
|||||
18F-FTHA | Quantifies BAT NEFA uptake |
|
|
|
(Ouellet et al. 2012) |
|
|
|
(Saari et al. 2020) | ||
|
|
(Din et al. 2018) | |||
|
|||||
|
|||||
|
|||||
11C-Acetate | Quantifies overall BAT metabolism |
|
|
|
(Blondin et al. 2015b ; Richard et al. 2022) |
|
|
|
(Blondin et al. 2017a
) |
||
|
|
(Blondin et al. 2017b ) | |||
|
|||||
15O-CO, 15O-H2O and 15O-O2 | Quantifies BAT blood flow and oxygen consumption |
|
|
|
(Muzik et al. 2013) |
|
|
(Din et al. 2018) | |||
|
|||||
|
|||||
6-[18F]-Fluorodopamine and 11C-MRB | Marker of BAT sympathetic innervation |
|
|
|
(Hwang et al. 2015) |
|
|||||
|
|||||
|
|||||
[11C]PBR28 | Marker of BAT mitochondrial content |
|
|
|
(Ran et al. 2018) |
|
|||||
|
|||||
18F-FBnTP | Detects changes in mitochondrial membrane potential and therefore detects BAT UCP1 activation |
|
|
|
(Madar et al. 2011) |
|
|||||
|
|||||
|
|||||
[11C]TMSX | Binds to adenosine A2A receptors on BAT |
|
|
|
(Lahesmaa et al. 2019) |
|
|||||
18F-FMPEP-d2 | Binds to cannabinoid receptor 1 on BAT |
|
|
|
(Lahesmaa et al. 2018) |
|
11C-MRB, (S,S)-11C-O-methylreboxetine; [11C]PBR28, [11C]N-acetyl-N-(2-methoxybenzyl)-2-phenoxy-5-pyridinamine; [11C]TMSX, [7-methyl-11C]-(E)-8-(3,4,5-trimethoxystyryl)-1,3,7-trimethylxanthine; 18F-FBnTP, 18F-fluorobenzyltriphenylphosphonium; 18F-FMPEP-d2, 3R,5R)-5-(3-(18F-fluoromethoxy)phenyl)-3-(((R)-1-phenylethyl)amino)-1-(4-(trifluoromethyl)-phenyl)pyrrolidin-2-one; 18FTHA, 18F-fluoro-thiaheptadecanoic acid; NEFA, non-esterified fatty acids; T2DM, type 2 diabetes mellitus.
18F-FTHA
18F-fluoro-thiaheptadecanoic acid (18F-FTHA), a long-chain fatty acid analogue, has been used to measure non-esterified fatty acid (NEFA) uptake by BAT during warm or cold exposure and during diet-induced thermogenesis (Ouellet et al. 2012, Blondin et al. 2017c , Saari et al. 2020). Similar to 18F-FDG, BAT NEFA uptake correlates positively with BAT thermogenesis, highlighting NEFAs as a substrate for BAT function (Din et al. 2016, Saari et al. 2020). The cold-induced rise in systemic NEFAs is greater in individuals with substantial BAT mass and activity, highlighting the interplay between BAT thermogenesis and WAT lipolysis (Blondin et al. 2015a, Chondronikola et al. 2016b). Similar to glucose, NEFA uptake by BAT only accounts for a small proportion of circulating and dietary fatty acid uptake (<1%) (Ouellet et al. 2012, Blondin et al. 2017c). Obese subjects have reduced BAT 18F-FTHA uptake during both warm and cold exposure, providing further evidence of decreased BAT function in obesity (Saari et al. 2020). However, BAT 18F-FTHA uptake (but not 18F-FDG) was preserved in older individuals with and without T2DM vs younger controls, suggesting 18F-FTHA may be a better radiotracer in these groups (Blondin et al. 2015b). Nonetheless, the volume of BAT in these individuals was small (median 4 mL), potentially consistent with preserved metabolic function of the minimal remaining BAT mass. These data also suggest that insulin resistance does not cause a compensatory increase in FA uptake by BAT to maintain thermogenesis.
This technique has limitations, for example BAT 18F-FTHA uptake rates during cold are lower compared with 18F-FDG (~15 vs 80 nmol/g tissue/min) so higher radiation doses are often required (Orava et al. 2011, Orava et al. 2013, Din et al. 2016). Furthermore, 18F-FTHA PET may not as accurately distinguish human BAT from WAT depots, due to considerable overlap in NEFA uptake, which could lead to overestimation of BAT volume when using 18F-FTHA (Carpentier et al. 2018). 18F-FTHA-PET cannot clarify the fate of NEFA uptake by BAT so it remains unclear whether these are immediately oxidised or converted to triglycerides for subsequent lipolysis. Finally, this technique does not quantify lipolysis of intracellular triglyceride stores, which is the main substrate for BAT thermogenesis.
11C-Acetate
In BAT, acetate is metabolised into acetyl-CoA and then fed into the Krebs cycle for aerobic respiration (Bender 2003). Therefore, the 11C-acetate tracer (with a half-life of ~20 min) provides a measure of BAT oxidative metabolism unlike the tracers mentioned previously. Cold exposure increases BAT 11C-acetate uptake and the rate of 11C decay from peak signal during cold exposure is much greater in BAT compared to skeletal muscles (longus colli, deltoid and trapezius), in keeping with high rates of oxidative metabolism by BAT during cold-induced thermogenesis (Ouellet et al. 2012). Although there are no guidelines to standardise the imaging methodology and analyses for 11C-acetate PET, the data derived from this technique generally complement the 18F-FDG and/or 18F-FTHA uptake data during cold exposure in healthy volunteers, for example, when investigating the effects of chronic cold acclimation, nicotinic acid and the β3-agonist (mirabegron) on BAT activity (Ouellet et al. 2012, Blondin et al. 2014, 2017a, 2020). However, BAT 18F-FDG uptake does not correlate with BAT oxidative metabolism (Blondin et al. 2015a) and reductions in BAT 18F-FDG uptake have been observed in T2DM and during dietary manipulations that are not seen when using 11C-acetate (Blondin et al. 2015b , Richard et al. 2022). While further research is needed to determine whether BAT mass and activity is dysregulated in T2DM, these findings highlight the need to be aware of such confounders and the importance of using more than one technique to quantify BAT activity. While 11C-acetate has been key to determining many important observations in human BAT physiology, there are also limitations with this technique (Table 2). For example, the short tracer half-life requires higher radiation doses, an on-site cyclotron and the use of dynamic PET, so is not possible for many centres, along with the more complicated analysis of these data. In addition, the 11C-acetate tracer does not discriminate BAT as effectively as 18F-FDG so requires the administration of both tracers which adds further radiation exposure, although the use of two tracers provides key comparative data.
15O
15Oxygen radiotracers (15O) in the form of 15O-CO, 15O-O2 and 15O-H2O have been used to measure BAT metabolic activity, through the quantification of BAT blood flow and oxygen extraction fraction (Muzik et al. 2012, Muzik et al. 2013, Din et al. 2016, Din et al. 2018). However, these tracers have an extremely short half-life of 2 min which poses logistical challenges with scanning and in particular necessitating an imaging facility with on-site cyclotron (Table 2). 15O-O2 PET scans, using BAT volumes obtained from 18F-FDG, quantified oxygen consumption by BAT during mild cold exposure to be no more than 25 kcal/day so accounts for only a small proportion of cold-induced thermogenesis (Muzik et al. 2013, Din et al. 2016). While cold acclimation can increase maximal BAT metabolism by ~200% (Blondin et al. 2017b ), these data suggest that interventions that selectively activate existing BAT are unlikely to increase EE substantially to achieve clinically meaningful weight loss, although such agents may have important benefits on other metabolic parameters. Therefore, pharmacotherapy aiming to increase EE to promote weight loss must also target other key metabolic tissues. 15O PET tracers have been used to identify the role of BAT in diet-induced thermogenesis in humans (Din et al. 2018), an effect potentially mediated by the hormone secretin (Laurila et al. 2021).
Other PET radiotracers
Additional tracers have been used to study human BAT. For example, radioligands for the norepinephrine transporter such as 6-[18F]-fluorodopamine and (S,S)-11C-O-methylreboxetine (11C-MRB) can localise BAT without the need for prior cold exposure, exploiting the rich sympathetic innervation in this tissue (Hadi et al. 2007, Hwang et al. 2015). Similarly [11C]N-acetyl-N-(2-methoxybenzyl)-2-phenoxy-5-pyridinamine ([11C]PBR28), a ligand for the translocator protein which is highly expressed on the outer mitochondrial membrane of BAT and other tissues, can detect BAT in humans (Ran et al. 2018). PET tracers can also provide new insights by demonstrating the presence of specific receptors regulating BAT function, an approach not covered in existing reviews. For example, (7-methyl-11C)-(E)-8-(3,4,5-trimethoxystyryl)-1,3,7-trimethylxanthine ((11C)TMSX) binds specifically to adenosine A2A receptors (A2AR) and has been used to investigate the stimulatory effects of adenosine on human BAT function (Lahesmaa et al. 2019). Similarly, (3R,5R)-5-(3-(18F-fluoromethoxy)phenyl)-3-(((R)-1-phenylethyl)amino)-1-(4-(trifluoromethyl)-phenyl)pyrrolidin-2-one (18F-FMPEP-d2) is an inverse agonist of the cannabinoid receptor 1 (CB1R) which demonstrated substantial uptake by murine BAT (Eriksson et al. 2015). Subsequent 18F-FMPEP-d2 administration to humans identified increased CB1R density during cold exposure and CB1R antagonism-enhanced BAT activity, demonstrating how PET tracers can be used to identify novel pathways regulating BAT function (Lahesmaa et al. 2018). In due course, additional tracers will improve our understanding of human BAT physiology. For example, the 18F-fluorobenzyl-triphenylphosphonium cation (18F-FBnTP) accumulates in mitochondria due to the higher mitochondrial membrane potential (Madar et al. 2015). In mice, 18FBnTP accumulates in BAT at room temperature and demonstrates rapid washout during cold exposure when UCP1 activation abolishes the proton gradient, but this tracer is yet to be tested in humans (Madar et al. 2015).
In summary, PET imaging is a non-invasive and very sensitive method to detect and assess all BAT depots. The use of various PET radiotracers has provided most of the key insights on human BAT physiology in vivo over the past 20 years, but as with any technique, PET has its limitations (Table 2). For example, PET cannot be used to quantify the uptake and release of multiple metabolites simultaneously, and most of the commonly used radiotracers (e.g. 18F-FDG, 18F-FTHA and 15O) are not capable of detecting BAT without preceding cold exposure or adrenergic stimulation as they rely on activation to stimulate tracer uptake. The narrow field-of-view on standard PET/CT scanners has also prevented comparison of all BAT depots simultaneously when using dynamic PET, so whether there are functional differences between certain depots is unclear. Additionally, some of these radiotracers are not widely available, costly and challenging to work with due to their short half-lives, further limiting its use in human BAT research. This has led to the development of alternative techniques.
Magnetic resonance imaging
MRI is an alternative BAT imaging modality with great potential since it is non-invasive and without radiation exposure. The higher water and iron-rich mitochondrial content of BAT than WAT translates to a lower fat fraction (FF) and transverse relaxation time (T2*) (Chen et al. 2013b , Hu et al. 2013). FF is calculated by quantifying the ratio of proton signals from fat to the total signals from fat and water. T2* is a time constant characterising the rate at which excited protons return to equilibrium. BAT, a well-vascularised organ rich in mitochondria, has numerous iron ions which disrupt magnetic field homogeneity, causing the desynchronisation of water protons, leading to faster dephasing of transverse magnetisation and thus a shorter T2* (Wood & Ghugre 2008, Ulla et al. 2013). MRI exploits these endogenous BAT signals to distinguish BAT from WAT at thermoneutrality, potentially negating the need for BAT activation through cold exposure prior to scanning (Hu et al. 2013) (Fig. 2A). Composite values of FF and T2* on MRI scans have been used to identify human BAT in vivo, confirmed in biopsies from these regions which demonstrate the typical histological features of BAT (Lidell et al. 2013, Reddy et al. 2014). The absence of radiation exposure from MRI has allowed BAT to be assessed in paediatric studies. These studies have revealed that BAT FF is associated with adiposity in children as in adults and demonstrated associations with wider metabolic health such as skeletal muscle mass, osteocalcin levels and even reduced hepatic lipid accumulation in a 1.5-year prospective study (Andersson et al. 2019, Tint et al. 2021).
PET/MR scanning has been shown to be a reliable and reproducible technique to detect human BAT (Fig. 2B) when compared to PET/CT (Gariani et al. 2015, Fraum et al. 2019). This technique has the advantage of reduced radiation exposure and allows simultaneous quantification of BAT FF, but PET/MR is not readily available in most imaging centres. Furthermore, unlike PET/CT scans, there is no standardised guidance for quantifying BAT mass using FF thresholds, which may limit comparability between studies (Lundström et al. 2015, Gifford et al. 2016, Holstila et al. 2017, Stahl et al. 2017). Nonetheless, this imaging technique has already been used to identify novel pathways regulating human BAT. For example, we recently determined that the serotonin transporter was highly expressed in human BAT, and that sertraline (an inhibitor of this transporter) reduced 18F-FDG uptake by BAT during cold exposure and increased BAT FF, revealing that the serotonin transporter protects BAT from serotonin-mediated suppression of thermogenesis (Suchacki et al. 2023). PET/MR imaging has also been used to assess differences in BAT activity between winter and non-winter swimmers (Søberg et al. 2021). Interestingly, there were no differences in 18F-FDG uptake by BAT during cold exposure between both groups and the study highlighted the importance of considering other factors that affect cold perception (Søberg et al. 2021). Although the use of PET/MR in human BAT imaging appears promising, the data are less clear regarding the use of MRI alone to localise human adult BAT. For example, MRI FF and T2* values in BAT do not always correlate with 18F-FDG uptake on PET (Franz et al. 2015, Holstila et al. 2017, McCallister et al. 2017, Deng et al. 2018) and there is substantial overlap in FF between human BAT (typically 50–90%) and WAT (80–95%) (Franz et al. 2015, Gifford et al. 2016, Holstila et al. 2017, Fraum et al. 2019). This is further compounded by the co-localisation of brown and white adipocytes within ‘BAT depots’ (Chen et al. 2013b ), as due to the relatively low resolution of this technique, the FF of each voxel will likely represent a combination of different cell types. The heterogeneity of human BAT lipid composition as well as its varied response during cold activation also results in voxels with widely varying FF values within the same depot (McCallister et al. 2017, Coolbaugh et al. 2019). These issues, as summarised in Table 3, contribute to difficulties in standardising an image analysis methodology highlighting the need for further work to validate the use of standalone MRI in BAT imaging.
Characteristics, advantages, disadvantages and key findings from various MR-based applications used in BAT imaging.
MR-based applications | Mechanism | Advantages | Disadvantages | Key finding(s) | References |
---|---|---|---|---|---|
MRI | Marker of BAT lipid content (FF) and mitochondrial content (T2*) |
|
|
|
(Deng et al. 2018) |
|
|
|
(Oreskovich et al. 2019) | ||
|
|
|
(Franz et al. 2015) | ||
|
|
||||
|
|||||
fMRI | BOLD signal changes as a marker of BAT oxygen consumption |
|
|
|
(Chen et al. 2013b ) |
|
|
||||
|
|
||||
|
|||||
Contrast-enhanced MRI using gadolinium-based contrasts, MION and 59Fe-SPION | Uses BAT-specific probes to measure BAT perfusion |
|
|
|
(Bartelt et al. 2011) |
|
|
||||
|
|||||
1H-MRS | Measures FF, relative changes in BAT temperature and categorises intracellular fatty acid content |
|
|
|
(Koskensalo et al. 2017) |
|
|
|
(Ouwerkerk et al. 2021) | ||
|
|
||||
|
|
||||
Hyperpolarised 13C MRS | Quantifies BAT oxygen consumption |
|
|
|
(Lau et al. 2014) |
|
|
||||
|
|||||
|
|||||
|
|||||
|
|||||
Hyperpolarised 129Xe MRS | Quantifies BAT blood perfusion and relative changes in BAT temperature |
|
|
|
(Branca et al. 2014) |
|
|
|
|||
|
|||||
|
BOLD, blood oxygenation level-dependent; fMRI, functional magnetic resonance imaging; MION, monocrystalline iron oxide nanoparticle; MRS, magnetic resonance spectroscopy; SPION, superparamagnetic iron oxide nanoparticle; TRL, triglyceride-rich lipoprotein.
Despite these limitations, serial MRIs during cold exposure have provided insights into BAT lipolysis. BAT FF decreases rapidly during cold exposure prior to plateauing after ~30 min, in keeping with initial hydrolysis of local triglyceride stores for fatty acid oxidation alongside ongoing replenishment of triglycerides (Oreskovich et al. 2019). However, MRI cannot ascertain the underlying mechanisms for intracellular triglyceride replenishment, including glycerol recycling by glycerol kinase (Chakrabarty et al. 1983, Weir et al. 2018), direct uptake of circulating NEFAs and/or triglyceride-rich lipoproteins (Chondronikola et al. 2016b , Ouellet et al. 2012), or through de novo lipogenesis from glucose (Held et al. 2018, Jung et al. 2021). Further studies and techniques are required to determine the contribution of these processes to triglyceride replenishment in human BAT. MRI can also be adapted in various applications to assess BAT metabolic function. For example, proton magnetic resonance spectroscopy (1H-MRS) can measure the thermogenic capacity of BAT by detecting changes in BAT temperature during cold activation since the resonance frequency of protons in water molecules are dependent on temperature in a linear fashion (Koskensalo et al. 2017). The rise in BAT temperature following cold exposure detected with 1H-MRS correlated positively with BAT 18F-FDG uptake, not only indicating that 1H-MRS is a reliable technique to measure BAT thermogenesis but also supporting the accuracy of 18F-FDG uptake as a surrogate marker of BAT metabolic activity (Koskensalo et al. 2017). MRS has also identified reduced unsaturated and polyunsaturated fatty acid content in human BAT vs WAT (Ouwerkerk et al. 2021). This technique could be used in future research to better understand the specific types of intracellular fatty acids released during lipolysis and synthesised from de novo lipogenesis during BAT thermogenesis.
Functional MRI (fMRI) detects changes in blood oxygenation, as the release of oxygen from haemoglobin alters the surrounding magnetic field resulting in blood oxygenation level-dependent (BOLD) signal changes (Ogawa et al. 1990). These signal changes are evident during BAT activation by cold exposure, supporting BOLD as a marker of BAT metabolic activity (Chen et al. 2013b , van Rooijen et al. 2013). This technique is semi-quantitative unlike 15O-PET scanning, but the sequences are available in most clinical MR scanners and with appropriate optimisation, BOLD signals can complement existing FF and T2* data to improve the utility of MRI to measure BAT activity (Table 3).
Contrast-enhanced MRI is another promising imaging technique which has not been previously covered in other imaging reviews. To date, this has been used in rodents to quantify BAT perfusion, by using agents such as gadolinium-based contrasts, monocrystalline iron oxide nanoparticles (MION) and lipoprotein-coated 59Fe-labelled superparamagnetic iron oxide nanoparticles (SPION) (Sbarbati et al. 2006, Bartelt et al. 2011, Chen et al. 2012, Jung et al. 2016, Yaligar et al. 2020). However, this technique holds significant promise in future human BAT studies as it is capable of assessing human BAT perfusion as an indirect marker of BAT activation without radiation exposure, as demonstrated in murine models (Yaligar et al. 2020). While these techniques only provide semi-quantitative measurements, the use of [59Fe]-SPIONs coated in triglyceride-rich lipoprotein (TRL) provided key data in murine BAT, demonstrating an increase in TRL uptake after just 10 min of cold exposure (Bartelt et al. 2011). However, the use of some contrast agents such as SPION and MION are limited in humans due to concerns of potential hepatic iron deposition and intracellular cytotoxic damage (Table 3). Hyperpolarised 13C MRS has also been used to detect uptake and utilisation of 13C-pyruvate by murine BAT and measuring formation of downstream products such as 13C-bicarbonate and 13C-lactate (Lau et al. 2014). This technique offers the exciting possibility of real-time in vivo metabolic flux analysis in BAT, which could be applied to other metabolic substrates and intermediates. However, the low resolution of this technique is a barrier to translation, as is the deeper location of human BAT which limits sensitivity, necessitating higher concentrations of 13C-labelled compounds to improve detection within tissues that would add considerable expense (Table 3). Finally, hyperpolarised 129Xe MRS has been used to quantify murine BAT perfusion and thermogenesis by exploiting the lipophilic property of xenon as well as the linear relationship between temperature and xenon chemical shift (Branca et al. 2014).
To summarise, the unique properties of MRI, in particular, the relatively lower cost and absence of ionising radiation compared with PET, make this an attractive imaging modality for the quantification of BAT mass that could be undertaken in large populations without cooling. However, small changes in patient position at different visits or motion artefacts during scanning can negatively affect the reproducibility of this technique. Although measurements such as FF, T2* and BOLD signals can be obtained using sequences available on clinical MR scanners, others such as hyperpolarised 13C MRS or contrast-enhanced MRI are more costly and technically challenging to perform, thus less widely available. Furthermore, the prolonged duration of some MR scanning limits the ability to undertake measurements in real time. Nonetheless, there are several novel MR-based techniques discussed above, such as hyperpolarised 13C and 1H-MRS, which have the potential to further dissect BAT thermogenesis and metabolic flux.
Supraclavicular skin temperature
Supraclavicular skin temperature (T SCV) measurement is a non-invasive, relatively inexpensive and simple method to assess human BAT, which is done using either infrared thermography or skin temperature probes (Jang et al. 2014, Ramage et al. 2016, Blondin et al. 2017b ). The T SCV (which overlies substantial BAT depots) is often compared with the skin temperature overlying a region without any underlying BAT depots such as the lower sternum (Fig. 2C) (Lee et al. 2011). These measurements positively correlate with other measurements of BAT activity such as 18F-FDG uptake, BAT volume and cold-induced thermogenesis (van der Lans et al. 2016, Law et al. 2018, Nirengi et al. 2019). T SCV increases within 5-10 min of cold stimulation, suggesting that these measurements can detect rapid changes in BAT activation (Robinson et al. 2014, Haq et al. 2017, Law et al. 2018), and this technique has been used to determine the circadian rhythm of BAT and the effect of pharmacological manipulations (Lee et al. 2016, Ramage et al. 2016).
However, there are several important caveats to consider, particularly as there is no consensus on the optimal methodology. For example, some studies compare TSCV to a reference region while others use TSCV during cold exposure or the change in TSCV during cold activation (van der Lans et al. 2016, Lee et al. 2011, Law et al. 2018, Nirengi et al. 2019). In addition, even the supraclavicular regions of interest are not standardised which leaves the technique open to bias, with the potential to choose parameters that obtain findings consistent with anticipated results (Symonds et al. 2012, Ang et al. 2017, Law et al. 2018). T SCV is not a direct measure of BAT temperature and can be confounded by other factors including the blood flow and vascular tone of superficial vessels, heat production from other adjacent tissues and differences in insulation (Lee et al. 2011, Jang et al. 2014, Nirengi et al. 2019). For example, there is a negative correlation between TSCV and adiposity, potentially limiting the utility of this technique when comparing lean and obese subjects (Gatidis et al. 2016, Sarasniemi et al. 2018). Importantly, measuring the differences in temperatures between locations (supraclavicular vs mediastinum) and conditions (cold vs thermoneutral) can reduce the confounding effect of adiposity on TSCV measurements (Chondronikola et al. 2016a, Nirengi et al. 2019). Finally, the various cooling protocols have distinct effects on skin temperature; for example, room cooling or liquid suits reduce supraclavicular and mediastinal temperatures unlike localised limb cooling. Therefore, a standardised approach needs to be encouraged as has been recommended for 18F-FDG PET/CT (Chen et al. 2016). To conclude, supraclavicular skin temperature measurements provide complementary information to approaches such as 18F-FDG PET but must be undertaken carefully, with full understanding of these limitations.
Contrast-enhanced ultrasound
Contrast-enhanced ultrasound (CEUS) is a non-invasive radiation-free technique to assess BAT perfusion using intravenous injection of microbubbles to increase echogenicity (Clerte et al. 2013). CEUS studies revealed a positive association between BAT perfusion and 18F-FDG uptake in BAT-positive individuals (Flynn et al. 2015). However, CEUS requires cold exposure or pharmacological BAT activation to detect changes in blood flow to localise BAT, while the limited field of view prevents detection of deeper BAT depots. Furthermore, the microbubbles have a relatively short half-life and are prone to bursting at low ultrasound frequencies, necessitating a constant contrast infusion throughout imaging. Lastly, this technique is prone to inter-operator variability, which reduces the reproducibility of this modality (Clerte et al. 2013).
Near-infrared imaging
Near-infrared spectroscopy (NIRS) measures oxygen consumption by detecting the differential spectral absorption of oxyhaemoglobin and deoxyhaemoglobin in the tissue of interest (Edwards et al. 1993). Since supraclavicular BAT is relatively superficial, oxygen consumption of human BAT can be measured. This measurement positively correlated with both 18F-FDG uptake by BAT and oxygen consumption data from 15O-PET scanning, validating NIRS as a measure of BAT metabolic activity in humans (Muzik et al. 2013, Nirengi et al. 2015). However, this technique visualises superficial tissues only so cannot visualise deeper BAT depots or quantify whole-body BAT mass. Furthermore, the greater adipose tissue depth in obese individuals may impact on the utility of NIRS in this group (Hartwig et al. 2017).
Near-infrared fluorescence imaging has also been used in mice to localise BAT. This technique uses fluorescent imaging probes that accumulate in BAT (Azhdarinia et al. 2013, Zhang et al. 2015). For example, PEP3 is a peptide that binds to receptors on the endothelium of BAT and beige adipose tissue, which when conjugated with a fluorophore is able to detect BAT (Azhdarinia et al. 2013). In addition, CRANAD-29 is a curcumin analogue lipophilic probe with a julolidine ring that reduces passive diffusion across cells (Zhang et al. 2015). CRANAD-29 is readily taken up by BAT due to the rich vasculature and was able to quantify BAT mass and detect WAT browning following adrenergic stimulation (Zhang et al. 2015). However, it remains unclear if this technique can be translated into humans due to the deeper location and heterogeneity of human BAT depots.
Microdialysis
Microdialysis involves the insertion of a semi-permeable catheter into the tissue of interest. Isotonic perfusion fluid is infused continuously and dialysate collected to quantify the concentration of metabolites in the interstitial fluid (Henriksson 1999). Microdialysis can measure compounds in a wide variety of tissues but we recently adapted this for use in human BAT (Weir et al. 2018) (Fig. 2D). Microdialysis is the only technique to date to quantify uptake and release of multiple compounds simultaneously by BAT, in combination with arterial sampling and real-time tissue blood flow measurements using 133Xe. Using this technique, we quantified glycerol release by BAT during cold exposure, consistent with substantial lipolysis of local triglyceride stores. We also demonstrated considerable release of lactate from BAT during both thermoneutral and cold conditions, revealing that most glucose taken up by BAT is not fully oxidised during thermogenesis. This technique also highlighted the importance of other substrates such as glutamate in BAT thermogenesis, as glutamate uptake by BAT increased during cold exposure (Weir et al. 2018). While this technique has provided new insights not possible with current imaging modalities, there are certain limitations. In addition to its invasiveness, the recovery of these metabolites takes time, requiring a slow infusion rate of perfusate which limits data acquisition during very acute changes in BAT activation. Furthermore, there is substantial radiation exposure from radiological-guided insertion of these catheters and the preceding 18F-FDG PET imaging for localisation. Finally, samples are collected from only one BAT depot and so relies on the assumption that BAT activity is similar between depots which may not be the case (Chen et al. 2013b).
Future perspectives
The techniques discussed above have provided the tools to assess human BAT function, for example, through the quantification of BAT substrate uptake (18F-FDG and 18F-FTHA PET, microdialysis), blood perfusion (15O-H2O PET, CEUS), thermogenesis (thermal imaging, 1H-MRS), oxidative metabolism (11C-acetate PET) and oxygen consumption (15O-O2 PET, fMRI BOLD, NIRS) (Fig. 3). Nonetheless, many key questions regarding human BAT physiology remain unanswered. For example, while we have quantified many of the substrates taken up by BAT, their fate following uptake and their contribution to human BAT thermogenesis is not fully understood. It is also unclear how BAT replenishes its intracellular triglyceride stores during and following cold exposure. Full understanding of these key physiological processes may identify new pathways and therapeutic targets to activate human BAT. Novel in vivo techniques in development, such as 13C hyperpolarised MRS, if successfully translated from murine to human studies, could help to clarify the role and importance of these substrates.
The genetics of BAT is another area of uncertainty. As depicted in Table 1, the volume and prevalence of BAT vary widely even in similar groups, suggesting a strong genetic component that determines an individual’s capacity to form BAT. Unfortunately, research into this field is significantly limited by the paucity of techniques that can quantify BAT mass without activation. It is possible that non-invasive techniques, such as MRI, can be developed to answer these questions in large population studies, as current techniques such as cold-activated PET are not suited to genome-wide association studies. These techniques will also be invaluable to understand the maximal capacity of human BAT development and the potential for WAT browning. While there have been studies looking at the effects of short-term stimulation of BAT depot expansion (Blondin et al. 2017b ), it remains unclear if BAT mass and metabolic activity can be expanded further over a longer duration or through the utilisation of UCP1-independent mechanisms in other adipose tissue depots (Ikeda et al. 2017).
Interventions to activate BAT such as cold stimulation and mirabegron also stimulate thermogenesis in other metabolic organs such as skeletal muscle and the cardiovascular system (Blondin et al. 2015a , Blondin et al. 2020). While these interventions increase EE and improve metabolic parameters, the specific role of BAT towards these cardiometabolic effects remains unclear. At present, there is no treatment to activate BAT selectively so other techniques may need to be employed. For example, microdialysis could be adapted to specifically activate BAT through localised drug delivery to assess its role without off-target organ stimulation. Additionally, new techniques are also required to determine the interplay between BAT and other metabolic organs during cold-induced thermogenesis (Deshmukh et al. 2019).
Finally, various PET tracers have provided most of the key insights into human BAT physiology over the past 20 years but, as discussed above, each have their limitations. Translation of current tracers in development such as 18FBnTP to humans may offer new insights on BAT physiology. However, the development of novel PET tracers will be key to further dissect thermogenesis by human BAT and other metabolic tissues. The development of total-body PET scanners will also allow analysis of all BAT depots simultaneously in addition to crosstalk with other metabolic tissues, while the lower radiation doses required for such scanners will allow repeated measurements to assist with longer term studies and may allow greater investigation in understudied populations such as children (Badawi et al. 2019).
Conclusion
Over the past decade, the renewed interest in activating human BAT as a treatment for obesity and associated cardiometabolic disease has led to the development of multiple techniques to assess human BAT function in vivo. These various modalities have been used to dissect human BAT physiology and begun to unravel its regulatory pathways. Despite the rapid progression, we have limited understanding of human BAT and many questions surrounding human BAT physiology remain unanswered. Further research using these existing techniques and novel modalities in development will help us fully understand the pathways regulating human BAT function and realise its therapeutic potential.
Declarations of interest
The authors have nothing to disclose.
Funding
RHS is supported by grants from the Medical Research Council (MR/S035761/1 and MR/W01937X/1) and The Chief Scientist Office (SCAF/17/02).
References
Admiraal WM, Verberne HJ, Karamat FA, Soeters MR, Hoekstra JBL & & Holleman F 2013 Cold-induced activity of brown adipose tissue in young lean men of South-Asian and European origin. Diabetologia 56 2231–2237. (https://doi.org/10.1007/s00125-013-2938-5)
Andersson J, Roswall J, Kjellberg E, Ahlström H, Dahlgren J & & Kullberg J 2019 MRI estimates of brown adipose tissue in children - Associations to adiposity, osteocalcin, and thigh muscle volume. Magnetic Resonance Imaging 58 135–142. (https://doi.org/10.1016/j.mri.2019.02.001)
Ang QY, Goh HJ, Cao Y, Li Y, Chan SP, Swain JL, Henry CJ & & Leow MK 2017 A new method of infrared thermography for quantification of brown adipose tissue activation in healthy adults (TACTICAL): a randomized trial. Journal of Physiological Sciences 67 395–406. (https://doi.org/10.1007/s12576-016-0472-1)
Au-Yong ITH, Thorn N, Ganatra R, Perkins AC & & Symonds ME 2009 Brown adipose tissue and seasonal variation in humans. Diabetes 58 2583–2587. (https://doi.org/10.2337/db09-0833)
Azhdarinia A, Daquinag AC, Tseng C, Ghosh SC, Ghosh P, Amaya-Manzanares F, Sevick-Muraca E & & Kolonin MG 2013 A peptide probe for targeted brown adipose tissue imaging. Nature Communications 4 2472. (https://doi.org/10.1038/ncomms3472)
Badawi RD, Shi H, Hu P, Chen S, Xu T, Price PM, Ding Y, Spencer BA, Nardo L, Liu W, et al.2019 First human imaging studies with the Explorer total-body PET scanner. Journal of Nuclear Medicine 60 299–303. (https://doi.org/10.2967/jnumed.119.226498)
Bahler L, Verberne HJ, Admiraal WM, Stok WJ, Soeters MR, Hoekstra JB & & Holleman F 2016 Differences in sympathetic nervous stimulation of brown adipose tissue between the young and old, and the lean and obese. Journal of Nuclear Medicine 57 372–377. (https://doi.org/10.2967/jnumed.115.165829)
Bakker LE, Boon MR, van der Linden RA, Arias-Bouda LP, van Klinken JB, Smit F, Verberne HJ, Jukema JW, Tamsma JT, Havekes LM, et al.2014 Brown adipose tissue volume in healthy lean South Asian adults compared with white Caucasians: a prospective, case-controlled observational study. Lancet. Diabetes and Endocrinology 2 210–217. (https://doi.org/10.1016/S2213-8587(1370156-6)
Bartelt A, Bruns OT, Reimer R, Hohenberg H, Ittrich H, Peldschus K, Kaul MG, Tromsdorf UI, Weller H, Waurisch C, et al.2011 Brown adipose tissue activity controls triglyceride clearance. Nature Medicine 17 200–205. (https://doi.org/10.1038/nm.2297)
Becher T, Palanisamy S, Kramer DJ, Eljalby M, Marx SJ, Wibmer AG, Butler SD, Jiang CS, Vaughan R, Schöder H, et al.2021 Brown adipose tissue is associated with cardiometabolic health. Nature Medicine 27 58–65. (https://doi.org/10.1038/s41591-020-1126-7)
Bender DA 2003 Tricarboxylic acid cycle. In Encyclopedia of Food Sciences and Nutrition 2 nd ed. pp. 5851–5856. Ed. Caballero B. Oxford, UK: Academic Press.
Blondin DP, Labbé SM, Tingelstad HC, Noll C, Kunach M, Phoenix S, Guérin B, Turcotte EE, Carpentier AC, Richard D, et al.2014 Increased brown adipose tissue oxidative capacity in cold-acclimated humans. Journal of Clinical Endocrinology and Metabolism 99 E438–E446. (https://doi.org/10.1210/jc.2013-3901)
Blondin DP, Labbé SM, Phoenix S, Guérin B, Turcotte ÉE, Richard D, Carpentier AC & & Haman F 2015a Contributions of white and brown adipose tissues and skeletal muscles to acute cold-induced metabolic responses in healthy men. Journal of Physiology 593 701–714. (https://doi.org/10.1113/jphysiol.2014.283598)
Blondin DP, Labbé SM, Noll C, Kunach M, Phoenix S, Guérin B, Turcotte ÉE, Haman F, Richard D & & Carpentier AC 2015b Selective impairment of glucose but not fatty acid or oxidative metabolism in brown adipose tissue of subjects with Type 2 diabetes. Diabetes 64 2388–2397. (https://doi.org/10.2337/db14-1651)
Blondin DP, Frisch F, Phoenix S, Guérin B, Turcotte ÉE, Haman F, Richard D & & Carpentier AC 2017a Inhibition of intracellular triglyceride lipolysis suppresses cold-induced brown adipose tissue metabolism and increases shivering in humans. Cell Metabolism 25 438–447. (https://doi.org/10.1016/j.cmet.2016.12.005)
Blondin DP, Daoud A, Taylor T, Tingelstad HC, Bézaire V, Richard D, Carpentier AC, Taylor AW, Harper ME, Aguer C, et al.2017b Four-week cold acclimation in adult humans shifts uncoupling thermogenesis from skeletal muscles to brown adipose tissue. Journal of Physiology 595 2099–2113. (https://doi.org/10.1113/JP273395)
Blondin DP, Tingelstad HC, Noll C, Frisch F, Phoenix S, Guérin B, Turcotte ÉE, Richard D, Haman F & & Carpentier AC 2017c Dietary fatty acid metabolism of brown adipose tissue in cold-acclimated men. Nature Communications 8 14146. (https://doi.org/10.1038/ncomms14146)
Blondin DP, Nielsen S, Kuipers EN, Severinsen MC, Jensen VH, Miard S, Jespersen NZ, Kooijman S, Boon MR, Fortin M, et al.2020 Human brown adipocyte thermogenesis is driven by β2-AR stimulation. Cell Metabolism 32 287–300.e7. (https://doi.org/10.1016/j.cmet.2020.07.005)
Branca RT, He T, Zhang L, Floyd CS, Freeman M, White C & & Burant A 2014 Detection of brown adipose tissue and thermogenic activity in mice by hyperpolarized xenon MRI. Proceedings of the National Academy of Sciences of the United States of America 111 18001–18006. (https://doi.org/10.1073/pnas.1403697111)
Broeders EP, Nascimento EB, Havekes B, Brans B, Roumans KH, Tailleux A, Schaart G, Kouach M, Charton J, Deprez B, et al.2015 The bile acid chenodeoxycholic acid increases human brown adipose tissue activity. Cell Metabolism 22 418–426. (https://doi.org/10.1016/j.cmet.2015.07.002)
Cannon B & & Nedergaard J 2004 Brown adipose tissue: function and physiological significance. Physiological Reviews 84 277–359. (https://doi.org/10.1152/physrev.00015.2003)
Carpentier AC, Blondin DP, Virtanen KA, Richard D, Haman F & & Turcotte ÉE 2018 Brown adipose tissue energy metabolism in humans. Frontiers in Endocrinology 9 447. (https://doi.org/10.3389/fendo.2018.00447)
Chakrabarty K, Chaudhuri B & & Jeffay H 1983 Glycerokinase activity in human brown adipose tissue. Journal of Lipid Research 24 381–390. (https://doi.org/10.1016/S0022-2275(2037978-5)
Chen YI, Cypess AM, Sass CA, Brownell AL, Jokivarsi KT, Kahn CR & & Kwong KK 2012 Anatomical and functional assessment of brown adipose tissue by magnetic resonance imaging. Obesity 20 1519–1526. (https://doi.org/10.1038/oby.2012.22)
Chen KY, Brychta RJ, Linderman JD, Smith S, Courville A, Dieckmann W, Herscovitch P, Millo CM, Remaley A, Lee P, et al.2013a Brown fat activation mediates cold-induced thermogenesis in adult humans in response to a mild decrease in ambient temperature. Journal of Clinical Endocrinology and Metabolism 98 E1218–E1223. (https://doi.org/10.1210/jc.2012-4213)
Chen YCI, Cypess AM, Chen YC, Palmer M, Kolodny G, Kahn CR & & Kwong KK 2013b Measurement of human brown adipose tissue volume and activity using anatomic MR imaging and functional MR imaging. Journal of Nuclear Medicine 54 1584–1587. (https://doi.org/10.2967/jnumed.112.117275)
Chen KY, Cypess AM, Laughlin MR, Haft CR, Hu HH, Bredella MA, Enerbäck S, Kinahan PE, Lichtenbelt W, Lin FI, et al.2016 Brown adipose reporting criteria in imaging STudies (BARCIST 1.0): recommendations for standardized FDG-PET/CT experiments in humans. Cell Metabolism 24 210–222. (https://doi.org/10.1016/j.cmet.2016.07.014)
Chondronikola M, Volpi E, Børsheim E, Porter C, Annamalai P, Enerbäck S, Lidell ME, Saraf MK, Labbe SM, Hurren NM, et al.2014 Brown adipose tissue improves whole-body glucose homeostasis and insulin sensitivity in humans. Diabetes 63 4089–4099. (https://doi.org/10.2337/db14-0746)
Chondronikola M, Volpi E, Børsheim E, Chao T, Porter C, Annamalai P, Yfanti C, Labbe SM, Hurren NM, Malagaris I, et al.2016a Brown adipose tissue is linked to a distinct thermoregulatory response to mild cold in people. Frontiers in Physiology 7 129. (https://doi.org/10.3389/fphys.2016.00129)
Chondronikola M, Volpi E, Børsheim E, Porter C, Saraf MK, Annamalai P, Yfanti C, Chao T, Wong D, Shinoda K, et al.2016b Brown adipose tissue activation is linked to distinct systemic effects on lipid metabolism in humans. Cell Metabolism 23 1200–1206. (https://doi.org/10.1016/j.cmet.2016.04.029)
Clerte M, Baron DM, Brouckaert P, Ernande L, Raher MJ, Flynn AW, Picard MH, Bloch KD, Buys ES & & Scherrer-Crosbie M 2013 Brown adipose tissue blood flow and mass in obesity: a contrast ultrasound study in mice. Journal of the American Society of Echocardiography 26 1465–1473. (https://doi.org/10.1016/j.echo.2013.07.015)
Cohade C, Osman M, Pannu HK & & Wahl RL 2003 Uptake in supraclavicular area fat ("USA-Fat"): description on 18F-FDG PET/CT. Journal of Nuclear Medicine 44 170–176.
Coolbaugh CL, Damon BM, Bush EC, Welch EB & & Towse TF 2019 Cold exposure induces dynamic, heterogeneous alterations in human brown adipose tissue lipid content. Scientific Reports 9 13600. (https://doi.org/10.1038/s41598-019-49936-x)
Cypess AM, Lehman S, Williams G, Tal I, Rodman D, Goldfine AB, Kuo FC, Palmer EL, Tseng YH, Doria A, et al.2009 Identification and importance of brown adipose tissue in adult humans. New England Journal of Medicine 360 1509–1517. (https://doi.org/10.1056/NEJMoa0810780)
Deng J, Neff LM, Rubert NC, Zhang B, Shore RM, Samet JD, Nelson PC & & Landsberg L 2018 MRI characterization of brown adipose tissue under thermal challenges in normal weight, overweight, and obese young men. Journal of Magnetic Resonance Imaging 47 936–947. (https://doi.org/10.1002/jmri.25836)
Deshmukh AS, Peijs L, Beaudry JL, Jespersen NZ, Nielsen CH, Ma T, Brunner AD, Larsen TJ, Bayarri-Olmos R, Prabhakar BS, et al.2019 Proteomics-based comparative mapping of the secretomes of human brown and white adipocytes reveals EPDR1 as a novel Batokine. Cell Metabolism 30 963–975.e7. (https://doi.org/10.1016/j.cmet.2019.10.001)
Diabetes Prevention Program Research Group, Knowler WC, , Fowler SE, , Hamman RF, , Christophi CA, , Hoffman HJ, , Brenneman AT, , Brown-Friday JO, , Goldberg R, , Venditti E, et al.2009 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet 374 1677–1686. (https://doi.org/10.1016/S0140-6736(0961457-4)
Din MU, Raiko J, Saari T, Kudomi N, Tolvanen T, Oikonen V, Teuho J, Sipilä HT, Savisto N, Parkkola R, et al.2016 Human brown adipose tissue [(15)O]O2 PET imaging in the presence and absence of cold stimulus. European Journal of Nuclear Medicine and Molecular Imaging 43 1878–1886. (https://doi.org/10.1007/s00259-016-3364-y)
Din MU, Saari T, Raiko J, Kudomi N, Maurer SF, Lahesmaa M, Fromme T, Amri EZ, Klingenspor M, Solin O, et al.2018 Postprandial oxidative metabolism of human brown fat indicates thermogenesis. Cell Metabolism 28 207–216.e3. (https://doi.org/10.1016/j.cmet.2018.05.020)
Edwards AD, Richardson C, van der Zee P, Elwell C, Wyatt JS, Cope M, Delpy DT & & Reynolds EO 1993 Measurement of hemoglobin flow and blood flow by near-infrared spectroscopy. Journal of Applied Physiology 75 1884–1889. (https://doi.org/10.1152/jappl.1993.75.4.1884)
Eriksson O, Mikkola K, Espes D, Tuominen L, Virtanen K, Forsbäck S, Haaparanta-Solin M, Hietala J, Solin O & & Nuutila P 2015 The cannabinoid Receptor-1 is an imaging biomarker of brown adipose tissue. Journal of Nuclear Medicine 56 1937–1941. (https://doi.org/10.2967/jnumed.115.156422)
Flynn A, Li Q, Panagia M, Abdelbaky A, MacNabb M, Samir A, Cypess AM, Weyman AE, Tawakol A & & Scherrer-Crosbie M 2015 Contrast-enhanced ultrasound: a novel noninvasive, nonionizing method for the detection of brown adipose tissue in humans. Journal of the American Society of Echocardiography 28 1247–1254. (https://doi.org/10.1016/j.echo.2015.06.014)
Franz D, Karampinos DC, Rummeny EJ, Souvatzoglou M, Beer AJ, Nekolla SG, Schwaiger M & & Eiber M 2015 Discrimination between brown and white adipose tissue using a 2-point Dixon water-fat separation method in simultaneous PET/MRI. Journal of Nuclear Medicine 56 1742–1747. (https://doi.org/10.2967/jnumed.115.160770)
Fraum TJ, Crandall JP, Ludwig DR, Chen S, Fowler KJ, Laforest RA, Salter A, Dehdashti F, An H & & Wahl RL 2019 Repeatability of quantitative brown adipose tissue imaging metrics on positron emission tomography with (18)F-Fluorodeoxyglucose in humans. Cell Metabolism 30 212-224.e214.
Gariani K, Gariani J, Amzalag G, Delattre BM, Ratib O & & Garibotto V 2015 Hybrid PET/MRI as a tool to detect brown adipose tissue: proof of principle. Obesity Research and Clinical Practice 9 613–617. (https://doi.org/10.1016/j.orcp.2015.05.004)
Gatidis S, Schmidt H, Pfannenberg CA, Nikolaou K, Schick F & & Schwenzer NF 2016 Is it possible to detect activated brown adipose tissue in humans using single-time-point infrared thermography under thermoneutral conditions? Impact of BMI and subcutaneous adipose tissue thickness. PLoS One 11 e0151152. (https://doi.org/10.1371/journal.pone.0151152)
Gifford A, Towse TF, Walker RC, Avison MJ & & Welch EB 2016 Characterizing active and inactive brown adipose tissue in adult humans using PET-CT and MR imaging. American Journal of Physiology-Endocrinology and Metabolism 311 E95–E104. (https://doi.org/10.1152/ajpendo.00482.2015)
Gilsanz V, Smith ML, Goodarzian F, Kim M, Wren TAL & & Hu HH 2012 Changes in brown adipose tissue in boys and girls during childhood and puberty. Journal of Pediatrics 160 604–609.e1. (https://doi.org/10.1016/j.jpeds.2011.09.035)
Hadi M, Chen CC, Whatley M, Pacak K & & Carrasquillo JA 2007 Brown fat imaging with (18)F-6-fluorodopamine PET/CT, (18)F-FDG PET/CT, and (123)I-MIBG SPECT: a study of patients being evaluated for pheochromocytoma. Journal of Nuclear Medicine 48 1077–1083. (https://doi.org/10.2967/jnumed.106.035915)
Hanssen MJ, Hoeks J, Brans B, van der Lans AA, Schaart G, van den Driessche JJ, Jörgensen JA, Boekschoten MV, Hesselink MK, Havekes B, et al.2015 Short-term cold acclimation improves insulin sensitivity in patients with type 2 diabetes mellitus. Nature Medicine 21 863–865. (https://doi.org/10.1038/nm.3891)
Haq T, Crane JD, Kanji S, Gunn E, Tarnopolsky MA, Gerstein HC, Steinberg GR & & Morrison KM 2017 Optimizing the methodology for measuring supraclavicular skin temperature using infrared thermography; implications for measuring brown adipose tissue activity in humans. Scientific Reports 7 11934. (https://doi.org/10.1038/s41598-017-11537-x)
Hartwig V, Guiducci L, Marinelli M, Pistoia L, Tegrimi TM, Iervasi G, Quinones-Galvan A & & L'Abbate A 2017 Multimodal imaging for the detection of brown adipose tissue activation in women: a pilot study using NIRS and infrared thermography. Journal of Healthcare Engineering 2017 5986452. (https://doi.org/10.1155/2017/5986452)
Heaton JM 1972 The distribution of brown adipose tissue in the human. Journal of Anatomy 112 35–39.
Held NM, Kuipers EN, van Weeghel M, van Klinken JB, Denis SW, Lombès M, Wanders RJ, Vaz FM, Rensen PCN, Verhoeven AJ, et al.2018 Pyruvate dehydrogenase complex plays a central role in brown adipocyte energy expenditure and fuel utilization during short-term beta-adrenergic activation. Scientific Reports 8 9562. (https://doi.org/10.1038/s41598-018-27875-3)
Henriksson J 1999 Microdialysis of skeletal muscle at rest. Proceedings of the Nutrition Society 58 919–923. (https://doi.org/10.1017/s0029665199001226)
Holstila M, Pesola M, Saari T, Koskensalo K, Raiko J, Borra RJ, Nuutila P, Parkkola R & & Virtanen KA 2017 MR signal-fat-fraction analysis and T2* weighted imaging measure BAT reliably on humans without cold exposure. Metabolism: Clinical and Experimental 70 23–30. (https://doi.org/10.1016/j.metabol.2017.02.001)
Hu HH, Perkins TG, Chia JM & & Gilsanz V 2013 Characterization of human brown adipose tissue by chemical-shift water-fat MRI. AJR. American Journal of Roentgenology 200 177–183. (https://doi.org/10.2214/AJR.12.8996)
Huttunen P, Hirvonen J & & Kinnula V 1981 The occurrence of brown adipose tissue in outdoor workers. European Journal of Applied Physiology and Occupational Physiology 46 339–345. (https://doi.org/10.1007/BF00422121)
Hwang JJ, Yeckel CW, Gallezot JD, Aguiar RB-D, Ersahin D, Gao H, Kapinos M, Nabulsi N, Huang Y, Cheng D, et al.2015 Imaging human brown adipose tissue under room temperature conditions with (11)C-MRB, a selective norepinephrine transporter PET ligand. Metabolism: Clinical and Experimental 64 747–755. (https://doi.org/10.1016/j.metabol.2015.03.001)
Ikeda K, Kang Q, Yoneshiro T, Camporez JP, Maki H, Homma M, Shinoda K, Chen Y, Lu X, Maretich P, et al.2017 UCP1-independent signaling involving SERCA2b-mediated calcium cycling regulates beige fat thermogenesis and systemic glucose homeostasis. Nature Medicine 23 1454–1465. (https://doi.org/10.1038/nm.4429)
Iwen KA, Backhaus J, Cassens M, Waltl M, Hedesan OC, Merkel M, Heeren J, Sina C, Rademacher L, Windjäger A, et al.2017 Cold-induced brown adipose tissue activity alters plasma fatty acids and improves glucose metabolism in men. Journal of Clinical Endocrinology and Metabolism 102 4226–4234. (https://doi.org/10.1210/jc.2017-01250)
Jang C, Jalapu S, Thuzar M, Law PW, Jeavons S, Barclay JL & & Ho KKY 2014 Infrared thermography in the detection of brown adipose tissue in humans. Physiological Reports 2 e12167. (https://doi.org/10.14814/phy2.12167)
Jastreboff AM, Aronne LJ, Ahmad NN, Wharton S, Connery L, Alves B, Kiyosue A, Zhang S, Liu B, Bunck MC, et al.2022 Tirzepatide once weekly for the treatment of obesity. New England Journal of Medicine 387 205–216. (https://doi.org/10.1056/NEJMoa2206038)
Jespersen NZ, Larsen TJ, Peijs L, Daugaard S, Homøe P, Loft A, de Jong J, Mathur N, Cannon B, Nedergaard J, et al.2013 A classical brown adipose tissue mRNA signature partly overlaps with Brite in the supraclavicular region of adult humans. Cell Metabolism 17 798–805. (https://doi.org/10.1016/j.cmet.2013.04.011)
Jung CSL, Heine M, Freund B, Reimer R, Koziolek EJ, Kaul MG, Kording F, Schumacher U, Weller H, Nielsen P, et al.2016 Quantitative activity measurements of brown adipose tissue at 7 T magnetic resonance imaging after application of triglyceride-rich lipoprotein 59Fe-Superparamagnetic iron oxide nanoparticle: intravenous versus intraperitoneal approach. Investigative Radiology 51 194–202. (https://doi.org/10.1097/RLI.0000000000000235)
Jung SM, Doxsey WG, Le J, Haley JA, Mazuecos L, Luciano AK, Li H, Jang C & & Guertin DA 2021 In vivo isotope tracing reveals the versatility of glucose as a brown adipose tissue substrate. Cell Reports 36 109459. (https://doi.org/10.1016/j.celrep.2021.109459)
Khanh VC, Zulkifli AF, Tokunaga C, Yamashita T, Hiramatsu Y & & Ohneda O 2018 Aging impairs beige adipocyte differentiation of mesenchymal stem cells via the reduced expression of sirtuin 1. Biochemical and Biophysical Research Communications 500 682–690. (https://doi.org/10.1016/j.bbrc.2018.04.136)
Koskensalo K, Raiko J, Saari T, Saunavaara V, Eskola O, Nuutila P, Saunavaara J, Parkkola R & & Virtanen KA 2017 Human brown adipose tissue temperature and fat fraction are related to its metabolic activity. Journal of Clinical Endocrinology and Metabolism 102 1200–1207. (https://doi.org/10.1210/jc.2016-3086)
Lahesmaa M, Eriksson O, Gnad T, Oikonen V, Bucci M, Hirvonen J, Koskensalo K, Teuho J, Niemi T, Taittonen M, et al.2018 Cannabinoid Type 1 receptors are upregulated during acute activation of brown adipose tissue. Diabetes 67 1226–1236. (https://doi.org/10.2337/db17-1366)
Lahesmaa M, Oikonen V, Helin S, Luoto P, U Din M, Pfeifer A, Nuutila P & & Virtanen KA 2019 Regulation of human brown adipose tissue by adenosine and A2A receptors – studies with [15O]H2O and [11C]TMSX PET/CT. European Journal of Nuclear Medicine and Molecular Imaging 46 743–750. (https://doi.org/10.1007/s00259-018-4120-2)
Lau AZ, Chen AP, Gu Y, Ladouceur-Wodzak M, Nayak KS & & Cunningham CH 2014 Noninvasive identification and assessment of functional brown adipose tissue in rodents using hyperpolarized 13C imaging. International Journal of Obesity 38 126–131. (https://doi.org/10.1038/ijo.2013.58)
Laurila S, Sun L, Lahesmaa M, Schnabl K, Laitinen K, Klén R, Li Y, Balaz M, Wolfrum C, Steiger K, et al.2021 Secretin activates brown fat and induces satiation. Nature Metabolism 3 798–809. (https://doi.org/10.1038/s42255-021-00409-4)
Law J, Morris DE, Izzi-Engbeaya C, Salem V, Coello C, Robinson L, Jayasinghe M, Scott R, Gunn R, Rabiner E, et al.2018 Thermal imaging is a noninvasive alternative to PET/CT for measurement of brown adipose tissue activity in humans. Journal of Nuclear Medicine 59 516–522. (https://doi.org/10.2967/jnumed.117.190546)
Lee P, , Ho KK, , Lee P, , Greenfield JR, , Ho KK, & Greenfield JR2011 Hot fat in a cool man: infrared thermography and brown adipose tissue. Diabetes, Obesity and Metabolism 13 92–93. (https://doi.org/10.1111/j.1463-1326.2010.01318.x)
Lee P, Smith S, Linderman J, Courville AB, Brychta RJ, Dieckmann W, Werner CD, Chen KY & & Celi FS 2014 Temperature-acclimated brown adipose tissue modulates insulin sensitivity in humans. Diabetes 63 3686–3698. (https://doi.org/10.2337/db14-0513)
Lee P, Bova R, Schofield L, Bryant W, Dieckmann W, Slattery A, Govendir MA, Emmett L & & Greenfield JR 2016 Brown adipose tissue exhibits a glucose-responsive thermogenic biorhythm in humans. Cell Metabolism 23 602–609. (https://doi.org/10.1016/j.cmet.2016.02.007)
Leibel RL, Rosenbaum M & & Hirsch J 1995 Changes in energy expenditure resulting from altered body weight. New England Journal of Medicine 332 621–628. (https://doi.org/10.1056/NEJM199503093321001)
Leitner BP, Huang S, Brychta RJ, Duckworth CJ, Baskin AS, McGehee S, Tal I, Dieckmann W, Gupta G, Kolodny GM, et al.2017 Mapping of human brown adipose tissue in lean and obese young men. Proceedings of the National Academy of Sciences of the United States of America 114 8649–8654. (https://doi.org/10.1073/pnas.1705287114)
Lidell ME, Betz MJ, Leinhard OD, Heglind M, Elander L, Slawik M, Mussack T, Nilsson D, Romu T, Nuutila P, et al.2013 Evidence for two types of brown adipose tissue in humans. Nature Medicine 19 631–634. (https://doi.org/10.1038/nm.3017)
Liu X, Zheng Z, Zhu X, Meng M, Li L, Shen Y, Chi Q, Wang D, Zhang Z, Li C, et al.2013 Brown adipose tissue transplantation improves whole-body energy metabolism. Cell Research 23 851–854. (https://doi.org/10.1038/cr.2013.64)
Lowell BB, Susulic V, Hamann A, Lawitts JA, Himms-Hagen J, Boyer BB, Kozak LP & & Flier JS 1993 Development of obesity in transgenic mice after genetic ablation of brown adipose tissue. Nature 366 740–742.
Lundström E, Strand R, Johansson L, Bergsten P, Ahlström H & & Kullberg J 2015 Magnetic resonance imaging cooling-reheating protocol indicates decreased fat fraction via lipid consumption in suspected brown adipose tissue. PLoS One 10 e0126705. (https://doi.org/10.1371/journal.pone.0126705)
Madar I, Isoda T, Finley P, Angle J & & Wahl R 2011 18F-Fluorobenzyl triphenyl phosphonium: a noninvasive sensor of brown adipose tissue thermogenesis. Journal of Nuclear Medicine 52 808–814. (https://doi.org/10.2967/jnumed.110.084657)
Madar I, Naor E, Holt D, Ravert H, Dannals R & & Wahl R 2015 Brown adipose tissue response dynamics: in vivo insights with the voltage sensor 18F-Fluorobenzyl triphenyl phosphonium. PLoS One 10 e0129627. (https://doi.org/10.1371/journal.pone.0129627)
Martinez-Tellez B, Sanchez-Delgado G, Garcia-Rivero Y, Alcantara JMA, Martinez-Avila WD, Muñoz-Hernandez MV, Olza J, Boon MR, Rensen PCN, Llamas-Elvira JM, et al.2017 A new personalized cooling protocol to Activate Brown Adipose Tissue in young adults. Frontiers in Physiology 8 863.
McCallister A, Zhang L, Burant A, Katz L & & Branca RT 2017 A pilot study on the correlation between fat fraction values and glucose uptake values in supraclavicular fat by simultaneous PET/MRI. Magnetic Resonance in Medicine 78 1922–1932. (https://doi.org/10.1002/mrm.26589)
McNeill BT, Morton NM & & Stimson RH 2020 Substrate utilization by brown adipose tissue: what's hot and what's not? Frontiers in Endocrinology 11 571659. (https://doi.org/10.3389/fendo.2020.571659)
Muzik O, Mangner TJ & & Granneman JG 2012 Assessment of oxidative metabolism in brown fat using PET imaging. Frontiers in Endocrinology 3 15–15. (https://doi.org/10.3389/fendo.2012.00015)
Muzik O, Mangner TJ, Leonard WR, Kumar A, Janisse J & & Granneman JG 2013 15O PET measurement of blood flow and oxygen consumption in cold-activated human brown fat. Journal of Nuclear Medicine 54 523–531. (https://doi.org/10.2967/jnumed.112.111336)
Nicholls DG & & Locke RM 1984 Thermogenic mechanisms in brown fat. Physiological Reviews 64 1–64. (https://doi.org/10.1152/physrev.1984.64.1.1)
Nirengi S, Wakabayashi H, Matsushita M, Domichi M, Suzuki S, Sukino S, Suganuma A, Kawaguchi Y, Hashimoto T, Saito M, et al.2019 An optimal condition for the evaluation of human brown adipose tissue by infrared thermography. PLoS One 14 e0220574. (https://doi.org/10.1371/journal.pone.0220574)
Nirengi S, Yoneshiro T, Sugie H, Saito M & & Hamaoka T 2015 Human brown adipose tissue assessed by simple, noninvasive near-Infrared time-resolved spectroscopy. Obesity 23 973–980. (https://doi.org/10.1002/oby.21012)
O’Mara AE, Johnson JW, Linderman JD, Brychta RJ, McGehee S, Fletcher LA, Fink YA, Kapuria D, Cassimatis TM, Kelsey N, et al.2020 Chronic mirabegron treatment increases human brown fat, HDL cholesterol, and insulin sensitivity. Journal of Clinical Investigation 130 2209–2219. (https://doi.org/10.1172/JCI131126)
Ogawa S, Lee TM, Kay AR & & Tank DW 1990 Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proceedings of the National Academy of Sciences of the United States of America 87 9868–9872. (https://doi.org/10.1073/pnas.87.24.9868)
Orava J, Nuutila P, Lidell ME, Oikonen V, Noponen T, Viljanen T, Scheinin M, Taittonen M, Niemi T, Enerbäck S, et al.2011 Different metabolic responses of human brown adipose tissue to activation by cold and insulin. Cell Metabolism 14 272–279. (https://doi.org/10.1016/j.cmet.2011.06.012)
Orava J, Nuutila P, Noponen T, Parkkola R, Viljanen T, Enerbäck S, Rissanen A, Pietiläinen KH & & Virtanen KA 2013 Blunted metabolic responses to cold and insulin stimulation in brown adipose tissue of obese humans. Obesity 21 2279–2287. (https://doi.org/10.1002/oby.20456)
Oreskovich SM, Ong FJ, Ahmed BA, Konyer NB, Blondin DP, Gunn E, Singh NP, Noseworthy MD, Haman F, Carpentier AC, et al.2019 MRI reveals human brown adipose tissue is rapidly activated in response to cold. Journal of the Endocrine Society 3 2374–2384. (https://doi.org/10.1210/js.2019-00309)
Ouellet V, Labbé SM, Blondin DP, Phoenix S, Guérin B, Haman F, Turcotte EE, Richard D & & Carpentier AC 2012 Brown adipose tissue oxidative metabolism contributes to energy expenditure during acute cold exposure in humans. Journal of Clinical Investigation 122 545–552. (https://doi.org/10.1172/JCI60433)
Ouwerkerk R, Hamimi A, Matta J, Abd-Elmoniem KZ, Eary JF, Abdul Sater Z, Chen KY, Cypess AM & & Gharib AM 2021 Proton MR spectroscopy measurements of white and brown adipose tissue in healthy humans: relaxation parameters and unsaturated fatty acids. Radiology 299 396–406. (https://doi.org/10.1148/radiol.2021202676)
Pi-Sunyer X, Astrup A, Fujioka K, Greenway F, Halpern A, Krempf M, Lau DC, le Roux CW, Violante Ortiz R, Jensen CB, et al.2015 A Randomized, Controlled Trial of 3.0 mg of liraglutide in Weight Management. New England Journal of Medicine 373 11–22. (https://doi.org/10.1056/NEJMoa1411892)
Porter C, Herndon DN, Chondronikola M, Chao T, Annamalai P, Bhattarai N, Saraf MK, Capek KD, Reidy PT, Daquinag AC, et al.2016 Human and mouse brown adipose tissue mitochondria have comparable UCP1 function. Cell Metabolism 24 246–255. (https://doi.org/10.1016/j.cmet.2016.07.004)
Ramage LE, Akyol M, Fletcher AM, Forsythe J, Nixon M, Carter RN, van Beek EJ, Morton NM, Walker BR & & Stimson RH 2016 Glucocorticoids acutely increase brown adipose tissue activity in humans, revealing species-specific differences in UCP-1 regulation. Cell Metabolism 24 130–141. (https://doi.org/10.1016/j.cmet.2016.06.011)
Ran C, Albrecht DS, Bredella MA, Yang J, Yang J, Liang SH, Cypess AM, Loggia ML, Atassi N & & Moore A 2018 PET imaging of human brown adipose tissue with the TSPO tracer [11C]PBR28. Molecular Imaging and Biology 20 188–193. (https://doi.org/10.1007/s11307-017-1129-z)
Reddy NL, Jones TA, Wayte SC, Adesanya O, Sankar S, Yeo YC, Tripathi G, McTernan PG, Randeva HS, Kumar S, et al.2014 Identification of brown adipose tissue using MR imaging in a human adult with histological and immunohistochemical confirmation. Journal of Clinical Endocrinology and Metabolism 99 E117–E121. (https://doi.org/10.1210/jc.2013-2036)
Richard G, Blondin DP, Syed SA, Rossi L, Fontes ME, Fortin M, Phoenix S, Frisch F, Dubreuil S, Guérin B, et al.2022 High-fructose feeding suppresses cold-stimulated brown adipose tissue glucose uptake independently of changes in thermogenesis and the gut microbiome. Cell Reports. Medicine 3 100742. (https://doi.org/10.1016/j.xcrm.2022.100742)
Robinson L, Ojha S, Symonds ME & & Budge H 2014 Body mass index as a determinant of brown adipose tissue function in healthy children. Journal of Pediatrics 164 318–22.e1. (https://doi.org/10.1016/j.jpeds.2013.10.005)
Saari TJ, Raiko J, U-Din M, Niemi T, Taittonen M, Laine J, Savisto N, Haaparanta-Solin M, Nuutila P & & Virtanen KA 2020 Basal and cold-induced fatty acid uptake of human brown adipose tissue is impaired in obesity. Scientific Reports 10 14373.
Samuelson I & & Vidal-Puig A 2020 Studying brown adipose tissue in a human in vitro context. Frontiers in Endocrinology 11 629. (https://doi.org/10.3389/fendo.2020.00629)
Sanchez-Delgado G, Acosta FM, Martinez-Tellez B, Finlayson G, Gibbons C, Labayen I, Llamas-Elvira JM, Gil A, Blundell JE & & Ruiz JR 2020 Brown adipose tissue volume and 18F-fluorodeoxyglucose uptake are not associated with energy intake in young human adults. American Journal of Clinical Nutrition 111 329–339. (https://doi.org/10.1093/ajcn/nqz300)
Sarasniemi JT, Koskensalo K, Raiko J, Nuutila P, Saunavaara J, Parkkola R & & Virtanen KA 2018 Skin temperature may not yield human brown adipose tissue activity in diverse populations. Acta Physiologica (Oxford, England) 224 e13095. (https://doi.org/10.1111/apha.13095)
Sbarbati A, Cavallini I, Marzola P, Nicolato E & & Osculati F 2006 Contrast-enhanced MRI of brown adipose tissue after pharmacological stimulation. Magnetic Resonance in Medicine 55 715–718. (https://doi.org/10.1002/mrm.20851)
Schlögl M, Piaggi P, Thiyyagura P, Reiman EM, Chen K, Lutrin C, Krakoff J & & Thearle MS 2013 Overfeeding over 24 hours does not activate brown adipose tissue in humans. Journal of Clinical Endocrinology and Metabolism 98 E1956–E1960. (https://doi.org/10.1210/jc.2013-2387)
Sharp LZ, Shinoda K, Ohno H, Scheel DW, Tomoda E, Ruiz L, Hu H, Wang L, Pavlova Z, Gilsanz V, et al.2012 Human BAT possesses molecular signatures that resemble beige/Brite cells. PLoS One 7 e49452. (https://doi.org/10.1371/journal.pone.0049452)
Søberg S, Löfgren J, Philipsen FE, Jensen M, Hansen AE, Ahrens E, Nystrup KB, Nielsen RD, Sølling C, Wedell-Neergaard AS, et al.2021 Altered brown fat thermoregulation and enhanced cold-induced thermogenesis in young, healthy, winter-swimming men. Cell Reports. Medicine 2 100408. (https://doi.org/10.1016/j.xcrm.2021.100408)
Stahl V, Maier F, Freitag MT, Floca RO, Berger MC, Umathum R, Berriel Diaz M, Herzig S, Weber MA, Dimitrakopoulou-Strauss A, et al.2017 In vivo assessment of cold stimulation effects on the fat fraction of brown adipose tissue using DIXON MRI. Journal of Magnetic Resonance Imaging 45 369–380. (https://doi.org/10.1002/jmri.25364)
Suchacki KJ, Ramage LE, Kwok TC, Kelman A, McNeill BT, Rodney S, Keegan M, Gray C, MacNaught G, Patel D, et al.2023 The serotonin transporter sustains human brown adipose tissue thermogenesis. Nature Metabolism [epub]. (https://doi.org/10.1038/s42255-023-00839-2)
Symonds ME, Henderson K, Elvidge L, Bosman C, Sharkey D, Perkins AC & & Budge H 2012 Thermal imaging to assess age-related changes of skin temperature within the supraclavicular region co-locating with brown adipose tissue in healthy children. Journal of Pediatrics 161 892–898. (https://doi.org/10.1016/j.jpeds.2012.04.056)
Thuzar M, Law WP, Dimeski G, Stowasser M & & Ho KKY 2019 Mineralocorticoid antagonism enhances brown adipose tissue function in humans: a randomized placebo-controlled cross-over study. Diabetes, Obesity and Metabolism 21 509–516. (https://doi.org/10.1111/dom.13539)
Tint MT, Michael N, Sadananthan SA, Huang JY, Khoo CM, Godfrey KM, Shek LP, Lek N, Tan KH, Yap F, et al.2021 Brown adipose tissue, adiposity, and metabolic profile in preschool children. Journal of Clinical Endocrinology and Metabolism 106 2901–2914. (https://doi.org/10.1210/clinem/dgab447)
Torgerson JS, Hauptman J, Boldrin MN & & Sjöström L 2004 Xenical in the prevention of diabetes in obese subjects (XENDOS) study: a randomized study of orlistat as an adjunct to lifestyle changes for the prevention of type 2 diabetes in obese patients. Diabetes Care 27 155–161. (https://doi.org/10.2337/diacare.27.1.155)
Ulla M, Bonny JM, Ouchchane L, Rieu I, Claise B & & Durif F 2013 Is R2* a new MRI biomarker for the progression of Parkinson’s disease? A longitudinal follow-up. PLoS One 8 e57904.
van der Lans AA, Hoeks J, Brans B, Vijgen GH, Visser MG, Vosselman MJ, Hansen J, Jörgensen JA, Wu J, Mottaghy FM, et al.2013 Cold acclimation recruits human brown fat and increases nonshivering thermogenesis. Journal of Clinical Investigation 123 3395–3403. (https://doi.org/10.1172/JCI68993)
van der Lans AA, Vosselman MJ, Hanssen MJ, Brans B & & van Marken Lichtenbelt WD 2016 Supraclavicular skin temperature and BAT activity in lean healthy adults. Journal of Physiological Sciences 66 77–83. (https://doi.org/10.1007/s12576-015-0398-z)
van Marken Lichtenbelt WD, Vanhommerig JW, Smulders NM, Drossaerts JM, Kemerink GJ, Bouvy ND, Schrauwen P & & Teule GJ 2009 Cold-activated brown adipose tissue in healthy men. New England Journal of Medicine 360 1500–1508. (https://doi.org/10.1056/NEJMoa0808718)
van Rooijen BD, van der Lans AAJJ, Brans B, Wildberger JE, Mottaghy FM, Schrauwen P, Backes WH & & van Marken Lichtenbelt WD 2013 Imaging cold-activated brown adipose tissue using dynamic T2*-weighted magnetic resonance imaging and 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography. Investigative Radiology 48 708–714. (https://doi.org/10.1097/RLI.0b013e31829363b8)
Vijgen GH, Bouvy ND, Teule GJ, Brans B, Hoeks J, Schrauwen P & & van Marken Lichtenbelt WD 2012 Increase in brown adipose tissue activity after weight loss in morbidly obese subjects. Journal of Clinical Endocrinology and Metabolism 97 E1229–E1233. (https://doi.org/10.1210/jc.2012-1289)
Virtanen KA, Lidell ME, Orava J, Heglind M, Westergren R, Niemi T, Taittonen M, Laine J, Savisto NJ, Enerbäck S, et al.2009 Functional brown adipose tissue in healthy adults. New England Journal of Medicine 360 1518–1525. (https://doi.org/10.1056/NEJMoa0808949)
Wadden TA, Sternberg JA, Letizia KA, Stunkard AJ & & Foster GD 1989 Treatment of obesity by very low calorie diet, behavior therapy, and their combination: a five-year perspective. International Journal of Obesity 13(Supplement 2) 39–46.
Wang Q, Zhang M, Ning G, Gu W, Su T, Xu M, Li B & & Wang W 2011 Brown adipose tissue in humans is activated by elevated plasma catecholamines levels and is inversely related to central obesity. PLoS One 6 e21006. (https://doi.org/10.1371/journal.pone.0021006)
Weir G, Ramage LE, Akyol M, Rhodes JK, Kyle CJ, Fletcher AM, Craven TH, Wakelin SJ, Drake AJ, Gregoriades ML, et al.2018 Substantial metabolic activity of human brown adipose tissue during warm conditions and cold-induced lipolysis of local triglycerides. Cell Metabolism 27 1348–1355.e4. (https://doi.org/10.1016/j.cmet.2018.04.020)
Whitehead A, Krause FN, Moran A, Maccannell ADV, Scragg JL, Mcnally BD, Boateng E, Murfitt SA, Virtue S, Wright J, et al.2021 Brown and beige adipose tissue regulate systemic metabolism through a metabolite interorgan signaling axis. Nature Communications 12. (https://doi.org/10.1038/s41467-021-22272-3)
Williams G & & Kolodny GM 2008 Method for decreasing uptake of 18F-FDG by hypermetabolic brown adipose tissue on PET. American Journal of Roentgenology 190 1406–1409. (https://doi.org/10.2214/AJR.07.3205)
Wood JC & & Ghugre N 2008 Magnetic resonance imaging assessment of excess iron in thalassemia, sickle cell disease and other iron overload diseases. Hemoglobin 32 85–96. (https://doi.org/10.1080/03630260701699912)
Yaligar J, Verma SK, Gopalan V, Anantharaj R, Thu Le GT, Kaur K, Mallilankaraman K, Leow MK & & Velan SS 2020 Dynamic contrast‐enhanced MRI of brown and beige adipose tissues. Magnetic Resonance in Medicine 84 384–395. (https://doi.org/10.1002/mrm.28118)
Yoneshiro T, Aita S, Matsushita M, Kameya T, Nakada K, Kawai Y & & Saito M 2011 Brown adipose tissue, whole-body energy expenditure, and thermogenesis in healthy adult men. Obesity 19 13–16. (https://doi.org/10.1038/oby.2010.105)
Zhang X, Tian Y, Zhang H, Kavishwar A, Lynes M, Brownell AL, Sun H