The impact of obesity on immune function in pediatric asthma

Abstract

Purpose of Review

Pediatric obese asthma is a complex disease that remains poorly understood. The increasing worldwide incidence of both asthma and obesity over the last few decades, their current high prevalence and the challenges in treating obese asthmatic patients all highlight the importance of a better understanding of the pathophysiological mechanisms in obese asthma. While it is well established that patients with obesity are at an increased risk of developing asthma, the mechanisms by which obesity drives the onset of asthma, and modifies existing asthma, remain unclear. Here, we will focus on mechanisms by which obesity alters immune function in asthma.

Recent Findings

Lung parenchyma has an altered structure in some pediatric obese asthmatics, known as dysanapsis. Central adiposity is linked to reduced pulmonary function and a better predictor of asthma risk in children than body mass index. Obesity in young children is associated with an increased risk of developing asthma, as well as early puberty, and hormonal alterations are implicated in obese asthma. Obesity and asthma each yield immunometabolic dysregulation separately and we are learning more about alterations in these pathways in pediatric obese asthma and the potential impact of bariatric surgery on those processes.

Summary

The recent progress in clarifying the connections between childhood obesity and asthma and their combined impacts on immune function moves us closer to the goals of improved understanding of the pathophysiological mechanisms underpinning obese asthma and improved therapeutic target selection. However, this common inflammatory disease remains understudied, especially in children, and much remains to be learned.

Introduction

Obese asthma (OA) is the intersection of the two most commonly occurring chronic diseases of childhood (1). Over the last few decades, both asthma and obesity have increased significantly worldwide (2) and currently 42% of adults(3) and 18% of children(4) in the United States are obese and 8% of adults and children are asthmatic(5). Moreover, 11% of obese adults (6), including 14.6% of obese women(6), and 15.7% of obese children (7) also have asthma. To add complexity, asthma is not a single condition but a disease encompassing a complex set of overlapping clinical phenotypes, including atopy and obesity (8). Both asthma and obesity(9) independently impact the immune system in many complex ways (10). Finally, there is substantial evidence that obesity and asthma may be pathophysiologically linked. First, it is well established that asthma is more prevalent in obese children (13–24) and adults (24–26), compared to their healthy weight counterparts. Second, obesity is an independent risk factor for development of pediatric asthma (12–23), with approximately one quarter of new pediatric asthma cases reported as directly attributable to obesity(11). Third, weight loss in OA adults and children has been shown to improve control of asthma symptoms in some patients (27–41). Finally, obesity is associated with both an increased risk of asthma development and increased asthma severity (26,42–46), and there is evidence that asthma may be an independent predictor of obesity(47,48), suggesting the link between obesity and asthma may be bidirectional(46).

Adult (22,24) and pediatric (21,22,49–51) OA patients experience a treatment-refractory form of asthma that is less responsive to preventative regimens. OA patients generally have more significant asthma exacerbations (49,52) and typically experience increased health care utilization (49) and require greater health care expenditures to control their asthma symptoms. Taken together, these data suggest obesity is both a powerful predictor of asthma incidence and a clear modifiable factor influencing asthma control. However, the multifactorial nature of both asthma and obesity makes establishing mechanistic pathophysiological link(s) between the two chronic inflammatory disorders quite complex. Furthermore, just as asthma is considered to be an “umbrella” diagnosis that encompasses many different mechanistic endotypes and clinical phenotypes, OA is also likely to have a variety of relevant altered molecular pathways underlying clinical heterogeneity(53–55). For example, while the majority of pediatric asthma patients are atopic(56), including in pediatric OA(57), atopy is not a uniform finding in OA. In order to optimize medical care for this complex disease, it is crucial to better understand the impact of OA on key immune pathways and on the functioning of immune cells and apply those mechanistic insights to optimizing therapeutic strategies.

In this review, we summarize recent work elucidating the mechanisms by which obesity impacts inflammation and immune function in asthma and thus contributes to the severe symptomatology observed in OA (Figure 1). We will focus on pediatric OA, but given the limitations of the literature and the importance of long-term impacts, we will incorporate data from adult human subjects as well as mouse models. It is important to note that when engaging in mechanistic studies of asthma or obesity that mouse models can be quite helpful. However, only a minority of mouse models of OA have defined mechanistic links between obesity and asthma and here we will focus on the subset of studies that include evaluation of the impact of obesity and asthma on pulmonary function in OA, non-obese asthma, non-asthmatic obesity and control cohorts (58–69) (Table 1).

Figure 1: Proposed Mechanisms Mediating OA in Children.

Pediatric OA is a complex, heterogenous disease that is likely explained by multiple mechanisms. There is evidence to support roles for obesity-associated changes to lung structure, cytokine expression, metabolite production and hormone secretion in worsening asthma severity.

Table 1: Summary of results from mouse models of OA.

that interrogate lung function in OA cohorts compared to healthy control, asthma-alone and obesity-alone cohorts. Up arrows (↑) indicate enriched populations, down arrows (↓) indicate less prevalent populations, sideways arrows (→) indicate no significant difference measured and double hyphens (--) indicate no data was reported for the given variable. Each color-coded row represents the pairwise comparison specified in the table legend (dark gray= OA vs healthy control; white= OA vs asthma alone, light gray= OA vs obesity alone). Asthma: A= Allergen used to induce asthma, B= Immunization protocol, C= Challenge protocol. Within the immunization protocol (Asthma, B) and challenge protocol (Asthma, C) description, s.c. = subcutaneous, i.n. = intra-nasal, i.t.= intra-tracheal, (w/v) = weight per volume. Diet Induced obesity: D= High-fat diet (HFD) vendor, E= Catalog number of HFD, F= Percent of energy derived from HFD, G=Number of weeks on HFD. Pulmonary Function: AHR= Airway Hyperresponsiveness, AR= Airway Remodeling. Immune Response: Eos= Eosinophils, Neu= Neutrophils, MΦ= Macrophage.

Publication		Mouse Model				Pulmonary Function		Immune Response					Adipokines
First Author	Year	Sex	Strain	Asthma	Diet Induced Obesity	AHR	AR	T cells	Cytokines	Eos	Neu	MΦ	Leptin	Adiponectin
Lee [89]	2019	F	C57BL/6	A) OVA B) 25μg s.c. (2x) C) 20μg/50μl i.n. (4x)	D) Harlan Laboratories E) D12492 F) 60% G) 12	↑	↑	--	Lung: ↑ IL-17 BALF: ↑ IL-4/5/13/17; ↓IFNγ Serum: ↑ IL-17	Lung: ↑1 BALF: ↑	Lung: ↑1 BALF: ↑	BALF: ↑	BALF: ↑ Serum: ↑	BALF: → Serum: →
						→	→	--	Lung: → IL-17 BALF: →IL-4/13/17; ↓IFNγ; ↑ IL-5 Serum: ↑ IL-17	Lung: →1 BALF: →	Lung: →1 BALF: →	BALF: →	BALF: ↑ Serum: ↑	BALF: → Serum: →
						--	--	--	--	--	--	--	--	--
Schröder [90]	2019	F	C57BL/6JRj	A) OVA B) 150μg/1mg i.p. (2x) C) 1.5% i.t.(4x)	D) Ssniff EF R/M E) TD88137 F) 42% G) 12	↑	↑	Lung: ↑ CD4+ BALF: ↑ T cells		BALF: ↑	BALF: ↑	BALF: →	--	--
						↓	→	Lung: → CD4+ BALF: ↓ T cells		BALF: →	BALF: ↓	BALF: →	--	--
						↑	↑	Lung: ↑ CD4+ BALF: → T cells		BALF: ↑	BALF: ↑	BALF: →	--	--
Zeng [91]	2019	M	C57BL/6	A) OVA B) 10μg i.p. (2x) C) 1 mg/mL aerosol (30 min daily × 7d)	D) MediScience Ltd. E) MD12032 F) 45% G) 16	↑	↑	Lung: ↑ Th17	Lung1: ↑ IL17A, RORγt Serum: ↑IL-1β/6/17A	--	--	--	--	--
						↑	↑	Lung: → Th17	Lung1: → IL17A, RORγt Serum: ↑IL-1β/6/17A	--	--	--	--	--
						↑	↑	Lung: → Th17	Lung1: → IL17A, RORγt Serum: ↑IL-1β/6/17A	--	--	--	--	--
*Chong [92]	2018	M/F	C57BL/6J	A) OVA B) 0.01% OVA i.p. C) 1% OVA aerosol (30 min daily × 8d)	D) MediScience Ltd. E) MD12032 F) 45% G) 12	↑	↑	--	--	BALF: ↑	BALF: ↑	--	--	--
						↑	↑	--	--	--	--	--	--	--
						↑	↑	--	--	BALF: ↑	BALF: ↓	--	--	--
Liang [93]	2018	F	C57BL/6	A) OVA B) 25μg i.p. (2x) C) 20μg/50μL i.n. (3x)	D) Harlan Laboratories E) D12492 F) 60% G) 12	↑	↑	--	BALF: ↑ IL-4/5/13/17	BALF: ↑	BALF: →	BALF: ↑	Serum: ↑	Serum: ↓
						↑	→	--	BALF: ↑ IL-4/5/17; → IL-13	BALF: ↑	BALF: →	BALF: ↑	Serum: ↑	Serum: ↓
						→	↑	--	BALF: ↑ IL-4/5/13/17	BALF: ↑	BALF: →	BALF: ↑	Serum: ↑	Serum: ↑
Zeng [94]	2018	M	C57BL/6	A) OVA B) 10μg i.p. (2x) C) 1 mg/mL aerosol (30 min daily × 7d)	D) MediScience Ltd. E) MD12032 F) 45% G) 16	↑	↑	Spleen: ↑Th17	Lung1: ↑IL-17A Serum: ↑IL-17	--	--	--	--	--
						↑	↑	Spleen: ↑Th17	Lung1: ↑IL-17A Serum: ↑IL-17	--	--	--	--	--
						↑	↑	Spleen: ↑Th17	Lung1: ↑IL-17A Serum: ↑IL-17	--	--	--	--	--
*Everaere [101]	2016	--	C57BL/6J	A) HDM B) 5 IR i.n. (1x) C) 5 IR i.n. (5x)	D) Research Diet Inc. E) D12492 F) 60% G) 12	↑	↑	Lung: ↑ CD4+, IL13+CD4+, IL-17A+CD4+	Lung2: ↑IL-1β/4/13/17A/23/33 VAT2: → IL-1β/17A, IFNγ; ↓IL-5/33	BALF: ↑	BALF: →	BALF: →	--	--
						↑	↑	Lung: ↑ CD4+, IL13+CD4+, IL-17A+CD4+	Lung2: ↑IL-1β/4/13/17A/23/33 VAT2: → IL-1β/17A, IFNγ; ↓IL-5/33	BALF: ↑	BALF: →	BALF: →	--	--
						↑	↑	Lung: → CD4+, IL13+CD4+, IL-17A+CD4+	Lung2: ↑IL-4/13/17A/33; → IL-1β/23 VAT2: → IL-1β/17A, IFNγ; ↓IL-5/33	BALF: ↑	BALF: →	BALF: →	--	--
Chen [95]	2015	--	BALB/c	A) OVA B) 25μg i.p. (3x) C) 6% (w/v) aerosol (daily × duration of diet > 12 weeks)	D) Research Diet Inc. E) D12451 F) 45% G) 12	↑	↑	--	Serum: ↑IL-4; ↓IFNg	Lung: ↑	--	--	--	--
						↑	↑	--	Serum: →IL-4; ↓IFNg	Lung: ↑	--	--	--	--
						↑	↑	--	Serum: ↓IL-4; IFNg	Lung: ↑	--	--	--	--
Kim [96]	2015	F	C57BL/6	A) OVA B) 100μg i.p. (2x) C) 10μg i.n. (3x)	D) Research Diet Inc. E) D12492 F) 60% G) 16	↑	↑	--	BALF: ↑ TNFα Serum: ↑ TNFα	BALF: ↑	BALF: ↑	--	Lung: → Serum: →	Lung: → Serum: →
						↑	→	--	Lung: ↑ TNFα BALF: ↑ TNFα Serum: ↑ TNFα	BALF: →	BALF: →	--	--	--
						↑	↑	--	BALF: ↑ TNFα Serum: ↑ TNFα	BALF: ↑	BALF: ↑	--	--	--
Jung [98]	2013	F	C57BL/6J	A) OVA B) 25μg s.c. (5x) C) 20μg/50μL i.n. days 27, 29, 31 and then twice a week until week 18	D) Feedlab E) -- F) 45% G) 16	↑	↑	--	Lung2: ↑ VEGF, TNFα, TGFβ BALF: ↑ VEGF, TNFα, TGFβ	BALF: ↑	BALF: ↑	BALF: ↑	Lung: ↑	Lung: ↓
						↓	↑	--	Lung2: → VEGF, TGFβ; ↑ TNFα BALF: ↑ TNFα; → VEGF; ↓ TGFβ	BALF: ↑	BALF: →	BALF: →	Lung: ↑	Lung: ↓
						↑	↑	--	Lung2: → VEGF, TGFβ, ↑ TNFα BALF: ↑TNFα; →VEGF; ↓TGFβ	BALF: ↑	BALF: ↑	BALF: ↑	Lung: ↓	Lung: ↑
Ryu [99]	2013	F	C57BL/6J	A) OVA B) 25μg s.c. (5x) C) 20μg/50μL i.n. days 27, 29, 31 and then twice a week until week 18	D) Feedlab E) -- F) 45% G) 16	↑	--	--	Lung2: ↑ VEGF, TNFα, TGFβ BALF: ↑ VEGF, TGFβ	BALF: ↑	BALF: ↑	BALF: ↑	Lung2: ↑	Lung2: →
						↓	--	--	Lung2: ↑ VEGF, TNFα, TGFβ BALF: ↑ TGFβ; → VEGF	BALF: →	BALF: →	BALF: →	Lung2: →	Lung2: →
						↓	--	--	Lung2: ↑ TNFα, TGFβ; ↓ VEGF BALF: ↓TGFβ, VEGF	BALF: ↑	BALF: →	BALF: ↑	Lung2: →	Lung2: →
Ge [97]	2013	M	C57BL/6J	A) CRA B) 10μg s.c. + 10μg i.p (1x), 1μg s.c. (1x) (2x) C) 1μg i.n. (1x) then 4μg i.n. (1x)	D) Bio-Serv E) F3282 E) 60% F) 16	↑	↑	--	Lung: ↑ IL-5, → IFNγ, IL-2/4/13, ↓ TNFα,	Lung: ↑ BALF: ↓	BALF: ↓	BALF: ↑	--	--
						↑	↓	--	Lung: → IL-4; ↓ IFNγ, TNFα, IL-2/5/13	Lung: ↓ BALF: ↓	BALF: ↓	BALF: ↑	--	--
						↑	↑	--	Lung: ↑ IL-5; → IFNγ, TNFα, IL-2/4/13	Lung: ↑ BALF: ↑	BALF: ↑	BALF: ↑	--	--

Table Legend

Obese Asthma vs Healthy Control

Obese Asthma vs Asthma Alone

Obese Asthma vs Obesity Alone

Structural Alterations in Lung Parenchyma and Function

Obesity is linked to reductions in pulmonary function in both adult and pediatric populations which could be secondary to asthma or could, in part, be independent of asthma. While obese adults typically demonstrate a restrictive deficit in pulmonary function, characterized by a reduction in forced vital capacity (FVC) in the presence of a normal ratio between forced expiratory volume in 1 second (FEV₁) and FVC (70,71), obese children typically demonstrate an obstructive pattern of pulmonary dysfunction characterized by increases in both FEV1 and FVC, but a lower FEV1/FVC ratio (72–74). Diminished pulmonary function in obese children may be partially a reflection of an altered relationship between lung parenchyma and airway caliber, known as dysanapsis. In the setting of dysanapsis, the growth of lung parenchyma is out of proportion to airway caliber, with normal measurements of FEV1 and FVC in the presence of an abnormal FEV1/FVC ratio(71). Children classified as overweight or obese were more likely to have airway dysanapsis, independent of asthma status (71). Importantly, in children with OA, dysanapsis was closely associated with increased severity of asthma symptoms and poor asthma control (71). Ekström et al. recently found the same pattern of airway resistance associated with persistent pediatric weight gain(75). To our knowledge, dysanapsis has not yet been evaluated in mice. A pathophysiological link between obesity and lung parenchymal growth (out of balance with airway caliber) has not been established and those mechanisms and potential connections to inflammation and immune dysregulation require further study.

Central Adiposity is Associated with Impaired Pulmonary Function and Increased Visceral Adipose Tissue

The quantification of extent and impact of obesity is challenging and age dependent. It is well-established that obesity, typically assessed in adults and children using body mass index (BMI), is an independent predictor of asthma risk (11,12,14–18,21,49,51,76). Children are considered overweight at BMI > 85^th percentile and obese at BMI > 95^th percentile for sex and age. However, in recent years the clinical relevance of BMI as a predictor of asthma risk has been called into question(77–79). BMI is a calculated assessment of the relationship of weight to height and therefore cannot not differentiate between muscle mass and adipose tissue, nor can it account for body fat distribution. This may explain why some authors have reported no association between obesity and asthma incidence(72,80–82). It is increasingly appreciated that specific patterns of body fat distribution, mainly abdominal obesity (also known as central obesity), may be a better predictor than BMI of pediatric asthma incidence (83–89). The mechanistic relationship between abdominal obesity and asthma remains unclear, especially in pediatric OA. However, there is evidence that poor lung function in asthmatic adults can be attributed to increases in visceral adipose tissue (VAT) (90). Furthermore, increases in VAT, as measured by magnetic resonance imaging or dual-energy x-ray absorptiometry, are associated with impaired pulmonary function and increased asthma risk in pediatric OA (83,89). Given the highly immunologically and metabolically active nature of VAT(9), and its role as a niche for key immune cells(91), it has also been proposed as an important mediator in OA (85). Moreover, several recent studies have reported that obesity-associated inflammatory signaling alters the inflammatory characteristics of VAT (9) in both mice(92–94) and humans (34,95,96). The potential roles of dysregulated VAT resident immune cells and peripheral immune cells impacted by the inflammatory environment in OA is discussed below (in “Immune Dysregulation in OA”).

The Role of Sex Hormones and Pubertal Timing

There are clear connections among sex hormones and asthma and obesity and pubertal timing. First, there is a well-known peripubertal shift in sex bias in asthma incidence(97). Specifically, in pre-pubescent populations asthma and other atopic diseases are more prevalent in males than females, but this trend is reversed post-puberty (97–100). This is seen in both more boys “growing out” of school-age asthma diagnoses, as well as late childhood (97,101) and adult-onset (102,103) asthma being more prevalent in females. Recent investigations have demonstrated potential roles for sex hormones in mediating asthma pathogenesis. For example, early pubertal onset is associated with increased asthma incidence (104,105). The mechanisms underlying this phenomenon remain unclear.

Obesity also has clear impacts on the hormonal state of the individual. Pre-pubescent rapid weight gain has been proposed to accelerate pubertal onset which may then hasten or otherwise encourage the development of asthma (106). A growing body of literature reports that early puberty appears to be correlated with the development of asthma in obese girls (107). A recent retrospective cohort study demonstrated pre-pubescent obesity conferred the highest risk of asthma development (108). Premenarchal females demonstrated an increased risk of developing obesity-related asthma compared to pre-pubertal males. In contrast, a separate study an increase in asthma risk in obese children of both sexes with early puberty (105). Recently, it was shown that in children in the Severe Asthma Research Program (SARP) increased serum androgen was correlated with improved lung function in boys, whereas increased serum estrogen was correlated with reduced lung function in girls (109). A separate population-based study of hormone levels in adult OA patients demonstrated that in obese women, but not non-obese women, increased serum levels of testosterone were associated with decreased asthma risk (110). This supports previous findings suggesting that sex hormones are potent modifiers of asthma and are influenced by obesity (111).

While female sex hormones are generally associated with increased airway inflammation and male sex hormones associated with decreased airway inflammation(112) in human studies, estrogen (113–117) and androgens, including testosterone (118–121), have each demonstrated protective (113–115,118,121) and pro-inflammatory (114–117,119) roles in mouse models of asthma. To our knowledge, only one study has been published that attempts to elucidate a mechanistic link between sex hormones and OA in mice, wherein estrogen mitigated airway inflammation by downregulating NLRP3 activation(122).

Overall, these data highlight the need for improved understanding of immunomodulatory capabilities of estrogen and testosterone, as well as other sex hormones, and the resulting mechanisms by which obesity may alter pubertal timing and affect both asthma onset and severity.

Immune Dysregulation in OA

Asthma and obesity are both chronic states of systemic, low-grade inflammation and have the ability to disrupt normal control points in a wide array of networks in our core physiological systems, ranging from the immune system to the cardiovascular and endocrine systems. In obesity(9,123) and asthma separately(124–129), and in their intersection in OA(34,130), there are alterations in adipokines (e.g. leptin)(124,130), chemokines(127), cytokines(34,125,128), and both innate(126,129) and adaptive cellular immune responses(34,123,129). In addition, there are well known alterations in the serum metabolites that bathe our circulating immune cells (e.g. glutamate(131) and short chain fatty acids(132)) as well as changes in the microbiome that are at least partially responsible for producing those altered metabolite levels(133)). All of these components exist in a complex network, which is carefully balanced. In obesity and asthma individually, there is evidence that this network has been disrupted and in OA we see evidence of immunometabolic dysfunction across human and mouse systems (Tables 1 and 2).

Table 2: Impact of OA on human immune cell subsets in adults and children.

Up arrows (↑) indicate enriched populations, down arrows (↓) indicate less prevalent populations, sideways arrows (→) indicate no significant difference measured for each comparison specified in the column header. Italicized entries indicate results from adult studies and non-italicized entries are from pediatric studies. OA = obese asthma, A= asthma (non-obese), O= obese (non-asthma), HC= healthy control (non-asthma, non-obese).

			Human Obese Asthma
Results			OA vs HC	OA vs A	OA vs O
Immune Function	Innate Immune Cells	Eosinophils		↑(143) submucosal →(143) sputum and blood	↑(161)
		Monocytes	CD14+CD16- ↓(141) CD14dimCD16+ ↓(141)
	Adaptive Immune Cells	CD4 T cells	→(128)	→(162)	→(162)
			→(163)	→(155,163)	→(163)
		Th1	↑(140,141)	↑(140,141)
		Th2		↓(140,141)
		Treg	↑(163)	↑(163)	↑(163)
	IgE				↑(161)
	Type 2 cytokines (serum)	IL-4	→(140)	→(140,142,164) ↓(165)	→(140,142,166)
		IL-5	→(140)	→(140,164) ↑(143) sputum	→(140)
		IL-13	→(140)	↓(140,164)	→(140)
	Type 1 cytokines (serum)	IFN-g	↑(165) →(140,141) ↓(142)	↑(165) →(140–142,164)	→(140–142)
		TNF-α	↑(140) →(127)	→(140)	→(140)
		IL-6	↑(140)	→(140,164)	→(140)
		IL-8		↑(164)
	Adipokines	Leptin	↑(165) →(140,166)	↑(140,141,165–167) ↑(166)	→(140,166)
		Adiponectin	→(161)	→(161)	→(161)
Pulmonary Function		FEV 1 /FVC	→(161)	↓(140) →(50,156,162,165)	↓(140) →(161)

Systemic inflammation is typically measured by acute-phase reactants (e.g. C-reactive protein (CRP), serum amyloid A (SAA), interleukin 6 (IL-6) and fibrinogen), which were recently reported to be significantly increased in the serum of OA and obese adults(134,135). Interestingly, SAA, but not CRP, has previously been linked to allergic airway inflammation in human adults (136). In addition, critical roles for SAA in mediating inflammatory responses have been shown in mouse models of asthma(137,138) and obesity(139,140). It is possible that these acute phase reactants, including SAA, may have direct mechanistic roles in OA and should be explored further.

Adipokine dysregulation, including altered leptin, is also a feature of OA. Obesity is associated with elevated serum leptin, which has many effects on immune function(141). Increases in serum leptin were associated with increased atopy in a cohort of children with allergic rhinitis, a related atopic condition (142). Leptin is known to impact immune function in pleotropic ways, including being a neutrophil chemoattractant(143), altering neutrophil chemotaxis and superoxide production in adult OA (144) and is connected to eosinophilic inflammation (145). Additionally, there is evidence that production of leptin by pulmonary tissue, as opposed to the systemic increases in leptin reported in obesity, enhances airway eosinophilia (146). Finally, leptin is known to have direct effects on immune cell function, particularly T cells(147–149), and the alterations in leptin level may have effects on this key anti-viral cell in OA as well(130,150).

Within the myriad of subsets of lymphocytes, CD4 T cells play an important role in guiding the character of the adaptive immune response and produce key cytokines driving that process. It is important to link our understanding of the more easily accessible peripheral blood immunophenotype(151,152) to the more challenging to access immunophenotype of the target tissues (e.g. adipose tissue)(95,153). In the peripheral blood, the inflammatory state triggered by obesity is classically thought to skew CD4+ T helper cells towards a T helper type 1 cell (Th1) phenotype(152,154,155). Allergic (or atopic) asthma, which accounts for more than half of all asthma cases in the United States(150), is classically associated with type 2 immune responses(156). Atopic asthma is linked to type 2 immunity, including alterations in the three main implicated cell types: eosinophils, type 2 Innate lymphoid cells (ILC2s) and CD4 T helper type 2 cells (Th2 cells). Here, we focus on the nature of the immune response in OA. Early studies showed that patients with OA and early onset asthma were more likely to be atopic (and thus likely have type 2 immune skewing) and more likely to have severe asthma(54). Using unsupervised clustering of asthmatic patients, two separate studies a cluster of older, obese, non-eosinophilic female asthmatics was identified (157,158). However, many of the OA patients were found outside this cluster, highlighting again that OA contains multiple endotypes (159). After those initial studies, with very limited immunophenotyping, peripheral blood studies in OA have provided a mixed picture, with evidence of increased (154,160), equivalent(160) and reduced(161) Th1-skewing, as well as evidence for decreased (160) and equivalent (161) Th2-skewing in OA patients compared to asthma alone. To add to the complexity in OA peripheral blood, sputum and endobronchial biopsies, in some settings, show increased eosinophil-relevant IL-5 and eosinophilia respectively in a subset of OA patients(162). Allergic asthma is the predominant form of asthma in children and may be underappreciated as a key endotype of OA, especially in pediatrics. Of note, there are racial and ethnic backgrounds wherein OA is known to be strongly associated with atopy, including in Puerto Rican children(20). Overall, there is not a monomorphic picture of CD4 T cell differentiation in OA, neither Th1 nor Th2, but the impression that there are multiple immune profiles possible in OA.

At the core of the symptomatology of OA is the severity of exacerbations, which are most often caused by viral respiratory infections. CD8 T cells play a key role in combating viral infections and there is recent evidence that obesity may alter their function. Specifically, there is an increase in inhibitory receptor expression (e.g. PD-1) in CD8 T cells from obese patients(163), suggestive of immune dysregulation in these patients. In the setting of persistent antigenic stimulation and chronic inflammation (e.g., chronic viral infection or malignancy) T cells can become exhausted, with altered expression of cell surface markers (including inhibitory receptors), transcriptional pathways and function(164). One of the recent advances in cancer therapy is the use of biologics targeting inhibitory receptors on immune cells to reinvigorate exhausted T cells(164) and improve immune targeting of tumors. Consistent with increased inhibitory receptor levels in obesity, obese patients with melanoma had better responses to these strategies (165,166). Further, should the immune dysregulation in CD8 T cells in obesity be similar to exhaustion, we could also expect concomitant altered mitochondrial function which has been shown in human T cell exhaustion(167).The impact of OA on CD8 T cell immunometabolic function and immunophenotype in the periphery has not yet been assessed in OA, though our group is studying these questions in humans and mice.

Metabolomics of obese and asthmatic patient samples, including from serum/plasma, breath condensate and urine(168–173), have identified altered water soluble and lipid metabolites. There are clear alterations in peripheral metabolites in obesity, including altered short chain fatty acids (SCFA) and water-soluble metabolites (e.g. elevated glutamate)(170–174). These metabolites may be altered in subject serum by diet directly or by alterations of the microbiome in content and/or function by inflammation and/or diet. In diet induced obesity in mice, high fat diet has been shown to yield higher acetate with blockade of allergic asthma and addition of propionate to mouse diet has been shown to impair Th2 differentiation and atopy(175). In addition, characterization of the adult respiratory metabolome delineated a metabolic phenotype in OA(176). This is relevant to immune function in OA because it is clear that SCFA and water soluble metabolites can directly skew T cell differentiation (e.g. elevated acetate and increased mouse Th17 differentiation(177)) and activation, including impacts on infection responses (e.g. acetate and influenza responses(178)). Thus, both water soluble and lipid metabolites may play important roles in the known increased severity of viral induced asthma exacerbations in OA via altered T cell function.

Beyond enumerating immune cell subsets and their individual functional states, transcriptional and epigenetic studies can guide our interpretation of immune profiling and immunometabolic dysregulation in OA. Work from Rastogi et al has shown altered methylation in both activation associated (PI3K pathway) and Th1 associated genes in pediatric OA(179). The former could possibly foster immune dysregulation via mimicry of persistent immune cell activation(164). Subsequent work in peripheral blood transcriptional studies in pediatric OA (both whole blood and CD4 T cells (155,180) and sputum cells from adult OA subjects(129)) has yielded evidence of complex immune dysregulation in these patients. Peripherally, there was evidence of altered CDC42 pathway signaling(152,155), involved in various aspects of CD4 T cell activation and differentiation(155), as well as altered NFκB, integrin and Hedgehog signaling in whole blood(180). In the target tissue, sputum cell RNA sequencing demonstrated a number of transcriptomic alterations, including in a gene module consistent with CTL function(181). This module was inversely correlated with BMI and included a number of markers of both CD8 T cell function (e.g. Granzyme B, IFN-γ, etc) and T cell exhaustion (e.g. TOX). Of note, many markers of CTL function are seen in exhaustion in a dysregulated pattern(167). However, it was unclear whether this suggests that CTL function was impaired in OA (given low gene module activity in OA) or whether an exhausted-like state was instead diminished in OA. Further studies of T cell signaling and activation pathways in OA are needed, including how they connect to clinical outcomes.

With regards to evidence of dysfunction, beyond alterations in cytokines, adipokines, metabolite and immune cell subset and function, we can look to infection responses as an evaluation of cellular function. Both H1N1 influenza(182) and COVID-19(183) have shown increased morbidity and mortality in obese adults and children, and COVID-19, unexpectedly, does not seem to show increased morbidity and mortality in atopic asthma(184). We currently lack information about the impact of OA on COVID-19 in humans and more broadly, additional insight will be gained by studies of baseline immune dysregulation and infection responses in mouse models of OA.

Altering weight and recovering immune function

What is the evidence that obesity is a modifiable factor in OA whose improvement can lead to clinical change? There is evidence that surgical weight loss interventions in adults (27,32,37–40) and non-surgical interventions in both adults (35,36) and children (29–31,33,34,41) lead to an improvement in asthma symptoms. While many of these studies do not report on pro-inflammatory biomarkers (27,29–32), there is evidence that weight loss may lead to a reduction in systemic inflammatory markers in children (34,41) and adults (35,40). However, the influence of bariatric surgery on inflammation and immune function is not well understood and much remains to be learned, especially in children. Some authors report improved asthma control in both children (33) and adults (36) without concomitant improvement in pro-inflammatory markers. Moreover, the efficacy of weight loss interventions in ameliorating asthma symptoms is reportedly influenced by atopy (37,39) and metabolic syndrome (38). To our knowledge, only two studies have investigated the effects of weight loss on systemic inflammation in pediatric OA (34,41). In these studies, non-surgical weight loss reduced systemic inflammatory markers in OA children compared to control groups. In a recent report on obese (non-asthmatic) children, weight loss following lifestyle intervention led to a reduction in serum markers of inflammation compared to baseline(185). The above data suggest the pro-inflammatory obesogenic environment worsens asthma and reductions in body weight can improve asthma control, but the underlying mechanisms warrant further investigation. Our group and others are learning more about alterations in pre/post bariatric surgery immune networks using studies of peripheral blood and adipose tissue.

CONCLUSION

Pediatric OA is a complex condition at the intersection of two chronic inflammatory diseases. Recent work has focused on structural alterations both in lung structure and location of adipose tissue, dysregulation of hormonal and immunometabolic function, with poorly characterized connections among these systems. Recent multi-modal studies in adult and pediatric subjects, with future work planned in human cells and mouse models, bring us closer to the goal of improved therapeutic targeting in these complex patients. However, there remains a dearth of immunometabolic data, especially in pediatric OA, and much remains to be done.

Key Points.

• OA is a heterogenous disease comprising multiple clinical phenotypes that are not likely to be explained by a singular mechanism and may be affected by race, age, sex and atopic state, among other phenotypes.

• There are significant immunometabolic and structural alterations in pediatric OA that remain incompletely understood.

• Mechanistic investigations into pediatric OA, especially as it relates to immune dysfunction and response to viral respiratory infections, are of fundamental importance especially in the era of COVID-19 wherein obesity is a clear risk factor for morbidity and mortality.

Abbreviations:

OA

Obese Asthma

AHR

Airway Hyperresponsiveness

ATM

Adipose Tissue Macrophages

BMI

Body Mass Index

FE_NO

Fractional exhaled nitric oxide

SARP

Severe Asthma Research Program

FVC

Forced Vital Capacity

FEV₁

Forced Expiratory Volume in 1 Second