A Comprehensive Review of The Impact of Obesity on Plasma Cell Disorders

Abstract

Multiple myeloma (MM) remains an incurable plasma cell malignancy. Although little is known about the etiology of MM, several metabolic risk factors such as obesity, diabetes, poor nutrition, many of which are modifiable, have been linked to the pathogenesis of numerous neoplasms including MM. In this article, we provide a detailed summary of what is known about the impact of obesity on the pathogenesis of MM, it’s influence on outcomes in MM patients, and discuss potential mechanisms through which obesity is postulated to influence MM risk and prognosis. Along with advancements in treatment modalities to improve survival in MM patients, focused efforts are needed to prevent or intercept MM at its earliest stages. The consolidated findings presented in this review highlight the need for clinical trials to assess if lifestyle modifications can reduce the incidence and improve outcomes of MM in high-risk populations. Data generated from such studies can help formulate evidence-based lifestyle recommendations for the prevention and control of MM.

Introduction

Multiple myeloma (MM) is the second most common hematologic malignancy characterized by neoplastic proliferation of plasma cell clones associated with overproduction of monoclonal immunoglobulins (1). It remains incurable despite many therapies approved in the last decade which improve survival.

In the US, the prevalence of obesity [body mass index (BMI) ≥30] and severe obesity (BMI ≥40) among adults (aged 20 years and over) has increased dramatically in recent decades. Indeed, from 1999–2000 through 2017–2018, the prevalence of obesity increased from 30.5% to 42.4% and that of severe obesity increased from 4.7% to 9.2% among adults (2). Similar rising trends in obesity (BMI ≥ age- and sex- specific 95^th percentile of the 2000 Centers for Disease Control and Prevention growth charts) were noted in youth (aged 2–19 years) from 1999–2000 through 2015–2016 (3). The incidence of numerous obesity-related cancers, including MM, has increased in younger adults (25–49 years) from 1995–2014, with the largest annual percent change in the 30–34 years age group (2.21% increase) (4). These findings in the light of the rising prevalence of obesity across all age groups highlight the need for a closer review of the current literature evaluating the association between obesity and MM (5). In this review, we will discuss the available evidence for obesity’s role in the etiology and pathogenesis of plasma cell disorders as well as potential mechanisms.

Obesity and MGUS

The first study suggesting a link between obesity and monoclonal gammopathy of undetermined significance (MGUS) was published in 2010. In that study, the authors report screening 1 996 black and white women for MGUS and found that obese individuals are 1.8 times more likely to develop MGUS than those with a normal BMI (6). Complementary analyses using data from the National Health and Nutritional Examination Survey (NHANES) study (cross-sectional study involving 12 482 persons; 365 MGUS cases) and Age, Gene/Environment Susceptibility-Reykjavik Study (AGES-RS) (prospective cohort study with 5 725 participants; 575 MGUS cases) saw a trend towards increased risk for MGUS with increased BMI but effect estimates were not statistically significant (7, 8). Of note, the AGES-RS study looked at 11 different measures of obesity in their analysis, including weight (kg), baseline BMI (kg/m²), percent body fat (%), fat (kg), total body fat (cm²), visceral fat (cm²), subcutaneous fat (cm²), two versions of abdominal circumference (cm), self-reported lifetime maximum weight and midlife BMI, and found no significant association (8). Some limitations of this study, however, were a possibility of selection bias (mean age of cohort was 77 years implicating selection of a healthier population) and that Iceland has an exclusively white population and results may not be applicable to other races. Thus, based on current evidence from large population-based studies (Table 1), the association between obesity and risk of MGUS is controversial. Additional studies addressing the above limitations would be instrumental in further understanding the role of obesity as a risk factor for MGUS development.

Table 1:

Obesity and Monoclonal Gammopathy of Undetermined Significance

Cohort/ Location	Study Design	N	Outcome	BMI (kg/m2)	Effect Estimate	95% CI	Study
Obesity and the risk of MGUS
Southern Community Cohort Study (SCCS)/ Southeastern USA	Cohort	1996 women; 60 MGUS	MGUS	>30	OR 1.80	1.03–3.14	Landgren et al Blood 2010
National Health and Nutritional Examination Survey (NHANES), USA	Cross-sectional study	12,482 persons; 365 MGUS	MGUS		Adjusted prevalence (%):	Standard Error:	Landgren et al Leukemia 2014
				<25	1.99	0.27
				25–30	2.43	0.25
				>30	2.72	0.32
					Ptrend 0.20
Age, Gene/ Environment Susceptibility-Reykjavik Study (AGES-RS)/ Reykjavik, Iceland	Prospective Cohort	5725 persons, 575 MGUS	MGUS	Midlife ≥25kg/m2	OR 1.15	0.90–1.45	Thordardottir et al Blood Advances 2017
			LC-MGUS		OR 1.10	0.86–1.41
Obesity increases the risk of transformation of MGUS to MM
Age, Gene/ Environment Susceptibility-Reykjavik Study (AGES-RS)/ Reykjavik, Iceland	Prospective Cohort	5725 persons, 575 MGUS→ 18 MM; 11 lymphoproliferative diseases (LPD) within 8 years	MGUS→ MM and other		HR 2.66	1.17–6.05	Thordardottir et al Blood Advances 2017
US Veterans Health Administration database	Retrospective Cohort	7878 MGUS (97% men)→ 329 MM	MGUS→ MM	25–29.9	HR 1.55	1.16–2.06	Chang et al JNCI 2017
				≥30	HR 1.98	1.47–2.68

Abbreviations - BMI: Body-Mass Index; 95%CI: 95% Confidence Interval; MGUS: Monoclonal Gammopathy of Undetermined Significance; LC-MGUS: Light Chain MGUS; MM: Multiple Myeloma; OR: Odds Ratio; HR: Hazard Ratio

Obesity increases the risk of transformation of MGUS to MM

Two large studies that assessed the impact of BMI on the risk of transformation of MGUS to MM found that overweight and obese individuals with MGUS were at a greater risk for progression to MM. Patients in the AGES-RS study (study characteristics outlined above) with midlife BMI ≥25 kg/m2 (mean age at time of “midlife” calculation 53.3 years for women and 52.1 years for men) had a 2.7 fold higher risk (95%CI 1.17–6.05) to develop MM and other lymphoproliferative diseases than normal weight individuals (8). These results were consistent with the US Veterans Health Administration Study (retrospective cohort of 7 878 MGUS cases followed prospectively for median duration of 68 months; 329 progressed to MM) that also showed an increased risk of progression to MM for overweight (Hazard Ratio, HR 1.55; 95%CI 1.16–2.06) and obese patients (HR 1.98; 95%CI 1.47–2.68) (9). BMI is a commonly used surrogate for obesity, but it does not provide detailed information regarding the distribution of body adiposity. A small cross sectional study of 40 MGUS and 32 MM patients found that MM patients had higher abdominal adipose tissue cross sectional areas and higher adipose tissue metabolic activity compared to patients with MGUS, thus suggesting that these adipose tissue parameters may play a role in the malignant transformation of MGUS to MM (10). This evidence (Table 1) suggests that obese patients are about twice as likely to transform from MGUS to MM.

Obesity and the risk of MM

Studies evaluating the association between obesity and risk of MM have been outlined in Table 2. A large prospective cohort study of hospitalized male U.S veterans (3 668 486 whites; 832 214 blacks) reported an increased risk of MM in obese white men (Relative Risk, RR 1.22; 95%CI 1.05–1.40) and obese black men (RR 1.26, 95%CI 1.02–1.56) as compared to non-obese white and black men respectively (11). The Iowa Women’s Health Study followed a prospective cohort of 37 083 post-menopausal women for 16 years and identified 95 cases of MM with increased incidence of MM in overweight and obese individuals as measured by various anthropometric parameters. The rate ratios (RR) for various parameters were – BMI ≥30 kg/m²; RR 1.5 (95%CI 0.92–2.6), weight ≥161 lbs; RR 1.9 (95%CI 1.1–3.4), waist circumference ≥36.26 inches; RR 2.0 (95%CI 1.1–3.5), as well as hip circumference ≥42.26 inches; RR 1.8 (95%CI 1.0–3.0) (12). Similarly, many other studies have demonstrated an increased incidence of MM with increasing BMI (13–16). For example, a meta-analysis of 10 prospective observational studies which collectively included 5 171 374 individuals evaluated the association between BMI and cancer risk found an excess risk for development of MM in both men (RR 1.11; 95%CI 1.05–1.18 per 5 kg/m² increase in BMI) and women (RR 1.11; 95%CI 1.07–1.15 per 5 kg/m² increase in BMI) (17). Analysis from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial which enrolled 142 982 participants at 10 centers in the U.S in a randomized, controlled trial and identified 243 cases with plasma cell neoplasms, revealed increased MM risk with elevated BMI at baseline (HR 1.69; 95%CI 1.18–2.41 for BMI ≥30 kg/m²) and at age 20 years (HR 3.08; 95%CI 1.71–5.54 for BMI ≥30 kg/m²) (18). Findings of the National Institutes of Health-AARP Diet and Health Study, a large prospective cohort study in the U.S including 485 049 participants (489 MM cases) demonstrated that excess body weight, both in early and late adulthood was associated with increased MM risk (at cohort entry: HR 1.10, 95%CI 1.00–1.22; at age 50 years: HR 1.14, 95%CI 1.02–1.28; at age 35 years: HR 1.20, 95%CI 1.05–1.36 and at age 18 years: HR 1.13, 95%CI 0.98–1.32 per 5 kg/m² increase in BMI) (19).

Table 2:

Obesity and Multiple Myeloma

Cohort/ Location	Study Design	N	Outcome	BMI (kg/m2)	Effect Estimate	95% CI	Study
Obesity and the risk of development of MM
Cancer registries from the Georgia Center for Cancer Statistics, the Metropolitan Detroit Cancer Surveillance System and the New Jersey Cancer registry, United States	Case-Control	White Race - 1086 Controls; 346 MM	MM	White: <18.5	OR 0.6	0.2–2.3	Brown et al Cancer Causes Control 2001
				18.5–24.9	OR 1.0
				25–29.9	OR 1.5	1.1–2.0
				≥30	OR 1.9	1.2–3.1
		Black Race - 903 Controls; 193 MM	MM	Black: <18.5	OR 1.1	0.3–4.2
				18.5–24.9	OR 1.0
				25–29.9	OR 1.3	0.9–1.8
				≥30	OR 1.5	0.9–2.4
Veterans affairs hospital across US	Prospective Cohort	4.50 Million	MM	Obese	White men: RR 1.22	1.05–1.40	Samanic et al Cancer Causes and Control 2004
					Black men: RR 1.26	1.02–1.56
Iowa Women’s Health Study	Prospective Cohort	37,083 participants; 95 MM cases	MM	25–29.9	Rate Ratio 1.3	0.78–2.0	Blair et al Epidemiology 2005
				≥30	Rate Ratio 1.5	0.92–2.6
Sweden	Prospective Cohort	362,552 male participants; 452 MM cases	MM	25–29.9	RR 0.96	0.79–1.16	Samanic et al Cancer Causes Control 2006
				>30	RR 0.58	0.37–0.93
Million Women Study, UK	Prospective Cohort	1,222,630 women; 491 MM cases	MM	<22.5	RR 0.8	0.64–1.0	Reeves et al BMJ 2007
				22.5–24.9	RR 1.0	0.84–1.19
				25–27.4	RR 1.11	0.92–1.32
				27.5–29.5	RR 1.11	0.88–1.4
				≥30	RR1.16	0.95–1.42
Norwegian Cohort, Norway	Prospective Cohort	2,000,424 persons; 3,233 plasma cell neoplasms	MM	<18.5	RR 0.69	0.38–1.25	Engeland et al Am J Epidemiology 2007
				18.5–24.9	RR 1.0
				25–29.9	RR 1.14	1.06–1.22
				≥30	RR 1.28	1.10–1.47
Participants from the Construction Industry’s Organization for Working Environment, Safety and Health; Sweden	Prospective Cohort	336,381 male Swedish construction workers; 520 MM cases	MM	18.5–25	IRR 1.0		Fernberg et al Cancer Research 2007
				25.1–30	IRR 1.04	0.86–1.24
				>30	IRR 0.70	0.46–1.06
European Prospective Investigation into Cancer and Nutrition (EPIC)	Prospective Cohort	371,983 participants; 139 MM cases	MM	Men:			Britton et al Haematologica 2008
				Weight (kg) <72.7	RR 1.0
				72.7–79.8	RR 1.49	0.89–2.48
				79.9–87.7	RR 1.49	0.88–2.53
				≥87.8	RR 1.77	1.02–3.05
					Ptrend 0.06
				BMI (kg/m2) <25	RR 1.0
				25–29.9	RR 1.33	0.79–2.23
				≥30	RR 1.17	0.80–1.72
					Ptrend 0.26
				Women:
				Weight (kg) <72.7	RR 1.0
				72.7–79.8	RR 0.69	0.39–1.23
				79.9–87.7	RR 1.19	0.71–1.99
				≥87.8	RR 0.95	0.55–1.63
					Ptrend 0.62
				BMI (kg/m2) <25	RR 1.0
				25–29.9	RR 0.93	0.55–1.56
				≥30	RR 1.06	0.72–1.58
					Ptrend 0.89
Swedish Twin Registry and Finnish Twin cohort	Prospective Cohort	70,067 persons; 140 MM cases	MM	≤18.49	N/A		Söderberg et al Eur J Cancer 2009
				18.5–24.99	RR 1.0
				25–29.99	RR 1.0	0.7–1.5
				≥30	RR 2.1	1.1–3.7
The Netherlands Cohort Study on Diet and Cancer	Prospective Cohort	120,852 participants; 4774 sub-cohort members; 279 MM cases	MM	BMI at baseline: 18.5–24.9	HR 1.0		Pylypchuk et al Am J Epidemiology 2009
				25–29.9	HR 1.23	0.95–1.58
				≥30	HR 1.13	0.68–1.88
				per 4 kg/m2 increment	HR 1.13	0.97–1.31
				BMI at Age 20 years: <20	HR 1.0	0.69–1.45
				20-<21.5	HR 1.0
				21.5-<23	HR 0.75	0.50–1.12
				23-<25	HR 1.10	0.75–1.63
				≥25	HR 1.16	0.69–1.95
				per 4 kg/m2 increment	HR 1.06	0.87–1.30
The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial	Prospective Cohort	142, 982 participants; 243 MM	MM	BMI at age 20 years:			Troy et al Am J Epidemiology 2010
				<18.5	HR 0.71	0.40–1.29
				18.5–24.9	HR 1.0
				25–29.9	HR 1.33	0.94–1.88
				≥30	HR 3.08	1.71–5.54
				BMI at baseline:
				<18.5	N/A
				18.5–24.9	HR 1.0
				25–29.9	HR 1.45	1.05–2.01
				≥30	HR 1.69	1.18–2.41
The Japan Public Health Center-based Prospective Study, Japan	Prospective Cohort	94,547 subjects; 88 MM cases	MM	<18.5	HR 0.56	0.13–2.36	Kanda et al Cancer, Epidemiology, Biomarkers & Prevention 2010
				18.5–22.9	HR 0.70	0.42–1.15
				23–24.9	HR 1.0
				25–29.9	HR 0.79	0.45–1.38
				≥30	HR 0.76	0.18–3.20
				1-unit increase	HR 1.01	0.95–1.09
California Teachers Study	Prospective Cohort	121,216 women; 111 MM cases	MM	At cohort entry: <20	RR 0.92	0.45–1.86	Lu et al Epidemiology 2010
				20–24.9	RR 1.0
				25–29.9	RR 0.83	0.53–1.31
				≥30	RR 0.86	0.48–1.55
				Reported for age 18: <20	RR 1.0
				20–21.9	RR 0.74	0.46–1.18
				≥22	RR 0.97	0.61–1.53
National Institutes of Health – AARP Diet and Health Study, USA	Prospective Cohort	485,049 participants; 489 MM cases	MM	BMI at baseline:			Hofmann et al Am J Epidemiology 2013
				<18.5	HR 0.30	0.04–2.17
				18.5–22.49	HR 1.0
				22.5–24.9	HR 1.02	0.73–1.43
				25–29.9	HR 1.09	0.80–1.48
				30–34.9	HR 1.26	0.89–1.78
				≥35	HR 1.55	1.01–2.39
				BMI at age 50 years:
				<18.5	HR 0.78	0.25–2.49
				18.5–22.49	HR 1.0
				22.5–24.9	HR 1.14	0.85–1.52
				25–29.9	HR 1.16	0.88–1.54
				30–34.9	HR 1.23	0.84–1.80
				≥35	HR 1.77	1.05–2.99
				BMI at age 35 years:
				<18.5	HR 0.77	0.36–1.66
				18.5–22.49	HR 1.0
				22.5–24.9	HR 1.42	1.12–1.79
				25–29.9	HR 1.27	0.99–1.63
				30–34.9	HR 1.41	0.89–2.22
				≥35	HR 2.53	1.24–5.18
				BMI at age 18 years:
				<18.5	HR 0.93	0.69–1.25
				18.5–22.49	HR 1.0
				22.5–24.9	HR 1.12	0.88–1.44
				>25	HR 1.38	1.04–1.82
International Multiple Myeloma Consortium	Pooled Analysis of 8 case-control studies	2,318 MM; 9,609 controls	MM	25–29.9	OR 1.1	1.0–1.3	Birmann et al CEBP 2017
				30–34.9	OR 1.1	1.0–1.3
				35+	OR 1.4	1.4–1.7
Nurses’ Health Study (NHS), Health Professionals Follow-up Study (HPFS), Women’s Health Study (WHS), USA	Prospective cohorts	1,21,700 female nurses in NHS; 51,529 male health professionals in HPFS; 39,876 female health professionals; 575 MM	MM	Cumulative average BMI	HR 1.17 per 5 kg/m2 increase	1.05–1.29	Marinac et al BJC 2018
				Young adult BMI	HR 1.28 per 5 kg/m2 increase	1.12–1.47
				Change in BMI since young adulthood	HR 1.09 per 5 kg/m2 increase	0.98–1.21
				Cumulative average physical activity	HR 0.98 per 10 MET-hrs	0.92–1.06
				Cumulative average walking	HR 1.0 per 10 MET-hrs	0.91–1.10
Nurses’ Health Study (NHS) and Health Professionals Follow-up Study (HPFS), USA	Prospective cohorts	1,21,700 female nurses in NHS and 51,529 male health professionals in HPFS; 582 MM	Weight cycling and MM risk	Weight loss	HR 1.30	0.65–2.62	Marinac et al JNCI Cancer Spectrum 2019
				Weight maintenance	HR 1
				Weight gain	HR 1.52	0.90–2.55
				Light cycling	HR 1.54	0.95–2.49
				Medium cycling	HR 1.25	0.76–2.05
				Extreme cycling	HR 1.71	1.05–2.80
			Body shape trajectories and MM Risk	Lean-stable	HR 1
				Lean-increase	HR 1.17	0.89–1.53
				Medium-stable	HR 1.27	0.97–1.66
				Medium-increase	HR 1.62	1.22–2.14
Obesity increases MM mortality
Cancer Prevention Study II	Prospective Cohort	900,053 participants; 708 MM deaths in M; 620 MM deaths in F	MM mortality	25–29.9	RR 1.18 (M)	1.01–1.39	Calle et al NEJM 2003
					RR 1.12 (F)	0.93–1.34
				30–34.9	RR 1.44 (M)	1.10–1.89
					RR 1.47 (F)	1.13–1.91
				35–39.9	RR 1.71(M)	0.93–3.14
					RR 1.44 (F)	0.91–2.28
National Cancer Institute Cohort Consortium	Pooled Analyses of 20 prospective studies	1,564,218 participants; 1,388 MM deaths	MM mortality	BMI at study entry: 25<27.5	HR 1.15	0.95–1.38	Teras et al BJH 2014
				27.5-<30	HR 1.24	1.01–1.52
				30-<35	HR 1.23	0.99–1.52
				35+	HR 1.52	1.15–2.02
				BMI (per 5kg/m2)	HR 1.09	1.03–1.16
				Young adult BMI: 25-<27.5	HR 1.11	0.87–1.40
				27.5-<30	HR 1.49	1.03–2.16
				30+	HR 1.82	1.22–2.73
				BMI (per 5kg/m2)	HR 1.22	1.09–1.35
Japan Collaborative Cohort Study (JACC), Japan	Prospective Cohort	109,698 subjects; 98 MM deaths	MM mortality	BMI (kg/m2):			Khan et al Asian Pac J Cancer Prev 2006
				<18.5	HR 0.79	0.32–1.98
				18.5–25	HR 1.0
				25–30	HR 0.72	0.39–1.33
				≥30	HR 2.79	1.01–7.69
				Walking/day:
				≥1 hr	HR 1.0
				30 min–1 hr	HR 1.19	0.60–2.36
				≤30 min	HR 1.99	1.16–3.39
Million Women Study, UK	Prospective Cohort	1,222,630 women; 284 MM deaths	MM mortality	<22.5	RR 0.99	0.74–1.32	Reeves et al BMJ 2007
				22.5–24.9	RR 1.0	0.78–1.28
				25–27.4	RR 1.26	0.99–1.59
				27.5–29.5	RR 1.13	0.82–1.55
				≥30	RR 1.63	1.28–2.08

Abbreviations - BMI: Body-Mass Index; 95%CI: 95% Confidence Interval; MM: Multiple Myeloma; OR: Odds Ratio; HR: Hazard Ratio; IRR: Incidence Rate Ratio; RR: Relative Risk

Consistent with these studies, a more recent pooled analysis of 8 case-control studies (2 318 MM; 9 609 controls) looked at the risk of MM in relation to BMI at 2 time points – usual adult BMI (at time of enrollment and study specific reference period) for all 8 studies and young adult BMI (ages 25–30 years) for 2 studies (20). They found that overweight or obese patients at time of study enrollment had a higher risk for MM (HR 1.1, 95%CI 1.0–1.3 for overweight and obese patients and HR 1.4, 95%CI 1.4–1.7 for patients with BMI 35+). Interestingly, patients with elevated BMI at both time points [study entry as well as at young adult age (ages 25–30 years)] had a significantly elevated MM risk compared with individuals with normal BMI on both measures (OR 1.7; 95%CI 1.1–2.6) (20) This study suggests that sustained BMI elevation during adulthood is associated with a higher risk than isolated elevated BMI in the recent years prior to diagnosis. Another pooled analysis in three large prospective cohorts, the Nurses’ Health Study (NHS), Health Professionals Follow-up Study (HPFS) and Women’s Health Study (WHS) with 575 MM cases demonstrated that MM risk increased by 17% per 5 kg/m² increase in cumulative average BMI and by 28% per 5 kg/m² increase in young adult BMI (21). Prospective data from the NHS and HPFS (582 MM cases) also revealed a statistically significant increased MM risk in weight cyclers compared with weight maintainers (HR 1.71; 95%CI 1.05–2.80) and in individuals with a medium-increase body shape trajectory compared with those with a lean-stable trajectory (HR 1.62; 95%CI 1.22–2.14) (22). On the contrary, analysis from a prospective cohort of Swedish men (362 552 participants, 452 MM cases) revealed a reduced MM risk in obese individuals with BMI >30 compared to individuals with BMIs in the normal range (RR 0.58; 95%CI 0.37–0.93) (23). The European Prospective Investigation into Cancer and Nutrition (EPIC) study (371 983 participants; 139 MM cases) showed statistically significant increased MM risk in heavier men (weight ≥ 87.8 kg) (RR 1.77; 95%CI 1.02–3.05) but no significant association was seen with higher BMI (BMI ≥28.7 kg/m²) (RR 1.52; 95%CI 0.92–2.51) (24). Similarly, several other studies showed no significant association between BMI and MM risk (25–28). However, the results of these studies need to be interpreted cautiously. Some of these studies reported a small number of incident MM cases possibly limiting their statistical power to detect a significant association. Overall, current evidence suggests that obesity, measured by various anthropometric parameters, increases the risk to develop MM in both men and women as well as white and black individuals. This risk is especially enhanced with sustained BMI elevation throughout adulthood. However, weight cycling has shown to have a detrimental effect on MM risk and attaining sustained weight loss poses many practical challenges. Additional studies are needed to develop a balanced approach to promote weight loss and mitigate the impact of obesity on MM risk.

Obesity increases MM mortality

Studies evaluating the association between obesity and MM mortality have been outlined in Table 2. The Cancer Prevention Study II (CPS-II), a prospective cohort of 9 00 053 participants, observed total 1 328 deaths due to MM and showed that overweight and obese individuals had a significantly higher mortality due to all cancers combined as well as for MM when compared to normal weight patients (29). Analysis from the Japan Collaborative Cohort Study (109 698 subjects; 98 MM deaths) revealed higher age and sex adjusted MM mortality risk with BMI ≥ 30kg/m² (HR 2.79; 95%CI 1.01–7.69) and walking ≤ 30 minutes/day (HR 1.99; 95%CI 1.16–3.39) (30). Another UK based study showed similar association between BMI and MM mortality (13). Similarly, a pooled analysis of 20 prospective studies within the National Cancer Institute Cohort Consortium (1 564 218 participants; 1 388 MM deaths) showed that patients with a BMI above normal at study entry and in young adulthood had an increased risk of death due to MM (HR 1.09; 95%CI 1.03–1.16 and HR 1.22; 95%CI 1.09–1.35 respectively for every 5 kg/m2 increase in BMI) as well as an elevated waist circumference (HR 1.06; 95%CI 1.02–1.10 per 5 cm) (31). Data from the African American BMI-Mortality Pooling Project (7 prospective cohorts; 239 597 participants) evaluating BMI as a risk factor for increased MM mortality among African Americans reported a statistically significant (p=0.04) rising trend for MM death across BMI ranging from 18.5 to <60 kg/m² with hazard ratios reaching 1.43 (men > women). It was hypothesized that elevated mortality could be due to increased incidence of MM and/or poorer survival (32). These studies support the association between obesity and elevated MM mortality.

The impact of obesity on outcomes in patients with MM Newly diagnosed MM

A study evaluating the association between BMI at the time of diagnosis of MM and overall survival in a cohort (n=2 968) of U.S. veterans found that patients who were underweight (BMI <18.5 kg/m²) had a higher all-cause mortality (HR 1.64; 95%CI 1.30–2.08) and those who were overweight (BMI 25–29.9 kg/m²) and obese (BMI ≥ 30 kg/m²) had a lower mortality (HR 0.82; 95%CI 0.75–0.91) and HR 0.75; 95%CI 0.67–0.84 respectively) when compared with the normal-weight group (BMI 18.5–24.9 kg/m²) (33). Additionally, patients with loss of ≥ 10% of baseline weight in the year leading up to MM diagnosis had significantly higher mortality (HR 1.52; 95%CI 1.34–1.72) compared with those who did not. However, after controlling for disease-related weight loss, age, race and co-morbidities being overweight or obese at the time of MM diagnosis was not significantly associated with decreased mortality (overweight: HR 0.98; 95%CI 0.86–1.11 and obese: HR 0.89; 95%CI 0.77–1.02) suggesting that disease-related weight loss was the primary predictor of outcomes (33).

Obesity and Post - Autologous Stem Cell Transplant (ASCT) MM

A single-center retrospective analysis of 142 MM patients undergoing ASCT revealed that increased BMI at transplant was associated with worse overall survival (OS) (HR 1.11; 95%CI 1.02–1.22) but not with progression free survival (PFS) (HR 1.02; 95%CI 0.97–1.08) in a multivariate analysis (34). A larger CIBMTR study analyzed the effect of BMI on outcomes of 1 087 MM patients who underwent autologous stem cell transplantation with high dose melphalan conditioning and found no overall effect of BMI on PFS, OS, progression, or non-relapse mortality (35).

Obesity and Relapsed MM

Retrospective analysis of 13 relapsed/refractory MM (RRMM) clinical trials (5 898 patients) demonstrated that overweight and obese patients had a trend towards slightly improved PFS (HR 0.90; 95%CI 0.82–0.99 and HR 0.88; 95%CI 0.79–0.97 respectively) and OS (HR 0.91; 95%CI 0.81–0.99 and HR 0.84; 95%CI 0.75–0.95 respectively) when compared to normal weight patients (36). Analysis from another prospective clinical trial (331 patients with RRMM) showed better median PFS (47.9 months vs 9.2 months) and OS (47.9 vs 20.5 months) in obese vs non-obese patients (37). These findings suggest that additional nutritional or muscle reserves often associated with higher BMIs (38) may confer a survival advantage in RRMM patients who have undergone multiple lines of therapy; however, additional studies assessing body composition parameters are needed before definitive conclusions can be drawn.

Taken together, these findings suggest that the influence of BMI in plasma cell disorders maybe disease stage dependent. In normal individuals, an elevated BMI is associated with an increased risk of development of plasma cell disorders and increased MM mortality and in individuals with MGUS and SMM; it also appears to be associated with an increased risk of progression to MM. However, at time of MM diagnosis, transplant, or relapse, excess BMI appears to have no effect on survival, or is associated with improved survival with the latter implying that high BMI patients are able to tolerate therapies better or have less disease related weight loss or cachexia. Disease-related weight loss and body composition are important constructs to consider in future studies to clarify the association between obesity and clinical outcome in MM patients.

Mechanisms by which obesity leads to MM

Several mechanisms linking obesity and cancer risk have been described in the literature. The role of visceral adipocytes, bone marrow adipocytes, adipokines such has adiponectin, resistin and leptin, inflammatory cytokines, especially IL-6 and TNF-α, insulin and insulin-like growth factor I (IGF-I) and sex hormones is outlined below (Figure 1).

Figure 1:

Role of Obesity in The Pathogenesis of Multiple Myeloma mTOR: Mechanistic/Mammalian Target of Rapamycin

JAK/STAT: Janus Kinase/Signal Transducer and Activator of Transcription

NFκB: Nuclear Transcription Factor κB IL-6: Interleukin-6

IL-10: Interleukin-10

IL-17: Interleukin-17

IL-1RA: Interleukin-1 Receptor Antagonist

TNF-α: Tumor Necrosis Factor-α

CRP: C-Reactive Protein

IGF-I: Insulin-like Growth Factor-I

IGF-IR: Insulin-like Growth Factor-I Receptor

Role of Visceral Adipocytes

Adipocytes are considered a major endocrine organ secreting adipokines and inflammatory factors (39). Adipocytes from overweight and obese persons display an altered cytokine profile when compared to normal weight persons due to increased production of inflammatory markers and leptin and decreased production of anti-inflammatory cytokines and adiponectin. The resultant enhanced inflammatory response has been postulated to increase genomic instability, disturb DNA repair, induce epigenetic changes and impact tumor progression (40, 41). Human MM cell lines were co-cultured with differentiated human adipocytes of normal, overweight, obese or super obese patients undergoing elective liposuction. This study demonstrated increased growth of MM cell lines exposed to all adipocyte conditioned media irrespective of BMI status, increased adhesion in MM cells exposed to obese/super obese adipocytes and increased tube formation in endothelial cells with overweight/obese/super obese adipocytes (42). Adipocytes have shown the ability to induce angiogenesis through secretion of angiogenic factors, adipokines (leptin) and cytokines (IL-6) and have thus emerged as potential targets for therapy (43). A recent study revealed that in obese MM patients, over-expression of acetyl-CoA synthetase 2 (ACSS2) induced by adipocyte-secreted cytokine angiotensin II, leads to stabilization of interferon regulatory factor 4 (IRF4) protein and upregulation of IRF4 transcriptional activity, thereby promoting myelomagenesis (44).

Role of Bone Marrow Adipocytes

Adipocytes are the major cellular component of the human bone marrow (BM) comprising up to 70% of the marrow volume and >10% of the total adipose mass in a healthy lean adult (45). While much of the emphasis on adiposity and MM focused on white adipose tissue (WAT), bone marrow adipose tissue (BMAT) is a newly recognized endocrine organ which is distinct from WAT. BMAT responds to growth hormones, insulin, thyroid hormone, release cytokines (IL-6, IL-1β, TNF-α, IGF-I) and adipokines (leptin, adiponectin) (46) and can influence neighboring cells in the bone microenvironment via autocrine, paracrine and endocrine signaling (47). BMAT has recently been found to contribute to oncogenesis and disease progression in MM by potentially influencing cell metabolism, angiogenesis, immune action and inflammation (48). Higher BMI correlates with higher level of BMAT, which in turn can provide a favorable microenvironment for MM cell growth (49, 50). BM adipocytes isolated from femoral biopsies of MM patients were shown to support MM growth in vitro and possibly protect MM cells from chemotherapy-induced apoptosis (51, 52). Increased BM angiogenesis has been associated with poor clinical outcomes in MM patients (53).

Role of Adiponectin

Adiponectin is a polypeptide hormone with anti-proliferative, anti-inflammatory and insulin sensitizing properties (54). Obese individuals have lower circulating levels of adiponectin as compared to normal weight individuals even though adiponectin is known to be mainly secreted by visceral adipose tissue (55) and decreased circulating adiponectin levels have been proposed to contribute to myelomagenesis in obese individuals. Individuals with higher adiponectin levels in a case-control study (73MM cases and 73 gender and age matched controls) had lower risk of MM (Q2: OR 0.44, Q3: OR 0.25 and Q4: OR 0.06 across quartiles of adiponectin) (56). Similarly, another study showed an inverse association between circulating levels of total and high molecular weight (HMW) adiponectin and subsequent MM risk in a prospective study of 174 MM patients and 348 controls within the PLCO Cancer Screening Trial (highest vs lowest quartile: OR 0.49 Ptrend 0.03 for total adiponectin and OR 0.44 Ptrend 0.01 for HMW adiponectin) (57). Another pooled investigation of 624 MM cases and 1 246 individually matched controls from seven cohorts participating in the MM Cohort Consortium revealed that higher total adiponectin levels were associated with reduced MM risk (highest vs lowest quartile: OR 0.64 Ptrend 0.001), particularly among overweight (OR 0.41 Ptrend <0.001) and obese individuals (OR 0.41 Ptrend 0.039) (58). They also measured circulating adiponectin levels in 213 patients (84 MGUS, 104 SMM and 25 MM) and found that adiponectin levels were significantly lower among patients with smoldering MM (SMM)/MM when compared to those with MGUS (16% lower for SMM and 20% lower for MM) (59). These findings suggest that higher circulating adiponectin levels in the pre-diagnostic stage may be protective against MM development. L-4F, an apolipoprotein peptide mimetic when used to augment serum concentration of HMW adiponectin in obese mice, improved bone mass by stimulating osteoblasts (60). Another study in MM bearing mice showed similar effects of L-4F on MM bone disease along with reduction in tumor burden and improved survival (61). These studies (Table 3) suggested that decreased host-derived adiponectin promotes myeloma growth and osteolysis and increasing adiponectin levels have a potential benefit in reducing the risk of MM and associated bone disease.

Table 3:

Obesity and Adipokines

Cohort/ Location	Study Design	N	Outcome	BMI (kg/m2)	Effect Estimate	95% CI	Study
Obesity and adiponectin
Veterans’ Administration General Hospital of Athens, Greece (NIMTS)	Case-Control study	73 MM and 73 gender and age matched controls	Adiponectin level and MM risk		(Quartiles of adiponectin)Q1: OR 1.0		Dalamaga et al Cancer Causes Control 2009
					Q2: OR 0.44	0.18–1.07
					Q3: 0.25	0.09–0.68
					Q4 : 0.06	0.01–0.25
Prostate, Lung, Colorectal and Ovarian (PLCO)Cancer Screening Trial	Prospective study	174 MM patients and 348 controls	Total Adiponectin levels and MM risk		(highest vs lowest quartile) OR 0.49	0.26–0.93	Hofmann et al Blood 2012
			HMW Adiponectin level and MM risk		OR 0.44	0.23–0.85
MM Cohort Consortium	Prospective study	624 MM cases and 1246 individually matched controls	Adiponectin levels and MM risk	Overall	OR 0.64	0.47–0.85	Hofmann et al Cancer Research 2016
				<25	OR 1.2	0.73–2.0
				25–29.9	OR 0.41	0.26–0.65
				≥30	OR 0.41	0.17–0.98
NCT01109407 and NCT01402284 clinical studies	Observational study	213 patients (84 MGUS, 104 SMM, 25 MM)	Adiponectin levels compared to MGUS	-	SMM: 16% lower	−31% to 2%	Hofmann et al Obesity 2017
					MM: 20% lower	−40% to 7%
Obesity and resistin
Veterans’ Administration General Hospital of Athens, Greece, (NIMTS)	Case-Control study	73 MM and 73 gender and age matched controls	Resistin levels and MM risk		(Quartiles of resistin) Q1: OR 1.0		Dalamaga et al Cancer Causes Control 2009
					Q2: OR 0.30	0.11–0.80
					Q3: OR 0.13	0.04–0.39
					Q4: 0.03	0.01–0.18
MM Cohort Consortium	Prospective study	178 MM cases and 358 individually matched controls	Resistin levels and MM risk		(Quartiles of resistin) Q1: OR 1		Santo et al BJC 2017
					Q2: OR 0.77	0.43–1.38
					Q3: OR 0.44	0.24–0.83
					Q4: OR 0.54	0.29–0.995
Obesity and leptin
Veterans’ Administration General Hospital of Athens, Greece, (NIMTS)	Case-Control study	73 MM and 73 gender and age matched controls	Leptin levels and MM risk		(Quartiles of leptin) Q1: OR 1.0		Dalamaga et al Cancer Causes Control 2009
					Q2: OR 1.65	0.59–4.44
					Q3: OR 0.99	0.35–2.86
					Q4: 2.09	0.79–5.52

Abbreviations - BMI: Body-Mass Index; 95%CI: 95% Confidence Interval; MGUS: Monoclonal Gammopathy of Undetermined Significance; MM: Multiple Myeloma; OR: Odds Ratio

One of the proposed biological mechanisms to explain this inverse association between adiponectin levels and MM risk is that adiponectin activates adiponectin receptors expressed by normal and MM cells (62) which in turn activate AMP kinase leading to mechanistic/mammalian target of rapamycin (mTOR) inhibition and downregulation of oxidative phosphorylation (63). The anti-inflammatory effects of adiponectin may be explained by inhibition of nuclear transcription factor κB (NF-κβ) and pro-inflammatory cytokine secretion (IL-6 or TNF-α) and induced expression of anti-inflammatory cytokines (IL-10 or IL-1 receptor antagonist) by adipocytes (64, 65). Experimental studies conducted in vitro and in animal models have also demonstrated adiponectin induced MM cell apoptosis (62).

Role of Resistin

Resistin is an adipokine that was initially shown to induce insulin resistance in rodents (66) and data linking obesity, resistin levels and MM risk in humans is controversial (Table 3). Some studies have found elevated resistin levels correlate with body fat mass (67) while others have found no association (68, 69). Human resistin is thought to be expressed at higher levels in circulating blood monocytes (70) and increases nuclear factor κB-related monocytic secretion of pro-inflammatory cytokines such as IL-6 (71, 72). Resistin is considered an inflammatory factor associated with other inflammatory markers (56). A prospective case-control study (178 MM cases and 358 individually matched controls from three cohorts participating in the MM cohort consortium) demonstrated a statistically significant inverse association between resistin levels and MM risk (OR 0.44 and OR 0.54 for third and fourth quartiles respectively vs the lowest quartile; Ptrend 0.03) among men (73). Lower resistin levels have been associated with increased MM risk. Thus, this has been postulated to reflect a compensatory negative feedback effect on the resistin pathway following production of IL-6, TNF-α and/or other cytokines that have known effects on proliferation and survival of MM cells (56).

Inflammatory cytokines

Obesity is a state of chronic inflammation associated with high levels of several inflammatory cytokines produced primarily by the adipose tissue - IL-6, C-reactive protein (CRP), and TNF-α (74). IL-6 levels have correlated with BM plasmacytosis, serum lactate dehydrogenase, beta 2 microglobulin and calcium in MM (75) as well as shorter survival (76–78). IL-6 also inhibits apoptosis in myeloma cells and promotes survival (79), and activates the Janus Kinase/Signal Transducer and Activator of Transcription (JAK/STAT3), phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT), mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) pathways which are known to increase production of anti-apoptotic proteins like myeloid cell leukemia-1 (Mcl-1), B-cell lymphoma – extra-large (Bcl-xL) and c-Myc in MM cells promoting survival and resistance to chemotherapy (80). In addition, IL-6 is also postulated to cause drug resistance through epigenetic modulation proteins, and it enhances DNA methyltransferase-1 thereby promoting methylation and deactivation of p53, facilitating MM cells to avoid apoptosis (80). IL-6 is thought to be secreted by plasma cells by an autocrine mechanism and through interactions between adhesion molecules on MM plasma cells and their respective receptors on BM stromal cells via a paracrine mechanism (81).

CRP is a polypeptide protein secreted by hepatocytes in response to IL-6 and has been used as an indicator of IL-6 production. A phase II trial of IL-1 receptor antagonist (IL-1Ra) and low-dose dexamethasone for patients with SMM or indolent MM who were at risk of progression to active MM demonstrated statistically significant improvement in PFS and OS in those with reduction in high sensitivity CRP (hs-CRP) (defined as ≥40% decrease in hs-CRP at 6 months when compared to baseline value) versus those without a reduction in CRP (median PFS: 104 months vs 11 months; median OS: not reached vs 7.9 years) (82). In that study, the authors hypothesized that IL-1Ra would inhibit IL-1 mediated production of IL-6 and MM cell growth and reduction in hs-CRP indicated successful targeting of IL-1/IL-6 pathway. In another study, elevated pre-transplant CRP (> upper limit of normal i.e. 8mg/L) was found to have an independent negative prognostic impact on post-transplant survival on multivariate analysis (HR 2.0; 95%CI 1.0–3.8) in MM patients undergoing delayed ASCT (83). In addition, there is evidence to suggest that CRP binds activating FCγ receptors, activates PI3K/AKT, MAPK/ERK and NF-κβ pathways, and inhibits caspase cascade activation induced by chemotherapy drugs and synergizes with IL-6 to protect MM cells from chemotherapy induced apoptosis (84).

TNF-α is a potent inflammatory mediator. TNF-α mRNA and protein are expressed by MM plasma cells (85). TNF-α induces expression of adhesion molecules on MM cell lines and on BM stromal cells leading to increased binding of MM cells to BM stromal cells and increased IL-6 secretion (86).

Role of Leptin

Leptin is a protein coded by the ‘obese’ gene, is mainly secreted by white adipocytes, is an important regulator of caloric intake and metabolic functions and correlates positively with body fat mass (87, 88). Leptin receptor is thought to be structurally and functionally similar to IL-6 receptors (87) and to some hematopoietic growth factor receptors (56). Several variants of leptin receptors with cytoplasmic domains of different lengths have been detected in different tissues. Pre-clinical studies have demonstrated that full-length leptin receptors can mediate activation of the JAK/STAT pathway and stimulate transcription through IL-6 responsive gene elements with a specificity like IL-6 receptors (89). There is evidence to support that leptin induces IL-6 expression in a concentration and time dependent manner by activation of leptin receptor which in turn activates insulin receptor substrate-1 (IRS-1), PI3K/AKT, activator protein 1 (AP-1) pathways (90, 91). Leptin is also thought to have proliferative and anti-apoptotic effects in T-lymphocytes, leukemic cells, hematopoietic progenitor cells, influences angiogenesis and stimulates cytokine secretion from T-lymphocytes and monocytes (87, 88). Newly diagnosed MM patients had higher leptin levels compared with healthy controls (56, 92), (Table 3). Furthermore, leptin increased expression of genes implicated in cell growth, viability and intracellular signaling and stimulated proliferation in myeloma cell lines suggesting leptin maybe a potential therapeutic target (92, 93).

Insulin and IGF axis

Obesity and diabetes mellitus (DM) are known hyperinsulinemic states and hyperinsulinemia has been linked to increased cancer risk (20, 94). IGF-I levels are less consistently elevated in obese/diabetic patients than insulin levels thereby suggesting that insulin is mainly implicated in the increased cancer risk (95). Insulin is a potent growth and survival factor for human MM cell signaling through hybrid receptors (96). MM cell lines express IGF-I, IGF-II and insulin receptors and respond to IGFs by evading apoptosis via distinct intracellular apoptotic pathways (96, 97). Insulin and IGFs protect MM cells from dexamethasone induced apoptosis and thus may play a role in maintenance of the malignant clone (97). However, the NHANES study analyzed associations between various obesity-related metabolic biomarkers in relation to MGUS prevalence, including C-peptide, insulin and glucose, but did not find significant associations (7). Metformin, an oral hypoglycemic agent commonly used in DM, lowers circulating levels of glucose and insulin by promoting uptake of glucose in the tissues and decreasing hepatic gluconeogenesis. Metformin use for ≥4 years has been associated with 53% lower risk of transformation of MGUS to MM in a cohort of diabetic U.S. veterans (98) possibly by interruption of the insulin and IGF receptor signaling pathways.

Sex Hormones

Rising BMI is associated with increased levels of estrone, estradiol and free estradiol in postmenopausal women via increased aromatase activity (99). There is considerable biologic interplay between sex hormone signaling and obesity related pathways associated with increased MM risk, for example, expressions of estrogen receptor (ER) and IGF-I receptor (IGF-IR) have been shown to correlate with each other (100), estrogen increases IGF-IR levels (101) and IGF-I in turn enhances ER responsiveness to estrogen (102). Estradiol administration can also stimulate secretion of cytokines including TNF-α (103). Obesity is associated with decreased circulating total and free testosterone levels in men possibly due to lower sex hormone binding globulins (SHBG) and genuine hypothalamic-pituitary-testicular axis suppression respectively (104). Low testosterone levels are found in most MM patients as well (105). Several cross-sectional studies have found a statistically significant negative correlation between plasma free dehydroepiandrosterone (DHEA) levels and measures of total adiposity (BMI, body fat mass and %fat) in both men and women (106). There is evidence to suggest that DHEA directly inhibited MM proliferation and IL-6 production by BM stromal cells (107). We thereby, postulate a possible association between lower circulating DHEA levels in obese individuals and increased MM risk.

Conclusion and Future Directions:

In conclusion, this review outlines the current associations between obesity and MM. Obesity has been shown to increase the risk of MM and the malignant transformation of MGUS to MM. Similarly, not surprisingly, obesity is also associated with increased MM mortality. Obesity, associated with increased visceral and bone marrow adipose tissue, is thought to contribute to myelomagenesis by increased levels of leptin, inflammatory cytokines like IL-6 and TNF-α, increased insulin and IGF levels as well as decreased circulating levels of adiponectin. The effect of obesity on outcomes in MM patients is not completely understood but may be clarified with additional studies investigating the influence of weight and body composition throughout the disease trajectory.

Obesity is a particularly interesting risk factor for MM because it is the only known risk factor that has the potential to be prevented or modified. However, prospective trials with lifestyle interventions promoting weight loss or improved body composition are warranted to clarify the degree to which altering these exposures impacts disease pathogenesis and outcomes. Studies to evaluate the feasibility of sustained weight loss and its impact on quality of life would also be essential in the light of possible detrimental effects of weight cycling on MM risk. In addition, broader pre-clinical studies to further characterize the complex molecular pathways by which obesity influences myelomagenesis can possibly provide potential exciting targets for treatment.