Seminars in Cancer Biology 64 (2020) 114–121
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Seminars in Cancer Biology
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Review
Autoimmune diseases and hematological malignancies: Exploring the
underlying mechanisms from epidemiological evidence
T
Kari Hemminkia, Wuqing Huangb, Jan Sundquistc, Kristina Sundquistc, Jianguang Jid,*
a
Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
Center for Primary Health Care Research, Lund University/Region Skåne, Sweden
c
Center for Primary Health Care Research, Lund University/Region Skåne, Sweden, Department of Family Medicine and Community Health, Department of Population
Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, USA
d
The Second Hospital of Hebei Medical University, China, Center for Primary Health Care Research, Lund University/Region Skåne, Sweden
b
ARTICLE INFO
ABSTRACT
Keywords:
Cohort study
Epidemiological study
Register-based study
Autoimmune diseases
Hematological malignancies
Autoimmune diseases are characterized by the irregular functioning of the immune system that leads to the loss
of tolerance to self-antigens. The underlying nature of autoimmune diseases has led to speculation that the risk of
malignancy might be higher or lower in patients with such diseases. However, the rarity and heterogeneity of
both autoimmune diseases and malignancies is the main challenge for systematic exploration of associations
between autoimmune diseases and cancer. The nationwide usages of electronic health records in Sweden and
other countries has created longitudinal clinical datasets of large populations, which are ideal for quantifying the
associations as well as possible guidance concerning the underlying mechanisms. In this report, we firstly
summarize the population-based epidemiological association studies between autoimmune diseases and subsequent hematological malignancies using data derived mainly from Swedish nationwide data. These include
over one million cancer cases and approximately 500,000 patients with medically diagnosed autoimmune disease. We further discuss the underlying mechanisms that contribute to the observed association between autoimmune diseases and hematological malignancies, including shared genetics, environmental factors, medical
treatments of autoimmune diseases as well as dysregulated immune function.
1. Introduction
Autoimmune diseases are a group of diseases that are characterized
by malfunction of the immune system that leads to the loss of tolerance
to self-antigens [1]. There are at least 80 types of autoimmune diseases,
which might affect around 5%–10% of the total population [1]. Some
diseases are relatively common, such as celiac disease, diabetes mellitus
type 1, Graves' disease, inflammatory bowel disease, multiple sclerosis,
psoriasis, rheumatoid arthritis, and systemic lupus erythematosus [1].
Some other diseases are very rare such as chorea minor, Behçet disease
and Reiter’s disease (Table 1). Nonsteroidal anti-inflammatory drugs
(NSAIDs), immunosuppressants and anti-tumor necrosis factor-alpha
(TNF) therapy can be used for the treatment of various autoimmune
diseases depending on the severity and type of disease [2,3]. While
these treatments might relieve symptoms, they do not typically cure the
disease.
The underlying nature of autoimmune diseases, i.e. irregular
function of the immune system has led to speculation that the incidence
of malignancy might be higher in patients with autoimmune diseases, in
particular, malignancy caused by immune dysregulation such as lymphoma. Even the opposite, decrease in the risk of cancer in patients
with autoimmune diseases, could be envisaged as a result of augmented
immune function; thus meta-analyses of cancers in patients with type 1
diabetes have shown decreased risks of breast cancer, and decreased
risk of breast and colorectal cancers in patients with rheumatoid arthritis [4,5].
The association between autoimmune diseases and malignancy was
initially observed from case reports concerning the high frequency of
non-Hodgkin lymphoma among individuals with autoimmune diseases
[6]. Associations of various solid cancers with different autoimmune
diseases were subsequently reported [7]. However, the rarity and heterogeneity of both autoimmune diseases and malignancies were the
main challenges of previous studies. Pertinent challenges are to identify
patients with autoimmune diseases and malignancy at a high sensitivity
⁎
Corresponding author at: The Second Hospital of Hebei Medical University, Center for Primary Health Care Research, Jan Waldenströms gata 35, Skåne University
Hospital, 205 02, Malmö, Sweden. Tel.: +4640391382; fax: +4640391370.
E-mail address: Jianguang.ji@med.lu.se (J. Ji).
https://doi.org/10.1016/j.semcancer.2019.06.005
Received 20 December 2018; Received in revised form 4 June 2019; Accepted 6 June 2019
Available online 07 June 2019
1044-579X/ © 2019 Elsevier Ltd. All rights reserved.
Seminars in Cancer Biology 64 (2020) 114–121
K. Hemminki, et al.
Table 1
Risk of non-Hodgkin lymphoma, Hodgkin disease, myeloma, and leukemia after a specific autoimmune disease.
Autoimmune disease
Addison disease
Amyotrophic lateral sclerosis
Ankylosing spondylitis
Autoimmune hemolytic anemia
Behçet disease
Celiac disease
Chronic rheumatic heart disease
Crohn’s disease
Diabetes mellitus type I
Discoid lupus erythematosus
Graves’/hyperthyroidism
Hashimoto/hypothyroidism
Immune thrombocytopenic purpura
Localized scleroderma
Lupoid hepatitis
Multiple sclerosis
Myasthenia gravis
Pernicious anemia
Polyarteritis nodosa
Polymyalgia rheumatica
Polymyositis/dermatomyositis
Primary biliary cirrhosis
Psoriasis
Reiter disease
Rheumatic fever
Rheumatoid arthritis
Sarcoidosis
Sjögren syndrome
Systemic lupus erythematosus
Systemic sclerosis
Ulcerative colitis
Wegener granulomatosis
All
NHL
HD
O
SIR
95%CI
14
15
37
78
25
156
109
173
226
19
208
183
76
13
2
44
24
45
16
229
35
29
275
3
32
698
144
143
107
52
185
87
3096
1.5
1.4
1.0
27.2
1.7
4.8
1.4
2.2
1.1
2.7
1.0
1.4
7.5
1.8
1.2
0.9
2.2
0.9
2.9
1.4
4.1
3.9
1.4
2.1
1.7
2.0
2.6
4.9
4.4
2.1
1.5
1.2
1.6
0.8
0.8
0.7
21.5
1.1
4.1
1.1
1.9
0.9
1.6
0.9
1.2
5.9
1.0
0.1
0.6
1.4
0.7
1.6
1.2
2.8
2.6
1.2
0.4
1.2
1.8
2.2
4.2
3.6
1.6
1.3
1.0
1.6
2.5
2.3
1.4
34.0
2.6
5.7
1.7
2.6
1.2
4.1
1.1
1.6
9.4
3.2
4.3
1.1
3.3
1.3
4.7
1.6
5.6
5.6
1.6
6.3
2.4
2.1
3.1
5.8
5.3
2.7
1.7
1.5
1.7
Myeloma
O
SIR
95%CI
O
2
1
5
6
10
9
7
18
26
1
11
16
9
2
0
8
3
5
3
20
5
1
35
0
3
93
57
8
21
1
22
12
371
2.1
1.0
1.3
19.9
5.6
1.3
1.0
1.7
1.3
1.8
0.6
1.6
7.0
3.4
0.2
0.0
0.4
7.2
2.7
0.6
0.4
1.0
0.8
0.0
0.3
0.9
3.2
0.3
7.6
5.4
3.0
43.6
10.3
2.4
2.1
2.7
1.9
10.0
1.1
2.6
13.3
12.3
1.5
3.2
1.2
6.6
2.2
6.3
2.6
1.9
0.6
0.6
0.4
1.2
1.4
2.0
0.0
1.3
2.9
9.5
2.7
19.5
3.5
14.9
14.7
2.6
1.4
3.2
10.3
5.0
8.4
0.4
1.4
1.9
2.0
0.3
2.6
7.8
2.1
5.2
0.0
0.9
1.0
1.8
4.2
3.9
13.4
9.8
12.9
2.1
2.2
3.4
2.2
0
0
16
0
6
0
23
15
0
0
52
15
4
0
0
13
4
13
0
43
4
0
23
0
8
81
19
4
11
19
38
26
457
SIR
Leukemia
95%CI
2.0
1.2
3.3
1.5
0.5
3.2
0.9
0.8
0.6
0.5
1.4
1.4
1.0
1.1
2.1
0.8
0.6
0.6
1.4
1.9
5.5
1.0
1.4
1.0
0.5
0.4
0.5
1.7
3.5
1.7
1.2
1.8
0.9
0.5
1.6
4.7
1.0
0.6
1.5
1.3
0.9
1.3
2.1
1.7
2.6
1.4
1.2
1.1
0.6
0.7
0.8
0.6
0.9
1.6
1.0
0.8
1.0
2.7
1.1
2.0
5.4
3.1
4.1
1.9
1.7
1.2
O
SIR
95%CI
7
2
15
19
10
10
53
49
25
4
115
27
25
4
3
34
5
48
8
117
8
4
60
0
21
234
44
6
27
18
65
61
1128
1.4
0.4
0.9
11.9
1.2
0.8
1.2
1.2
2.5
1.9
1.2
1.1
5.6
1.5
5.9
1.3
0.9
2.2
2.8
1.8
1.9
1.3
1.3
0.6
0.0
0.5
7.2
0.6
0.4
0.9
0.9
1.6
0.5
1.0
0.7
3.6
0.4
1.1
0.9
0.3
1.6
1.2
1.5
0.8
0.4
1.0
2.9
1.3
1.5
18.6
2.2
1.5
1.6
1.6
3.6
4.8
1.5
1.6
8.3
4.0
17.4
1.8
2.0
2.9
5.6
2.1
3.7
3.5
1.7
1.8
1.4
1.5
1.7
2.2
1.3
1.1
1.6
1.4
1.1
1.2
1.1
0.6
1.4
0.8
0.8
1.3
1.4
2.7
1.6
2.1
3.7
3.1
2.0
1.4
2.1
1.5
O, observed case; SIR, standardized incidence ratio; CI, confidence interval; NHL, non-Hodgkin lymphoma; HD, Hodgkin disease. Bold type indicates that the 95% CI
does not include 1.00.
International Classification of Diseases (ICD) codes. ICD-7 code was
used to retrieve patients diagnosed with autoimmune diseases in the
years between 1964 and 1968; ICD-8 codes were used between 1969
and 1986; ICD-9 codes were used between 1987 and 1996, and ICD-10
codes were used for patients between 1997 and 2010 (Supplementary
Table 1).
The quality and coverage of the Swedish Hospital Register has been
examined extensively. As compared to the diagnoses from medical
journals (gold standard), the positive predictive values (PPV) is around
85–95% for all the diagnoses from the Swedish Hospital Discharge
Register [17]. As for specific autoimmune diseases, the reported PPV is
95% for rheumatoid arthritis, 86% for celiac disease, 87% for Wegener
granulomatosis, and 74% for Crohn's disease and ulcerative colitis [18].
A total of 33 autoimmune diseases with a relatively high prevalence
were retrieved from the register. The selected diseases include not only
autoimmune diseases but also autoinflammatory and chronic inflammatory diseases because there is a considerable overlap between
them. In Sweden, more than 400,000 individuals have been previously
diagnosed with autoimmune diseases [18]. Among them, 92% were
diagnosed with only one specific autoimmune disease, and the remainder were diagnosed with two or more diseases.
The Swedish Cancer Registry, which was founded in 1958, is
maintained by the National Board of Health and Welfare. At present, its
coverage is over 90% [19]. The Cancer Registry uses 4-digit ICD-7
codes to record anatomical site of malignancies. In Sweden, it is compulsory for clinicians and pathologists/cytologists to report all newly
diagnosed cancers to the Cancer Registry, which guarantees high coverage and high sensitivity of the reported cancer cases.
In the original papers, we reported subsequent risks of various
and specificity as well as to improve the representativeness of the study
population. To overcome these limitations, our research group has been
able to use nationwide registers in Sweden, which are well-known for
their long history that cover the whole Swedish population (more than
10 million people) to systematically assess the associations between
autoimmune diseases and cancer at a national level. The association
between autoimmune diseases and cancer has been extensively reviewed previously, and most of these studies focused on the association
with specific autoimmune diseases [5,8–16]. A recent review by Giat
and colleagues summarized the association between autoimmunity and
cancer with a main focus on reports from cohort studies [7], but the
data from the largest studies in this topic, i.e. from the Swedish nationwide registers, were just briefly mentioned. The results from the
Swedish nationwide registers are summarized in this article focusing on
hematological malignancies diagnosed after autoimmune diseases.
2. SOURCES OF DATA
We have used several nationwide registers in our previous studies
including the Swedish Cancer Registry, the Swedish Hospital Inpatient
and Outpatient Registers, as well as other nationwide registers such as
the Total Population Register to retrieve demographic factor data (including gender, education, disposable income, et al). The Swedish
Hospital Register includes the Swedish Hospital Discharge Register,
which was founded in 1964 by the National Board of Health and
Welfare and has had complete nationwide coverage since 1987, and the
Swedish Outpatient Register, which was founded in 2001 with complete coverage. A cohort of patients with autoimmune diseases were
recorded in the register according to the different versions of the
115
Seminars in Cancer Biology 64 (2020) 114–121
K. Hemminki, et al.
hematological malignancies in patients with autoimmune disease using
standardized incidence ratio (SIR), which was adjusted for a range of
clinical and demographic factors, including age at diagnosis of autoimmune diseases, gender, period, region of living, and socioeconomic
status. Additional adjustments for smoking (using chronic obstructive
pulmonary disease as a surrogate), alcohol drinking (using alcoholism
as a surrogate), and obesity might be applied for specific autoimmune
diseases.
We used network visualization to present the observed associations
between various autoimmune diseases and hematological malignancies
from the nationwide Swedish Registers. Different colors represent various hematological malignancies. The degree of thickness of the lines
represents the strength of the association, which is categorized by the
thinness (SIR of 1.0–3.0), the middle (SIR of 3. 1–5.0), and the thickness
(SIR > 5.0), respectively. Positive associations are shown using solid
line, whereas negative associations are shown using dashed line.
incidence of myeloma was significantly higher among individuals
hospitalized after ankylosing spondylitis and systemic sclerosis [22].
The risk of leukemia was increased after a total of 13 autoimmune
diseases [23], and the highest risk was noted for autoimmune hemolytic
anemia (SIR = 11.9) and immune thrombocytopenic purpura
(SIR = 5.6).
The overall risk of non-Hodgkin lymphoma after any autoimmune
diseases was largely consistent among men (SIR = 1.7) and women
(SIR = 1.6), and no significant sex differences were observed for specific autoimmune diseases [20]. For Hodgkin lymphoma [21], the
overall risk was slightly lower in women (SIR = 1.8) as compared to
men (SIR = 2.4). For specific autoimmune diseases, rheumatoid arthritis showed a significantly higher risk in men (SIR = 4.9, 95%CI
3.6–6.4) as compared to women (SIR = 2.3, 95%CI 1.6–3.0), whereas
no significant sex differences were observed for other autoimmune
diseases.
Early age at onset was reported to be a worse prognostic factor for
some autoimmune diseases, such as diabetes mellitus type I and systemic lupus erythematosus, which might be used as a proxy of disease
severity [24]. The overall risk of non-Hodgkin lymphoma diagnosed
before age 60 years in patients with autoimmune diseases was significantly higher (SIR = 2.2, 95%CI 2.0–2.3) than that in patients diagnosed at age older than 60 years (SIR = 1.5, 95%CI 1.5–1.6) [20].
The overall risks of Hodgkin lymphoma diagnosed before 35 years (SIR
1.4, 95%CI 1.0–1.8) were lower than that diagnosed at age older than
50 years (SIR = 2.2, 95%CI 2.0–2.5) [21].
For specific histological subtype of non-Hodgkin lymphoma
(Table 2), the SIR of diffuse large B cell lymphoma was 1.6, and it was
1.3 for follicular and mantel cell lymphoma, and 2.2 for cutaneous/
peripheral T cell lymphoma. Only autoimmune diseases associated with
at least one of the histological subtype of non-Hodgkin lymphoma were
listed in Table 2. Our data showed that autoimmune diseases do not
exclusively associate with a particular histological subtype of nonHodgkin lymphoma, although a higher SIR was noted for cutaneous/
peripheral T-cell lymphoma. For example, the risk of cutaneous/peripheral T-cell was very high (15.9) after celiac disease, but a moderately
increased risk was noted for diffuse large B cell lymphoma (3.3). In
addition, Sjögren syndrome was associated with diffuse large B cell
lymphoma (5.5), follicular (5.8) and mantel cell lymphoma (4.1).
For specific leukemia (Table 3), the incidence of acute lymphoblastic leukemia, acute myeloid leukemia, chronic myeloid leukemia
was significantly higher among patients with autoimmune diseases as
3. Associations of autoimmune diseases with hematological
malignancies
In Table 1 we present the SIR of non-Hodgkin lymphoma, Hodgkin
disease, myeloma and leukemia after a specific autoimmune disease.
The incidence of non-Hodgkin lymphoma was 60% higher among patients with all autoimmune diseases as compared to the general population [20]. A total of 21 specific autoimmune diseases showed a positive association with subsequent non-Hodgkin lymphoma (N = 3096),
and none of them showed a negative association (Fig. 1). For specific
diseases, the association was observed for patients with autoimmune
hemolytic anemia (SIR = 27.2), immune thrombocytopenic purpura
(SIR = 7.5), polymyositis/dermatomyositis, primary biliary cirrhosis,
myasthenia gravis, Behçet disease, rheumatoid fever, ulcerative colitis,
polymyalgia rheumatica, and chronic rheumatic heart disease, Sjögren
syndrome, celiac disease, systemic lupus erythematosus, polyarteritis
nodosa, discoid lupus erythematosus, sarcoidosis, Crohn disease, systemic sclerosis, rheumatoid arthritis, Hashimoto/hypothyroidism and
psoriasis. As for Hodgkin lymphoma [21], a positive association was
noted for a total of 11 autoimmune diseases including autoimmune
hemolytic anemia (SIR = 19.9), sarcoidosis (SIR = 10.3), systemic
lupus erythematosus (SIR = 8.4), immune thrombocytopenic purpura
(SIR = 7.0), polyarteritis nodosa (SIR = 6.6), polymyositis/dermatomyositis (SIR = 6.3), Behçet’s disease (SIR = 5.6), Sjögren’s syndrome,
rheumatoid arthritis, polymyalgia rheumatica and psoriasis. The
Fig. 1. Association between autoimmune diseases and hematological malignancy [20–23,33].
116
Seminars in Cancer Biology 64 (2020) 114–121
K. Hemminki, et al.
Table 2
Risk of non-Hodgkin lymphoma by histological subtypes after an autoimmune disease.
Autoimmune disease
Autoimmune hemolytic anemia
Celiac disease
Chronic rheumatic heart disease
Crohn disease
Immune thrombocytopenic purpura
Localized scleroderma
Myasthenia gravis
Polyarteritis nodosa
Polymyalgia rheumatica
Polymyositis/dermatomyositis
Primary biliary cirrhosis
Psoriasis
Rheumatoid arthritis
Sarcoidosis
Sjögren syndrome
Systemic lupus erythematosus
Systemic sclerosis
Ulcerative colitis
All
Diffuse large B-cell
Follicular
O
SIR
95%CI
O
SIR
95%CI
2
25
22
46
19
3
8
4
57
9
7
57
126
27
41
28
10
46
603
5.5
3.3
2.3
2.8
7.8
2.2
3.9
4.7
1.7
5.8
4.0
1.2
2.2
2.7
5.5
6.6
3.0
1.7
1.6
0.5
2.1
1.4
2.1
4.7
0.4
1.7
1.2
1.3
2.6
1.6
0.9
1.8
1.8
4.0
4.4
1.4
1.2
1.5
5
3
6
16
5
4
2
0
16
5
3
31
57
12
28
9
5
20
282
20.0
0.7
1.0
1.5
3.7
4.3
1.7
6.3
0.1
0.4
0.8
1.2
1.1
0.2
46.9
2.0
2.2
2.4
8.6
11.2
6.1
0.8
5.1
2.5
1.1
1.6
1.8
5.8
3.0
2.2
1.2
1.3
0.5
1.6
0.5
0.7
1.2
1.0
3.8
1.4
0.7
0.7
1.1
1.4
12.0
7.4
1.5
2.0
3.2
8.4
5.7
5.2
1.8
1.4
20.4
4.9
3.5
3.7
12.1
6.5
7.8
12.1
2.2
11.0
8.2
1.5
2.6
3.9
7.5
9.6
5.5
2.3
1.8
Cutaneous/Peripheral T-cell
Mantel cell
O
SIR
95%CI
O
SIR
95%CI
2
17
2
9
3
2
0
1
4
1
1
28
17
4
1
0
0
5
107
36.9
15.9
1.4
3.7
9.3
11.2
3.5
9.2
0.1
1.7
1.8
1.1
135.6
25.5
5.2
7.1
27.5
41.0
15.9
1.7
0.0
0.2
91.2
6.3
2.2
4.9
0.8
0.5
4.7
17.9
7.7
1.0
4.8
4.3
4.3
2.2
2.8
1.1
0.0
0.3
0.0
0.0
2.8
1.3
0.7
0.0
44.3
2.5
27.4
24.4
6.2
3.6
7.2
6.2
1.1
0.4
2.3
4.0
0.8
1.4
1.7
4.1
1.7
0.0
0.3
0.8
0.3
1.1
0.0
23.1
1.8
2.5
5.1
10.6
9.8
1.3
2.2
0.4
1.8
3.0
2.6
1
2
0
6
2
0
0
0
6
0
1
7
13
3
4
1
0
8
81
1.6
1.3
0.7
1.1
3.2
1.7
O, observed case; SIR, standardized incidence ratio; CI, confidence interval; Bold type indicates that the 95% CI does not include 1.00.
compared to the general population, whereas the incidence of chronic
lymphoblastic leukemia was close to the general population. Only autoimmune diseases associated with at least one of the subtypes of leukemia were listed. A total of seven autoimmune diseases were associated with acute myeloid leukemia, two autoimmune diseases
associated with acute and chronic lymphoblastic leukemia, and one
with chronic myeloid leukemia.
malignancies, and 13 diseases associated with one hematological malignancy. Considering patient numbers, Beçhet disease presenting with
only 733 patients had positive associations with two hematological
malignancies and polyarteritis nodosa with three associations (Table 4).
Autoimmune hemolytic anemia and systemic sclerosis also associated
with relatively many hematological malignancies.
5. Discussion
4. Summarizing of the association
5.1. Surveillance bias
In Table 4 we present the number of associations with hematological malignancy for each autoimmune disease. As the number of associations is related to the sample size it is relevant in this context to
consider the number of patients for each autoimmune disease, also
shown in Table 4. We found that none of these autoimmune diseases
associated with all the four hematological malignancies, and none of
them negatively associated with hematological malignancy. A total of
seven autoimmune diseases, including autoimmune hemolytic anemia,
immune thrombocytopenic purpura, polyarteritis nodosa, polymyalgia
rheumatic, rheumatoid arthritis, sarcoidosis, and systemic lupus erythematosus, associated with three hematological malignancies. In
addition, six autoimmune diseases associated with two hematological
Several underlying mechanisms have been proposed to interpret the
observed association between various autoimmune diseases and cancer.
We will describe them in the following section. It is well-known that
patients with chronic diseases, such as autoimmune diseases, might
have frequent medical contacts with clinicians thus leading to the detection of relatively indolent cancer at an earlier stage, i.e. surveillance
bias [25–27]. One way to overcome surveillance bias is to explore
whether cancer mortality is higher in patients with autoimmune diseases based on the hypothesis that surveillance bias would be minimal
if both the incidence and mortality are higher in patients with autoimmune diseases. We have systematically explored the standardized
Table 3
Risk of specific leukemia after an autoimmune disease.
Autoimmune disease
ALL
O
Autoimmune hemolytic anemia
Crohn disease
Diabetes mellitus type I
Immune thrombocytopenic purpura
Pernicious anemia
Polyarteritis nodosa
Polymyalgia rheumatica
Rheumatoid arthritis
Sarcoidosis
Systemic lupus erythematosus
Wegener granulomatosis
All
0
2
10
1
2
0
3
14
2
1
1
58
CLL
SIR
95%CI
0.9
2.8
1.8
3.6
0.1
1.3
0.0
0.3
3.5
5.1
10.5
13.2
1.8
2.77
2.0
2.1
1.1
1.7
0.3
1.5
0.2
0.0
0.0
1.3
5.3
4.7
7.3
12.1
6.4
2.2
AML
O
SIR
95%CI
12
9
3
5
5
1
31
67
12
5
11
291
20.8
0.7
5.2
3.6
0.6
0.9
1.2
1.1
1.2
1.2
0.8
1.0
10.7
0.3
1.0
1.1
0.2
0.0
0.8
0.8
0.6
0.4
0.4
0.9
36.4
1.3
15.5
8.4
1.3
5.1
1.7
1.4
2.0
2.8
1.4
1.2
CML
O
SIR
95%CI
2
14
3
3
19
5
35
69
12
13
23
309
5.9
1.6
1.3
3.5
4.1
8.8
2.5
1.9
2.0
4.7
2.8
1.9
0.6
0.9
0.3
0.7
2.5
2.8
1.8
1.5
1.0
2.5
1.8
1.7
21.6
2.7
3.9
10.2
6.4
20.7
3.5
2.4
3.4
8.0
4.3
2.1
O
SIR
95%CI
1
13
3
2
2
0
7
17
3
2
3
102
8.5
3.3
2.0
6.1
1.4
0.0
1.7
0.4
0.6
0.1
48.5
5.6
5.9
22.3
5.0
1.8
1.4
1.2
1.9
1.2
1.4
0.7
0.8
0.2
0.2
0.2
1.4
3.7
2.3
3.6
7.0
3.5
2.0
O, observed case; SIR, standardized incidence ratio; CI, confidence interval; ALL, acute lymphoblastic leukemia; CLL, chronic lymphoblastic leukemia; AML, acute
myeloid leukemia; CML, chronic myeloid leukemia. Bold type indicates that the 95% CI does not include 1.00.
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K. Hemminki, et al.
Table 4
Number of hematologial malignancy associated with different autoimmune diseases.
Autoimmune diseases
No. case
No. positive association
No. negative association
Addison’s disease
Amyotrophic lateral sclerosis
Ankylosing spondylitis
Autoimmune hemolytic anemia
Behçet’s disease
Celiac disease
Chorea minor
Chronic rheumatic heart disease
Crohn’s disease
Diabetes mellitus type I
Discoid lupus erythematosus
Graves’ disease
Hashimoto’s thyroiditis
Immune thrombocytopenic purpura
Localized scleroderma
Lupoid hepatitis
Multiple sclerosis
Myasthenia gravis
Pernicious anemia
Polyarteritis nodosa
Polymyalgia rheumatica
Polymyositis/dermatomyositis
Primary biliary cirrhosis
Psoriasis
Reiter’s disease
Rheumatic fever
Rheumatoid arthritis
Sarcoidosis
Sjögren’s syndrome
Systemic lupus erythematosus
Systemic sclerosis
Ulcerative colitis
Wegener’s granulomatosis
2704
9321
13472
1330
733
34637
142
22763
35689
122684
2814
46234
35503
10212
2225
5584
24615
3757
11704
1625
33108
2507
4187
108607
1281
3637
106941
18995
9053
9690
3381
55048
3022
0
0
1
3
2
1
0
1
1
1
1
0
1
3
0
1
0
1
1
3
3
2
1
2
0
2
3
3
2
3
2
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NHL
HD
*
*
*
*
*
Myeloma
*
*
*
*
*
*
*
*
Leukemia
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
associated with cancers highlighted that are also in excess in immunosuppressed patients, most notably non-Hodgkin lymphoma
[30–32]. A total of 21 autoimmune diseases were associated with an
increased risk of non-Hodgkin lymphoma, whereas none of them were
negatively associated with non-Hodgkin lymphoma thus strongly suggesting that dysregulation of the immune system in patients with autoimmune diseases plays an important role for the subsequent development of non-Hodgkin lymphoma.
In an earlier study, we wanted to test the model that the developmental origin of B-cells may explain why autoimmune stimulation
differentially affects B-cell neoplasms and the magnitude of risk [33].
We adopted the cell of origin classification of Seifert and coworkers
[34]; germinal center-derived cell types were considered diffuse large
B-cell lymphoma, follicular lymphoma and Hodgkin lymphoma. Pregerminal center-derived tumors were acute lymphocytic leukemia and
most chronic lymphocytic leukemia. The results showed that the developmental origin of B-cells provided classifying features about the
associated autoimmune diseases. We speculated that autoimmune stimulation may be boosted by the germinal center events of rapid cell
division and somatic hypermutation, likely to deliver damage contributing to the transformation [34]. Support to the inflicted damage is
provided by the known one order of magnitude higher mutation lead in
B-cell lymphomas compared to acute lymphocytic leukemia and
chronic lymphocytic leukemia [35].
mortality ratios due to hematological malignancies in patients with
autoimmune diseases [23], and the results were largely consistent with
the data from SIRs, which suggests that the observed associations between autoimmune diseases and hematological malignancies might be
largely accurate.
Another way to overcome surveillance bias is to exclude cancer
cases identified during the first year of follow-up after autoimmune
diseases. Our previous studies found that the relative risk of leukemia
might be somewhat lower when patients with leukemia diagnosed
during the first year of follow-up were excluded [23], but most of the
observed associations were still significant. It should be noted that excluding cancer cases during the first year of follow-up might be a
conservative assessment because the accuracy of diagnosis of cancers,
which were histologically or cytologically confirmed, was not compromised by lead time bias, rather the diagnosis was shifted earlier. It
should be noted that the observed number of hematological malignancies subsequent to some specific autoimmune diseases were very
few; thus, the calculated SIRs from this study might not be generalized
to the general population for such autoimmune diseases.
5.2. Immunological and developmental factors
It is known that dysregulation of the adaptive immune system lies at
the core of autoimmune and immune-mediated disease pathogenesis
[28,29]. Dysregulation of both the innate and adaptive immune system
might be associated with an increased risk of solid and hematological
malignancies, which might be the basis for the observed associations
between autoimmune diseases and cancer. However, other factors, such
as shared genetic and/or environmental factors, as well as medical
treatments, might also play an important role for the observed association, which we will discuss in detail in the following sections based
on the current evidence from epidemiological studies.
It is quite striking that the number of autoimmune diseases
5.3. Genetic factors
It is commonly recognized that most autoimmune diseases are developed in genetically predisposed individuals after the trigger by
various environmental factors. Intensive genetic studies have been
implemented for various autoimmune diseases. Family-based linkage
analyses have found some genetic variants associated with various
autoimmune diseases. For example, tumor necrosis factor receptor 2
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K. Hemminki, et al.
polymorphism has been consistently shown to be associated with the
susceptibility for systemic lupus erythematosus [36,37].With the rapid
development of SNP arrays, hundreds of genome-wide association
studies (GWA study) have been done so far to explore the association
between genetic polymorphisms and various autoimmune diseases
[38–44]. Indeed, many genetic polymorphisms have been identified to
be associated with common as well as rare autoimmune diseases. For
example, more than 160 susceptible loci have been identified for inflammatory bowel diseases [45], and more than 80 susceptibility loci
are now reported to show robust genetic association with systemic
lupus erythematosus [46]. For rare disorders, such as Behçet's disease,
many genes including IL10, IL23R, CCR1, STAT4, KLRC4, GIMAP2/
GIMAP4, and UBAC2 have been identified to be associated with it from
GWA studies [47]. Some of the genetic polymorphisms have been found
to be associated with more than one autoimmune disease, suggesting
pleiotropic effect of these genes on autoimmune diseases. For example,
a total of 14 non-HLA shared loci are associated with both celiac disease
and rheumatoid arthritis [48]. Such pleiotropic effects might contribute
to the observed association between autoimmune diseases and cancer.
How might the genetic mechanisms link autoimmune diseases and
hematological malignancy? One can explore the relative risk of hematological malignancies in first- and second-degree relatives of patients
with autoimmune diseases. Depending on the magnitude of the observed association in first-, and second-degree relatives, one can disentangle the underlying contribution of genetic factors from shared
environmental factors. In addition, multiple autoimmune diseases in
the same individual, diagnosis of autoimmune diseases at a young age
and autoimmune diseases presenting in several family members might
provide additional evidence for the contribution of shared genetic
factors to the observed contribution.
We have found that non-Hodgkin lymphoma was associated with a
family history of discoid lupus erythematosus, Sjögren syndrome and
psoriasis, whereas Hodgkin disease was associated positively with a
family history of pemphigus, and negatively associated with a family
history of three autoimmune diseases [49]. For myeloma, no significant
associations were noted with a family history of autoimmune diseases.
In addition, we have also explored the risk of autoimmune diseases
among family members with haematological malignancies. A significantly increased risk of angiitis hypersensitive (2.7), Sjögren syndrome (1.4), rheumatoid arthritis (1.1) and Wegener granulomatosis
(1.6) was noted among family member of patients with non-Hodgkin
lymphoma. In addition, the risk of Behçet disease (3.3), dermatitis
herpetiformis (2.4), multiple sclerosis (1.3), primary biliary cirrhosis
(2.0) and rheumatoid arthritis (1.2) risks were increased among family
member of patients with Hodgkin disease [49].
potential risk factor for primary biliary cirrhosis, systemic sclerosis and
autoimmune thyroid diseases [55–58].
To explore the contribution of shared environmental factors on the
associations between autoimmune diseases and cancer, epidemiologists
can explore the association of autoimmune diseases in spouses of patients with hematological malignancy. In addition, epidemiologists can
use an adoptive study design to explore whether the adoptees might
experience an increased risk of hematological malignancy when their
adoptive parents are diagnosed with autoimmune diseases; adoptees
might share common environmental factors with their adoptive parents
but no common genetic factors. To our knowledge, adoptive studies
concerning the association between autoimmune diseases and hematological malignancy are still lacking due to the rareness of study
power. However, several previous studies have tried to explore the
contribution by shared environmental factors by using spouse study
design. For example, the overall risk of gastric cancer in husbands with
affected wives with autoimmune diseases was 0.97 (95% CI 0.89–1.07),
and the risk in wives with affected husbands was 0.89 (95% CI
0.74–1.06) [59]. The observation between spouses suggests that shared
environmental factors might play no role for the observed association
between autoimmune diseases and gastric cancer. Further studies using
an adoptive study design as well as spouse study design are highly
needed to explore the underlying contribution of shared environmental
factors on the observed association.
5.5. Treatment-related factors
Patients with less severe diseases such as autoimmune thyroid disease are usually receiving symptomatic or replacement therapy (a
conservative approach), whereas patients with more severe autoimmune diseases such as systemic lupus erythematosus are usually
treated with immunosuppressive or immune-modulation therapy (aggressive therapy) with the aim to prevent further organ damage
[2,3,60–62]. Patients with severe forms of autoimmune diseases might
receive immunosuppressive therapy for a long period of time
[2,3,60–62]. As discussed above, immunosuppression is cancer promoting as shown in many previous studies among patients who received a kidney transplant and were treated with immunosuppression
drugs [63,64]. Tumor necrosis factor-alpha (TNF) plays a crucial role in
the pathogenesis of some autoimmune diseases, such as inflammatory
bowel disease, ankylosing spondylitis, rheumatoid arthritis, and psoriasis [65]. Currently, anti-TNF therapy has been regularly used for the
treatment of autoimmune diseases, which might be associated with an
increased risk of cancer [66].
Studies exploring the underlying contribution of immunosuppressive therapy on the observed association between autoimmune diseases and cancer might be a challenge as it might be hard to
disentangle the contribution by shared genetic and environmental
factors for the occurrence of comorbidity. One way to study the contribution by immunosuppressive therapy is to examine the relative risk
of cancer stratified by the subsequent follow-up time after the diagnosis
of autoimmune diseases. Patients with an increased risk of cancer noted
only at the late periods, such as 10 years after autoimmune diseases,
might be contributed by immunosuppressive therapy as the development of most solid tumors needs more than 10 years although leukemia
may appear earlier [67–69]. In addition, a trend with an increasing
relative risk with follow-up time after autoimmune disease might provide clues for the therapeutic effect on the observed associations.
Our previous studies found that the overall risk of cancers in the
stomach, colon, liver, lung, skin (squamous cell) and non-thyroid endocrine glands and of lymphoma (Hodgkin and non-Hodgkin) and
leukemia was significantly increased among patients with sarcoidosis
[70], but only kidney cancer showed an increased risk after ten years of
follow-up thus suggesting a possible therapeutic effect. The risks of
cancers of the upper aerodigestive tract, esophagus, skin (SCC), stomach, liver, pancreas, lung, kidney, bladder, and nervous system and
5.4. Environmental factors
Environmental factors that contribute to the development of autoimmune diseases might explain part of the observed association as
many autoimmune diseases and cancer share the same environmental
risk factors. The significant increase in the incidence of autoimmune
diseases such as type 1 diabetes and multiple sclerosis in industrialized
countries over recent decades suggests that environmental factors play
an important role in the development of autoimmune diseases [50,51].
Recent evidence from GWAS studies, as well as twin studies, suggest
that genetic predisposition accounts for approximately 30% of the
variations of all autoimmune diseases and the remainder are contributed by environmental factors, including toxic chemicals, dietary
components, gut microbial imbalance, and infections [15]. Infections
by Epstein-Barr virus are associated with systemic lupus erythematosus
with an underlying mechanism of ‘molecular mimicry’ [15]. Gut microbiota has been suggested to be associated with several autoimmune
diseases, such as type 1 diabetes and inflammatory bowel disease
[52–54]. Smoking is a well-known risk factor for the development of
rheumatoid arthritis and systemic lupus erythematosus as well as a
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non-Hodgkin lymphoma were significantly increased after hospitalization for psoriasis [71]. Nervous system tumor and bladder cancer
showed an increased risk even after 10 years of follow-up.
It should be noted that some patients with autoimmune diseases,
such as in patients with ankylosing spondylitis and rheumatoid arthritis
are treated with prolonged anti-inflammatory medication, which might
be protective of many cancers [72,73]. Non-steroidal anti-inflammatory
drugs are frequently used for the treatment of conditions like arthritis
by inhibition of autoimmune inflammatory responses and relieving pain
through blocking cyclooxygenase (COX) enzymes, which can promote
the production of prostaglandins, a mediator which causes inflammation and pain. Regular use of anti-inflammatory drugs has consistently
been shown to be associated with a reduced risk of many common
cancers, such as breast, and colorectal cancer [72,73]. It is thus reasonable that the observed negative association between autoimmune
disease and cancer might be due to the anti-tumor effect by non-steroidal anti-inflammatory drugs, however, such effect might be compromised by other cancer promoting factors or medical treatments.
References
[1] L. Wang, F.S. Wang, M.E. Gershwin, Human autoimmune diseases: a comprehensive
update, J. Intern. Med. 278 (4) (2015) 369–395.
[2] G.R. Burmester, J.E. Pope, Novel treatment strategies in rheumatoid arthritis,
Lancet (London, England) 389 (10086) (2017) 2338–2348.
[3] G. Comi, M. Radaelli, Soelberg Sorensen P: evolving concepts in the treatment of
relapsing multiple sclerosis, Lancet (London, England) 389 (10076) (2017)
1347–1356.
[4] M.F. Sona, S.K. Myung, K. Park, G. Jargalsaikhan, Type 1 diabetes mellitus and risk
of cancer: a meta-analysis of observational studies, Jpn. J. Clin. Oncol. 48 (5)
(2018) 426–433.
[5] T.A. Simon, A. Thompson, K.K. Gandhi, M.C. Hochberg, S. Suissa, Incidence of
malignancy in adult patients with rheumatoid arthritis: a meta-analysis, Arthritis
Res. Ther. 17 (2015) 212.
[6] M.A. Lopez-Olivo, J.H. Tayar, J.A. Martinez-Lopez, E.N. Pollono, J.P. Cueto,
M.R. Gonzales-Crespo, S. Fulton, M.E. Suarez-Almazor, Risk of malignancies in
patients with rheumatoid arthritis treated with biologic therapy: a meta-analysis,
Jama 308 (9) (2012) 898–908.
[7] E. Giat, M. Ehrenfeld, Y. Shoenfeld, Cancer and autoimmune diseases, Autoimmun.
Rev. 16 (10) (2017) 1049–1057.
[8] G.C. Goobie, S. Bernatsky, R. Ramsey-Goldman, A.E. Clarke, Malignancies in systemic lupus erythematosus: a 2015 update, Curr. Opin. Rheumatol. 27 (5) (2015)
454–460.
[9] G. Egiziano, S. Bernatsky, A.A. Shah, Cancer and autoimmunity: harnessing longitudinal cohorts to probe the link, Best Pract. Res. Clin. Rheumatol. 30 (1) (2016)
53–62.
[10] A.P. Kyritsis, S. Boussios, N. Pavlidis, Cancer specific risk in multiple sclerosis patients, Crit. Rev. Oncol. Hematol. 98 (2016) 29–34.
[11] O.O. Olumuyiwa-Akeredolu, E. Pretorius, Rheumatoid arthritis: notable biomarkers
linking to chronic systemic conditions and Cancer, Curr. Pharm. Des. 22 (7) (2016)
918–924.
[12] J.U. Staniforth, S. Erdirimanne, G.D. Eslick, Thyroid carcinoma in Graves’ disease: a
meta-analysis, Int. J. Surg. (London, England) 27 (2016) 118–125.
[13] S. Yadlapati, P. Efthimiou, Autoimmune/Inflammatory arthritis associated lymphomas: who is at risk? Biomed Res. Int. 2016 (2016) 8631061.
[14] A. Ladouceur, S. Bernatsky, R. Ramsey-Goldman, A.E. Clarke, Managing cancer risk
in patients with systemic lupus erythematous, Expert Rev. Clin. Immunol. 14 (10)
(2018) 793–802.
[15] A. Klein, A. Polliack, A. Gafter-Gvili, Rheumatoid arthritis and lymphoma:
Incidence, pathogenesis, biology, and outcome, Hematol. Oncol. 36 (Dec. (5))
(2018) 733–739.
[16] A. Vlagea, S. Falagan, G. Gutierrez-Gutierrez, J. Moreno-Rubio, M. Merino,
F. Zambrana, E. Casado, M. Sereno, Antinuclear antibodies and cancer: a literature
review, Crit. Rev. Oncol. Hematol. 127 (2018) 42–49.
[17] J.F. Ludvigsson, E. Andersson, A. Ekbom, M. Feychting, J.L. Kim, C. Reuterwall,
M. Heurgren, P.O. Olausson, External review and validation of the Swedish national
inpatient register, BMC Public Health 11 (2011) 450.
[18] J. Ji, J. Sundquist, K. Sundquist, Gender-specific incidence of autoimmune diseases
from national registers, J. Autoimmun. 69 (2016) 102–106.
[19] J. Ji, K. Sundquist, J. Sundquist, K. Hemminki, Comparability of cancer identification among death registry, Cancer registry and hospital discharge registry, Int. J.
Cancer 131 (9) (2012) 2085–2093.
[20] M. Fallah, X. Liu, J. Ji, A. Forsti, K. Sundquist, K. Hemminki, Autoimmune diseases
associated with non-Hodgkin lymphoma: a nationwide cohort study, Ann. Oncol. 25
(10) (2014) 2025–2030.
[21] M. Fallah, X. Liu, J. Ji, A. Forsti, K. Sundquist, K. Hemminki, Hodgkin lymphoma
after autoimmune diseases by age at diagnosis and histological subtype, Ann. Oncol.
25 (7) (2014) 1397–1404.
[22] K. Hemminki, X. Liu, A. Forsti, J. Ji, J. Sundquist, K. Sundquist, Effect of autoimmune diseases on incidence and survival in subsequent multiple myeloma, J.
Hematol. Oncol. 5 (2012) 59.
[23] K. Hemminki, X. Liu, A. Forsti, J. Ji, J. Sundquist, K. Sundquist, Subsequent leukaemia in autoimmune disease patients, Br. J. Haematol. 161 (5) (2013) 677–687.
[24] M.J. Amador-Patarroyo, A. Rodriguez-Rodriguez, G. Montoya-Ortiz, How does age
at onset influence the outcome of autoimmune diseases? Autoimmune Dis. 2012
(2012) 251730.
[25] S.L. Craig, A.R. Feinstein, Antecedent therapy versus detection bias as causes of
neoplastic multimorbidity, Am. J. Clin. Oncol. 22 (1) (1999) 51–56.
[26] E.R. Haut, P.J. Pronovost, Surveillance bias in outcomes reporting, Jama 305 (23)
(2011) 2462–2463.
[27] K. Hemminki, O. Hemminki, A. Försti, K. Sundquist, J. Sundquist, X. Li, Surveillance
bias in cancer risk after unrelated medical conditions: example urolithiasis, Sci.
Rep. 7 (2017) 8073.
[28] E. Pedemonte, G. Mancardi, D. Giunti, A. Corcione, F. Benvenuto, V. Pistoia,
A. Uccelli, Mechanisms of the adaptive immune response inside the central nervous
system during inflammatory and autoimmune diseases, Pharmacol. Ther. 111 (3)
(2006) 555–566.
[29] M. El Behi, S. Dubucquoi, D. Lefranc, H. Zephir, J. De Seze, P. Vermersch, L. Prin,
New insights into cell responses involved in experimental autoimmune encephalomyelitis and multiple sclerosis, Immunol. Lett. 96 (1) (2005) 11–26.
[30] S. Birkeland, H. Storm, L. Lamm, L. Barlow, L. Blohme, B. Forsberg, B. Eklund,
O. Fjeldbord, M. Friedberg, L. Frödin, et al., Cancer risk after renal transplantation
in the Nordic countries, 1964-1986, Int. J. Cancer 60 (1995) 183–189.
[31] I. Rama, J.M. Grinyo, Malignancy after renal transplantation: the role of
6. Conclusions
Utilizing large-scale nationwide Swedish data, we have been able to
explore medically verified data on the associations of autoimmune
disease and hematological malignancy. The obtained results clearly
show that the autoimmune diseases are heterogeneous in regard to
hematological malignancy, and the magnitude of the observed associations vary depending on specific autoimmune diseases as well as
different hematological malignancies.
Epidemiological studies have tried to explore the underlying mechanisms behind the association, such as shared genetic and/or shared
environmental factors, therapeutic effect, dysregulated immune function etc. Further evidence from advanced study design might give extra
clues, such as using bivariate twin modeling or adoptive studies to
disentangle the genetic factors from shared environmental factors.
Unfortunately, such studies are still lacking although highly needed.
Contributors
WH, KH, JJ, KS, and JS were responsible for the study concept and
design. JS, KS, and JJ obtained funding. KS and JS acquired the data. JJ
drafted the manuscript, and all authors revised it for important intellectual content. KH and WH contributed equally to this work.
Funding
This work was supported by grants awarded to Dr Jianguang Ji by
the Swedish Research Council (2016-02373), Cancerfonden (CAN2017/
340) and Crafoordska stiftelsen, to Dr Kristina Sundquist by the
Swedish Research Council as well as by ALF funding from Region Skåne
awarded to Jan Sundquist, Kristina Sundquist, and Dr Jianguang Ji. The
funding agencies had no role in the design and conduct of the study; in
the collection, analysis, and interpretation of the data; or in the preparation, review, or approval of the manuscript. The researchers were
independent of the funding agencies.
Acknowledgement
The authors wish to thank the CPF’s science editor Patrick Reilly for
his valuable comments on the text.
Appendix A. Supplementary data
Supplementary material related to this article can be found, in the
online version, at doi:https://doi.org/10.1016/j.semcancer.2019.06.
005.
120
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K. Hemminki, et al.
gut microbiota: a novel diagnostic test for determining dysbiosis in patients with
IBS or IBD, Aliment. Pharmacol. Ther. 42 (1) (2015) 71–83.
[53] S. Devkota, E.B. Chang, Interactions between diet, bile acid metabolism, gut microbiota, and inflammatory bowel diseases, Dig. Dis. (Basel, Switzerland) 33 (3)
(2015) 351–356.
[54] T. Vatanen, E.A. Franzosa, R. Schwager, S. Tripathi, T.D. Arthur, K. Vehik,
A. Lernmark, W.A. Hagopian, M.J. Rewers, J.X. She, et al., The human gut microbiome in early-onset type 1 diabetes from the TEDDY study, Nature 562 (7728)
(2018) 589–594.
[55] M.M. Freemer, T.E. King Jr., L.A. Criswell, Association of smoking with dsDNA
autoantibody production in systemic lupus erythematosus, Ann. Rheum. Dis. 65 (5)
(2006) 581–584.
[56] K. Chang, S.M. Yang, S.H. Kim, K.H. Han, S.J. Park, J.I. Shin, Smoking and rheumatoid arthritis, Int. J. Mol. Sci. 15 (12) (2014) 22279–22295.
[57] Y.J. Zhang, L. Zhang, X.L. Huang, Y. Duan, L.J. Yang, J. Wang, Association between
cigarette smoking and impaired clinical symptoms in systemic sclerosis: a review,
Cell. Immunol. 318 (2017) 1–7.
[58] B.D. Juran, K.N. Lazaridis, Environmental factors in primary biliary cirrhosis,
Semin. Liver Dis. 34 (3) (2014) 265–272.
[59] J. Ji, J. Sundquist, K. Sundquist, Family history of autoimmune diseases and risk of
gastric cancer: a national cohort study, Eur. J. Cancer Prev. 27 (May (3)) (2018)
221–226.
[60] G. Murphy, L. Lisnevskaia, D. Isenberg, Systemic lupus erythematosus and other
autoimmune rheumatic diseases: challenges to treatment, Lancet (London, England)
382 (9894) (2013) 809–818.
[61] L. Lisnevskaia, G. Murphy, D. Isenberg, Systemic lupus erythematosus, Lancet
(London, England) 384 (9957) (2014) 1878–1888.
[62] I.B. McInnes, G. Schett, Pathogenetic insights from the treatment of rheumatoid
arthritis, Lancet (London, England) 389 (10086) (2017) 2328–2337.
[63] S.A. Acuna, Etiology of increased cancer incidence after solid organ transplantation,
Transplant. Rev. (Orlando, Fla) 32 (4) (2018) 218–224.
[64] B. Sprangers, V. Nair, V. Launay-Vacher, L.V. Riella, K.D. Jhaveri, Risk factors associated with post-kidney transplant malignancies: an article from the CancerKidney International Network, Clin. Kidney J. 11 (3) (2018) 315–329.
[65] G.P. Doss, G. Agoramoorthy, C. Chakraborty, TNF/TNFR: drug target for autoimmune diseases and immune-mediated inflammatory diseases, Front. Biosci.
Landmark Ed. (Landmark Ed) 19 (2014) 1028–1040.
[66] S. Bonovas, S. Minozzi, T. Lytras, M. Gonzalez-Lorenzo, V. Pecoraro, S. Colombo,
I. Polloni, L. Moja, M. Cinquini, V. Marino, et al., Risk of malignancies using antiTNF agents in rheumatoid arthritis, psoriatic arthritis, and ankylosing spondylitis: a
systematic review and meta-analysis, Expert Opin. Drug Saf. 15 (sup1) (2016)
35–54.
[67] J. Ji, X. Liu, K. Sundquist, J. Sundquist, K. Hemminki, Cancer risk in patients
hospitalized with polymyalgia rheumatica and giant cell arteritis: a follow-up study
in Sweden, Rheumatology (Oxford) 49 (6) (2010) 1158–1163.
[68] X. Shu, J. Ji, X. Li, J. Sundquist, K. Sundquist, K. Hemminki, Cancer risk in patients
hospitalised for Graves’ disease: a population-based cohort study in Sweden, Br. J.
Cancer 102 (9) (2010) 1397–1399.
[69] X. Shu, J. Ji, X. Li, J. Sundquist, K. Sundquist, K. Hemminki, Cancer risk among
patients hospitalized for Type 1 diabetes mellitus: a population-based cohort study
in Sweden, Diabet. Med. 27 (7) (2010) 791–797.
[70] J. Ji, X. Shu, X. Li, K. Sundquist, J. Sundquist, K. Hemminki, Cancer risk in hospitalized sarcoidosis patients: a follow-up study in Sweden, Ann. Oncol. 20 (6)
(2009) 1121–1126.
[71] J. Ji, X. Shu, K. Sundquist, J. Sundquist, K. Hemminki, Cancer risk in hospitalised
psoriasis patients: a follow-up study in Sweden, Br. J. Cancer 100 (9) (2009)
1499–1502.
[72] A. Mohammed, N.S. Yarla, V. Madka, C.V. Rao, Clinically relevant anti-inflammatory agents for chemoprevention of colorectal Cancer: new perspectives, Int.
J. Mol. Sci. 19 (8) (2018).
[73] C. Saka Herran, E. Jane-Salas, A. Estrugo Devesa, J. Lopez-Lopez, Protective effects
of metformin, statins and anti-inflammatory drugs on head and neck cancer: a
systematic review, Oral Oncol. 85 (2018) 68–81.
immunosuppression, Nat. Rev. Nephrol. 6 (9) (2010) 511–519.
[32] S. Chattopadhyay, A. Sud, G. Zheng, H. Yu, K. Sundquist, J. Sundquist, A. Försti,
R. Houlston, A. Hemminki, K. Hemminki, Second primary cancers in non-Hodgkin
lymphoma: Bi-directional analyses suggesting role for immune dysfunction, Int. J.
Cancer 143 (2018) 2449–2457.
[33] K. Hemminki, X. Liu, J. Ji, A. Forsti, Origin of B-Cell neoplasms in autoimmune
disease, PLoS One 11 (6) (2016) e0158360.
[34] M. Seifert, R. Scholtysik, R. Kuppers, Origin and pathogenesis of B cell lymphomas,
Methods Mol. Biol. 971 (2013) 1–25.
[35] L.B. Alexandrov, S. Nik-Zainal, D.C. Wedge, S.A. Aparicio, S. Behjati, A.V. Biankin,
G.R. Bignell, N. Bolli, A. Borg, A.L. Borresen-Dale, et al., Signatures of mutational
processes in human cancer, Nature 500 (7463) (2013) 415–421.
[36] T. Komata, N. Tsuchiya, M. Matsushita, K. Hagiwara, K. Tokunaga, Association of
tumor necrosis factor receptor 2 (TNFR2) polymorphism with susceptibility to
systemic lupus erythematosus, Tissue Antigens 53 (6) (1999) 527–533.
[37] A.S. Al-Ansari, W.E. Ollier, J. Villarreal, J. Ordi, L.S. Teh, A.H. Hajeer, Tumor necrosis factor receptor II (TNFRII) exon 6 polymorphism in systemic lupus erythematosus, Tissue Antigens 55 (1) (2000) 97–99.
[38] K. Wang, R. Baldassano, H. Zhang, H.Q. Qu, M. Imielinski, S. Kugathasan,
V. Annese, M. Dubinsky, J.I. Rotter, R.K. Russell, et al., Comparative genetic analysis of inflammatory bowel disease and type 1 diabetes implicates multiple loci
with opposite effects, Hum. Mol. Genet. 19 (10) (2010) 2059–2067.
[39] K. Yamamoto, R. Yamada, Genome-wide single nucleotide polymorphism analyses
of rheumatoid arthritis, J. Autoimmun. 25 (Suppl) (2005) 12–15.
[40] Genome-wide association study of 14,000 cases of seven common diseases and
3,000 shared controls, Nature 447 (7145) (2007) 661–678.
[41] D.L. Armstrong, R. Zidovetzki, M.E. Alarcon-Riquelme, B.P. Tsao, L.A. Criswell,
R.P. Kimberly, J.B. Harley, K.L. Sivils, T.J. Vyse, P.M. Gaffney, et al., GWAS identifies novel SLE susceptibility genes and explains the association of the HLA region,
Genes Immun. 15 (6) (2014) 347–354.
[42] K.M. de Lange, L. Moutsianas, J.C. Lee, C.A. Lamb, Y. Luo, N.A. Kennedy, L. Jostins,
D.L. Rice, J. Gutierrez-Achury, S.G. Ji, et al., Genome-wide association study implicates immune activation of multiple integrin genes in inflammatory bowel disease, Nat. Genet. 49 (2) (2017) 256–261.
[43] J.C. Lee, D. Biasci, R. Roberts, R.B. Gearry, J.C. Mansfield, T. Ahmad, N.J. Prescott,
J. Satsangi, D.C. Wilson, L. Jostins, et al., Genome-wide association study identifies
distinct genetic contributions to prognosis and susceptibility in Crohn's disease, Nat.
Genet. 49 (2) (2017) 262–268.
[44] R. Alberts, E.M.G. de Vries, E.C. Goode, X. Jiang, F. Sampaziotis, K. Rombouts,
K. Bottcher, T. Folseraas, T.J. Weismuller, A.L. Mason, et al., Genetic association
analysis identifies variants associated with disease progression in primary sclerosing cholangitis, Gut 67 (8) (2018) 1517–1524.
[45] B.D. Ye, D.P. McGovern, Genetic variation in IBD: progress, clues to pathogenesis
and possible clinical utility, Expert Rev. Clin. Immunol. 12 (10) (2016) 1091–1107.
[46] L. Chen, D.L. Morris, T.J. Vyse, Genetic advances in systemic lupus erythematosus:
an update, Curr. Opin. Rheumatol. 29 (5) (2017) 423–433.
[47] A. Gul, Genetics of Behcet's disease: lessons learned from genomewide association
studies, Curr. Opin. Rheumatol. 26 (1) (2014) 56–63.
[48] A. Zhernakova, E.A. Stahl, G. Trynka, S. Raychaudhuri, E.A. Festen, L. Franke,
H.J. Westra, R.S. Fehrmann, F.A. Kurreeman, B. Thomson, et al., Meta-analysis of
genome-wide association studies in celiac disease and rheumatoid arthritis identifies fourteen non-HLA shared loci, PLoS Genet. 7 (2) (2011) e1002004.
[49] K. Hemminki, A. Forsti, K. Sundquist, J. Sundquist, X. Li, Familial associations of
lymphoma and myeloma with autoimmune diseases, Blood Cancer J. 7 (1) (2017)
e515.
[50] T.M. Triolo, A. Fouts, L. Pyle, L. Yu, P.A. Gottlieb, A.K. Steck, Identical and nonidentical twins: risk and factors involved in development of islet autoimmunity and
type 1 diabetes, Diabetes Care 42 (Feb. (2)) (2019) 192–199.
[51] B. Mansouri, S. Asadollahi, K. Heidari, M. Fakhri, F. Assarzadegan, M. Nazari,
A. Divani, Risk factors for increased multiple sclerosis susceptibility in the Iranian
population, J. Clin. Neurosci. 21 (12) (2014) 2207–2211.
[52] C. Casen, H.C. Vebo, M. Sekelja, F.T. Hegge, M.K. Karlsson, E. Ciemniejewska,
S. Dzankovic, C. Froyland, R. Nestestog, L. Engstrand, et al., Deviations in human
121