Literature DB >> 23285188

Common infectious agents and monoclonal B-cell lymphocytosis: a cross-sectional epidemiological study among healthy adults.

Delphine Casabonne1, Julia Almeida, Wendy G Nieto, Alfonso Romero, Paulino Fernández-Navarro, Arancha Rodriguez-Caballero, Santiago Muñoz-Criado, Marcos González Díaz, Yolanda Benavente, Silvia de Sanjosé, Alberto Orfao.   

Abstract

BACKGROUND: Risk factors associated with monoclonal B-cell lymphocytosis (MBL), a potential precursor of chronic lymphocytic leukaemia (CLL), remain unknown.
METHODS: Using a cross-sectional study design, we investigated demographic, medical and behavioural risk factors associated with MBL. "Low-count" MBL (cases) were defined as individuals with very low median absolute count of clonal B-cells, identified from screening of healthy individuals and the remainder classified as controls. 452 individuals completed a questionnaire with their general practitioner, both blind to the MBL status of the subject. Odds ratios (OR) and 95% confidence interval (CI) for MBL were estimated by means of unconditional logistic regression adjusted for confounding factors.
RESULTS: MBL were detected in 72/452 subjects (16%). Increasing age was strongly associated with MBL (P-trend<0.001). MBL was significantly less common among individuals vaccinated against pneumococcal or influenza (OR 0.49, 95% confidence interval (CI): 0.25 to 0.95; P-value=0.03 and OR: 0.52, 95% CI: 0.29 to 0.93, P-value=0.03, respectively). Albeit based on small numbers, cases were more likely to report infectious diseases among their children, respiratory disease among their siblings and personal history of pneumonia and meningitis. No other distinguishing epidemiological features were identified except for family history of cancer and an inverse relationship with diabetes treatment. All associations described above were retained after restricting the analysis to CLL-like MBL.
CONCLUSION: Overall, these findings suggest that exposure to infectious agents leading to serious clinical manifestations in the patient or its surroundings may trigger immune events leading to MBL. This exploratory study provides initial insights and directions for future research related to MBL, a potential precursor of chronic lymphocytic leukaemia. Further work is warranted to confirm these findings.

Entities:  

Mesh:

Year:  2012        PMID: 23285188      PMCID: PMC3532166          DOI: 10.1371/journal.pone.0052808

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Monoclonal B-cell lymphocytosis (MBL) is defined by the presence of <5×109 clonal B-cells/L in peripheral blood (PB) of healthy individuals [1], [2]. Two entities can be distinguished within MBL, based on the absolute count of clonal B-cells: a) those diagnosed in clinical settings and associated with lymphocytosis with a median absolute count of clonal B-cells >1.5×109/L; and b) population-screened MBL, the so-called “low-count” MBL, with very low median absolute count of clonal B-cells of about 0.05×109/L, identified in population-screening studies of healthy individuals using high-sensitive flow cytometry approaches [3], [4]. Based on immunophenotypic grounds, MBL can be classified as chronic lymphocytic leukaemia (CLL)-like MBL, with a CD5+, CD23+ and CD20low phenotype representing the most common subgroup (∼ 75/80% of MBL), atypical-CLL (CD5+, CD20bright) and CD5MBL [2]. With advanced flow cytometry techniques, low count “CLL-like” MBL is detected in 12%–14% [5], [6] of healthy adults in population-screening studies. Recent research suggests systematic occurrence of clinical CLL-like MBL prior to CLL [7]. However, most CLL-like MBL patients never develop clinical complications and the estimated yearly rate of progression of clinical CLL-like MBL to CLL with treatment requirement is 1–2% [8]; in turn, the rate of progression of “low count” CLL-like MBL is still unknown. The aetiology of MBL and CLL remains unknown and few studies have been reported on potential risk factors for MBL. Unambiguous risk factors associated to both CLL and MBL are increasing age [9] and genetic susceptibility [10]. In turn, male predominance is also recurrently reported in CLL but results on MBL are controversial [11]. Exposure to pesticide, herbicides and chemical agents has also been associated with CLL [12]. Caucasian ethnicity has long stood as a risk factor for CLL with lower incidence rates among Asian than Caucasian Americans. However, recent studies reported higher CLL incidence rates among Asian US born than Asian foreign born [13] subjects and increasing trends in CLL incidence rates in Taiwan [14]. Altogether, these results suggest a potential role for some strong but unidentified environmental factors in the aetiology of CLL. Recently, Moreira et al. (2012) reported that the risk of hospitalisation for infections was more common in newly diagnosed clinical MBL and CLL patients than controls [15]. Other risk factors associated with MBL might include living near a hazardous waste site [11]. As part of a study examining the prevalence of MBL in the general population [5], [6], we investigated potential risk factors associated with “low count” MBL using a cross-sectional study design among 452 healthy subjects randomly selected from the Primary Health Care system of the region of Salamanca (Spain). This exploratory study provides initial insights and directions for future research related to MBL, a potential precursor of chronic lymphocytic leukaemia. In particular our findings suggest that exposure to infectious agents leading to serious clinical manifestations in the patient or its surroundings may trigger immune events leading to MBL.

Methods

Design and Subjects

As part of a study examining the prevalence of MBL through highly sensitive multicolor flow cytometry in a cohort of 639 healthy adults with normal PB lymphocyte counts from the general population of the Primary Health Care system region of Salamanca (northwest-central Spain) [5], we investigated risk factors associated with “low-count” MBL. All these 639 cases have been described previously in clinical, as well as phenotypic/genetic and molecular terms [5], [6]. Among the 639 subjects older than 40 years, 452 (71%) completed a questionnaire with their general practitioner, both blind to the MBL status of the subject. Individuals with MBL were denoted as cases and the remainder classified as controls. MBL cases were further classified as either “CLL-like” or non-“CLL-like” MBL, based on the presence versus absence of a CD5+, CD23+ and CD20dim immunophenotype, respectively. The research protocol was approved by the Ethics Committee of the Cancer Research Center of Salamanca and all participants gave their written informed consent in accordance with the Declaration of Helsinki.

Immunophenotypic Analyses

The flow cytometry approach has been described in detail in the previous study [5]. In brief, per case, between 1 and 4 mL of EDTA-anticoagulated PB was immunophenotyped using a highly sensitive 8-color flow cytometry. The minimum number of clustered cellular events required to define the presence of a clonal B-cell population was 50.

Statistical Analyses

All statistical analyses were performed using STATA10.1 (Statacorp, USA). We used unconditional logistic regression adjusted for age (<50, 50–59, 60–69, 70 or more) and sex to calculate odds ratios (OR) and 95% confidence intervals (CI) for MBL in relation to different risk factors from the questionnaire. Further adjustment for family size, number of children or number of siblings was performed as appropriate (for instance, the variable self-reported history of infections among children was further adjusted for number of children). Since pneumococcal and influenza vaccinations are generally provided from the age of 60 years in Spain, further analyses stratified by age (≥60 years) were performed. Self-reported current drug use was grouped into 14 major groups of drugs as per the Anatomical Therapeutic Chemical Classification System (2003). Sensitivity analysis restricting the outcome to CLL-like MBL was performed.

Results

Overall, 72/452 subjects (16%) were diagnosed with “low-count” MBL (mean absolute B-cell count: 0.055; standard deviation: 0.216; maximum: 1.172×109 B-cells/L) (Table 1). Most cases (60/72; 83%) were classified as CLL-like MBL. About half of the cases (48%) and the controls (49%) were males (P = 0.9). OR of “low-count” MBL cases increased with increasing age (P<0.001). Cases and controls did not differ in terms of area of recruitment, residence of birth, tobacco and alcohol consumption, body mass index, height, weight and women reproductive history (data not shown).
Table 1

Socio-demographic and descriptive characteristics of “low-count” monoclonal B-cell lymphocytosis (MBL) cases and non-MBL subjects (controls).

Controls N = 380MBL cases N = 72OR1 & 95% CI
SEX
Male181 (48%)35 (49%)Ref
Female199 (53%)37 (51%)1.04 (0.62 to 1.75)
P-het = 0.9
AGE
<5092 (24%)6 (8%)Ref
50–5999 (26%)7 (10%)1.09 (0.35 to 3.35)
60–6978 (21%)19 (26%)3.74 (1.42 to 9.84)
70–7985 (22%)26 (36%)4.70 (1.84 to 12.00)
80 or more26 (7%)14 (19%)8.26 (2.89 to 23.62)
P-trend<0.0001
mean (SD)60 (13)70 (11)
range40 to 9743 to 95
AREA OF RECRUITMENT
Salamanca suburb64 (17%)8 (11%)Ref
Salamanca centre95 (25%)19 (26%)1.50 (0.60 to 3.73)
Rural221 (58%)45 (63%)1.46 (0.64 to 3.34)
P-het = 0.6
RESIDENCE AT BIRTH
Salamanca City221 (59%)40 (57%)Ref
Salamanca county, excluding Salamanca city97 (26%)23 (33%)1.11 (0.62 to 1.99)
Other Spanish counties45 (12%)7 (10%)0.95 (0.39 to 2.31)
Other country9 (2%)0 (0%)NA
P-het = 0.9
TOBACCO CONSUMPTION
Never220 (58%)48 (67%)Ref
Past90 (24%)15 (21%)0.86 (0.40 to 1.85)
Current69 (18%)9 (13%)1.08 (0.44 to 2.65)
P-het = 0.9
ALCOHOL CONSUMPTION
Never212 (56%)42 (60%)Ref
2–4 times/week50 (13%)7 (10%)0.92 (0.37 to 2.32)
Week-end56 (15%)4 (6%)0.57 (0.18 to 1.77)
Everyday58 (15%)17 (24%)1.57 (0.72 to 3.43)
P-het = 0.2
BODY MASS INDEX, kg/cm2
<2584 (29%)15 (27%)Ref
25–29129 (45%)23 (42%)0.88 (0.42 to 1.85)
≥3075 (26%)17 (31%)1.00 (0.45 to 2.22)
P-trend = 1.0
mean (SD)27.6 (4.6)27.8 (4.0)
 missing 92 (24%) 17 (24%)

Adjusted for age (<50, 50–59, 60–69, 70+) and sex.

Ref: reference group; N: number; SD: standard deviation; het: heterogeneity.

OR: Odds ratio; CI: confidence interval.

Adjusted for age (<50, 50–59, 60–69, 70+) and sex. Ref: reference group; N: number; SD: standard deviation; het: heterogeneity. OR: Odds ratio; CI: confidence interval. Conversely, a clear association with transmission and exposure to infection agents was found (Figure 1). In detail, “low-count” MBL cases were less likely to have reported having pneumococcal (OR: 0.49; 95% CI: 0.25 to 0.95; P = 0.03) and influenza (OR: 0.52; 95% CI: 0.29 to 0.93; P = 0.03) vaccination and more likely to have had pneumonia (OR: 3.26; 95% CI: 1.03 to 10.27; P = 0.04), meningitis (OR: 11.73; 95%CI: 1.45 to 95.13; P = 0.02) or influenza (OR: 6.72; 95% CI: 0.31 to 146.70; P = 0.2). Albeit based on small numbers, such association was also supported by an increased number of reported infectious diseases in the children of cases (OR: 2.14; 95%: 0.92 to 5.01; P = 0.08) and of respiratory diseases among their siblings (OR: 4.35; 95% CI: 1.23 to 15.34; P = 0.02). Furthermore, the OR for “low-count” MBL increased with increasing number of children among cases with children (P<0.001), such trend being observed separately in men and women (P<0.001). However, childless individuals were also three times more likely to have been diagnosed with MBL compared to individuals with only 1 child and no potential confounders could explain this association.
Figure 1

Odds ratios for “low-count” monoclonal B-cell lymphocytosis by selected potential variables related to infectious agents.

Ref: reference group; N: number; het: heterogeneity; OR: Odds ratio; CI: confidence interval 1: Adjusted for age (<50, 50–59, 60–69, 70+) and sex 2: Further adjusted for family size (using the total number of children and siblings; categories: <6; 6 or more; missing). 3: Further adjusted for number of siblings (categories: <2; 3 or more; missing) Further adjusted for number of children (0/2; 3or more; missing) Adjusted for age (<70, 70+) and sex, Ncontrols = 189; Ncases = 59 P-values were calculated using Wald-test. Black squares indicate OR, the area of each square being proportional to the amount of statistical information contributed. Horizontal lines represent 95% CI.

Odds ratios for “low-count” monoclonal B-cell lymphocytosis by selected potential variables related to infectious agents.

Ref: reference group; N: number; het: heterogeneity; OR: Odds ratio; CI: confidence interval 1: Adjusted for age (<50, 50–59, 60–69, 70+) and sex 2: Further adjusted for family size (using the total number of children and siblings; categories: <6; 6 or more; missing). 3: Further adjusted for number of siblings (categories: <2; 3 or more; missing) Further adjusted for number of children (0/2; 3or more; missing) Adjusted for age (<70, 70+) and sex, Ncontrols = 189; Ncases = 59 P-values were calculated using Wald-test. Black squares indicate OR, the area of each square being proportional to the amount of statistical information contributed. Horizontal lines represent 95% CI. MBL cases were also more likely to report haematological cancer and solid cancer among their first-degree relatives, compared to controls (Table 2). Conversely, cases and controls did not differ in terms of the current use of any of the 14 different groups of drugs. However, 6% (N = 4) of “low-count” MBL cases versus 12% (N = 44) of controls (OR: 0.30; 95% CI: 0.10 to 0.87; P = 0.03), reported treatment for diabetes (Table S1 in File S1). Noteworthy, all associations described above were retained when the analyses were restricted to CLL-like MBL (Table 3). MBL load was not associated with any of the exposure variables, whereas normal B-cell count was decreasing with increasing age and was higher in women than men (data not shown).
Table 2

Odds ratios (OR) estimates, with 95% confidence intervals (CI), for “low-count” monoclonal B-cell lymphocytosis by self-reported family history of cancer.

Controls N = 380MBL cases N = 72OR1 & 95% CI
Ever had family history of haematological cancer
None356 (94%)63 (87%)ref
1 family member affected2 22 (12%)8 (28%)1.96 (0.79 to 4.86)
2 family members affected2 2 (1%)1 (3%)3.70 (0.28 to 49.35)
P-trend = 0.07
Ever (any family members)2 24 (6%)9 (13%)2.07 (0.87 to 4.93); P = 0.1
 Participant1 (<1%)0 (0%)NA
 1st degree relatives2 22 (6%)9 (13%)2.23 (0.93 to 5.38); P = 0.07
   Father 4 (1%) 4 (6%) 11.49 (2.42 to 54.55); P = 0.002
   Mother 4 (1%) 0 (0%) NA
   Sibling 3 11 (3) 6 (8) 2.46 (0.84 to 7.17); P = 0.1
   Children 4 4 (1%) 0 (0%) NA
 2nd degree relatives2 (<1%)0 (0%) NA
Ever had family history of solid cancer
None168 (44%)26 (36%)
1 family member affected2 145 (38%)32 (44%)1.57 (0.87 to 2.84)
2 family members affected2 48 (13%)9 (13%)1.57 (0.87 to 2.84)
3 family members affected2 18 (5%)4 (6%)1.66 (0.49 to 5.65)
4 family members affected2 1 (<1%)1 (2%)9.87 (0.42 to 232.60)
P-trend =  0.2
Ever (any family members)2 212 (56%)1.54 (0.89 to 2.66); P = 0.1
 Participant27 (7%)0.83 (0.32 to 2.15); P = 0.7
 1st degree relatives2 164 (43%)2.02 (1.17 to 3.47); P = 0.01
   Father 87 (23%)1.03 (0.54 to 1.97); P = 0.9
   Mother 57 (15%)0.86 (0.38 to 1.96); P = 0.7
   Sibling 3 60 (16%)2.92 (1.59 to 5.36); P = 0.001*
    Prostate , 5 6 (2%) 6.31 (1.99 to 20.00); P = 0.002
   Children 4 6 (2%)1.56 (0.28 to 8.59); P = 0.6
 2nd degree relatives62 (16%)0.95 (0.39 to 2.32); P = 0.9
Ever had family history of solid and/or haematological cancers 2
Never156 (41%)20 (28%)ref
With family history of solid cancer only200 (53%)43 (60%)1.89 (1.04 to 3.45)
With family history of haematological cancer only12 (3%)6 (8%)4.23 (1.33 to 13.50)
With family history of both type of cancers12 (3%)3 (4%)1.93 (0.46 to 8.09)
P-heterogeneity = 0.02

Ref: reference group; N: number; NA: not estimated; het: heterogeneity.

OR: Odds ratio; CI: confidence interval; 1st degree relatives: parents, siblings and children; 2nd degree relatives: grand-parents.

Adjusted for age (<50, 50–59, 60–69, 70+) and sex.

Further adjusted for family size (using the total number of children and siblings; categories: <6; 6 or more; missing).

Further adjusted for number of siblings (categories: <2; 3 or more; missing).

Further adjusted for number of children (<2; 3 or more; missing).

Adjusted for number of brothers (<3; 3 or more; missing).

Table 3

Odds ratios (OR) estimates, with 95% confidence intervals (CI), for “low-count” CLL-like monoclonal B-cell lymphocytosis (60 out of 72 cases) by previous associated factors.

ControlsN = 380MBL casesN = 60OR1 & 95% CI
Age
<5092 (24%)6 (10%)Ref
50–5999 (26%)5 (8%)0.78 (0.23 to 2.66)
60–6978 (21%)16 (27%)3.19 (1.19 to 8.57)
70–7985 (22%)22 (37%)4.06 (1.56 to 10.52)
80 or more26 (7%)11 (18%)6.56 (2.21 to 19.45)
mean (SD)60 (13)69 (12)
P-trend<0.0001
range40 to 9743 to 93
Self-reported infectious diseases among
Children2 32 (8%)8 (13%)2.33 (0.95 to 5.69); P = 0.06
Self-reported respiratory diseases among
Sibling3 7 (2%)4 (7%)4.32 (1.13 to 16.56); P = 0.03
Self-reported vaccination against
Pneumococcus4 78 (41%)14 (29%)0.48 (0.24 to 0.99); P = 0.05
Influenza153 (40%)26 (43%)0.58 (0.31 to 1.07); P = 0.08
Self-reported respiratory tract infections
Pneumonia8 (2%)6 (10%)4.18 (1.31 to 13.27); P = 0.02
Influenza1 (<1%)1 (2%)7.49 (0.35 to 162.48); P = 0.2
Meningitis3 (<1%)1 (2%)9.79 (0.80 to 119.99); P = 0.07
Number of children
None57 (15%)14 (23%)3.24 (0.96 to 10.85)
167 (18%)4 (7%)Ref
2141 (37%)11 (18%)1.07 (0.32 to 3.61)
366 (18%)11 (18%)2.07 (0.59 to 7.32)
4 or more46 (12%)20 (33%)4.23 (1.24 to 14.43)
P-trend (in parous)<0.0001
Diabetes treatment 44 (12%)3 (5%)0.27 (0.08 to 0.91); P = 0.04
Ever had family history of haematological cancer
Ever (any family members)5 24 (6%)8 (13%)2.18 (0.88 to 5.40); P = 0.09
1st degree relatives5 22 (6%)8 (13%)2.36 (0.94 to 5.94); P = 0.07
  Father 4 (1%)4 (7%)16.30 (3.30 to 80.58); P = 0.001
Ever had family history of solid cancer
1st degree relatives5 164 (43%)34 (57%)1.72 (0.97 to 3.08); P = 0.07
 Sibling 4 60 (16%)21 (35%) 2.43 (1.25 to 4.73); P = 0.009
  Prostate 6 6 (2%)6 (10%) 5.95 (1.71 to 20.73); P = 0.005

1Adjusted for age (<50, 50–59, 60–69, 70+) and sex.

Further adjusted for number of children (<2; 3 or more; missing).

Further adjusted for number of siblings (categories: <2; 3 or more; missing).

Among 60 years old and older , N

Further adjusted for family size (using the total number of children and siblings; categories: <6; 6 or more; missing).

Further adjusted for number of brothers (<3; 3 or more; missing).

Ref: reference group; N: number; OR: Odds ratio; CI: confidence interval; SD: standard deviation.

Ref: reference group; N: number; NA: not estimated; het: heterogeneity. OR: Odds ratio; CI: confidence interval; 1st degree relatives: parents, siblings and children; 2nd degree relatives: grand-parents. Adjusted for age (<50, 50–59, 60–69, 70+) and sex. Further adjusted for family size (using the total number of children and siblings; categories: <6; 6 or more; missing). Further adjusted for number of siblings (categories: <2; 3 or more; missing). Further adjusted for number of children (<2; 3 or more; missing). Adjusted for number of brothers (<3; 3 or more; missing). 1Adjusted for age (<50, 50–59, 60–69, 70+) and sex. Further adjusted for number of children (<2; 3 or more; missing). Further adjusted for number of siblings (categories: <2; 3 or more; missing). Among 60 years old and older , N Further adjusted for family size (using the total number of children and siblings; categories: <6; 6 or more; missing). Further adjusted for number of brothers (<3; 3 or more; missing). Ref: reference group; N: number; OR: Odds ratio; CI: confidence interval; SD: standard deviation.

Discussion

To our knowledge, this is the first epidemiological study investigating risk factors associated with MBL in the general population. In contrast to CLL, the male predominance was not observed for “low-count” MBL in our data whereas, as expected, OR of cases increased with increasing age. Our main findings were that lifetime exposure to several infectious agents might be associated with MBL aetiology. Assuming that MBL, in particular CLL-like subtype, is a precursor of CLL [7], our findings are consistent with previous studies on CLL reporting that a personal history of pneumonia was associated with subsequent development of CLL [16]–[18]. Recent data also showed an increased risk of hospitalisation for infections among newly diagnosed clinical MBL than controls [15]. Since general population “low-count” CLL-like MBL is 100 times more common than CLL among the elderly [19] and persists over time without clinical progression [4], it was therefore postulated that “low-count” CLL-like MBL are less likely than clinical CLL-like MBL to progress to CLL: among 76 examined patients (median age: 66 years; range: 25–92 years) with low-count population-screening CLL-like MBL, none developed CLL after a 3-year median follow-up, even if they were found to carry 13q deletion with the same frequency to that observed in patients with newly diagnosed CLL and clinical MBL [4]. Hence, “low-count” CLL-like MBL might even be a normal stage of the immunosenescence process [4]. The observed link with infections for “low-count” CLL-like MBL might appear of limited value if the rate of progression of “low-count” CLL-like MBL to CLL is very low; however this progression rate is still unknown and large prospective studies are needed to evaluate which patients with MBL will advance to CLL. The progression from CLL-like MBL of “low-count” or clinical populations to CLL might then be due to the occurrence in MBL cells of specific biological and molecular profiles [20], potentially combined with exposure to some unknown environmental risk factors. Several hypotheses have been advanced to explain an infectious route in CLL. Accordingly, recent reports [21] suggest that chronic and persistent antigenic stimulation may have a role in MBL and CLL aetiology and, respiratory tract infections could particularly be triggers for CLL development [16]. Hepatitis C virus has also been suggested as a potential candidate for dysregulation of the immune system with recent data showing that the three MBL subtypes are more frequent in HCV infected individuals than in the general population [22]. In our data, we could not distinguish between the different hepatitis and no statistical significant association was observed with overall self-reported history of hepatitis or vaccination against hepatitis. We observed that family history of cancer in particular haematological cancers was more common in patients with MBL than controls. In the published literature, MBL is indeed more frequent in families with CLL cases, in particular among first-degree relatives of patients with familial CLL [23]. Unfortunately, we could not differentiate here the association by haematological subtypes as this information was unavailable. In relation to the use of diabetes treatment and chronic lymphocytic leukaemia, data in the literature is inconsistent; while some authors report an increased risk of CLL among diabetic patients [24], others suggest a lower risk of lymphoma [25] and other cancers [26] particularly when using metformin. Further studies are needed to clarify this finding.There are several limitations of this study. The questionnaire provided limited information on occupation (either job title or company type/name was reported). Hence, occupational exposure to contaminants, organic solvents, herbicides or infections could not be examined. Furthermore the origin and type (viral/bacterial and chronic/acute) of infections that occurred among the children and other family members were not specified. However, this type of data is clearly difficult to collect in epidemiological settings. Other potential limitations of our study are the lack of validation of self-reports of family history even though questionnaires were filled in with general practitioners, as well as the limited information on timing of infection relative to date of recruitment. Despite the fact that the number of cases in each stratum was relatively small for some categories and that the number of comparisons performed was high, our results point out a potential role of infectious agents in the development of “low-count” MBL in the general population, particularly of those involved in respiratory infections. However, a reverse causality effect that would result on detecting a more suppressed immune system among subjects with MBL or already in the pathway of CLL cannot be excluded, as decreased numbers of normal PB B-cells as well as CD4+CD8+ double-positive T-cells have been specifically reported in "low-count” MBL [27]. Recent findings showing that regulatory T-cells increase gradually from controls to “clinical” MBL to CLL [28], and that most “low-count” MBL subjects show T-cell clones especially among CD4+CD8+ T-cells [4] further support the hypothesis of an altered immune system of MBL patients. Further studies analyzing dysregulations of the immune system in MBL compared to controls are required. Although selection biases cannot be ruled out, the robustness of the study relies in that neither the interviewers nor the study subjects were aware of the MBL status. This small exploratory study provides initial insights and directions for future research. Further studies are needed to evaluate the association between MBL and CLL and to examine the role of infectious agents in the development and progression of both entities. Table S1 and list of members of the Primary Health Care Group of Salamanca for the Study of MBL (List S1) (DOC) Click here for additional data file.
  28 in total

1.  Link found between Agent Orange and chronic lymphocytic leukaemia.

Authors:  Charles Marwick
Journal:  BMJ       Date:  2003-02-01

2.  Circulating regulatory T cells in &#x0022;clinical&#x0022; monoclonal B-cell lymphocytosis.

Authors:  G D'Arena; G Rossi; M M Minervini; L Savino; F D'Auria; L Laurenti; M I Del Principe; S Deaglio; A Biagi; L De Martino; V De Feo; T Statuto; P Musto; G Del Poeta
Journal:  Int J Immunopathol Pharmacol       Date:  2011 Oct-Dec       Impact factor: 3.219

3.  Lymphoid malignancies in U.S. Asians: incidence rate differences by birthplace and acculturation.

Authors:  Christina A Clarke; Sally L Glaser; Scarlett L Gomez; Sophia S Wang; Theresa H Keegan; Juan Yang; Ellen T Chang
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2011-04-14       Impact factor: 4.254

4.  Diabetes mellitus, medications for type 2 diabetes mellitus, and cancer risk.

Authors:  Carlo La Vecchia
Journal:  Metabolism       Date:  2011-05-06       Impact factor: 8.694

5.  CLL-like B-lymphocytes are systematically present at very low numbers in peripheral blood of healthy adults.

Authors:  J Almeida; W G Nieto; C Teodosio; C E Pedreira; A López; P Fernández-Navarro; A Nieto; A Rodríguez-Caballero; S Muñoz-Criado; M Jara-Acevedo; A Romero; A Orfao
Journal:  Leukemia       Date:  2011-01-14       Impact factor: 11.528

6.  General population low-count CLL-like MBL persists over time without clinical progression, although carrying the same cytogenetic abnormalities of CLL.

Authors:  Claudia Fazi; Lydia Scarfò; Lorenza Pecciarini; Francesca Cottini; Antonis Dagklis; Agnieszka Janus; Anna Talarico; Cristina Scielzo; Cinzia Sala; Daniela Toniolo; Federico Caligaris-Cappio; Paolo Ghia
Journal:  Blood       Date:  2011-08-29       Impact factor: 22.113

Review 7.  CLL-like monoclonal B-cell lymphocytosis: are we all bound to have it?

Authors:  Lydia Scarfò; Antonis Dagklis; Cristina Scielzo; Claudia Fazi; Paolo Ghia
Journal:  Semin Cancer Biol       Date:  2010-09-15       Impact factor: 15.707

8.  Monoclonal B-cell lymphocytosis (MBL) with normal lymphocyte counts is associated with decreased numbers of normal circulating B-cell subsets.

Authors:  Alexander W Hauswirth; Julia Almeida; Wendy G Nieto; Cristina Teodosio; Arancha Rodriguez-Caballero; Alfonso Romero; Antonio López; Paulino Fernandez-Navarro; Tomas Vega; Martin Perez-Andres; Peter Valent; Ulrich Jäger; Alberto Orfao
Journal:  Am J Hematol       Date:  2012-06-08       Impact factor: 10.047

9.  Monoclonal B cell lymphocytosis in hepatitis C virus infected individuals.

Authors:  Claudia Fazi; Antonis Dagklis; Francesca Cottini; Lydia Scarfò; Maria Teresa Sabrina Bertilaccio; Renato Finazzi; Massimo Memoli; Paolo Ghia
Journal:  Cytometry B Clin Cytom       Date:  2010       Impact factor: 3.058

10.  Genome-wide association study identifies a novel susceptibility locus at 6p21.3 among familial CLL.

Authors:  Susan L Slager; Kari G Rabe; Sara J Achenbach; Celine M Vachon; Lynn R Goldin; Sara S Strom; Mark C Lanasa; Logan G Spector; Laura Z Rassenti; Jose F Leis; Nicola J Camp; Martha Glenn; Neil E Kay; Julie M Cunningham; Curtis A Hanson; Gerald E Marti; J Brice Weinberg; Vicki A Morrison; Brian K Link; Timothy G Call; Neil E Caporaso; James R Cerhan
Journal:  Blood       Date:  2010-12-03       Impact factor: 22.113

View more
  14 in total

Review 1.  Monoclonal B-cell lymphocytosis and early-stage chronic lymphocytic leukemia: diagnosis, natural history, and risk stratification.

Authors:  Paolo Strati; Tait D Shanafelt
Journal:  Blood       Date:  2015-06-11       Impact factor: 22.113

2.  Molecular and cytogenetic characterization of expanded B-cell clones from multiclonal versus monoclonal B-cell chronic lymphoproliferative disorders.

Authors:  Ana Henriques; Arancha Rodríguez-Caballero; Ignacio Criado; Anton W Langerak; Wendy G Nieto; Quentin Lécrevisse; Marcos González; Emília Cortesão; Artur Paiva; Julia Almeida; Alberto Orfao
Journal:  Haematologica       Date:  2014-01-31       Impact factor: 9.941

3.  Effects of aging, cytomegalovirus infection, and EBV infection on human B cell repertoires.

Authors:  Chen Wang; Yi Liu; Lan T Xu; Katherine J L Jackson; Krishna M Roskin; Tho D Pham; Jonathan Laserson; Eleanor L Marshall; Katie Seo; Ji-Yeun Lee; David Furman; Daphne Koller; Cornelia L Dekker; Mark M Davis; Andrew Z Fire; Scott D Boyd
Journal:  J Immunol       Date:  2013-12-11       Impact factor: 5.422

4.  Effects of prostaglandin E2 on p53 mRNA transcription and p53 mutagenesis during T-cell-independent human B-cell clonal expansion.

Authors:  Shabirul Haque; Xiao Jie Yan; Lisa Rosen; Steven McCormick; Nicholas Chiorazzi; Patricia K A Mongini
Journal:  FASEB J       Date:  2013-10-21       Impact factor: 5.191

5.  Combined patterns of IGHV repertoire and cytogenetic/molecular alterations in monoclonal B lymphocytosis versus chronic lymphocytic leukemia.

Authors:  Ana Henriques; Arancha Rodríguez-Caballero; Wendy G Nieto; Anton W Langerak; Ignacio Criado; Quentin Lécrevisse; Marcos González; Maria L Pais; Artur Paiva; Julia Almeida; Alberto Orfao
Journal:  PLoS One       Date:  2013-07-03       Impact factor: 3.240

6.  Association of polygenic risk score with the risk of chronic lymphocytic leukemia and monoclonal B-cell lymphocytosis.

Authors:  Geffen Kleinstern; Nicola J Camp; Lynn R Goldin; Celine M Vachon; Claire M Vajdic; Silvia de Sanjose; J Brice Weinberg; Yolanda Benavente; Delphine Casabonne; Mark Liebow; Alexandra Nieters; Henrik Hjalgrim; Mads Melbye; Bengt Glimelius; Hans-Olov Adami; Paolo Boffetta; Paul Brennan; Marc Maynadie; James McKay; Pier Luigi Cocco; Tait D Shanafelt; Timothy G Call; Aaron D Norman; Curtis Hanson; Dennis Robinson; Kari G Chaffee; Angela R Brooks-Wilson; Alain Monnereau; Jacqueline Clavel; Martha Glenn; Karen Curtin; Lucia Conde; Paige M Bracci; Lindsay M Morton; Wendy Cozen; Richard K Severson; Stephen J Chanock; John J Spinelli; James B Johnston; Nathaniel Rothman; Christine F Skibola; Jose F Leis; Neil E Kay; Karin E Smedby; Sonja I Berndt; James R Cerhan; Neil Caporaso; Susan L Slager
Journal:  Blood       Date:  2018-04-19       Impact factor: 25.476

7.  Aberrant Epstein-Barr virus antibody patterns and chronic lymphocytic leukemia in a Spanish multicentric case-control study.

Authors:  Delphine Casabonne; Yolanda Benavente; Claudia Robles; Laura Costas; Esther Alonso; Eva Gonzalez-Barca; Adonina Tardón; Trinidad Dierssen-Sotos; Eva Gimeno Vázquez; Marta Aymerich; Elias Campo; Gemma Castaño-Vinyals; Nuria Aragones; Marina Pollan; Manolis Kogevinas; Hedy Juwana; Jaap Middeldorp; Silvia de Sanjose
Journal:  Infect Agent Cancer       Date:  2015-02-09       Impact factor: 2.965

Review 8.  New insights into monoclonal B-cell lymphocytosis.

Authors:  Christina Kalpadakis; Gerassimos A Pangalis; Sotirios Sachanas; Theodoros P Vassilakopoulos; Stavroula Kyriakaki; Penelope Korkolopoulou; Efstathios Koulieris; Maria Moschogiannis; Xanthi Yiakoumis; Pantelis Tsirkinidis; Marie-Christine Kyrtsonis; Georgia Levidou; Helen A Papadaki; Panayiotis Panayiotidis; Maria K Angelopoulou
Journal:  Biomed Res Int       Date:  2014-09-11       Impact factor: 3.411

9.  HLA specificities are associated with prognosis in IGHV-mutated CLL-like high-count monoclonal B cell lymphocytosis.

Authors:  María García-Álvarez; Miguel Alcoceba; Miriam López-Parra; Noemí Puig; Alicia Antón; Ana Balanzategui; Isabel Prieto-Conde; Cristina Jiménez; María E Sarasquete; M Carmen Chillón; María Laura Gutiérrez; Rocío Corral; José María Alonso; José Antonio Queizán; Julia Vidán; Emilia Pardal; María Jesús Peñarrubia; José M Bastida; Ramón García-Sanz; Luis Marín; Marcos González
Journal:  PLoS One       Date:  2017-03-01       Impact factor: 3.240

10.  Small clonal B-cell population in the bone marrow as a possible tool in the diagnosis of occult primary parotid lymphoma.

Authors:  Martha Romero; Guido R González-Fontal; Mónica Duarte; Carlos Saavedra; Andrés F Henao-Martínez
Journal:  Colomb Med (Cali)       Date:  2016-03-30
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.