Diabetes mellitus (DM) is a type of metabolic disease characterized by hyperglycemia. It is caused by either defected insulin secretion or damaged biological function, or both. The statement of a high-level blood glucose that a body is in for a long time will lead to dysfunction of a variety of tissues. Nowadays, such methods as taking antidiabetic medicines or injecting insulin to cope with diabetes are the usual practice, but there is no way of thorough treatment. Recently, researchers [
Two researchers (Yue and Wu) have conducted document retrieval to the relationship between betatrophin and DM independently and elaborately, who have searched such database in the text as PubMed, MEDLINE, Embase, Cochrane Library with “betatrophin and diabetes,” “Angptl8 and diabetes,” “RIFL and diabetes,” and “Lipasin and diabetes” combined and searched others including CNKI, China Wan-Fang database, and Chongqing VIP database with “betatrophin and diabetes.” The latest search date is May 1, 2015. We have studied every article selected as “Related Articles” by PubMed and searched it to get extra potentially related articles. We have also searched the references and contacted the authors to get extra articles. When there was ambiguity about the results or lack of sufficient data, we contacted all authors to make it clear. The searching method has been made beyond linguistic limits, but we only included the articles published in English or Chinese language.
The following criteria have to be met for the articles to be included: (1) case-control study; (2) the cases in those studies that were type 2 diabetes; (3) all the case groups which were in accordance with international criteria for diagnosis of type 2 diabetes; (4) articles published as papers until May 2015; (5) articles that provided directly or indirectly the results on relevant research index in case group and control group.
Exclusion criteria are defined as follows: (1) articles in which the case group was diagnosed with type 1 diabetes; (2) research with insufficient data; (3) research with data that could not be converted; (4) adopting the best-quality among research papers that were duplicated, repeatedly collected, or with similar data.
The two researchers entered into each database, respectively, with standard procedures and extracted research data independently. If there was a discrepancy, the researchers would appraise the data together. The following information was gathered including the first author, publication year, nationality, blood sample, experimental method, sample size of patients and the control group, and Mean and Standard Deviation (SD) (part of the data were converted) of betatrophin levels.
The review and analysis were guided to conduct by the PRISMA statement for preferred reporting of meta-analysis [
The RevMan5.3 statistical software provided by The Cochrane Collaboration was applied, with Mean and SD as statistics to evaluate strength of association. According to heterogeneity inspection results, corresponding pooled method was chosen: when there was no significant heterogeneity in research results (
After the initial screening, there were 104 papers which reached screening stage including 71 in English and 33 in Chinese. After strict selection process, a total of 11 articles [
Characteristics of eligible studies included in the meta-analysis.
First author | Publication year | Country | Sample | Methods | Cases | Controls | ||
---|---|---|---|---|---|---|---|---|
Subjects ( |
Betatrophin |
Subjects ( |
Betatrophin | |||||
Fenzl [ |
2014 | Germany | Plasma | ELISA | 18 | 1646.5 ± 551.12 | 19 | 1643.4 ± 1002.11 |
Chen [ |
2014 | China | Serum | ELISA | 112 | 798.6 ± 449.78 | 137 | 692.7 ± 339.44 |
Espes [ |
2014 | Sweden | Plasma | ELISA | 27 | 893 ± 415.69 | 18 | 639 ± 280.01 |
Fu [ |
2014 | USA | Serum | ELISA | 14 | 5560 ± 2731.41 | 15 | 2190 ± 929.52 |
Hu [ |
2014 | China | Serum | ELISA | 83 | 613.08 ± 65.15 | 83 | 296.57 ± 52.16 |
Gómez-Ambrosi [ |
2014 | Spain | Serum | ELISA | 15 | 13500 ± 8800 | 33 | 45100 ± 24400 |
Wang [ |
2015 | China | Serum | ELISA | 35 | 1123.52 ± 319.01 | 31 | 669.15 ± 318.16 |
Xie [ |
2014 | China | Serum | ELISA | 50 | 412.53 ± 237.67 | 50 | 306.20 ± 283.82 |
Yamada [ |
2015 | Japan | Serum | ELISA | 30 | 1614 ± 647 | 12 | 300 ± 236 |
Guo [ |
2015 | China | Serum | ELISA | 56 | 162.56 ± 42.25 | 60 | 123.52 ± 28.19 |
Xie [ |
2015 | China | Serum | ELISA | 50 | 833.45 ± 456.21 | 50 | 541.68 ± 136.2 |
Flowchart demonstrating those studies that were processed for inclusion in the meta-analysis.
All this meta-analysis outcomes were shown in Figures
(a) Forest plot of the circulating level of betatrophin in T2DM patient, studies are pooled with random-effects model. (b) Forest plot of the circulating level of betatrophin in Chinese T2DM patient, studies are pooled with random-effects model. (c) Forest plot of the circulating level of betatrophin in Caucasians T2DM patient, studies are pooled with random-effects model.
(a) Forest plot of the circulating level of betatrophin in T2DM patient plasma. (b) Forest plot of the circulating level of betatrophin in T2DM patient serum.
(2) A subgroup analysis was carried out based on different group of people. The results showed that heterogeneity (
(3) Another subgroup analysis was made based on different types of blood samples. The two papers with plasma as research sample did not present a conclusion of heterogeneity (
In addition, the random effect model was carried out to do pooled analysis according to the result of heterogeneity (
All the forest plot data summary.
Subgroup | Article number | Total (95% CI) |
|
|
|
Model |
---|---|---|---|---|---|---|
Chinese | 6 | 214.15 [57.65, 370.65] | 99% | 2.68 |
|
Random |
Caucasian | 4 | 98.40 [−1585.08, 1781.88] | 95% | 0.11 |
|
Random |
Plasma | 2 | 220.47 [31.27, 409.67] | 0 | 2.28 |
|
Fixed |
Serum | 9 | 358,64 [198.04, 519.24] | 99% | 4.38 |
|
Random |
Total | 11 | 329.46 [182.51, 476.42] | 99% | 4.39 |
|
Random |
According to Begg’s and Egger’s tests (Begg,
Funnel plot based on 11 case-control studies.
DM is a metabolic disorder caused by pancreatic beta cells defect or damage [
Previous report showed that betatrophin-encoded protein could significantly promote the proliferation of mouse pancreatic beta cells with increasing number so as to enhance glucose tolerance. With these striking study findings, many scholars conducted research on this newly discovered peptide and examined the relevance between betatrophin and T2DM by detecting the circulating levels of betatrophin in T2DM patients. However, the conclusions were contradictory.
This meta-analysis showed that the pooled value of Mean [95% CI] was of statistical significance, revealing increased circulating levels of betatrophin in T2DM. By subgroup analyses, (1) all the research samples for Chinese people were serum, and the results showed that betatrophin circulating level increased in the serum of Chinese T2DM patients; (2) betatrophin circulating level increased in the plasma of the T2MD patients. Since the study subjects are all Caucasian, we could make a conclusion for the moment: increased plasma betatrophin circulating levels in Caucasian T2DM patients.
However, the result showed that circulating levels of betatrophin in Caucasian T2DM patients have no statistical significance. There are differences between the result of this subgroup analyses and the overall result. Nevertheless, the results were consistent with the conclusions by Fenzl et al. [
During the screening, Ebert et al. [
In this meta-analysis, the entire included case group is T2DM patients. Since the pathogenesis of T1DM is different from that of T2DM, we have not included articles on T1DM research. There have been scholars who have explored, among which Espes et. al. [
According to the forest plot A, substantial heterogeneity (
This is meta-analysis investigating the association between betatrophin and DM, which has significantly increased the statistical power. However, the present results of meta-analysis have some limitations. First, DM is a kind of disease influenced by multiple factors and there are complex interactions between them. In this meta-analysis we have not enough data to evaluate the interaction of betatrophin in diabetes and other factors. Second, we have no access to the data that are not published, so the publication bias cannot be avoided absolutely. Third, our search languages are only English and Chinese and research data of other races may have influence on the results. Fourth, we did not get the original data of the included literature, so we cannot guarantee the accuracy of the data.
Despite the limitations above, we believe that based on the positive results of the meta-analysis, it is worth for more scholars making further study in prospective study and follow-up research.
In conclusion, the meta-analysis of all published case-control studies on betatrophin and T2DM revealed increased circulating levels of betatrophin in patients with type 2 diabetes.
The authors declare no competing financial interests.
Song Yue and Jingyang Wu have contributed to the design of the study and analysis and interpretation of data and prepared all figures and tables. Song Yue, Jingyang Wu, Lei Liu, and Lei Chen drafted a part of the paper. Song Yue, Jiahua Zhang, and Jingyang Wu took part in analyzing data and drafting a part of the paper. All authors reviewed the paper.
The authors thank Miss Hu-nan in Dalian University of Foreign Languages for English language edition. This study was supported by National Natural Science Foundation of China (81300783) and Important Platform of Science and Technology for the University in Liaoning Province (16010).