The aim of the study is to determine the association between Behavioral Lifestyles  and longevity in the elderly. A search strategy was conducted in the PsycInfo, Medline, PubMed, Web of Science (WoS), and Scopus databases. The primary outcome was mortality/survival. Four variables  were analyzed to evaluate the role of potential moderators. Ninety-three articles, totaling more than 2,800,000 people, were included in the meta-analysis. We found that the lifestyles analyzed predict greater survival. Specifically, doing regular physical activity, engaging in leisure activities, sleeping 7–8 h a day, and staying outside the BMI ranges considered as underweight or obesity are habits that each separately has a greater probability associated with survival after a period of several years. In general, it is genetic and environmental factors which are held to be the main determinants of survival and longevity ” is trying to empirically test whether psycho-behavioral factors, such as behavioral life styles, should be considered as a missing link in a new paradigm to account for healthy and active longevity for the simple reason that se while these behaviors are developed across the lifespan, they can be reinforced and promoted, enhanced, or reduced throughout older age , and survival (continued existence or life) and longevity  shows that since the middle of the nineteenth century, increasing and non-interrupted growth of life expectancy has continued to the present day  Between 2015 and 2050, the proportion of the world's population over 60 years will nearly double from 12 to 22%. (2) By 2020, the number of people aged 60 years and older will outnumber children younger than 5 years. (3) In 2050, 80% of older people will be living in low- and middle-income countries. (4) The pace of population aging is much faster than in the past. (5) All countries face major challenges to ensure that their health and social systems are ready to make the most of this demographic shift.The WHO , p. 10 ihealthy aging could be understood and enhanced considering that despite the fact that it is “being widely used in academic and policy circles, […] there is surprisingly little consensus on what this might comprise or how it might be defined or measured” WHO (Taking into account an aging of aging (aging plus?) panorama, the WHO not only presents useful demographic projections for planning the near future but speculates about how red” WHO , p. 41.healthy aging, arguing that it must be considered in a more comprehensive and global sense , connecting both the life-course—as a scenario for the development of the person in interaction with his/her context as well as the most important expression of health—and functionality in old age. Thus, healthy aging is defined as the process of developing and maintaining the functional ability that enables well-being in older age .PsyBel Research Project is to discover the contribution of those intrinsic mental and physical capacities such as bio-physical, emotional, attitudinal, motivational, cognitive, and personality characteristics. Thus, psycho-behavioral factors are supported by the WHO to be determinants for healthy aging and causal conditions of all demographic indicators of health at individual and population level, taking into consideration that these human psycho-behavioral conditions determine health through the interactions between biological and environmental conditions. This is a new position that must be tested. Measuring the relative contribution of these intrinsic psycho-behavioral conditions to survival, mortality, and longevity opens a new paradigm and requires that not only bio-medical and environmental factors be taken into consideration but also interactive psycho-behavioral determinant of aging and health. The PsyBel Project attempts to explore this relevant area and this meta-analytic study is a small first step forward in this direction. Thus, we start with a set of behavioral lifestyles since they are considered by Hendriks and Hatch  required for improving health.There is no academic definition of  The WHO  stated t The WHO , p. 2. IIt is worth remembering when healthy lifestyles started. Socio-historical and demographic events began to lead to an extraordinary growth of life expectancy in the middle of the nineteenth century. At this time, mortality in women was very high because of death from puerperal fever. Dr. Philipp Semmelweis, a Hungarian gynecologist, was working in a Viennese hospital. He observed that gynecologists went directly from the dissection room to the delivery room without taking any antiseptic measures. He then discovered that the incidence of puerperal fever could be drastically cut by the use of hand disinfection in obstetrical clinics when the obstetric doctor and matron started washing their hands carefully before proceeding to the birth.A century after those events, the concept of lifestyles or healthy life habits gained widespread importance through the link to the Alameda County Study, which started in 1965 and has continued in several waves until the present day. It was designed to investigate normal daily habits, including social relationships, in order to detect risk factors for poor health and mortality in everyday life. The first wave comprised 6,928 participants who completed questionnaires and were followed at intervals for up to 20 years after the initial investigation.seven risk factors—or health practices—associated with poor physical health and excess mortality: drinking excessive amounts of alcohol, smoking cigarettes, being obese, sleeping fewer, or more than 7–8 h per night, being physically inactive, eating between meals, and not eating breakfast.The study yielded Alameda County Study continued using health questionnaires in 1965, 1973, 1985, 1988, 1994, 1999, and 2005. In their examination of the first collected data, Wingard et al. ((1) never smoking; (2) drinking less than five drinks at one sitting; (3) sleeping 7–8 h a night; (4) exercising; (5) maintaining desirable weight for height; (6) avoiding snacks, and (7) eating breakfast regularly. Although a last systematic review of the Alameda County study findings  Regular physical activity; (2) Weight control; (3) Healthy diet; and (4) Sleeping 7–8 h per night. To do this, combined estimates of the effect size are obtained, and their significance is evaluated. In addition, the potential moderating role of four variables related to the study design and the characteristics of the participants is analyzed.This report follows the guidelines of the APA task force recommendations about reporting standards for quantitative research in Psychology, and especially in meta-analysis articles , and Scopus, up to April 2021. The searching strategy was guided by a specific question: Which healthy lifestyle factors are related to longevity in the elderly? Four healthy lifestyle factors were considered as behavior lifestyles: (1) Regular physical or cognitive exercises; (2) healthy diet; (3) sleeping 7 h; (4) weight control. The selected keywords were: “longevity,” “life expectancy,” “lifestyle,” “healthy lifestyle,” “physical activity,” “exercise,” “diet, healthy,” “body weight,” “sleep hygiene/classification,” “sleep/epidemiology,” “sedentary behavior,” “longitudinal studies,” “follow-up studies,” “prospective studies,” “twin studies,” “meta-analysis,” and “elderly” or “aged.” No time restrictions were imposed. The words selected were introduced as free terms and they were searched in the title, abstract, and keywords boxes. The searching strategy is available in p-value was required to estimate the confidence interval. If the confidence interval or exact p-value were not reported, the study was excluded. The flow diagram of the study identification and selection is shown in The inclusion criteria were as follows: (1) the study assessed the association between the selected healthy lifestyle factors on longevity; (2) the target population of the study was focused on the elderly; (3) the study involved outcome indicators as a measure of one or more of the four healthy lifestyle factors; (4) the design of the study was a prospective study; (5) the study reported statistical results on the association between healthy lifestyle factors and mortality or survival. The exclusion criteria were as follows: (1) the study did not address specifically mortality or survival; (2) the study did not address any of our selected healthy lifestyle factors; (3) the design of the study was not longitudinal; (4) the mean age of the sample population was not elderly, over the study period. Additionally, if two studies were based on the same dataset, even partially, the study with more follow-up years was selected. When a study did not report the statistic that reflects the association assessed and their confidence interval, an exact Database searches were conducted in April 2021. Potentially eligible studies were selected in two steps; the first step was based on the title and abstract screening. Irrelevant references were removed. The second step was based on the full-text reading of potentially relevant studies. The pre-specified eligibility criteria were checked in both phases. For each reference, the following variables were systematically extracted, and they were entered into a summary table: (1) Author, year; (2) number of follow-up years; (3) sample size at the baseline; (4) percentage of female participants; (5) mean age at baseline; (6) overall death rate; (7) death rate of the reference group; (8) Dataset or project name; (9) participants (10) predictor variables; (11) outcome; (12) Assessment/Instrument(s); (13) Index type ; (14) Effect size; (15) Confidence interval of the effect size. The collected data is available through the author's mail account.Regular physical exercises, healthy diet, sleeping 7 h, and weight control were the healthy lifestyle factors selected due to their significant association, according to previous literature, with a higher probability or a larger longevity. Also, those factors have been widely studied and are supported by several previous studies.There were several measures reported by the selected studies. Specially, several ways of operationalizing and quantifying the variables of interest were observed. It should be noted that, the categories of the studies were based on those measures.(1A) Physical activity (Yes-No), which involves studies where the participants were classified in two groups “Physically active” vs. “Not physically active.” (1B) Physical activity Frequency, based on the studies where the physical activity is quantified by the number of times per week performed and categories ranging from Never to Regularly or Often were used. (1C) Vigorous Physical activity, which involves the studies that quantify various types of physical activity in METs  or in hours per week, also quantiles  were calculated and those were the references to set cut-off points to build categories. (1D) Walking, based on the studies using the frequency per day or week, the distance of walking, or the walking at a brisk pace in minutes per day as the basis for their proposed categories. (1E) Leisure activities or Leisure physicalactivities, which involves the studies that ask about engaging in several leisure activities, and the practice of physical activity may or may not be present as a leisure activity. In those studies, the measure was based on the frequency, the number of activities engaged, or the number or hours invested. It was not possible to select just one category for the focus group, as the cut-off points of the categories differ among studies. However, the Sedentary or Physically Inactive group has been taken as the control group in the five dimensions of physical activity. In the opposite, the highest measure/category reported was considered as the focus group. Despite the previous statement, the HR has been calculated in reference to the medium category in two studies , by the intensity of the activity performed , by taking walks on a regular basis, or engaging leisure activities. Based on that criterion, we have done a sub-division within the regular physical exercise factor see  for bettIn the case of the Healthy Diet factor, some studies used the adherence of participants to the Mediterranean diet as a measure, other studies reported the frequency or number of daily servings of fruits and vegetables (WHO recommendations), and other studies focus on measuring the amount of calories consumption. In all studies, the control group was determined by the lowest adherence to the Mediterranean Diet (score), the lowest frequency of fruit and vegetable intake or the lowest number of servings; instead of, the focus group was determined as the opposite category to the control group, for example the highest frequency of fruit and vegetable intake.Respect of the Sleeping 7–8 h factor, two of the three selected studies established 7–8 sleeping h as the control group and one of them used 6 h as control group; and a greater number or lesser number of sleeping hours, than control group, was considered the focus group.(4A) Obesityrepresented by a BMI ≥ 30, (4B) Overweight represented by a 25 ≤ BMI < 30, and (4C) Underweight represented by a BMI < 20 (or BMI < 22 in some studies). The control group for this factor has been defined as the Normo-weight (20 ≤ BMI < 25) and the three BMI categories mentioned before were considered the focus group. The cut-off points of the categories are comprised in most studies.Regarding the Weight control factor, with body mass index (BMI) as a proxy, the categories used refer mostly to the limits established by the World Health Organization, although in other studies the authors considered the division into quantiles or cut-off points based on the median or mean of the complete sample or by gender sample. For our purpose, a sub-division of Weight control was assumed as follows: It must be mentioned that the selected studies reported analyses based on one or more of the four factors of healthy lifestyle studied in this meta-analysis. In the studies that reported separate estimates by gender, they were taken as two different samples in the same study. Sixty-one studies assessed regular physical activity, 14 studies focused on healthy diet, 3 studies assessed sleeping 7–8 h, and 36 studies assessed control weight  for mortality. The value in the numerator refers always to the condition assessed, and that in the denominator the category for control. Thus, values lesser than one reflect smaller mortality , whereas values larger than one reflect larger mortality . The results of the primary studies were generally presented directly as HR values, but were sometimes presented as proportions, RRs, or OR. To convert the OR and/or RR values to HR values, the formulas of Zhang and Kai , and year of publication.Table 3. Finally, the analyzes and figures were performed using the R package “metafor” . The median sample size was 6,382, ranging from 148 to 654,827. The median of the average age was 64.5 years (38.7–93.1 years). Studies were conducted in Europe (36.6%), United States (34.4%), Asia (12.9%), United Kingdom (9.7%), Australia (2.1%), Central America (1.1%), South America (1%), and United States and Europe at the same time (2.1%). The median follow-up time was 12 years, varying between 2 and 46 years see .The means and ranges in the four moderators of the included studies are shown in active= 0.75; 95%CI: 0.672–0.831; HRfrecuency = 0.705; 95%CI: 0.609–0.817; HRvigorous = 0.684; 95%CI: 0.639–0.730], supporting the hypothesis of the physical activity as an important factor associated to a significantly smaller rate of mortality. The results also show a significant heterogeneity with the three-focus group .The forest plots with the studies involved in Walking and Leisure Activities/Leisure Physical Activities are shown in Walking (12) = 29.471, p < 0.001; QLeisureActivity (11) = 61.964, p < 0.001].Regarding the studies referred to the “leisure activities/leisure physical activity,” the control group was integrated by people who rarely perform this type of activity. The results showed a significant association between frequent leisure time activities and/or leisure physical activities and mortality , that means participants who frequently engage in leisure time activities and/or leisure physical activities get a mortality risk of 19% lower than people who rarely or never perform those activities. Again, it should be noted that the heterogeneity in both factors is high .The forest plot with the studies involved in the healthy diet factor are presented in Sleeping(6) = 17.207, p < 0.001].obesity(31) = 278.422, p < 0.001; Qoverweight(28) = 179.732, p < 0.001; Qunderweight(25) = 75.228, p < 0.001].Body mass index was considered as a proxy for weight control. The forest plots with the three groups of BMI are shown in Four variables  were analyzed to evaluate the role of potential moderators. Obviously, we have not analyzed the potential role of moderators in those factors whose effect is not significant. That is, it was analyzed for all factors except overweight. INTENSITY, and another called QUANTITY. The objective was to analyse a potential moderator effect. The analysis of the “Intensity-Quantity” moderator showed a no significant effect  therefore it is possible to conclude that the disaggregation does not evidence any difference. Based on this result, the “PA Vigorous” group is proposed as a unique PA dimension.In addition, the studies involved in the “PA Vigorous” dimension reported measures based on the PA intensity in some cases, and measures referred to the PA quantity in other cases. When the intensity of the physical activity was informed, it usually was measured in METs (PA is estimated as the energy cost of a given activity divided by resting energy expenditure), and the PA quantity was linked to the number of hours per week, hours per month or kilocalories consumed for the subject during a regular physical activity. For this reason, two categories were considered, one called On the other hand, the association between the mortality rate and frequently engaging in leisure time activities, including or not physical activities, is moderated by the average age of participants at baseline. In other terms, performing leisure time activities has less relation to the mortality rate (the association is lower) the older the person is at the beginning of the study.For the Sleeping factor, the length of the follow-up interval and the year of publication of the study are moderators of the association between the mortality rate and sleep 7 or 8 h. In the case of follow-up years, the negative slope indicates that the association is smaller the more years it is followed during the study. The slope is positive for the year of publication and indicates that the association is greater in the most recent studies.Regarding the BMI, the only significant moderator of the association between the mortality rate and overweight is the length of the follow-up years of the study, which shows a positive slope, which means that the association is greater the greater the follow-up years. It should be noted that the association between overweight and the rate of mortality was not significant.The results of the moderators should be interpreted cautiously, since the high number of tests (40) predicts that, assuming a significance threshold of α = 0.05, in the absence of any effect 5% of the tests will be significant . In this case there are more significant results , but some of them are probably mere type I errors.The well-known tendency to facilitate the publication of significant results over non-significant ones can produce an over-estimation of the effect size, or even the appearance of an artificial, non-existent effect. We have evaluated the degree to which this anomaly, known as publication bias, could be a potential threat to the results of this meta-analysis. In this respect, we have made visual inspection of the funnel-plot figures and we have tested for asymmetry with the Egger's test, the rank correlation test, and the Trim and Fill method. We have also calculated the fail-safe numbers for those effects that are significant. The results are summarized in The table shows that all the results are safe from this threat, in the sense that, although the effect may have been over-estimated, at least it exists and is not a by-product of selective publication, as all fail-safe numbers exceed Rosenthal's criterion. Asymmetry tests reveal no evidence of publication bias. The Trim and Fill test has imputed several values to some of the funnel plot. However, in no case has the estimate ceased to be significant after the imputation of values.The results of the present meta-analysis allow us to reliably conclude that lifestyles are associated with mortality . The four factors studied, which are usually identified as healthy lifestyles, allow us to predict greater survival. Specifically, doing regular physical activity, engaging in leisure activities, sleeping 7–8 h a day, and staying outside the BMI ranges considered as underweight or obesity are habits that each separately has a greater probability associated with survival after a period of several years.In all the analyses carried out, we have detected high and statistically significant levels of heterogeneity. This means that in this field of research, like any other that studies complex, high-level constructs, the levels of control over variables are low. Longevity is associated with multiple factors, both environmental and genetic, whose isolated and interacting effects have combined impacts that are very difficult to isolate. Primary studies identify factors with significant associations, but they are probably multi-moderated effects. Furthermore, the operationalization of the factors is very diverse and not always clear, in addition to being frequently based on self-reports that are not always sufficiently reliable. Let us think of the varied operationalizations that have been used of walking or diet, as well as the problems of fidelity of memory about them. The fact that significant factors appear despite these difficulties is remarkable. Nevertheless, we must not forget that this high level of heterogeneity does not allow us to accurately predict the results of future similar studies.Physical activity, Walking, and Leisure activities or Leisure physical activities. Based on our findings, all these categories showed that physical activity is an important factor associated with a lower rate of mortality, in all groups.Regarding regular physical activity, we analyzed 61 studies which were operationalized and quantified differently. Therefore, our classification includes several possible measures used in the studies reviewed: walking (one of the most common types of activity among older adults) in populations with low activity, regular weekly walks would reduce mortality by 28% within a period of about 13 years in the average. Our results are similar to previous studies that have shown that high intensity walking reduces all-cause mortality , generating increased research into diets rich in fruit and vegetables, under the assumption that an increase in their consumption would reduce the incidence of cancer and cardiovascular disease  or obesity (BMI 30.0 and above) is associated with higher mortality rate than the normo-weight (BMI range 20–24.9). Taking into consideration the high and increasing prevalence of overweight and obesity worldwide  and mortality, suggesting the protective metabolic effects of increased body fat. Furthermore, Zajacova et al.  found thThe present meta-analysis includes large published studies representing in total more than 2,800,000 people. The analyses included study populations from Europe, North, Central and South America, Europe, United Kingdom, Asia, and Australia. However, the studies were highly heterogeneous in their methods, with different ways of operationalizing and quantifying the variables of interest. Regardless, the categories of the studies were based on those measures, trying to create a coherent and enlightening classification for each lifestyle studied. Also, results were in line with those of other meta-analyses.Physical Activity in all its parameters, these include oxygen consumption, heart rate, meters by time, and other target measures; for Diet, objective measures include diet outcome, such as cholesterol levels; for Weight control, BMI; and finally, for Sleeping, polysomnography (PSG).Regarding the comments in the introduction referring to the methodology, and specifically the healthy lifestyles measures, our analysis does not include any subjective measures such as satisfaction or even subjective health self-reports (indirect measures). In the four lifestyles analyzed, objective measures are also available that  could have complemented subjective measures: In Although all studies were adjusted for multiple potential moderators, there are likely to remain different factors, such as unrecorded changes in exposure over time given the length of follow up, possible stressful situations, important life events occurring between baseline and follow up, etc., that could substantially affect the results.Further research should use more objective measures, eliminating the threat of bias caused by systematic differences in healthy lifestyles. In addition to better understanding the relationship between these healthy lifestyles and mortality, researchers should address the differences between: (1) studies carried out with objective measures and (2) studies with self-reported data, and analyse this categorization as a moderator. Does the effect size change, and how much? Response distortion must be controlled when self-reports are taken as measures. There must be a control of two types of distortions to self-reports (Fernández-Ballesteros and Botella, In sum, perhaps the most critical aspect in meta-analysis is the appropriateness of the methods used by researchers in outcome evaluation and some restriction must be introduced as criteria for inclusion in health evaluation research program.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.RF-B is the IP of the project. RF-B, MS-I, and JB designed the meta-analysis. EV-L extracted the information from the studies and performed the codification. EV-L and JB designed and performed the statistical analyses. RF-B and MS-I contributed to the interpretation of the results. RF-B, EV-L, and MS-I wrote the manuscript with support from JB. All authors contributed to the final version of the manuscript.This study is one of the objectives of the Research Project granted by the Spanish Ministry of Science and Innovation: Project: PID2019-109761RB-I00.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: Possible influences of statin therapy on the risk of cardiovascular events, cancer, and all-cause mortality in people living with HIV (PLWH) remain unclear. We performed a meta-analysis to systematically evaluate the efficacy of statin in PLWH.Methods: Relevant cohort studies were retrieved via a search of the Medline, the Embase, and the Web of Science databases until June 14, 2021. The data were combined with a random-effects model by incorporating the between-study heterogeneity.Results: A total of 12 multivariate cohort studies with 162,252 participants were eligible for the meta-analysis and 36,253 (22.3%) of them were statin users. Pooled results showed that statin use was independently related to a reduced mortality risk in PLWH . In addition, results of the meta-analysis showed that statin use was not significantly associated with a reduced risk of cardiovascular events in PLWH compared to the statin non-users . However, statin use was significantly related to a reduced risk of cancer in PLWH . Sensitivity analyses by excluding one study at a time showed consistent results. No significant publication biases were observed.Conclusion: Statin use is associated with reduced all-cause mortality in PLWH. In addition, statin use is related to a reduced risk of cancer, although the risk of cardiovascular events seems not significantly affected. People living with HIV (PLWH) have been associated with higher risk of the atherosclerotic cardiovascular diseases (ASCVDs) , 2 and nStatins, also known as 3-hydroxy-3-methylglutaryl CoA (HMG-CoA) reductase inhibitors, are a category of cholesterol-lowering medications, which have become a mainstay for the primary and secondary prevention of ASCVDs , 10. In The instructions of the Meta-analysis of Observational Studies in Epidemiology (MOOSE)  and the Studies were obtained by search of the electronic databases of the Medline, the Embase, and the Web of Science databases via the combined search terms:  “human iThe inclusion criteria were:  cohort sThe processes of database search, data extraction, and study quality assessment were independently and separately performed by the two authors. If discrepancies occurred, a discussion with the corresponding author was indicated. Following data were recorded into a predefined Excel form for data management:  name of p-values reported in the original papers. Data of RRs were further logarithmically transformed to stabilize variance and normalized the distribution  software was applied for the meta-analysis and statistics.Risk ratios and their corresponding 95% CIs were chosen as the general measure for the relationship between statin use and incidence of all-cause mortality, CV events, and cancer. Data of RRs were extracted directly from the original studies and SEs of RRs were calculated based on 95% CIs or ribution . The hettatistic . A signiogeneity . Sensitiogeneity . The potogeneity . p < 0.0p < 0.001; p for Cochran's Q test = 0.09, I2 = 41%). Sensitivity analysis by excluding one study at a time showed the consistent results . Specifically, studies limited to the prospective cohort studies also showed the consistent results . In addition, studies limited to PLWH on ART also showed the similar results .A total of nine studies , 30, 31 p = 0.48, I2 = 42%; p > 0.05). However, a meta-analysis of the four studies .A total of five studies , 31, 32  studies , 30, 31 p = 0.522). For the meta-analyses of CV events and risks of cancer, the Egger's regression tests were not performed, since the limited numbers of datasets were included.The funnel plots for the meta-analyses of the association between statin use and mortality, CV events, and cancer risks are shown in In this meta-analysis of the cohort studies, we found that in PLWH, statin use was significantly related to a reduced risk of all-cause mortality and a decreased incidence of cancer. However, the incidence of CV events was not significantly affected. These results suggested that although previous clinical trials have proved the benefits of statin in improving lipid profile in PLWH, current evidence from the epidemiological studies did not show that statin use was associated with a reduced risk of CV events in this population. However, statin use in PLWH is associated with improved survival and according to our results, reducing cancer-related adverse events are likely to be involved in the benefits of statin in PLWH.As far as we know, only one previous meta-analysis published in 2018 evaluated the association between statin use and all-cause mortality in PLWH . This mecytomegalovirus, and mechanisms related to ART  and low-density lipoprotein cholesterol (LDL-C) in PLWH as shown in the previous clinical trials , 19, thed to ART . The othd to ART . Anotherd to ART , 45. Sind to ART , 47, theThis study has some limitations. Firstly, one important limitation of this meta-analysis is the nature of the exposure studied. Among the included observational studies, only the study by Bedimo et al.  explicitIn conclusion, the results of this meta-analysis showed that statin use was significantly related to a reduced risk of all-cause mortality and a decreased incidence of cancer in PLWH. However, the incidence of CV events was not significantly affected. Although clinical trials are needed to validate the findings, these results suggested that statin use in PLWH is associated with improved survival and reducing cancer-related adverse events is likely to be involved in the benefits of statin in PLWH.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.YL and ZW conceived and designed the study. YL and HX selected the studies and collected the data. YL and JZ analyzed the data. YL drafted the manuscript. All the authors interpreted the results, revised the draft manuscript, and read and approved the final version of the manuscript.This study was supported by the National Natural Science Foundation of China (No. 81904040).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


CDKAL1) contributes to islet β-cell function and insulin secretion by inhibiting the activation of CDK5. The current studies on the relationship between CDKAL1 polymorphisms rs7756992 A>G and rs7754840 C>G and the risk of gestational diabetes mellitus (GDM) have drawn contradictory conclusions.The CDK5 regulatory subunit-associated protein 1-like 1 (CDKAL1 polymorphisms and GDM risk with the summary odds ratio (OR) and 95% confidence interval (CI). In addition, trial sequential analysis (TSA) and false-positive report probability (FPRP) analysis were performed to confirm the study findings.A meta-analysis with a fixed- or random-effects model was conducted to estimate the correlation between studied vs. AA: OR = 1.23, 95% CI = 1.08, 1.41, p = 0.002; GG vs. AA: OR = 1.47, 95% CI = 1.05, 2.05, p = 0.024 for rs7756992; and CG vs. GG: OR = 1.36, 95% CI = 1.13, 1.65, p = 0.002; CC vs. GG: OR = 1.76, 95% CI = 1.37, 2.26, p < 0.001 for rs7754840). The TSA confirmed a significant association between rs7754840 and the susceptibility to GDM because the cumulative Z-curve crossed both the conventional cutoff value and the TSA boundaries under the heterozygote and homozygote models.A total of 13,306 subjects were included in the present study. Meta-analysis results showed that the variant heterozygous and homozygous genotypes of the two polymorphisms were associated with increased GDM risk in comparison with the wild-type AA genotype (AG This study supported the finding that rs7756992 and rs7754840 are associated with susceptibility to GDM. However, further functional studies are warranted to clarify the mechanism. Gestational diabetes mellitus (GDM), defined as an abnormal glucose tolerance onset or first recognition in pregnancy , is apprTCF7L2 rs7903146, CDKAL1 rs7756992 and rs7754840, MTNR1B rs10830962, and FTO rs8050136) are associated with the risk of GDM  and false-positive report probability (FPRP) analysis in this meta-analysis.The CDK5 regulatory subunit-associated protein 1-like 1 (CDKAL1) is located at the human chromosome 6p22.3, encoding a 65-Ku CDKAL1 protein. CDKAL1 is mainly expressed in human pancreatic islet cells and shows considerable homology with CDK5RAP1, a well-known inhibitor of CDK5 activation. CDK5 has been suggested to downregulate insulin secretion through the formation of p35/CDK5 complexes , 14. In CDKAL1 rs7756992 and/or rs7754840 and the risk of GDM were searched in PubMed, Web of Science, the China National Knowledge Infrastructure (CNKI), and Wanfang databases, with languages limited to English and Chinese. The latest search was performed on March 31, 2021. The search terms “CDK5 regulatory subunit associated protein 1-like 1,” “CDKAL1,” “GDM,” “gestational diabetes mellitus,” “variation,” “polymorphism,” and “SNP” were used as retrieval words. Studies were also identified by a manual search of the references cited in the retrieved studies.Published studies of Inclusion criteria were as follows: 1) original study on the association between rs7756992 and/or rs7754840 polymorphisms and the risk of GDM and 2) case–control study or GWAS with independent data, 3) with genotype and/or allele distribution information, and 4) with sufficient data for calculating an OR with its corresponding 95% CI.Exclusion criteria were as follows: 1) duplicate data, 2) no specific genotype or allele data, and 3) family-based study, review, systematic review or meta-analysis, case report, comment, and editorial.Two professional investigators (X-YY and L-PS) independently searched articles and extracted target data from the included studies. If there were any dispute, it was settled by X-YY and L-PS. Data on the first author, year of publication, country, diagnostic criteria, source of controls, number of cases and controls, mean age, mean body mass index (BMI), genotype, and/or allele distribution were extracted.In the present study, the Newcastle-Ottawa Scale (NOS) was used to assess the quality of target studies . The scoI2 index was calculated to quantify the degree of heterogeneity across studies, and a corresponding p less than 0.1 was considered significant .The ORs with their corresponding 95% CIs were used to assess the strength of association between the polymorphism and GDM risk. The nificant , 19. Thenificant  were usep-value. An FPRP less than 0.2 was considered as a noteworthy association , with an alpha level equal to the observed ociation , 22.Meta-analysis might be affected by the increased risk of random errors and repeated significance testing . TSA canCDKAL1 gene and GDM; 2) six articles concerned a non-human model of GDM; 3) 15 were not case–control or GWASs; and 4) eight studies did not focus on the topic of CDKAL1 rs7756992/rs7754840 and the risk of GDM. According to the study selection strategy, 13 studies (nine in English and four in Chinese) met the research theme, of which 10 were considered to be of high quality (score ≥5) and the other three [Hu et al. .In total, six high-quality studies containing 2,376 GDM cases and 4,458 controls explored the relationship between rs7756992 and the risk of GDM –34. The vs. AA: OR = 1.20, 95% CI = 1.03, 1.39, p = 0.022 in Asians, OR = 1.35, 95% CI = 1.04, 1.76, p = 0.023 in Caucasians; and AG vs. AA: OR = 1.22, 95% CI = 1.06, 1.41, p = 0.005 and GG vs. AA: OR = 1.49, 95% CI = 1.01, 2.19, p = 0.044 in the sample size ≥200 group). These results are shown in In the stratified analysis by ethnicity and sample size (≥200 or <200) of the cases, positive results were found by comparing the variant AG heterozygous and GG homozygous genotypes with the wild-type homozygous AA genotype .The association between rs7754840 and the risk of GDM has been explored in 10 high-quality studies, including 4,819 GDM patients and 5,873 controls , 29–37. vs. GG: OR = 1.45, 95% CI = 1.15, 1.83, p = 0.002 in Asians, OR = 1.21, 95% CI = 1.07,1.37, p = 0.003 in sample sizes ≥200 and OR = 3.32, 95% CI = 1.40, 7.90, p = 0.007 in smaller sample size groups; CC vs. GG: OR = 1.82, 95% CI = 1.35, 2.44, p < 0.001 in Asians and OR = 1.74, 95% CI = 1.33, 2.28, p < 0.001 in sample sizes ≥200 group). These results are shown in The stratified analysis suggested a significant association between rs7754840 and GDM risk  or sample size . The subsequent leave-one-out analysis showed that after removing the report by Zhang et al. (pheterogeneity and I2) changed from 0.012% and 66% to 0.135% and 43%.Meta-regression analysis was performed to explore the source of heterogeneity by ethnicity and the sample size of the case group (≥200). In the homozygous genotype comparison of rs7756992, meta-regression analysis showed that heterogeneity was not significantly associated with ethnicity  might be the main heterogeneity source in the heterozygote genotype comparison. However, in the homozygous genotype comparison, we did not find ethnicity  or sample size  to be a significant cause of the heterogeneity between studies. In addition, leave-one-out analysis showed that no single factor had a significant association with the observed heterogeneity.For the observed significant heterogeneity of rs7754840 and the susceptibility to GDM, meta-regression analyses showed that the sample size  and rs7754840  in the present study. Sensitivity analyses suggesting no single study significantly changed the pooled ORs , 0.043 (sample size ≥200), and 0.165 (Asian group) for rs7756992 A>G, and 0.021 , 0.026 (sample size ≥200), and 0.028 (Asian group) for rs7754840 C>G in heterozygous genotype comparisons; in addition, FPRP values were 0.013 , 0.017 (sample size ≥200), and 0.022 (Asian group) for rs7754840 C>G in homozygous genotype comparisons. These FPRP values suggested that the above positive findings were probability correct and reliable Table 3.CDKAL1 rs7756992 and the risk of GDM under the heterozygote model (AG vs. AA). However, in the homozygote model (GG vs. AA), the cumulative Z-curve crossed only the conventional boundary but did not cross the TSA boundary, indicating that additional studies were necessary (vs. GG) and homozygote models (CC vs. GG) because the cumulative Z-curve crossed both the conventional cutoff value and TSA boundaries . One study has shown that variants located at the gene intron region mainly inactivate the splice-donor site and change the splicing pattern of pre-mRNA , the National Natural Science Foundation of China (81760614), the Key R&D Program (2018AB62004), and College Students’ Innovation Project .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Interleukin-10 (IL-10), a kind of anti-inflammation cytokine, has a key role in the development of acute kidney injury (AKI). Recently, several studies addressed the link between the risk of AKI and the IL-10 -1082 A/G polymorphism with conflicting findings.To identify the effects of the IL-10 -1082 A/G polymorphism on the risk of AKI, we designed this case-control study. This study recruited 320 AKI patients and 408 ICU patients without AKI. The association between the AKI risk and this polymorphism was analyzed using the logistic regression analysis adjusted for confounding factors.The IL-10 -1082 A/G polymorphism enhanced the risk of AKI. After stratified analysis, this polymorphism increased the risk of AKI among the males, smokers, those aged exceeding 60 years old, and overweight individuals (BMI ≥ 25). Moreover, -1082 A/G polymorphism was remarkably related with APACHE II score and eGFR.Collectively, the IL-10 -1082 A/G polymorphism is linked with an elevated risk of AKI. Further studies in China need be performed to verify these results. Acute kidney injury (AKI) is a group of complex syndromes characterized by serum creatinine increasing apace or urine produced decrease . AKI occInterleukin (IL)-10 is a pivotal anti-inflammatory cytokine, which is primarily produced by blood cells and organ cells. IL-10 has a key role in restricting excessive inflammatory responses, which could upregulate innate immunity and promote tissue repairing mechanisms to keep tissue homeostasis during inflammation and infection . PreviouIL-10 gene is shown to be located on chromosome 1q32.1. Rs1800896 polymorphism is an important locus in the promoter region of IL-10 gene . RecentlHelsinki declaration.This study recruited 320 patients with AKI and 408 controls. AKI was diagnosed according to selection criteria by the KDIGO guideline . We collBlood samples of all participants were to extract DNA . Relevant polymorphisms were genotyped using the PCR-RFLP method. In order to assess the genotyping error, we selected 10 % samples to re-genotype.2) test; continuous variables were addressed by the t test. For controls, a good-fitness χ2 test was performed to calculate the P-value of the HWE test. Logistic regression analysis with adjustment of age, sex, BMI, smoking, and alcohol status was utilized to calculate odds ratios (ORs) and 95 % confidence intervals (95 % CIs). A P-value < 0.05 was showed as remarkable difference. All statistical analysis was calculated by SPSS 21.0.categorical variables were calculated by the Chi-square (χP > 0.05). The creatinine levels in AKI patients were markedly higher than in controls (P < 0.05). Other specific clinical characteristics of AKI are listed in Table 320 AKI cases and 408 matched controls from ICU were investigated, and they aged 52.17 ± 8.19 and 52.64 ± 7.98 years old, respectively. As for age, sex, smoking, alcohol and BMI, we did not observe evident differences between two groups (PHWE = 0. 970). Table P = 0.027; AG + GG versus AA, adjusted OR, 1.36; 95 %CI, 1.02–1.83; P = 0.040). Moreover, G allele carriers elevated the risk of AKI .This polymorphism distribution in controls conformed to the HWE test .Previous studies indicated that inflammatory reaction played a crucial role in the pathogenesis of AKI . Both ThThe link between the risk of kidney diseases and the IL-10 -1082 A/G polymorphism has been explored before. Jaber et al. indicated that G allele carriers who produced higher levels of IL-10 was linked with a lower risk of mortality among acute renal failure patients  which waObviously, abovementioned studies yielded inconsistent findings regarding the association between this polymorphism (-1082 A/G) and the risk of kidney diseases. The following aspects may be potential reasons. One, the dominant reason may due to disease heterogeneity. The Brazilian study by Dalboni et al. indicated that this locus was not related with the risk of AKI in the ICU patients . HoweverSubgroup analysis showed the IL-10 -1082 A/G polymorphism strengthened the risk of AKI among males, smokers, older individuals (age ≥ 60 years), and those overweight patients (BMI ≥ 25). Last, we found that this polymorphism was markedly related with APACHE II score, and eGFR in AKI individuals. Furthermore, this study indicated that this polymorphism was connected to the risk of ischemic and septic AKI.Several limitations were shown in this study. First, the sample size of this retrospective study was not large enough; we only enrolled 320 AKI patients and 408 controls. Further large-scale studies are necessary to verify our results. Second, the genotype distribution may not represent the general population, because all enrolled individuals were from the hospital, which may lead to selection bias. Third, this study only investigated one polymorphism and did not study gene-gene interaction. Fourth, we did not detect the IL-10 levels in three kind genotypes of individuals respectively. It is of note that previous studies demonstrated that GG genotype carriers showed elevated IL-10 levels compared with other genotypes . Fifth, In summary, the IL-10 -1082 A/G polymorphism enhances the risk of AKI in Chinese Han subjects. Further studies in different races should be conducted to validate these findings.


The relationship between diet quality indices and risk of ovarian and endometrial cancers were unclear. We aimed at conducting a systematic review to evaluate the epidemiological evidence.Embase, PubMed, Web of Science and Scopus databases were searched for eligible studies up to December 2020. Epidemiological studies reported the association of the diet quality with risk of ovarian and endometrial cancers were evaluated.Eleven eligible studies were identified, of which six studies were case-control studies, four were cohort studies, and one was case-cohort study. All studies were considered as high-quality with low risk of bias. Seven studies evaluated the association of diet quality with risk of ovarian cancer. Four studies reported null association for diet quality indices such as Healthy Eating Index (HEI)-2005, HEI-2010, Mediterranean Diet Score (MDS) and Recommended Foods Score (RFS). Two studies reported significantly inverse association for Alternate Healthy Eating Index (AHEI)-2010 and Healthy Diet Score (HDS) indices. One study reported significantly increased risk of ovarian cancer associated with higher level of Dietary Guidelines for Americans Index. Dose-response analysis showed pooled relative risks of 0.98  and 0.94  for each 10 points increase in the HEI-2005 and AHEI-2010 indices. Seven studies evaluated the association of diet quality with risk of endometrial cancer. Three studies reported significantly inverse association of diet quality as assessed by the MDS and Diet Score Quintiles with risk of endometrial cancer. Four studies reported null association for other diet quality indices including HEI-2005, HEI-2010, RFS and HDS. Dose-response analysis showed a pooled relative risk of 0.87  for one unit increment of the MDS.This study suggests little evidence on the association between diet quality and risk of ovarian cancer. Adherence to high quality diet, as assessed by MDS, might be associated with lower the risk of endometrial cancer. Ovarian and endometrial cancers are two most common gynecological cancers and the leading cause of death due to gynecological cancer among women in Western countries . AccordiRisk factors for ovarian cancer include absence of pregnancy, early age of menarche, late age at menopause, family history of ovarian cancer, smoking and benign gynecological conditions . Diet maAlthough it is important to understand the role of individual dietary constituents, foods are not consumed in isolation. Diet quality indices such as the Healthy Eating Index-2005 (HEI-2005), Healthy Eating Index-2010 (HEI-2010), Alternate Healthy Eating Index-2010 (AHEI-2010) and Mediterranean diet score (MDS)/Alternate Mediterranean Diet Score (aMDS) address the complexity of the diet and the likely interaction between multiple diet components . The higA thorough understanding of the relation between diet quality and risk of ovarian and endometrial cancers could facilitate the development of more effective strategy and recommendation on cancer prevention in women. Thus, we aimed at conducting a systematic review to evaluate the association between diet quality and risk of ovarian and endometrial cancers.This study was performed in adherence to PRISMA guidance . Two resThe Embase, PubMed, Web of Science and Scopus databases were searched up to Dec 2020, using the Mesh terms as well as the following words:  AND  AND (cancer OR tumor OR neoplasm OR carcinoma). We also searched Google Scholar for grey literature. Language of publication was restricted to English. Besides, we screened the reference lists of relevant studies to identify other potential studies. The search strategies were presented in The inclusion criteria were as follows: (1) Study design should include cohort study, case-cohort or case-control study; (2) Studies should report diet quality indices as exposure of interest, such as HEI-2005, HEI-2010, AHEI-2010, MDS, other diet quality indices; (3) Studies should report ovarian or endometrial cancer as the outcome of interest; (5) Studies should report relative risk (RR), risk ratio, rate ratio, hazard ratio, odds ratio with the corresponding 95% confidence interval (CI) as the measure of association. When two or more studies covered the same study population, we selected the most recent one, or the most informative study, or extracted information from both studies as appropriate.A structured data extraction form was used to collect the study-specific information, which included the first author of the study, year of publication, study design, study location, study population, size of cohort/number of controls, age at baseline, exposures, exposure assessment methods, outcomes, outcome ascertainment, number of cases, follow-up time, risk estimates, and confounder adjustment. When there were multiple risk estimates in a study, we extracted the one most appropriately adjusted for the confounders in the analysis.The study quality was assessed by two researchers (YHZ and ZL) independently. The Newcastle-Ottawa Scale, which was developed to evaluate the quality of observational studies, was used as the assessment tool . A study2 statistic . One study reported significantly increased risk of ovarian cancer associated with high quality diet as assessed by “Dietary Guidelines for Americans Index” . Four studies reported null associations with RRs ranged from 0.76  to 1.03  for other diet quality indices such as HEI-2005, HEI-2010, aMDS and RFS. The main results for these seven included studies were shown in Seven studies evaluated the association of diet quality with risk of ovarian cancer. Two studies reported significantly inverse association of diet quality as assessed by AHEI-2010 and HDS with risk of ovarian cancer . Two studies assessed the diet quality using AHEI-2010 index, with pooled RR of 0.94  for each 10 points increase. Since limited number of studies were included in the dose-response results, these non-significant results should still be interpreted with caution due to lack of power.In the dose-response meta-analysis of three studies assessing diet quality with HEI-2005 index, the pooled RR for each 10 points increase was 0.98  without statistical heterogeneity . Four studies reported null association with RRs ranged from 0.83  to 0.98  for other diet quality indices including HEI-2005, HEI-2010, RFS and HDS. The main results for the seven included studies were shown in Seven studies evaluated the association of diet quality with risk of endometrial cancer. Three studies reported significantly inverse association of diet quality as assessed by the MDS and Diet Score Quintiles with risk of endometrial cancer (Ricceri et al.  study: Ro et al.  study: RThis review of epidemiological studies suggested little clear association of major diet quality indices, including HEI-2005, HEI-2010, AHEI-2010, aMDS and RFS, with risk of ovarian cancer. Of note, adherence to higher quality of diets, as assessed by MDS, may be associated with a lower risk of endometrial cancer. Dose-response analysis suggested a 13% reduction in risk of endometrial cancer for one unit increment in MDS in women. However, this inverse association with endometrial cancer was not observed for other diet quality indices including HEI-2005, HEI-2010 and RFS etc.Assessment of the overall quality of diet instead of single nutrients can address the likely interaction between multiple diet components . PreviouOur results suggested that, compared with other dietary indices HEI-2005, HEI-2010 and AHEI-2010, the MDS may capture aspects of diet more relevant to endometrial cancer. In a large case-control study in Italian population, there was a reduced risk of endometrial cancer for increasing adherence to the Mediterranean diet . The MedThere are several limitations in the study. Despite there are certain commonalities on the diet components for these diet quality indices, the weights of each components, assessment methods, and categories of the diet indices varied from study to study. The diet quality indices in these studies included HEI-2005, HEI-2010, AHEI-2010, aMDS and RFS, etc., Due to high heterogeneity of the diet quality as assessed by various diet quality indices, this review was mainly based on a systematic review of the current evidence, and little quantitative conclusion could be drawn. Although the dose-response meta-analyses for certain dietary indices were performed, the pooled risk estimates, especially the non-significant results, were still inconclusive due to the inclusion of a limited number of epidemiological studies. These results should still be interpreted with caution due to lack of statistical power. Further evidence from well-designed, large-scale cohort studies are still warranted before we could draw a confirmative conclusion. Furthermore, the epidemiological studies in the review were conducted in the Western population. As such, we should be more cautious in generalizing the results to other areas, especially where the dietary patterns and habits are different, such as Asia and Africa. In addition, non-English databases were not searched in the review, which may lead to publication bias.In conclusion, this systematic review of the epidemiological studies suggests little evidence on the association between diet quality and risk of ovarian cancer. Adherence to high quality diets, as assessed by MDS, may be associated with lower risk of endometrial cancer. If a causal association could be confirmed by further well-designed studies, the adherence of the Mediterranean diet guidance might be encouraged for the prevention of endometrial cancer in women.fusan2020@sina.com.The datasets during and/or analyzed during the current study are available from the corresponding author on reasonable request. Requests to access these datasets should be directed to Y-HZ developed the research design, interpreted the results, and also had primary responsibility for the final content. ZL and M-ZT analyzed the data and interpreted the results. Y-HZ drafted manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The existing knowledge about the association between NLRP3 rs35829419/rs10754558 polymorphisms and susceptibility to autoimmune diseases (AIDs) remains controversial. Herein, a meta-analysis was performed to evaluate such association. We searched databases for relevant studies published in English up to February 2021. Stata14 was used to assess the odds ratio (OR). As for NLRP3 rs35829419, no significant association to overall AIDs was found in three genetic models . However, subgroup analysis by disease type showed that NLRP3 rs35829419 A allele may have a significant protective effect on rheumatoid arthritis (RA) susceptibility [A vs. C: 0.74 (0.57–0.96)]. NLRP3 rs10754558 polymorphism contributes to significantly reduce the risk of AIDs in the allelic model [G vs. C: 0.78 (0.71–0.87)], homozygote co-dominant model [GG vs. CC: 0.63 (0.51–0.77)], heterozygote co-dominant model [GC vs. CC: 0.78 (0.66–0.91)], dominant model [GG/GC vs. CC: 0.73 (0.63–0.84)], and recessive model [GG vs. GC/CC: 0.73 (0.62–0.88)]. In the subgroup analysis by ethnicity, association was observed between the NLRP3 rs10754558 G allele and AIDs in Latin Americans, but not in European, Arabian, or Asian populations. Stratification by disease type showed a significant association of the NLRP3 rs10754558 G allele with type 1 diabetes (T1D), RA, and systemic lupus erythematosus (SLE), but not with celiac disease (CD), multiple sclerosis (MS), or myasthenia gravis (MG). This meta-analysis suggests that the NLRP3 rs10754558, but not rs35829419, polymorphism is associated with susceptibility to AIDs, especially in Latin American individuals. Autoimmune diseases (AIDs) are characterized by a host immune response against self-antigens that damages host tissues. Autoimmune diseases are caused by a combination of genetic factors and environmental factors  and (“polymorphism” or “SNP” or “variation” or “mutation”). All eligible studies were retrieved, and their references were checked and manually searched for finding other relevant articles. The related literature published in previous meta-analyses was also searched to identify other special publications. Only articles published in English and with human subjects were selected for this meta-analysis.Studies included in this meta-analysis had to meet all four criteria: (a) evaluation of association of rs35829419 or rs10754558 with AIDs risk; (b) original study and case-control design; (c) provision of sufficient genotype or allele data in cases and controls to calculate odds ratio (OR) and 95% confidence intervals (CIs); (d) full-text available. The definitions of patients with different types of AIDs in the selected literature followed internationally recognized guidelines such as the European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) , a dominant model , a recessive model , a homozygote co-dominant model , and a heterozygote co-dominant model , respectively. Subgroup analyses were conducted by ethnicity and disease type. Heterogeneity analysis was examined by the Chi-square based on Q-test. If the result of this heterogeneity test was p < 0.05, then the pooled OR was analyzed using a random-effects model (the DerSimonian and Laird method) to evaluate the association of NLRP3 Single-nucleotide polymorphisms with AIDs. Otherwise, a fixed-effects model (the Mantel–Haenszel method) was selected. Besides, in order to quantitatively estimate heterogeneity, we used another measure, I2 = 100% × (Q – df)/Q. The I2 statistic estimated the degree of inconsistency in the studies . Publication bias was investigated using Begg's funnel plot and Eegg's test. If the funnel plot was asymmetric, and the Eegg's result was p < 0.05, it was considered that there might be a publication bias. Meanwhile, we performed a sensitivity analysis in which one study was removed, and the rest were conducted to evaluate whether the results were affected statistically significantly. In this study, the meta-analysis was performed by using the software STATA version 14.0 .Hardy–Weinberg equilibrium (HWE) was tested by the Chi-square test. The crude OR and its 95% CIs in each case-control study were used to evaluate the strength of association between NLRP3 rs35829419 or rs10754558 polymorphisms and the risk of AIDs. The statistical significance of the pooled OR was determined by the Z-test, and a n = 4), T1D (2), CD (3), SLE (2), psoriatic arthritis , MS (1), and MG (1). All cases were patients with AIDs, and the controls were free of AIDs. In the included articles, although three articles were published by the same author, the research populations did not overlap with each other. The genotyping methods included fluorescence-based competitive allele-specific (KASPar), TaqMan, and multiplex ligation detection reaction (MLDR). The baseline characteristics of the eligible studies are summarized in Initially, 115 studies were identified by electronic searches. Among them, according to the title and abstract, a total of 79 non-inflammatory susceptibility studies were excluded. Finally, 36 full-text articles were included in our detailed analysis. After careful evaluation of the published literature based on the inclusion and exclusion criteria, we finally identified 12 articles to be included in this meta-analysis . For thep < 0.05). Among these articles, three articles came from the Latin American populations, six articles came from the European populations, three articles came from the Arab populations, and one article came from the Asian populations. Ethnicity-subgroup meta-analysis was performed to determine the association of the NLRP3 rs35829419 and rs10754558 polymorphisms with AIDs in different races. Furthermore, disease-subgroup meta-analysis was conducted to explore the association of the NLRP3 rs35829419 and rs10754558 polymorphisms with PsA, T1D, CD, MS, RA, SLE, and MG.Details of allele and genotype frequencies are shown in p = 0.029) and the homozygote co-dominant model . In the subgroup analysis by ethnicity, statistically slightly decreased AIDs risks were found among European populations in the allelic model . However, in other genetic models, no association between NLRP3 rs35829419 polymorphism and AIDs susceptibility was observed. More importantly, among the Latin American and Arabian populations, we also found no association between NLRP3 rs35829419 polymorphism and AIDs risk in any genetic model. In the subgroup of disease type, there were no significantly decreased or increased risks of PsA, T1D, CD, MS, SLE, and MG in any genetic model. However, in the RA group, remarkably decreased risks were found in the allelic model  and the homozygote co-dominant model . No significant associations were found in any other genetic model. Details of the meta-analysis are shown in In the included studies, we observed significant heterogeneity in some models, so the random effects model was applied, and the M–H fixed effects model was used in the other models. In all, when all eligible studies were pooled into the meta-analyses, we found that no significant AIDs risk was associated with the NLRP3 rs35829419 polymorphism in the allelic model , the heterozygote co-dominant model , or the dominant model . However, a protected effect was found in the recessive model , the homozygote co-dominant model , the heterozygote co-dominant model , the dominant model , and the recessive model . The mutation of allele from C to G can play a protective role against AIDs. Besides, in the subgroup analysis by ethnicity, significantly decreased AIDs risks were also observed among the Latin American populations in all genetic models. Among the Arabian populations, we only observed a significant reduction in the risk of AIDs in the dominant model and the heterozygote co-dominant model. In other genetic models, no association between NLRP3 rs10754558 polymorphism and AIDs susceptibility was observed. However, among European and Asian populations, we found no relationship between NLRP3 rs10754558 polymorphism and AIDs risk in any genetic model. In the subgroup of disease type, no significantly decreased or increased risks of CD and MG were found in any genetic model. However, in the RA group, remarkably decreased risks were found in all genetic models. In the T1D group, other genetic models in addition to the heterozygote co-dominant model showed that NLRP3 rs10754558 polymorphism was associated with a decreased risk of T1D. In the SLE group, the results of the allelic model, the homozygote co-dominant model, and the recessive model indicate that NLRP3 rs10754558 polymorphism can help reduce the risk of SLE. In the MS group, the results of the heterozygote co-dominant model and the dominant model also show the protective effect of NLRP3 rs10754558 polymorphism. No significant associations were found in any other genetic models. Details of the meta-analysis are shown in Since there was no significant heterogeneity in the following eight articles, the M–H fixed effects model was used for meta-analysis. On the whole, NLRP3 rs10754558 polymorphism contributed to reducing the risk of AIDs in all genetic models, including the allelic model (G vs. C: OR = 0.78, 95% CI = 0.71–0.87, t = 1.36, p = 0.199; AA/AC vs. CC: t = 1.36, p = 0.199; G vs. C: t = −1.25, p = 0.259; GG/GC vs. CC: t = −1.81, p = 0.120; Begger's funnel plot and Egger's test were performed to assess the publication bias of the literature. In all comparative models, the shape of the funnel plots was asymmetrical, which shows some evidence of publication bias . Howeverp = 0.339/p = 0.565, p < 0.001/p < 0.001, Pooling the eligible studies, we found no association of NLRP3 rs35829419 with AIDs risk in the allele/dominant model (Single-nucleotide polymorphisms of DNA sequence are caused by nucleotide variation at the chromosome genome level and are among the important causes for drug responsiveness, disease susceptibility, and ethnic difference Shastry, . RecentlCompared with previous meta-analyses, the published articles chosen in our research were stricter and more comprehensive. We searched all articles concerning the relationship between the NLRP3 rs35829419/rs10754558 polymorphisms and AIDs susceptibility and published in recent years through several databases, and excluded those inflammatory diseases such as Crohn's disease, ulcerative colitis, primary gout, and atherosclerosis, which were not removed in other meta-analyses. Previous meta-analyses focused on the relationship between NLRP3 polymorphisms and all inflammatory diseases, but our research was mainly concerned with the relationship between NLRP3 polymorphisms and AIDs. Finally, 12 qualified case–control studies were chosen in our research.The NLRP3 rs35829419 variant is a C>A polymorphism located in exon 3 of its gene (Theodoropoulou et al., The NLRP3 rs10754558 variant is a C>G polymorphism located in the 3′-UTR. Mutations in the 3′-UTR of NLRP3 gene may alter the activity of the inflammasome pathway by affecting the stability of mRNA and ultimately regulate the production of inflammatory factors including IL-1β and IL-18 (Hitomi et al., There are some limitations that we cannot avoid. First, although the results of publication bias in our study are not significant, publication bias may also be caused by some unpublished studies of negative results or some articles ignored during the literature search. Second, some included studies have relatively small sample sizes, which may lead to lower statistical power, especially in the stratified analysis. Third, during subgroup analyses based on ethnicity and disease types, the numbers of studies in some subgroups are too small, which may reduce our analytical power. Moreover, in some studies, the control population does not conform to HWE, which may influence the accuracy of results. In addition, we found that although the authors of the original literature included in this meta-analysis did not statistically analyze age factors between the case and control groups for CD and T1D, there appeared to be significant age differences between the two groups. Whether it affects the association between NLRP3 polymorphism and susceptibility to CD or T1D is unclear. Finally, the research objects of our meta-analysis mainly focus on AIDs, including systemic AIDs and organ-specific AIDs. Different types of AIDs may have different pathogenesis due to their different pathophysiology and disease severity. NLPR3 may play a different role in different types and severity of AIDs. We speculate that these factors may have some influence on the results of the meta-analysis of the association of NLPR3 gene polymorphisms in autoimmune diseases.In conclusion, the NLRP3 rs35829419 polymorphism may not be related to the risk of AIDs. However, NLRP3 rs10754558 allele G may have a protective effect on the risk of AIDs, especially in the Latin American population. In addition, NLRP3 rs10754558 polymorphism is associated with the occurrence of various AIDs, such as SLE, RA, and T1D. Further clinical research and functional analysis are needed to explore whether NLRP3 rs10754558 affects the production of cytokines through the inflammasome pathway.The original contributions presented in the study are included in the article/ZW conducted the statistical analysis and revised the manuscript. TL designed the study and wrote the manuscript. SW collected the data and all authors contributed to the completion of the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Drug resistance frequently led to the failure of chemotherapy for malignant cancers, hence causing cancer relapse. Thus, understanding mechanism of drug resistance in cancer is vital to improve the treatment efficacy. Here, we aim to evaluate the association between SMAD4 expression and the drug resistance in cancers by performing a meta-analysis.neg population vs SMAD4pos population. The HRs and risk ratios (RRs) with 95% confidence intervals (CIs) were used to explore the association between SMAD4 expression losses with drug resistance in cancers.Relevant studies detecting SMAD4 expression in cancer patients treated with chemo-drugs up till December 2020 were systematically searched in four common scientific databases using selected keywords. The pooled hazard ratio (HR) was the ratio of hazard rate between SMAD4After an initial screening according to the inclusion and exclusion criteria, eleven studies were included in the meta-analysis. There were a total of 2092 patients from all the included studies in this analysis. Results obtained indicated that loss of SMAD4 expression was significantly correlated with drug resistance with pooled HRs (95% CI) of 1.23 (1.01–1.45), metastasis with pooled RRs (95% CI) of 1.10 (0.97–1.25) and recurrence with pooled RRs (95% CI) of 1.32 (1.06–1.64). In the subgroup analysis, cancer type, drug type, sample size and antibody brand did not affect the significance of association between loss of SMAD4 expression and drug resistance. In addition, there was no evidence of publication bias as suggested by Begg’s test.Findings from our meta-analysis demonstrated that loss of SMAD4 expression was correlated with drug resistance, metastasis and recurrence. Therefore, SMAD4 expression could be potentially used as a molecular marker for cancer resistance. Drug resistance in cancers contributes to the failure of chemotherapy and the subsequent cancer relapse, finally causing the death of patients –3. Develet al. revealed that a high frequency of SMAD4 gene mutations existed in human colorectal cancers, thus showing that inactivation of SMAD4 is important during cancer progression [et al. who demonstrated an inhibition of prostate cancer growth and progression in the presence of SMAD4 [The pathway ligands, such as TGFβs, BMPs and activins, bind to the TGFβ receptors to phosphorylate SMAD2 and SMAD3, forming a SMAD2/SMAD3 complex that subsequently interacts with SMAD4 to form a trimer complex, then which is translocated into the nucleus to initiate the downstream target genes transcription . During gression . This fiof SMAD4 . Additioof SMAD4 , 17. Theet al. also found that SMAD4 inactivation had promoted the cancer progression and drug resistance of colorectal cancer in both in vitro and in vivo settings [In the clinical studies, most of the reports showed that SMAD4 loss was correlated with cancer malignancy and prognosis. There are also several systematic reviews that studied the clinicopathological significance of SMAD4 loss in various cancers , 18–20, settings , 22. Howsettings , 24. ThuSystematic review of several databases was conducted in December 2020 with no lower limitation set for date of publication. The potentially relevant publications were searched in several established databases, including PubMed, EMBASE, Cochrane library and ISI Web of Science. Medical subheading (MeSH) terms related to SMAD4 (or DPC4) in combination with words related to cancer (Cancer* or Adenocarcinoma* or Carcinoma* or Tumor*), chemotherapy (or Chemoradiation or chemo* or drug), as well as terms related to patient (or patient*) were used to retrieve eligible studies.1035 articles were extracted from the initial search using the combined MeSH terms. There were 152 articles identified from PubMed, 214 articles from ISI Web of Science, 652 articles from EMBASE and 17 articles from Cochrane library. A detailed screening process was illustrated as shown in Studies were included based on the following criteria: (1) the study objects were the patients; (2) the patients had to be treated with chemotherapy or chemoradiation; (3) the studies had to detect the SMAD4 expression level in tumor tissue; (4) the results in the studies had to show the overall survival curve data or present the HRs and 95% CIs. Studies were excluded according to the following criteria: (1) studies with duplicated data or a repeated analysis; (2) letters, reviews, case reports or conference; (3) study objects were xenografted animals with patient-derived cancer cells. (4) SMAD4 mutations with unknown protein function.pos, number of SMAD4neg, outcome , P value, HRs  with 95% CIs from multivariate analysis.The articles that have fulfilled both inclusion and exclusion criteria were reviewed and vital information was extracted by two investigators (X.W. and Lee S.H.) independently. Any disagreement was discussed and a consensus was reached for all issues. The following information were collected from each study: first author’s name, year of publication, cancer type, drug type, SMAD4 test, antibody brand, antibody dilution, sample size, number of SMAD4The quality of the included studies in meta-analysis was evaluated using the Newcastle-Ottawa quality assessment scale (NOS) . The scaet al. [Pheter <0.05, significant heterogeneity) and the I2 statistic . The random-effects model was applied in pooling the HRs (95% CIs) to avoid significant heterogeneity (Pheter <0.05 and I2 > 50%). A sensitivity analysis evaluating the stability of the results was performed by eliminating one study at a time. Publication bias was evaluated using the funnel analysis and begg’s test, with P < 0.05 to be considered significant. All statistical analysis was performed using the STATA software, version 16.0 . Meta-analysis was performed in STATA 16.0 using the metan package. All P values were two tailed tests.The pooled HRs were determined using HRs with their 95% CIs obtained from the studies. When the HR data cannot be obtained in the articles directly, a mathematical estimation based on the overall survival curve was performed according to the previously published methods demonstrated by Tierney et al. –28. The pos and SMAD4neg subgroups and treated with drugs. Six out of the eleven articles studied colorectal cancer. The other articles were about pancreatic cancer as shown in The main characteristics of these studies were tabulated in Those eleven selected articles were subjected to multivariate analysis, whereby random-effects model was used to combine the effect of the SMAD4 expression loss on chemoresistance. The pooled HR (95% CI) was calculated to be 1.23 (1.01–1.45) , indicatPES) was 1.15  in pancreatic cancer subgroup while the pooled HR  was 1.46  in colorectal cancer subgroup  in SANTA CRUZ subgroup was 1.22 , pooled HR in Abcam subgroup was 1.41 , while HR in the other brand subgroup was 1.20   , Table 3PES <0.01 (PES) was 1.20  when sample size greater than 150, the HRs was 1.41  when sample size less than 150  of 5-FU chemo-drug subgroup was 1.38 (0.92–1.85), HR (95% CI) of gemcitabine subgroup was 1.25 (0.61–1.89), whereas HR (95% CI) of the combined drugs was 1.36 (0.62–2.09) , Table 3than 150 , Table 3I2 value obtained was 34.5%, Pheter = 0.122, which revealed there was no heterogeneity among these eleven studies Click here for additional data file.S1 TableOS, overall survival; HR, Hazard Ratio.(PDF)Click here for additional data file.


CYP2R1 rs10741657, CYP2R1 (low frequency) rs117913124, DHCR7/NADSYN1 rs12785878, GC rs3755967, CYP24A1 rs17216707, AMDHD1 rs10745742 and SEC23A rs8018720. Seven case-control and three cohort studies were eligible for quantitative synthesis (n = 10). Meta-analysis results suggested no association with T1D . Heterogeneity was found in DHCR7/NADSYN1 rs12785878 . Sensitivity analysis showed exclusion of any single study did not alter the overall pooled effect. No association with T1D was observed among a Caucasian subgroup. In conclusion, the evidence from the meta-analysis indicates a null association between selected variants affecting serum 25(OH)D concentrations and T1D.Several observational studies have examined vitamin D pathway polymorphisms and their association with type 1 diabetes (T1D) susceptibility, with inconclusive results. We aimed to perform a systematic review and meta-analysis assessing associations between selected variants affecting 25-hydroxyvitamin D [25(OH)D] and T1D risk. We conducted a systematic search of Medline, Embase, Web of Science and OpenGWAS updated in April 2021. The following keywords “vitamin D” and/or “single nucleotide polymorphisms (SNPs)” and “T1D” were selected to identify relevant articles. Seven SNPs (or their proxies) in six genes were analysed:  Type 1 diabetes (T1D) is a chronic autoimmune disease, resulting from autoimmune degradation of pancreatic ß-cells leading to the inability to produce and/or use insulin ,3. UndiaEmerging evidence suggests low vitamin D status may play a role in T1Dpredisposition. Vitamin D is a steroid prohormone, with nutrition status approximated via serum 25-hydroxyvitamin D [25(OH)D] concentrations . NotablyAssociation between serum 25(OH)D concentrations and T1D risk is supported by evidence from in vitro and animal experiments ,13,14, aCYP2R1, DHCR7/NADSY1, GC, CYP24A1, AMDHD1 and SEC23A, which have been used as genetic instrumental variants in this study [Using selected vitamin D related genetic variants, it is possible in a genetic epidemiological setting to establish evidence of an etiological role of 25(OH)D in T1D pathophysiology. Since 25(OH)D synthesis is regulated by genes, single nucleotide polymorphisms (SNPs) may alter the bioavailability and target effects of vitamin D metabolites. Large-scale genome-wide association studies (GWAS) have identified several SNPs from genes influencing 25(OH)D levels; is study ,22.As individual studies may not have enough statistical power to identify an association between selected genetic variants affecting serum 25(OH)D concentrations and T1D, a meta-analysis is a useful statistical tool to pool data from published studies, where increasing the statistical power can give more accurate estimates of effect sizes. In this study, we perform a systematic review and meta-analysis of all existing studies reporting an association between selected 25(OH)D related genetic variants (exposure) and T1D risk (outcome) in humans (population). This topic provides a further scientific understanding of T1D pathophysiology and the potentiality of preventing T1D through increases in 25(OH)D concentrations.https://www.crd.york.ac.uk/prospero/ (accessed on 10 January 2021).This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines . Registr2 > 0.8), locating any additional studies fitting the inclusion criteria. Full search strategies are presented in A search was conducted in four databases: Ovid Medline (1964-present), Ovid Embase (1947-present), Web of Science (1975-present), IEU OpenGWAS (2020-present) from inception to April 2021. The primary search terms were as follows: humans, single nucleotide polymorphism, genetic variation, type 1 diabetes mellitus and vitamin D. The selection of articles in Medline and Web of Science was performed using Medical Subject Headings (MeSH) to define these descriptors. The selection of articles in Embase was performed using Emtree (Embase subject headings) to define these descriptors. Boolean operators  were also combined with keywords and subject headings. An initial pilot search was undertaken to improve inclusion clarity of study inclusion and exclusion, improving accuracy and consistency. The strategy was developed by one reviewer (L.N.) and proofread for syntax, spelling and overall structure by two reviewers (E.H. and J.S.). As part of the development process, we used two relevant, existing studies ,25 for v2 > 0.8 influencing 25(OH)D pathways for association with T1D status and 25(OH)D concentrations, were of interest. Eligible studies met the population, exposure, outcome (PEO) approach [1.Population: human of any gender and age, race and geographical distribution.2.CYP2R1 (common variant) rs10741657, CYP2R1 (rare variant/low frequency) rs117913124, DHCR7/NADSYN1 rs12785878, GC rs3755967, CYP24A1 rs17216707, AMDHD1 rs10745742, SEC23A rs8018720. Of these selected SNPs, six are common variants identified based on the results of a recent GWAS for 25(OH)D concentration [DHCR7/NADSY1 and both CYP2R1 variants), and two downstream (CYP24A1 and GC) of the 25(OH)D metabolite biochemical pathway. Two genes outside the vitamin D metabolism pathway (AMDHD1 and SEC23A) were also found to be significant variants and hence were included. 25(OH)D related proxies not directly present in the recent GWAS were also included if found in high linkage disequilibrium (r2 > 0.8) using the Ldproxy function in LD link .Exposure: a biological approach to the selection of genetic variants was used, including variants having a biological link to the exposure. Seven vitamin D related SNPs were selected: ntration . Strong 3.Outcome: the primary outcome measure, T1D, was defined by the World Health Organization criteria: diabetes symptoms , accompanied by exogenous insulin usage once T1D had been diagnosed . T1D cou4.Study design: peer-reviewed genetic association, cohort, cross-section, or case-control observational studies and Mendelian randomization (MR) studies, as well as clinical trials and unpublished cohort studies.5.A sample size of at least 50 cases and 50 controls were mandatory for sufficient data extraction. Where there were multiple publications from the same study population, the most recent highest quality results with the largest sample size were used.6.The publication reported genotype distribution in both cases and controls in order to estimate an odds ratio (OR) with a 95% confidence interval (CI).Studies testing exposure of selected genetic variants or their proxies with rapproach  as follo1.Conference papers.2.Other types of diabetes.The following exclusion criteria were also used:No language, publication status, or publication date limitations were imposed.Literature was searched in duplicate independently by two authors (L.N. and J.S.), and approved by a third author (E.H.). After excluding duplicates, article selection was carried out in two passes. In the first pass, title and abstract screening occurred for the selection of relevant papers meeting the eligibility criteria. In the second pass, proposed articles from the first pass were screened in full text for compliance with inclusion criteria. To ensure literature saturation, reference lists of obtained studies from original database searches were manually scanned for potential unidentified additional studies by one author (L.N.), with eligibility confirmed by a second author (J.S.). Furthermore, OpenGWAS was used to identify unpublished studies, locating one FinnGen cohort study sharing summary-level data fitting the search parameters. Datasets were also identified in the UK Biobank, a large-scale prospective cohort study.Data were extracted independently by two authors (L.N. and J.S.) using a predetermined data extraction template. The following data were extracted from the articles included in this systematic review: first author; region/demographic information; publication year; study design characteristics; participant characteristics, including gender and ethnicity if reported; the number of cases and controls studied; mean age (or range) at the onset of T1D in cases; outcome measure, diagnostic criteria of T1D; mean age (or range) of the control group; how the controls were selected; genotyping methods, genotype distribution, and allele frequency in cases and controls; all reported patient outcome measures; key findings; protocol availability and funding sources. Corresponding authors were contacted by e-mail for missing or unreported data a maximum of three attempts, to avoid any assumptions made from unclear information. All disagreements were resolved by consensus, or with the input of a third author (E.H. or A.Z.).2 > 0.8) was extracted and used to estimate the related effect. In studies where the OR per vitamin-D-increasing allele was not reported, we estimated the allelic effect from the contingency table of T1D distribution by SNP genotypes, where OR was computed by dividing the odds of T1D in the heterozygotes  by that in the homozygotes . Meta-analysis was performed using the random-effects model  [2 statistic, with heterogeneity considered to be substantial if the p-value for the Cochran’s Q test < 0.05 or I2 > 50%. All p-values were for two-tailed tests, and <0.05 was considered statistically significant.All mentioned statistical analyses were performed with STATA 16.0 software  and R 4.0.2 software by two authors (L.N. and A.Z.). For each variant, OR per vitamin D-increasing allele was extracted from individual studies for the meta-analysis, as per the SUNLIGHT consortium . If a st method) . HeterogWe conducted sensitivity analyses by removing a single study at a time, evaluating the integrity of the results. Subgroup analysis was performed by restricting the sample to the Caucasian population, to examine the possible effects of population stratification. Initial protocol pre-specified plan for further MR analyses, which were not conducted as it was considered redundant given clear results.The methodological quality of eligible studies was evaluated using Critical Appraisal Skills Program tools for cohort and case-control studies . Two autTwo reviewers assessed the risk of bias due to missing results in a synthesis (L.N. and A.Z.). Potential publication bias was assessed by examining for asymmetry using Begg’s funnel plot for each SNP . If publInitially, 290 potential studies were identified from the search. The summary characteristics of included studies are shown in Similarly, none of the eligible studies endeavoured to control for vitamin D dietary intake through infancy and/or childhood, a known risk factor of T1D. However, when study quality was assessed, all included studies presented with a low risk of bias using the CASP tools, with no deviation from the Hardy-Weinberg equilibrium in controls reported in all case-control studies, and only some studies presenting with one item partially unmet .Statistical methods to control confounding varied between studies. Most studies adjusted for different potential confounding factors, such as age, sex, genotype batch, geographical origin and BMI see . Two remCYP2R1), rs117913124 A/G (CYP2R1 low frequency), rs12785878 G/T (DHCR7/NADSYN1), rs3755967 T/C (GC), rs17216707 C/T (CYP24A1), rs10745742 C/T (AMDHD1), rs8018720 C/G (SEC23A) were reported in three or more studies and taken forward to the meta-analyses. Associations between the SNPs and T1D, using individual and pooled OR estimates, are displayed in All specified polymorphisms (namely rs10741657 G/A (CYP2R1), the reported ORs ranged from 0.46 to 1.11 (p = 0.01) with little heterogeneity among the studies (I2 = 25.1%). For rs117913124 A/G (CYP2R1 low frequency), the ORs ranged from 1.00 to 1.07 . For rs12785878 G/T (DHCR7/NADSYN1), the ORs ranged from 0.78 to 1.06 (p = 0.02). There was evidence of moderate between-study heterogeneity (I2 = 64.8%). For rs3755967 T/C (GC), the OR ranged from 0.99 to 1.53 . In the evaluation for publication bias, asymmetry in Begg’s funnel plot was observed for GC rs3755967 (CYP24A1), the OR ranged from 0.96 to 1.03 (p = 0.37), with little indication of heterogeneity (I2 = 18.0%). For rs10745742 C/T (AMDHD1), the OR ranged from 1.00 to 1.02 (p = 0.90). Again, there was no sign of heterogeneity (I2 = 0.0%). For rs8018720 C/G (SEC23A), the OR ranged from 0.97 to 1.05 (p = 0.19) with little heterogeneity among the studies (I2 = 42.8%). In view of these individual estimates, under the studied models no statistically significant associations between any of the seven SNPs alone (or their proxies) and T1D were found. Other than in rs3755967 (GC), no other asymmetry in Begg’s funnel plot was observed. No outcome reporting bias was detected in any of the studies.For rs10741657 G/A . A subgroup analysis performed on the Caucasian population found no manifestations of association, with no major changes in primary outcomes . AnalyseOur extensive systematic review and meta-analysis did not provide support for an association between 25(OH)D related variants and T1D. Our review identified 10 studies for inclusion, which were all relatively high quality, presenting only minor systematic flaws in methodology. However, evidence from published studies was inconsistent, and for most polymorphisms, only a handful of studies were found. Many of the studies were small, limiting the statistical power of each meta-analysis, and preventing robust sensitivity analyses to evaluate associations by possible sources of heterogeneity, such as geographic location, and ancestry.To the best of our knowledge, our study is the largest and most comprehensive systematic review and meta-analysis on the topic. The largest of the previous studies was a recently published MR study , which aCYP2R1 common variant polymorphisms with T1D in 578 German participants, providing early support for the causal role of 25(OH)D in the pathogenesis of T1D. Hussein et al. [n cases = 120) between the CYP2R1 common variant with risk of T1D. Smaller study over-estimates of effect can yield asymmetric funnel plots that can be explained by a restrictive study population [GC rs3755967 , which was unanticipated given the studies included in the analyses of this variant were all of European ancestry, with adjustments for confounding factors. However, DHCR7 affects skin synthesis of vitamin D following exposure to UVB radiation from the sunlight and may be particularly sensitive to subtle variations in population structure. Variants affecting vitamin D metabolism have been shown to display population-specific patterns in frequency [Bsml polymorphism in the vitamin D-receptor gene was only associated with T1D in those with Asian ancestry [High heterogeneity was found in the meta-analysis requency , and arerequency . This haancestry . Differiancestry .Vitamin D status is mainly determined by lifestyle factors, such as exposure to sunlight, dietary supplementation and intake, as well as personal characteristics including obesity and age. Indeed, common genetic variants typically have modest effects, and they only account for a small amount of the variation in 25(OH)D levels . TherefoGiven the limited number of studies, we were unable to assess ethnic differences in the association between 25(OH)D variants and T1D. Given ethnicity may affect the function and expression of vitamin D related genes ,52,53, iOur study benefits from the systematic way in which results have been summarised, our comprehensive search strategy and the inclusion of grey literature. The design captures lifetime differences in 25(OH)D levels, rather than a single vitamin D measurement. Our study also has some limitations requiring consideration. Despite including information from the largest available databases to supplement all published data, available information remains limited. The relatively small number of included studies prevented us from undertaking analysis to examine the associations in diverse ethnic groups or to account for other population characteristics. There was little to no information from populations that were vitamin D deficient. For example, the FinnGen study in Finland commenced in 2017, after the National Nutrition Council had launched the national food fortification of vitamin D (2002) . TherefoInvestigating for smaller causal effects may be important for public health, due to a high prevalence of low 25(OH)D concentrations in many populations. Findings need to be elucidated by conducting larger scale epidemiological investigations, exploiting the potential for vitamin D related genetic variants as a risk factor for T1D, to confirm or refute the study findings. Furthermore, said studies will need to investigate the role of 25(OH)D related genetic variants in the context of clinical deficiency, where even subtle increases in concentrations may help, providing a more comprehensive understanding of the association between variants affecting serum 25(OH)D concentration and T1D.Results from this meta-analysis showed no large effect of a genetically determined reduction in 25(OH)D concentrations by selected polymorphisms on T1D risk, despite the strong association seen in some observational studies. Although the hypothesis that a different SNP distribution from vitamin D related genes is associated with T1D was not confirmed by this study, small effects cannot be discounted. To make conclusive estimates in complex diseases, such as T1D, further characterization of complex interactions between genetic and environmental factors, like the included variants affecting serum 25(OH)D concentrations, need to be considered.