This article systematically and critically reviews the epidemiologic evidence on the association between exposure to TCDD or Agent Orange, a TCDD-contaminated herbicide used during the Vietnam War, and prostate cancer risk. Articles evaluated include 11 studies of three cohorts, four case–control or cross-sectional studies, and three case-only studies of military veterans with information on estimated Agent Orange or TCDD exposure; 13 studies of seven cohorts, one case–control study, and eight proportionate morbidity or mortality studies of Vietnam veterans without information on Agent Orange exposure; 11 cohort studies of workers with occupational exposure to TCDD; and two studies of one community cohort with environmental exposure to TCDD. The most informative studies, including those of Vietnam veterans involved in Agent Orange spraying or other handling, herbicide manufacturing or spraying workers with occupational TCDD exposure, and community members exposed to TCDD through an industrial accident, consistently reported no significant increase in prostate cancer incidence or mortality. Only some potentially confounded studies of Vietnam veterans compared with the general population, studies with unreliable estimates of Agent Orange exposure, and analyses of selected subgroups of Vietnam veterans reported positive associations. Overall, epidemiologic research offers no consistent or convincing evidence of a causal relationship between exposure to Agent Orange or TCDD and prostate cancer. More accurate exposure assessment is needed in large epidemiologic studies to rule out a causal association more conclusively.To inform risk assessment and regulatory decision-making, the relationship between 2,3,7,8-tetrachlorodibenzo-The online version of this article (doi:10.1007/s10654-014-9931-2) contains supplementary material, which is available to authorized users. In a 19decreased significantly with higher estimated TCDD body burden   (Table Pheterogeneity = 0.08), or that were restricted to veterans who spent a maximum of 2 years in Southeast Asia . The former association may have been influenced by differences in diagnostic intensity if health care usage was greater among Vietnam than non-Vietnam veterans, as suggested by some data  among Ranch Hands and 28 of 54 [52 %] among comparison subjects) were “diagnosed as a direct result of the examinations” scheduled for the study, and that “these data are consistent with the hypothesis that the increased SIR for … prostate cancer might be at least partially explained by the medical examinations that these men received” . These cP = 0.72) (Table Ptrend = 0.003). These findings suggest that exposures in Southeast Asia other than Agent Orange, or factors associated with longer duration of military service, may be responsible for observed associations with prostate cancer. The correlation between serum TCDD levels and time served in Southeast Asia was not reported, but it appeared to be modest, based on a table showing quartiles of serum TCDD by quartiles of years in Southeast Asia.Pavuk et al.  undertooPtrend = 0.42) (Table Ptrend = 0.04) and among those who served for less than two years . When Ranch Hands and comparison subjects were analyzed separately, high versus low cumulative TCDD was not significantly associated with prostate cancer risk in either group. Time served in Southeast Asia and last year of duty also were not significantly associated with prostate cancer risk among Ranch Hands, but longer time served in Southeast Asia (dichotomized at 789 days) was significantly associated with increased risk among comparison subjects . Of note, the distribution of Gleason score (disease grade indicating likelihood of tumor spread) did not differ significantly between the 62 Ranch Hand prostate cancer cases and the 89 comparison subject cases (P = 0.44). This finding suggests that the two groups were equally affected by the detection of low-grade disease by means of PSA testing.Finally, in the most recent analysis of prostate cancer incidence in the Air Force Health Study, estimated 20-year cumulative TCDD level was not significantly associated with prostate cancer risk . The adjTaken together, results from the Air Force Health Study demonstrate no clear association between TCDD exposure and prostate cancer risk. The higher risk in both Ranch Hands and comparison subjects relative to the U.S. general population, combined with the lack of a difference between Ranch Hands and comparison subjects, as well as the absence of a significant difference in prostate cancer mortality between study subjects and the general population, suggests that increased prostate cancer screening among study participants compared with the general population may be responsible for much or all of the observed excess incidence. The positive associations within certain subgroups selected based on shorter duration of military service or geographic location exclusively in or outside of Vietnam were not well justified in advance, and were potentially biased or due to chance if numerous subgroups were tested.Methodological strengths and limitations of the Air Force Health Study have been thoroughly discussed e.g., , 76–81).–81.76–81Another key strength of this study is the inclusion of a comparison group of veterans matched on age, race, rank, and military occupation and controlling for military service involving aircraft missions in Southeast Asia, thereby making the groups equivalent in terms of “combat-induced physiologic, psychophysiologic, and other related morbidity and mortality disorders,” as well as “the effects of alcohol consumption, the use of chemoprophylactic and/or illicit drugs, and the acquisition of tropical diseases associated with life in [Southeast Asia]” . NotablyMembers of 22 U.S. Army Chemical Corps units assigned to South Vietnam between 1966 and 1971 were responsible for the storage, handling, mixing, application, and equipment maintenance of tear gas, burning agents, and herbicides, including Agent Orange . Due to Subsequently the cohort was expanded to include 2,872 male U.S. Army veterans with at least one assignment to the Chemical Corps in Vietnam, and a comparison group of 2,737 male U.S. Army veterans last discharged from the Chemical Corps but never assigned to Southeast Asia . Ri. Ri34]. Among 2,720 veterans referred to the Portland, Oregon, VA Medical Center for initial prostate biopsy and without a history of prostate cancer, 203 were classified as exposed to Agent Orange based on self-report at the time of hospital enrollment (before prostate biopsy) or military service in “a location where [Agent Orange] was known to have been used,” and the remaining 2,517 were classified as unexposed . SubjectDespite these relatively small differences by exposure status, the adjusted OR for prostate cancer (vs. no prostate cancer) in exposed versus unexposed veterans was 1.52 (1.07–2.13)  was conducted in 2004 to evaluate associations between Agent Orange exposure and self-reported disease outcomes . Agent OPtrend = 0.15). The combination of self-reported exposure and self-reported disease is highly susceptible to information bias. The validity and reliability of the exposure opportunity index model have also been questioned on the basis of widely heterogeneous exposure estimates ) (Table stimates . Moreovetration) , and avetration) . Thus, tThree other studies of prostate cancer in veterans compared patient and disease characteristics between prostate cancer patients with and without reported Agent Orange exposure Table  98–100]–10098–10At a West Virginia cancer center between 1995 and 2005, 29 Vietnam veterans with Agent Orange exposure determined by eligibility for VA benefits and 52 Vietnam veterans without Agent Orange exposure underwent permanent brachytherapy for prostate cancer . Those wAmong 1,495 veterans at four VA medical centers who underwent radical prostatectomy for prostate cancer in 1988–2007, including 206 classified in the electronic medical record as having been exposed to Agent Orange and 1,289 classified as unexposed, exposed patients were significantly more likely to be younger at the time of radical prostatectomy, have lower-stage disease, and have a lower preoperative PSA level . HoweverAmong 93 veterans at the Augusta, Georgia, VA medical center who underwent radical prostatectomy for prostate cancer in 2005–2009, those classified in the electronic medical records (based on self-report and military records confirming military service “in an area in which [Agent Orange] had been sprayed”) as exposed were older at the time of radical prostatectomy than those classified as unexposed, and were less likely to have positive surgical margins, but did not differ significantly in terms of preoperative PSA level, prostate volume, biopsy or prostatectomy Gleason score, tumor pathological stage, extracapsular extension, seminal vesicle invasion, lymph node metastasis, or subsequent mortality (with a median follow-up of 64 months) . ResultsIn summary, three VA hospital-based studies in the U.S. , 34, 92 In its Veterans and Agent Orange updates, the IOM Committee takes into consideration studies of Vietnam veterans that lack estimates of exposure to Agent Orange/TCDD or restriction to a subgroup of veterans known to have had high potential for Agent Orange exposure –32. As sThe Government of Australia conducted a series of retrospective cohort studies comparing Australian veterans of the Vietnam War with either conscripts who served only in Australia or the general population of Australia. Australian military personnel in Vietnam were mostly stationed in Phuoc Tuy Province, which was not heavily sprayed with Agent Orange; thus, the average exposure of Australian troops to Agent Orange was probably low, if any . AnalyseOther epidemiologic studies of Australian veterans of the Vietnam War were based on comparisons between Vietnam veterans and the general Australian population, rather than veterans stationed elsewhere. Although most  of thesThe U.S. CDC designed the Vietnam Experience Study to evaluate the health consequences of military service in Vietnam, where “Vietnam Experience” was used as “a generic term for a wide range of health-influencing exposures operating among those who served in the military in Vietnam” . The autNotably, the CDC designed another study specifically to evaluate the potential health effects of Agent Orange exposure. However, this study was stopped after the exposure assessment phase because serum TCDD levels measured in 1987 did not differ between veterans who were stationed in the most heavily sprayed area of Vietnam (III Corps) and veterans who served in Germany or the U.S. during the same years . TherefoA case–control study of 606 prostate cancer cases (61 % participation) and 471 age-matched controls randomly selected from electoral rolls (43 % participation) in Western Australia found a non-significant increase in prostate cancer risk in association between self-reported military service in Vietnam (age-adjusted OR = 2.12 [0.88–5.06]) . The estA retrospective cohort study of 2,783  male New Zealand veterans who served in Vietnam found no significant increase in prostate cancer incidence (SIR = 1.17 [0.98–1.39]) or mortality (SMR = 1.03 [0.55–1.76]) in comparison with the general New Zealand population  among all Vietnam veterans combined, compared with the general male population of Korea , and sprayers of the same herbicides . The review of the results on prostate cancer risk among herbicide manufacturers and sprayers is complicated by the fact that several partially overlapping study groups have been included in various reports. Several studies conducted in Europe and Oceania (most of which had been reported separately) were combined in a pooled analysis coordinated by IARC ; similarIn our review, we considered the combined publication of the two pooled analyses , the NIOThe combined IARC/NIOSH pooled analysis comprised 21,863 male and female workers exposed to phenoxy herbicides or chlorophenols from 32 cohorts of manufacturing workers from Austria, Denmark, Finland, Germany, Italy, the Netherlands, New Zealand, Sweden, the United Kingdom, and the United States, and four cohorts of sprayers from Australia, Canada, New Zealand, and the United Kingdom  . The perOverall, 13,831 workers from 28 cohorts (63.3 %) were classified as exposed to TCDD , and 7,553 workers (34.5 %) were classified as unexposed to TCDD (479 workers from a UK plant [2.2 %] could not be classified as to TCDD exposure). The SMR for prostate cancer was 1.11  among exposed workers and 1.10  among unexposed workers .Collins et al. , 138 repA further analysis included 2,122 workers at four pentachlorophenol production plants that were part of the NIOSH pooled study . A subco‘t Mannetje et al.  extendedThe mortality of 2,106 male production workers employed in two Dutch plants included in the IARC pooled study was updated to 2006 . A totalThe mortality follow-up of one of the plants from Germany included in the IARC pooled study was extended to 2007 . The cohThe only group of workers not included in the IARC or the NIOSH pooled analysis is a cohort of 243 male workers who were involved between 1953 and 1969 in clean-up, repair, maintenance, or demolition activities at a German plant where an accident entailing release of TCDD occurred in 1953 . Serum TSubsets of workers who developed chloracne, indicating high TCDD exposure, were identified in the NIOSH pooled cohort (630 workers)  and in tTwo other studies provided limited information on prostate cancer risk associated with potential occupational exposure to TCDD-contaminated herbicides. In the Agricultural Health Study, a cohort of 55,332 male pesticide applicators from Iowa and North Carolina, no association was found between self-reported use of 2,4,5-T  and risk of prostate cancer, based on 566 cases after a mean follow-up period of 4.3 years (detailed results not reported) . In a poIn summary, although a formal combination of results is complicated by the overlap among reports, studies of manufacturers and sprayers of TCDD-contaminated herbicides consistently indicate no significant increase in risk of prostate cancer. This conclusion comports with that of a meta-analysis of 20 cohort studies of phenoxy herbicide manufacturing workers published through 2003, in which the combined SMR for prostate cancer was 1.16 (0.85–1.57) . LimitatPart of the population living in six Italian municipalities was exposed to TCDD as a result of an accident in a trichlorophenol production plant in Seveso in 1976. Several reports on cancer mortality or incidence in this area have been published; the most recent analyses are based on follow-up for cancer mortality through 2001  and cancThe exposed group was divided among those living in 1976 (or migrating during 1976–1985) in zone A, with the highest exposure (median serum TCDD level in 1976 = 447.0 ppt); zone B, with intermediate exposure (median serum TCDD = 94.0 ppt); and zone R, with low exposure (median TCDD level = 48.0 ppt). The reference group comprised the remaining areas of the six municipalities, as well as five surrounding municipalities. Cancer incidence was based on record linkage with the regional population-based cancer registry, and the mortality follow-up was based on vital status information obtained from the municipalities of residence and on cause of death obtained from the regional statistical office.The cancer incidence analysis was based on people living in the contaminated area  . This anThe cancer mortality analysis included also those individuals who were born or immigrated into the study area between 1976 and 1985  . The obsIn summary, there is no evidence of an increased risk of prostate cancer in the community exposed to the Seveso accident with follow-up extending over 20–25 years. While the number of individuals in the zone with highest exposure is relatively small, and exposure was classified with some error based on geographic zone of residence instead of individual serum TCDD level, the results in the combined zones A and B are not compatible with a significant association between TCDD exposure and prostate cancer.A recent meta-analysis of cohort studies of TCDD and prostate cancer calculated a meta-SMR of 1.26 (1.00–1.57) based on 13 military and occupational cohorts (one of which reported an SIR) and a meta-RR of 1.04 (0.84–1.28) based on four military and community cohorts . This meThe best available epidemiologic studies of exposure to Agent Orange/TCDD show no significant association with prostate cancer incidence or mortality. Specifically, the only two studies of Vietnam veterans with exposure to Agent Orange confirmed by elevated serum TCDD levels—namely, the Air Force Health Study and the Army Chemical Corps study—found no significant increase in prostate cancer incidence , 73 or mIn his well-known and widely implemented guidelines for the evaluation of potential causal associations, Sir Austin Bradford Hill specified that the guidelines were intended to be applied to “an association between two variables, perfectly clear-cut and beyond what we would care to attribute to the play of chance. What aspects of that association should we especially consider before deciding that the most likely interpretation of it is causation?” . In the The null results are also coherent with toxicological data from experimental animal studies. Specifically, although TCDD promotes a variety of tumors in different strains of rats, mice, and hamsters through a non-genotoxic mechanism believed to involve the Ah receptor , 14–16, The only studies that found a significant positive association with prostate cancer were those in which the exposure under evaluation was self-reported or geography-based Agent Orange exposure , 92, 94 In conclusion, studies of Vietnam veterans, herbicide manufacturers or sprayers, and community members known to be highly exposed to Agent Orange or TCDD consistently demonstrate the absence of a significant increase in prostate cancer incidence or mortality in these groups. Several bias-prone studies of veterans with poorly characterized Agent Orange exposure reported an excess of prostate cancer, but such findings cannot reliably be attributed to an effect of Agent Orange/TCDD rather than confounding or bias. Toxicological findings in animals are also coherent with the absence of a carcinogenic effect of TCDD on the prostate. Overall, the scientific evidence establishes no causal association between exposure to Agent Orange or TCDD and prostate cancer in humans. However, the most rigorously designed studies may lack sufficient power to determine whether RRs of the magnitude generally reported (approximately 0.3–3.0) were statistically significantly different from 1.0. Development of more sensitive biomarkers of past exposure to Agent Orange or TCDD could enable larger studies to rule out a causal association more conclusively.Supplementary material 1 (DOCX 176 kb)Below is the link to the electronic supplementary material.


NCOA3) plays a critical role in lipid metabolism as well as adipogenesis and obesity. The present study aims to investigate the association between NCOA3 SNPs and dyslipidemia in the Chinese Han population.Nuclear receptor coactivator-3 (NCOA3) is involved in various physiological processes. Emerging evidence from previous studies using animal models suggests that the NCOA3 gene  Chinese Han subjects were recruited. Four tag SNPs  in Four SNPs  were associated with triglyceride levels. Except for SNP rs10485463, genotype distributions and allele frequencies of the other three NCOA3 SNPs  were significantly different between hypertriglyceridemia subjects and normal group. Significant differences were also observed in allele frequencies and genotype distributions of SNP rs10485463 between low-HDL cholesterolemia subjects and normal group. Carriers of rs2425955 T allele had a lower risk of hypertriglyceridemia compared to GG genotype. Similar results were observed from rs6094753. Subjects with rs6066394 CT genotype had a lower risk of hypertriglyceridemia than those with the TT genotype; however, CC and TT genotypes showed no significant difference in the risk of hypertriglyceridemia. Similar results were found in the association between rs6066394 and hypercholesterolemia. The variant alleles of rs2425955, rs6066394 and rs6094753 were associated with a lower risk of hypertriglyceridemia compared with the wild-type alleles. The G allele of rs10485463 was associated with an increased risk of low-HDL cholesterolemia. In the log-additive model the association between rs2425955 and hypertriglyceridemia remained significant after Bonferroni correction, and genotypes with variant alleles were associated with a lower risk of hypertriglyceridemia.NCOA3 might influence the risk of dyslipidemia and serum lipid levels in Chinese Han population.In summary, this study demonstrated that variation in  NCOA3), a member of the p160 family of nuclear receptor coactivators, plays significant roles in various physiological processes, such as mammary gland development, cell reproduction, somatic growth, and female generative function [Nuclear receptor coactivator-3 (function –7.NCOA3) plays a primary role in adipogenesis as well as obesity by regulating the gene expression of peroxisome proliferator-activated receptor γ (PPARγ) - the master regulator of adipocyte development and differentiation [NCOA3 knockout mice with a significantly decreased gene expression of PPARγ [NCOA3 ablation led to a significantly higher VAT/SCAT weight ratio under HFD versus normal diet - providing an evidence of the role in redistributing fat distribution for NCOA3 [Previous studies provided evidence that the NCOA3 gene  and decreased energy expenditure (EE), while caloric restriction reduced NCOA3 levels, resulting in improved PGC-1α activity, increased EE and an improved metabolic profile, such as lower fasting cholesterol, triglycerides, and free fatty acids levels. Disturbance in energy homeostasis, which is sustained by a balance between energy intake and energy expenditure, may lead to metabolic diseases such as obesity, dyslipidemia, and atherosclerosis [In addition to its crucial role in controlling adipogenesis and fat distribution, emerging evidence from metabolic studies –22 has sclerosis .NCOA3 plays a critical role in adipogenesis, energy homeostasis, and lipid metabolism. However, to the best of our knowledge, studies on NCOA3 gene so far are carried out mainly on animal models, with no published epidemiologic studies that investigated the association of human NCOA3 single nucleotide polymorphisms (SNPs) and metabolic disorders. In this study, we intended to analyze the association between polymorphisms of human NCOA3 and dyslipidemia.Dyslipidemia is a significant risk factors for coronary heart disease, which is a major public health problem in the worldwide. Although the exact cause of dyslipidemia is unknown, blood lipid level is influenced by multiple genetic and environmental factors and their interactions , 25. It 47.6 % of the respondents were males, with an average age of 58 ± 10 years. The percentages of subjects with hypertriglyceridemia, hypercholesterolemia, low-HDL cholesterolemia, and hyper-LDL cholesterolemia were 30.6, 18.7, 15.9, and 30.1 %, respectively. Table P = 0.009, 0.004, 0.019, and 0.006, respectively), and subjects carrying the variant allele of the four SNPs had a lower level of triglyceride than those who were homozygous for the wild-type allele. However, the significant association between these four SNPs and three other serum lipid parameters  were not observed  (data not shown). Allele frequencies and genotype distributions of the four SNPs in NCOA3 are presented in Table NCOA3 SNPs  were significantly different between hypertriglyceridemia subjects and normal group. Significant differences were also observed in allele frequencies and genotype distributions of SNP rs10485463 between low-HDL cholesterolemia subjects and normal group.The genotype distributions of the four NCOA3 SNPs . Subjects carrying the variant allele of SNP rs2425955 (genotypes: GT and TT) had a lower risk of developing hypertriglyceridemia compared to those who were homozygous for the wild-type allele G . Similar results were obtained from SNP rs6094753 . Subjects with the CT genotype of rs6066394 had a lower risk of hypertriglyceridemia than those with the TT genotype ; but those with the CC and TT genotypes showed no significant differences in the risk of suffering from hypertriglyceridemia . Besides, the CT genotype of rs6066394 was slightly associated with a lower risk of hypercholesterolemia compared to the TT genotype . Similarly, the CC and TT genotypes of rs6066394 showed no significant differences in the risk of developing hypercholesterolemia . The GG genotype of SNP rs10485463 was associated with low-HDL cholesterolemia in comparison to the CC genotype ; however, there was no significant difference between the CG and CC genotypes in affecting HDL levels .Logistic regression analysis revealed that hypertriglyceridemia was associated with three In addition, we explored the association of the allele of the four SNPs with dyslipidemia. As shown in Table NCOA3 polymorphisms and dyslipidemia was further investigated through inheritance models. Only rs2425955 was significantly associated with hypertriglyceridemia after Bonferroni correction (P = 0.0010) .Figure NCOA3 might influence the risk of dyslipidemia and serum lipid levels in Chinese Han population.In this study, our findings indicated that variation in NCOA3 ablation leads to reduced body weight and adipocyte volume due to impaired white adipocyte differentiation, and a significant decrease in the expression of PPARγ, while re-expression of NCOA3 restored the adipocyte differentiation program. During adipocyte differentiation, NCOA3 served as coactivator that synergistically facilitates the gene expression of PPARγ with specific transcriptional factors of the CCAAT/enhancer-binding proteins(C/EBP) [Previous studies have now convincingly demonstrated that the NCOA3 gene plays a critical role in adipogenesis by controlling the expression of PPARγ gene which is the master regulator of adipocyte development and differentiation –16. In as(C/EBP) , 9.PPARγ, a member of the nuclear hormone receptors that can interacts with its binding partner - retinoid X receptor α, can bind to DNA within the promoter elements of target genes . PPARγ, Hence, the diverse biological functions of PPARγ, such as regulation in lipid metabolism, lipid storage and so on, might be influenced by the NCOA3 gene through controlling PPARγ gene expression. And it can be further concluded that the NCOA3 gene might have association with plasma lipid levels and dyslipidemia, especially with hypertriglyceridemia. NCOA3 SNPs were associated with plasma levels of triglyceride, and except rs10485436, three other SNPs of NCOA3 gene were associated with a decreased risk of hypertriglyceridemia. In the further inheritance model analysis, only rs2425955 was significantly associated with hypertriglyceridemia after Bonferroni correction.In the present study, our data showed that fourNCOA3 caused by polymorphism rs2076546 may lead to decrease in PPARγ expression level which may lead to increase in the plasma levels of triglyceride and hypertriglyceridemia. Hence, the association of rs2425955 with hypertriglyceridemia might be explained by the effect of rs2076548 which is in LD with rs2425955.SNP rs2425955 is in linkage disequilibrium (LD) with rs2076546 (D’ = 1) based on the Chinese HapMap data. SNP rs2076546 is in the coding region of NCOA3 gene. Although rs2076546 is a synonymous SNP and causes no change from threonine , the stuNCOA3. Hsia et al. found several functional E2F binding sites in the intron 1 and exon 1 of NCOA3 gene which were crucial for NCOA3 gene activation [NCOA3 may have potential effect on gene transcription. Based on the consideration, we intended to indentify putative E2F binding sites in intron 1 using the JASPAR database [In addition, rs2425955 is located at the intron 1 of tivation . E2Fs, ctivation –38. Theitivation . Previoutivation ,40. We sdatabase , and fouNCOA3 SNPs and dyslipidemia in humans. Our sample size is relatively small, replication of the finding from this study with a larger sample is necessary to further explore the role of the target gene and its variation in the development of metabolic disorders.The reasons mentioned above may explain the association between rs2425955 and hypertriglyceridemia in our study. There is scarcely any information about the relationship between Besides, SNP rs10485463 was associated with low-HDL cholesterolemia, and SNP rs6066394 was slightly associated with a lower risk of hypercholesterolemia in our study. However, in the analysis of inheritance models the association between the four SNPs and dyslipidemia (hypercholesterolemia and low-HDL cholesterolemia) was not observed after bonferroni correction. Therefore, whether the two SNPs (rs10485463 and rs6066394) are associated with dyslipidemia needs to be further studied.NCOA3 might be in association with dyslipidemia and serum lipid levels in the Chinese Han population.The four NCOA3 SNPs were associated with plasma levels of triglyceride, and except rs10485436, three other SNPs of NCOA3 gene were associated with a decreased risk of hypertriglyceridemia. In addition, SNP rs10485463 was associated with low-HDL cholesterolemia, and SNP rs6066394 was slightly associated with a lower risk of hypercholesterolemia. In conclusion, our present study revealed that the polymorphisms in This study recruited participants from two sources, both in Jilin Province, Northeast of China: from the General Hospital of Jilin Chemical Group Corporation and from a survey of the prevalence and risk factors of chronic diseases among adults in Jilin. One hundred and ninety-two (192) Chinese Han subjects were randomly selected from individuals who received routine health examinations at the General Hospital of Jilin Chemical Group Corporation between September 2009 and June 2010. Three hundred and thirty- seven (337) subjects were recruited from a survey conducted in July 2012 on the prevalence and risk factors of chronic diseases among adults in Jilin Province. All study participants accepted general health examination included blood pressure, BMI, and plasma levels of lipids. A total of 529  subjects with an average age of 59 ± 10 years were included in this study. All subjects were unrelated Chinese Han.Dyslipidemia was assessed according to the Guidelines on Prevention and Treatment of dyslipidemia in Chinese Adults : hypertrThe study was approved by the ethics committee of the School of Public Health, Jilin University, and informed consents were provided by all subjects.NCOA3 were chosen from the HapMap database (HapMap Genome Brower release # 24) [2 cut-off of 0.8, tagger pairwise as pairwise methods and MAF cut-off of 10 %. Four tag SNPs  of NCOA3 were chosen. The positions of rs2425955, rs6066394, rs10485463, and rs6094753 are intron 1, intron 1, intron 2, and intron 8 of the NCOA3 gene respectively.NCOA3 gene is located in chromosomal region 20q12. Tag SNPs for se # 24) . In the Genomic DNA was extracted from peripheral blood samples using standard protocol (phenol/chloroform extraction), and the quality and quantity were determined by spectrophotometry.Genotyping was conducted by polymerase chain reaction (PCR) and MALDI-TOF mass spectrometry  using thNCOA3 SNPs and quantitative clinical traits was assessed by covariance analysis. The goodness of fit Chi-square test was used to check if genotype distributions were in HWE. The Chi-square test was used to check if allele frequencies and genotype distributions were significantly different between dyslipidemia group and normal group. The associations between the allele of the four SNPs of NCOA3 and dyslipidemia were evaluated by odds ratios and their 95 % confidence intervals (CI) using Chi-square test. Logistic regression analysis was used to detect associations between genotypes of NCOA3 SNPs and dyslipidemia. When we explored the association using logistic regression without any adjustment, we set hypercholesterolemia, hypertriglyceridemia, low-HDL cholesterolemia, and hyper-LDL cholesterolemia as the dependent variables, and genotypes as independent variable. When we explored the association after adjustment for age and sex, we set hypercholesterolemia, hypertriglyceridemia, low-HDL cholesterolemia, and hyper-LDL cholesterolemia as the dependent variable, genotypes, sex, and age (continuous) as independent variable, and enter as method. The strength of any evident association was explored by calculating odds ratios together with their 95 % CI. Besides, the association between the four NCOA3 SNPs and dyslipidemia in five inheritance models  was analyzed using SNPstats programs [P values for correcting multiple testing  = 0.0025). LD blocks of SNPs were constructed using SNP genotyping data in this study, and estimation of LD of 4 SNPs in NCOA3 (D’ and r2 represent the degree of LD) was analyzed by haploview 4.2 software. The power of this study was evaluated by Power and Sample Size software version 3.1.2 [P-value <0.05 was considered statistically significant.Clinical and biochemical data were expressed as mean ± SD or percentage. One sample Kolmogorov-Smirnov test was applied to evaluate whether TG, TC, LDL, and HDL were in normal distributions. Two variables, TG and HDL, were logarithmically transformed to conform to normality in order to allow covariance analysis. The association between the four programs . To reduon 3.1.2 , 47, and


Boronia, a large and difficult-to-germinate genus. Germination syndromes were highly variable but correlated with broad patterns in seed morphology and phylogenetic relationships between species. Seasonal temperatures influenced the rate and/or magnitude of germination responses in six species, and interacted with fire cues in complex ways. The combined effects of heat shock and smoke ranged from neutral to additive, synergistic, unitive or negative and varied with species, seasonal temperatures and duration of incubation. These responses could not be reliably predicted from the effect of the application of single cues. Based on these findings, fire season and fire intensity are predicted to affect both the magnitude and timing of seedling emergence in wild populations of species with physiological dormancy, with important implications for current fire management practices and for population persistence under climate change.Dormancy and germination requirements determine the timing and magnitude of seedling emergence, with important consequences for seedling survival and growth. Physiological dormancy is the most widespread form of dormancy in flowering plants, yet the seed ecology of species with this dormancy type is poorly understood in fire-prone vegetation. The role of seasonal temperatures as germination cues in these habitats is often overlooked due to a focus on direct fire cues such as heat shock and smoke, and little is known about the combined effects of multiple fire-related cues and environmental cues as these are seldom assessed in combination. We aimed to improve understanding of the germination requirements of species with physiological dormancy in fire-prone floras by investigating germination responses across members of the Rutaceae from south eastern Australia. We used a fully factorial experimental design to quantify the individual and combined effects of heat shock, smoke and seasonal ambient temperatures on germination of freshly dispersed seeds of seven species of  Many plant species in fire-prone regions worldwide rely on recruitment from soil seed banks for population persistence in the face of recurring fires –3. DevelPhysiological dormancy (hereafter referred to as PD) is the most common and phylogenetically widespread form of dormancy in angiosperms, and is overcome by various processes such as stratification and after-ripening . Once doGiven that fire is a frequent and predictable occurrence in many of the world’s major biomes , and thaA further factor hampering our understanding of PD species and fire is a lack of data regarding the combined effects of multiple fire-related cues and environmental cues on their germination. Considerable work conducted in fire-prone regions has demonstrated that germination of many species, predominantly those with physical dormancy, is promoted by heat shock ,24,26–31et al. [et al. [Leucopogon spp. (Ericaceae), and demonstrated a mechanistic link with seasonal germination requirements. A follow-up study by Ooi [Fire season is a relatively understudied component of the fire regime with the potential to impact on recruitment patterns in a diverse range of species . Signifiet al.  found th [et al. ,18 documy by Ooi  found thPrescribed burning for bushfire hazard reduction is already causing regional shifts in peak fire season . While tThe Rutaceae is an important cosmopolitan family and is one of the most significant plant families in the Sydney region of south eastern Australia, comprising a large proportion of rare and nationally threatened species . RutaceaBoronia. The approach we take recognises that, for many species, a germination event comprises two distinct phases: dormancy alleviation and the subsequent stimulation of germination [in situ. Specifically, we asked:We aimed to improve understanding of the seed ecology of Australian Rutaceae, and of fire-prone species with PD more generally, by investigating the role of seasonal ambient temperatures and fire-related cues in the germination of the largest Australia genus, mination ,16,59–61mination ,16,59–61Do fire-related cues such as heat shock and smoke promote germination, and if so, how do they interact with each other?Is there an effect of seasonal ambient temperatures on the germination responses to fire-related cues?How variable are germination syndromes within the genus, and can patterns be explained by differences in seed morphology or phylogenetic relatedness?What are the implications of these germination syndromes for post-fire emergence patterns and current fire management practices?cf. Mediterranean-type climates where dry summers usually restrict germination to the cooler, wetter months.The study was conducted in the Sydney region of south eastern Australia, with the approval of the New South Wales Office of Environment and Heritage (Scientific Licence No. SL101105). The regional climate is temperate with no dry season, according to the Köppen classification . As rainBoronia seeds is ballistic [viz. black seeds and brown seeds) were evident in the B. anemonifolia subsp. anemonifolia (hereafter B. anemonifolia) collection, however, the latter were discarded as they were typically  unfilled with low viability (7.7 ± 7.4%) of filled seeds. Different maturation times between species and logistical constraints meant that the time elapsed between seed collection and commencement of experiments ranged from 5 weeks  to 9 weeks , during which seeds were stored in envelopes under ambient temperatures varying between c. 20–25°C. Seed weights were determined using an electronic balance accurate to 0.00001 grams. Seed fill and viability were assessed via a cut test [We selected study species based on their fecundity, comparable flowering phenology, and our ability to locate large enough populations to gather sufficient seed. The resulting seven species comprise a mixture of rare and common shrubs from fire-prone heaths and woodlands, and represent three different evolutionary lineages within the genus . Mature allistic . Two discut test , wherebycut test .B. ledifolia; 4 replicates of 20 seeds each for B. anemonifolia, B. floribunda, B. fraseri and B. serrulata; 4 replicates of 18 seeds each for B. pinnata, and 3 replicates of 24 seeds each for B. thujona. Heat shock treatments were applied by placing seeds in aluminium foil cups and exposing them to 90°C in a pre-heated oven for 10 minutes. This temperature and duration of heating falls within the range of conditions experienced by seeds in the upper layers of the soil during the passage of fire [The individual and combined effects of heat shock, smoke and seasonal ambient temperatures on the germination of fresh seed were tested in a fully orthogonal laboratory experiment with 12 possible factorial combinations of heat shock , smoke , and seasonal temperature . Seed availability varied between species and enabled replication within treatments as follows: 4 replicates of 25 seeds each for  of fire , and has of fire ,68, incl of fire . Smoke t of fire ,42,69. R of fire , and heaReplicates of seeds were placed on moistened filter paper in 9 cm Petri dishes. Dishes were sealed with plastic wrap to reduce desiccation and then placed inside temperature- and light-controlled incubators set to one of three seasonal temperature regimes  on a 12hπ and was analysed using three-factor, orthogonal generalised linear models (GLMs) with logistic link functions. Models took the form η = β0 + β1 × H + β2 × S + β3 × SeAut + β4 × SeWin + β5 × H · S + β6 × H · SeAut + β7 × H · SeWin + β8 × S · SeAut + β9 × S · SeWin + β10 × H · S · SeAut + β11 × H · S · SeWin where η is the logit proportion of filled seeds germinated, H is the effect of heat shock, S is the effect of smoke treatment, SeAut is the effect of autumn/spring temperature treatment, SeWin is the effect of winter temperature treatment, and β0-β11 are regression coefficients with β0 corresponding to the control treatment at summer temperatures. The proportion of filled seeds germinated is given by π = eη / (1 + eη).Analyses were conducted using R 3.2.2 . The numModels were fitted to the data after six weeks and again after 14 weeks at the conclusion of the experiment. We used the maximum germination response observed across all treatments after six weeks to estimate the proportion of seeds that were non-dormant at dispersal . p-values [Model parameters were estimated using Bayesian Markov Chain Monte Carlo (MCMC) methods with uninformative priors. Sampling was performed in JAGS  via the p-values . Bayesiap-values .B. thujona after 6 weeks’ incubation however, the 3-way interactions between heat shock, smoke and seasonal temperatures had to be dropped from the model to enable convergence. Overdispersion detected in the GLMs for B. thujona after 6 weeks and after 14 weeks, respectively, and in the GLMs for B. floribunda, B. pinnata and B. serrulata after 14 weeks, was effectively addressed by fitting generalised linear mixed models (GLMMs) with an observation-level random effect for Petri Dish, ε, where ε ~ N.Mixing of chains was good except in several datasets with a high incidence of extreme probabilities (i.e. 0% germination in some treatments). In such cases, placing an arbitrary constraint on the linear predictor  substantially improved chain convergence . For B. B. floribunda and B. serrulata, each with c. 50% of seeds non-dormant and able to germinate over a narrow range of conditions. Further incubation up to 14 weeks resulted in only moderate improvements to the maximum germination responses observed for all species after 6 weeks  represented: i) relatively small seeds with an elaiosome and dull, textured surfaces ; ii) relatively small seeds with smooth, shiny surfaces and no elaiosome ; and iii) much larger seeds with an elaiosome and shiny, textured surfaces  Tables . Seed fierrulata .B. anemonifolia was restricted almost entirely to summer temperatures , and occurred up to six times faster at winter and autumn/spring temperatures than at summer temperatures. Germination of B. serrulata in response to smoke treatment was four times faster at cooler temperatures (autumn/spring and winter) than at summer temperatures, and two to four times faster than the combined heat shock plus smoke treatment at cooler temperatures (autumn/spring and winter). Smoke treatment also resulted in two to three times faster germination of B. thujona relative to the combined heat shock and smoke treatment with no consistent effect of seasonal temperature on germination speed. Germination of B. ledifolia and B. pinnata was insufficient to discern patterns in relative germination rates between treatments although winter temperatures consistently delayed the onset of germination relative to warmer temperatures. The time to onset of germination of B. fraseri was the same in response to heat shock and the heat shock plus smoke treatment , however, germination commenced one to two weeks earlier at summer temperatures. The combined heat shock plus smoke treatment promoted three times faster germination at summer temperatures compared with autumn/spring temperatures, and in comparison with the heat shock only treatment at summer temperatures.Time to onset for ock only , Table 5examined , Table 5Seasonal temperatures influenced the timing and magnitude of germination in response to fire cues for the majority of species examined. This highlights the role of seasonal temperatures—not just direct fire cues such as heat shock and smoke—as important drivers of germination in fire-prone regions . In MediBoronia and other genera with PD in fire-prone regions might be expected to exhibit seasonal emergence patterns. The first is where germination is restricted to a particular seasonal temperature range and simply does not occur outside that range . This mechanism is best exemplified by B. anemonifolia where germination of fresh seeds only occurred at summer temperatures (preference). The window within which soils remain moist enough to facilitate seedling emergence and establishment after a given rainfall event is likely to narrow as temperature increases, and soils are expected to dry out much faster in summer than in autumn/spring or winter [B. floribunda and B. serrulata, comparable levels of maximum germination had been reached across all three seasonal temperatures by the end of the experiment  whose above-ground populations may be completely eliminated by a single fire event .The maximum germination response observed for each species was in response to some form of smoke treatment, either as a solitary cue (5 spp.) or in combination with heat shock (2 spp.) , furtherB. fraseri and B. ledifolia, and that it enhanced the speed and magnitude of germination of B. anemonifolia in the presence of smoke  species is widely known, however, there are relatively few reports of positive responses to heat shock in species with PD e.g. some Apiaceae , Ericaceof smoke . As an iperature . The degosystems ,31,67,88ervation .B. fraseri and B. ledifolia, it may be that the testa is restricting radicle growth and embryo enlargement, and that heat shock weakens the structural integrity of the testa and lowers its resistance to radicle penetration. Reports of positive responses to nicking or removing sections of testa in other Australian Rutaceae are consistent with this interpretation [In physically dormant species, heat shock is a dormancy-breaking mechanism whereby exposure to extreme temperatures breaks an impermeable seed coat which otherwise prevents imbibition and germination. In PD species with permeable seed coats, however, the mechanism by which heat shock promotes germination is unknown. For species with larger seeds and thicker testas, such as retation –92.The limited germination responses observed for several species are attributable to high levels of primary dormancy which was not overcome during the study, rather than to application of inappropriate germination cues. These species require some form of seasonal stratification, after-ripening and/or other biological process during burial before the majority of seeds will lose dormancy and their responsiveness to germination cues such as heat shock, smoke and seasonal temperatures can be adequately determined ,60,73. TB. pinnata, where overall responses were too low to elucidate its germination requirements, the range of observed responses could be broadly characterised by three main germination syndromes: 1) germination is greatest in response to a combination of heat shock and smoke, and is entirely restricted to summer temperatures (B. anemonifolia); 2) germination is greatest in response to smoke and either a) cooler seasonal temperatures promote faster germination (B. floribunda and B. serrulata), or b) there is no apparent effect of seasonal temperatures (B. thujona); and 3) heat shock is essential for germination and warmer seasonal temperatures promote the greatest and fastest responses (B. fraseri and B. ledifolia). Notably, these species groupings/syndromes are consistent with the three broad patterns in seed morphology identified in the study species (B. pinnata); and section Valvatae (syndrome 3 species). Hence, patterns in seed morphology and/or interspecific phylogenetic relationships could be useful predictors of germination syndromes in hitherto unstudied members of the genus and family, as well as in other plant families with poorly known or highly variable germination requirements. Recognising such patterns and relationships between candidate taxa a priori, and explicitly incorporating them into the design of future comparative studies of seed ecology, could vastly improve our ability to identify important functional groups based on shared responses [Germination responses were highly variable between the study species even though they are closely related congeners with comparable habitat requirements, including several taxa that co-occur. Aside from  species , which cesponses , and proThe evidence for seasonal germination requirements in the Rutaceae presented in this study, together with reports of seasonal emergence patterns in wide variety of PD taxa from fire-prone regions around the world including south eastern Australia , south wCurrent fire management practices for biodiversity conservation are predicated almost exclusively on critical fire-return intervals and the avoidance of too frequent or infrequent fire for sensitive species . This stS1 Dataset(XLSX)Click here for additional data file.


DTNA and FAM136A genes have been identified in familial Meniere’s disease, and this genomic strategy will facilitate the discovery of the genetic basis of familial vestibular disorders.The two most common vestibular disorders are motion sickness and vestibular migraine, affecting 30 and 1–2 % of the population respectively. Both are related to migraine and show a familial trend. Bilateral vestibular hypofunction is a rare condition, and some of patients also present cerebellar ataxia and neuropathy. We present recent advances in the genetics of vestibular disorders with familial aggregation. The clinical heterogeneity observed in different relatives of the same families suggests a variable penetrance and the interaction of several genes in each family. Some Mendelian sensorineural hearing loss also exhibits vestibular dysfunction, including DFNA9, DFNA11, DFNA15 and DFNA28. However, the most relevant finding during the past years is the familial clustering observed in Meniere’s disease. By using whole exome sequencing and combining bioinformatics tools, novel variants in  Vestibular disorders (VDs) are considered a group of diseases leading to transient or permanent loss of vestibular function. Regardless of their clinical heterogeneity, several families with vestibular symptoms affecting different relatives have been described. However, the contribution of genetic variations, either common or rare variants, to develop a specific vestibular disease is largely unknown. Some of the reasons for this missing heritability in VDs are the limitations in clinical phenotyping, the overlapping symptoms among different VDs and the clinical heterogeneity observed in families with variable penetrance Table . AccordiIn this review, we will update the evidences to support the genetic contribution in some of the vestibular disorders with familial aggregation.The two most common vestibular disorders are motion sickness and vestibular migraine, affecting 30 and 1–2 % of the population, respectively. Both are complex, multifactorial disorders with a strong genetic contribution. Table PVRL3, GPD2, ACO1, AUTS2, GPR26, UBE2E2, CBLN4, BLOC1S5, LINGO2 and CPNE4. These genes involve a large variety of functions such as ocular and brain development, insulin resistance, otolith biogenesis or iron homeostasis  that segregated with hearing loss. Hearing impairment in the present family had an early childhood onset and progressed, from mild to severe, before the second decade. Impaired hearing was accompanied by vestibular areflexia and in one of the subjects with mild renal dysfunction [The mutation was identified in a consanguineous family diagnosed with autosomal recessive SNHL. A homozygous region of 47.4 Mb on chromosome 6p21.1–q15 was shared by the two affected siblings. This region contains 247 genes including the known deafness gene function .SLC26A4 gene, which encodes pendrin, an anion exchanger expressed in the endolymphatic sac, in different epithelial cells of the cochlea and vestibular labyrinth, as well as in the kidney and thyroid gland. Mutations in this gene cause DFNB4 and Pendred’s syndrome, both of which are related to EVAS [SLC26A4 gene using direct sequencing observing a total of 23 pathogenic mutations, 13 of which were unique [SLC26A4 mutations with wider aqueducts at the midpoint and more severe hearing loss [SLC26A4 gene mutations and the nature, degree, and progression of hearing loss [SLC26A4 gene therapy targeted to the endolymphatic sac restored hearing and balance in SLC26A4 mutant mice [Enlarged vestibular aqueduct syndrome (EVAS) is the most common form of inner ear malformation caused by a dilated vestibular aqueduct. It has been associated with a mutation in the  to EVAS . Some ste unique , while oing loss . Neverthing loss , 45 did ing loss . SLC26A4ant mice .Ménière’s disease (MD) is a clinical syndrome that affects the inner ear, and it is characterized by episodes of spontaneous vertigo, usually associated with unilateral fluctuating SNHL, tinnitus and aural fullness . The preMICA, TLR10 and NFKB1 influence the hearing outcome in sporadic MD [Several comorbidities are associated with MD, including migraine, obesity, psoriasis and systemic autoimmune disorders . Althougradic MD –56.AQP2 and AQP4 genes [AQP3 was found in 11 of 34 patients with MD [The hypothesis of a channelopathy has supported aquaporins (AQP) as molecular targets in MD. These proteins are water channels, the function of which is to transport water and solutes along the osmotic gradient, and four of them (AQP 1–4) are expressed in the human inner ear . Water pP4 genes , and a h with MD .KCNE1 and KCNE3 in Japanese population, produced contrasting results, and it could not be replicated [Moreover, the association with allelic variants of two voltage-gated potassium channel genes, plicated , 62.ADD1 gene, encoding a cytoskeletal protein, which interacts with the Na+, K+, -ATPase transporter, leading to its faster activity [Finally, in a case–control study, the predisposition to develop MD was linked to a common variant in the activity ; howeveractivity .DTNA and FAM136A genes in an autosomal dominant Spanish family with MD segregating the phenotype in three women in consecutive generations. DTNA encodes alpha-dystrobrevin, a dystrophin-associated protein which interacts with transmembrane proteins and actin in the basolateral membranes of epithelial cells, and it is associated with tight junction reorganization [DTNA gene is a rare splice-site acceptor skipping in exon 21. FAM136A is a mitochondrial protein of unknown function, and the mutation chr2:70527974C > T leads to a novel stop codon which shortens the protein product. Both FAM136A and DTNA proteins are expressed in the neurosensorial epithelium of the crista ampullaris of the rat. Further studies are needed to investigate DTNA and FAM136A genes in sporadic MD.Familial MD (FMD) should be considered if at least two family members (first or second degree) fulfill all the criteria of definite or probable MD . Most fanization . The ideThe improvement in phenotyping families with vestibular symptoms combined with exome sequencing will facilitate the identification of rare variants and genes involved in familial vestibular disorders.


Dengue virus (DENV) infection causes viral haemorrhagic fever that is characterized by extensive activation of the immune system. The aim of this study is to investigate the kinetics of the transcriptome signature changes during the course of disease and the association of genes in these signatures with clinical parameters.Sequential whole blood samples from DENV infected patients in Jakarta were profiled using affymetrix microarrays, which were analysed using principal component analysis, limma, gene set analysis, and weighted gene co-expression network analysis. We show that time since onset of disease, but not diagnosis, has a large impact on the blood transcriptome of patients with non-severe dengue. Clinical diagnosis (according to the WHO classification) does not associate with differential gene expression. Network analysis however, indicated that the clinical markers platelet count, fibrinogen, albumin, IV fluid distributed per day and liver enzymes SGOT and SGPT strongly correlate with gene modules that are enriched for genes involved in the immune response. Overall, we see a shift in the transcriptome from immunity and inflammation to repair and recovery during the course of a DENV infection.Time since onset of disease associates with the shift in transcriptome signatures from immunity and inflammation to cell cycle and repair mechanisms in patients with non-severe dengue. The strong association of time with blood transcriptome changes hampers both the discovery as well as the potential application of biomarkers in dengue. However, we identified gene expression modules that associate with key clinical parameters of dengue that reflect the systemic activity of disease during the course of infection. The expression level of these gene modules may support earlier detection of disease progression as well as clinical management of dengue. An acute dengue virus infection usually starts with a febrile disease phase that can progress to severe disease around the time fever abates (defervescence). Here we study dengue patients that were included very early after the onset of disease and carefully monitored in a longitudinal cohort study. Our results show that time after the onset of disease has a major impact on the transcriptome profile of patients with dengue, which is confirmed by comparing our results with three other dengue studies that included patients at different disease stages. There is a gradual shift in transcriptome profile from an ‘immunity & inflammation’- to a ‘repair & recovery’ phenotype. Furthermore, the expression of gene network modules could be linked to specific clinical parameters of dengue virus infection. Platelet counts and the levels of fibrinogen and albumin are shown to be good markers for the activity and timing of the disease, reflecting relevant biological processes in the patient. In contrast, conventional WHO classification systems did not show any association with any of the 25 gene modules identified and only yielded a few differentially expressed genes. The expression level of gene modules specific for certain biological processes in dengue support earlier detection of progression to severe disease and may improve clinical management. Dengue virus (DENV) infection is endemic in South-East Asia and has a large impact on society, both in terms of burden of disease as in economic costs . DENV beTo investigate the underlying biological processes involved in DENV pathogenesis, several studies have applied transcriptome profiling to cohorts of dengue patients –5. Some In this study, we investigated the biology of dengue pathogenesis over time in a cohort of dengue patients from Jakarta, Indonesia, where dengue is endemic and incidence increases during the rainy season . Using aThe research ethics committee of the Faculty of Medicine, University of Indonesia in Jakarta, Indonesia, approved this study. Patients were included after written informed consent. If patients were younger than 18 years written informed consent was obtained from the parent and/or legal guardian. Data and samples were anonymized with a study number.Between March and June 2010 all patients ≥ 14 years of age with a fever onset ≤ 48 hours before presentation and a clinical suspicion of dengue were recruited in community health centers (‘puskesmas’) in Jakarta, Indonesia. Blood was drawn and a NS1 antigen and IgM/IgG antibody rapid test  was performed. If tested positive for NS1 and/or IgM, patients were admitted to the Cipto Mangunkusomo Hospital in Jakarta for seven days. The admission was only dependent on a positive outcome from the rapid test and not based on clinical disease severity. Clinical data were recorded daily with a standard case report form. Blood samples were collected on every other day (including the day of admission), both for clinical laboratory tests and for transcriptome profiling. At day 3, 5 and 7 of admission ultrasound examination was performed to investigate whether patients suffered from ascites and/or pleural effusion. In this study, day 0 refers to the day of admission unless stated otherwise. According to the inclusion criteria, onset of disease was less than 48 hours before admission. Patients were classified according to the 2009 WHO dengue case classification [All diagnostic assays were performed at the Department of Microbiology, Faculty of Medicine, University of Indonesia, Jakarta. The diagnosis of the rapid test was confirmed with detection of NS1 antigen (Panbio) and/or IgM antibodies (Focus diagnostics) and/or a positive RT-PCR (see next section). IgM and IgG antibodies were determined in all collected sequential samples. Patients with a positive IgG in the sample from day 3–4 after admission were considered as secondary DENV infection, while patients with a negative IgG in this sample were considered as a primary DENV infection. In two patients viral RNA could not be detected, but they were included, because these patients were NS1 and IgM positive.Reverse transcriptase PCR (RT-PCR) was performed to determine the infecting serotype according to the method described in Lanciotti et al . RNA was2, 3.2 μl 10mM dNTPs, 0.4 μl Super Script II RTase (Invitrogen), 0.15μl 5 U Platinum Taq-polymerase (Invitrogen), 0.8 μl 10 μM D1 primer, 0.8 μl 10 μM D2 primer, 8 μl RNA. The RT step consisted of 53°C for 30 minutes and denaturation at 95°C for 5 minutes. This was followed by 30 cycles of denaturation at 95°C for 45 seconds, annealing at 60°C for 30 seconds, and extension at 72°C for 90 seconds. The RT-PCR was concluded with a single cycle extension at 72°C for 7 minutes.A semi-nested RT-PCR was performed for serotyping. The first amplification reaction had a reaction volume of 40 μl, consisting of 4 μl 10x PCR buffer with 1.5 mM MgCl2, 2.0 μl 10 mM dNTPs, 0.15μl 5 U/μl Platinum Taq-polymerase (Invitrogen), 1μl of each D1, TS1, TS2, TS3, TS4 primer (10 μM), 2μl of the product from the first PCR. PCR 2 was performed with initial denaturation at 95°C for 5 minutes, followed by 35 cycles of denaturation at 95°C for 45 seconds, annealing at 60°C for 30 seconds, extension at 72°C for 60 seconds and one final single cycle extension at 72°C for 7 minutes.The second PCR amplification had a reaction volume of 25μl, consisting of 2.5μl 10x PCR buffer with 1.5 mM MgClAfter amplification, PCR products were analysed by electrophoresis. Eight μl of PCR product was loaded on 2% agarose gel in TAE buffer and stained with Ethidium Bromide. The product was visualized with UV light.Blood was collected in Tempus Blood RNA tubes . Total RNA was isolated from whole blood using the Tempus Spin RNA isolation kit . Globin RNA was removed from total RNA preparations using the Globiclear kit (Life Technologies). RNA concentrations and OD 260/280 ratios were measured with the NanoDrop ND-1000 UV-VIS spectrophotometer . Assessment of RNA quality and purity was performed with the RNA 6000 Nano assay on the Agilent 2100 Bioanalyzer . RNA (100 ng) was labelled using the MessageAmp Premier RNA Amplication kit (Applied Biosystems) and hybridized to Human Genome U133 plus 2 gene chips (Affymetrix), according to the manufacturer’s recommendations. Image analysis was performed using GeneChip Operating Software (Affymetrix). Microarray Suite version 5.0 software (Affymetrix) was used to generate .dat and .cel files for each experiment. The raw data has been deposited in the arrayExpress database under access number E-MTAB-3162.Analysis of the arrays was performed using R 2.15/Bioconductor ,12. GeneWe applied weighted gene correlation network analysis (WGCNA) using the available R libraries . This meDuring the 2010 dengue outbreak in Jakarta, Indonesia, 157 patients were recruited into this study. Of these patients, 52 were admitted to the hospital with a positive dengue IgM and/or NS1 rapid test. All four dengue serotypes were circulating during this outbreak. Out of the 52 admitted patients, 26 patients were selected for blood transcriptome analysis based on the completeness of clinical data , and the availability of samples from day 0 and day 4 of admission and a confirmed laboratory diagnosis of the rapid test for DENV infection see . FifteenA maximum of three tempus tubes from each patient was included in this analysis. We included a total of 61 tempus tubes from 26 patients. 20 tempus tubes were collected at day 0 of admission  and 20 at day 4 ; these time points were therefore analysed in detail. An overview of the timepoints and disease categories is provided in To obtain a global overview of the dengue transcriptome profiles, we applied principal component analysis (PCA) . This noTo obtain insight into the transcriptional changes that are associated with disease severity and time since admission, we performed differential gene expression analysis and gene set analysis in dengue patient and control transcriptomes (FDR ≤ 0.05 and fold change ≥ 2). We used the 2009 WHO dengue case classification system to group patients and excluded the single case with severe disease from gene expression analysis. Combining data from all time points revealed that 161 genes were up- and 73 genes were downregulated in WS- patients compared to healthy controls . In WS+ Over the past few years, several studies have examined the transcriptional profile of dengue infections. Three cross-sectional studies  ,7,18 werThe type I interferon pathway is known to be differentially expressed in DENV infection . We inveTo functionally annotate the differences in gene expression, we performed gene set analysis using the Reactome curated pathway database . ApplyinIn addition to severity signatures, we investigated the transcriptional changes related to time since admission in our longitudinal cohort. By comparing day 0 dengue samples to healthy control samples, we observed an up-regulation of pathways related to innate immunity and cytokine signalling . When weNext, we investigated the association between the identified gene modules and clinical parameters. To this end, we used weighted gene correlation network analysis (WGCNA) that organizes genes into 25 modules that are subsequently correlated to 18 clinical parameters . This anIn contrast to the above-mentioned clinical parameters, the 1997 WHO dengue case classification as well as the 2009 WHO dengue case classification showed no significant association with any of the gene modules, suggesting that these classifications do not reflect the underlying biological processes, or that there are no differences in the underlying biological processes. The non-specific warning signs ‘abdominal pain’ and ‘vomiting’ showed no statistical significant associations, which is in line with the generic nature of these symptoms. In contrast, DENV-specific warning signs including ‘epistaxis’ and ‘gum bleeding’ did correlate with the gene modules B-antiquewhite4, O-brown4, M-salmon4 and W-sienna3. Enriched GO terms for genes in the O-brown4 module are “cell organelles”, such as mitochondrion and cytoplasm. Module W-sienna3 has wound healing and coagulation as enriched GO terms and module M-salmon4 is related to catabolic processes. Ascites, which is a typical sign of plasma leakage, is significantly associated with modules G-palevioletred3 and P-yellowgreen. These two gene modules were not associated with time, suggesting that this is a specific biological pathway. All in all, network analysis showed that the WHO classifications couldn’t be related to specific gene modules; however, there are many significant correlations between gene modules and dengue-specific clinical parameters.In order to identify genes that may serve as a marker of immune activation in the early phase of disease, we focused on modules with a strong negative correlation with time after admission. These modules contain genes that are upregulated specifically in the earliest phase of disease that could represent biomarkers for disease progression, including modules M-salmon4, R-cyan, T-lightyellow, U-orange, and X-darkorange. By correlating genes contained in these modules with clinical parameters that mark disease severity, genes associated with can be identified. Five genes in the module T-lightyellow showed a significant direct association with the platelet count , includiIn this study, we examined DENV infected patients with uncomplicated disease using transcriptome profiling. By using a variety of analysis techniques, we show that time since admission, which is a proxy for time since onset of disease, is the most important determinant of the blood transcriptome profile changes in DENV infected patients. Regardless of the analysis techniques used, we did not observe differences in blood transcriptional profiles between WS- and WS+ patients. Conversely, the clinical parameters platelet count, albumin, fibrinogen, SGOT, SGPT and volume of IV fluid administered showed a highly significant association with specific gene modules. Gene module expression may serve as a novel marker to monitor the biological processes involved in dengue pathogenesis.A recurring theme in our results is that time after the onset of disease is the main determinant of transcriptome profile changes in DENV infected patients. This observation is in line with the results reported by Sun et al., although PBMCs were used in that study . MoreoveIn contrast to the strong signal related to time since onset of disease, there was no detectable transcriptional difference between WS- and WS+ patients. Earlier studies showed that gene expression patterns from patients with DSS did segregate from those of DF and DHF patients ,18. ThisThe clinical parameter platelet count has frequently been associated with DENV infection  and was The occurrence of plasma leakage in dengue patients has been extensively documented. We observe that markers of plasma leakage, including the quantity of IV-fluid supplied and the levels of albumin, were both associated with the same gene modules as platelet count. Plasma leakage tends to correlate inversely with the platelet count  and it hIn severe dengue, dysregulation of coagulation is frequently observed. Fibrinogen is consumed after thrombin generation and decreased levels have been detected in severe dengue . The strIn our study, gene modules were enriched for metabolic and catabolic processes, kinase activity and organelles, such as mitochondria. Loke et al., also showed that many upregulated genes in the acute phase were involved in metabolic processes and shared between acute DF, DHF and DSS samples , suggestOur results indicate involvement of the liver in dengue pathogenesis. Especially the gene modules involved in inflammation and immunity correlated with the liver enzymes SGOT and SGPT, suggesting that dengue induced inflammation affects the liver. Moreover, ten individual genes showed a significant association with the liver enzyme SGOT. The liver may be affected directly by viral replication or indirectly by cytokines and immune cells. One surprising finding from our study is differential regulation of several genes that play a role in diabetes. The genes adiponectin receptor 1, sestrin 3, KCNJ15 and G-protein coupled receptor 27 have all been described to play a role in insulin resistance, decreased insulin secretion and impaired blood glucose homeostasis ,25,52. IFuture studies should aim to carefully track time since the start of infection, as time is the main source of variance in transcriptomes from dengue patients. Since the transcriptome effects in time are larger than potential transcriptome effects between severity classes, a synchronous longitudinal cohort is an absolute requirement for any biomarker study. Furthermore, individual symptoms and markers appear to better reflect the biological processes underlying dengue pathogenesis. Classification on the basis of gene signatures related to specific symptoms, rather than overall diagnosis, may enable earlier identification of patient subgroups that are at increased risk of developing severe dengue, and to a better understanding of dengue disease pathogenesis.S1 Checklist(DOC)Click here for additional data file.S1 InformationFor every contrast, the probeset ensemble genome identifier, the average expression, the log fold change in expression, and the adjusted p value  are given.(XLSX)Click here for additional data file.S2 InformationFor every contrast, the proportion active genes and significance  are given for every pathway. In every case, pathway differential regulation is assessed for up-regulated genes, down-regulated genes, and for up- or down-regulated (‘mixed’) genes.(XLSX)Click here for additional data file.S3 Information(DOCX)Click here for additional data file.S1 TableWS- and WS+ indicate non-severe dengue without and with warning signs, respectively.(DOCX)Click here for additional data file.


Lactobacillus. Data from in vitro studies suggested that lactic acid suppressed TNFα via the HNF1α/C5 pathway. In conclusion, gut microbes and their hosts respond to excess energy influx as an organic whole, severe steatosis and related tolerance of goose liver may be partially attributable to gut microbiotic products and suppressed complement system, and lactic acid from gut microbiota participates in the suppression of hepatic TNFα/inflammation through the HNF1α/C5 pathway.Goose can develop severe hepatic steatosis without overt injury, thus it may serve as a unique model for uncovering how steatosis-related injury is prevented. To identify the markedly prosteatotic and protective mechanisms, we performed an integrated analysis of liver transcriptomes and gut microbial metagenomes using samples collected from overfed and normally-fed geese at different time points. The results indicated that the fatty liver transcriptome, initially featuring a ‘metabolism’ pathway, was later joined by ‘cell growth and death’ and ‘immune diseases’ pathways. Gut microbiota played a synergistic role in the liver response as microbial and hepatic genes affected by overfeeding shared multiple pathways. Remarkably, the complement system, an inflammatory component, was comprehensively suppressed in fatty liver, which was partially due to increased blood lactic acid from enriched  Finally, hepatic injury due to oxidative and inflammatory stresses as well as enhanced lipid peroxidation occurs when the adaptive mechanism is overwhelmedFatty liver disease contains a sequence of clinical pathological syndromes from simple steatosis to steatohepatitis, fibrosis, and even cirrhosis. It can be divided into alcoholic fatty liver disease (AFLD) and non-alcoholic fatty liver disease (NAFLD) depending on alcohol intakefoie gras) production within 2–3 weeks of overfeeding. In overfed geese, liver weight can increase from approximately 100 g to approximately 800 g in 2 weeks due to a large amount of lipid accumulation101213de novo synthesized endogenous lipids, as well as an absence of leptin gene homologs due to positive selectionGoose, as the descendant of a migratory bird, has an excellent capacity to deposit fat in the liver. In the goose industry, this capacity has been utilized for fatty liver , and that gut microbiota played a key role in these mechanisms. To test this, we performed an integrated analysis on the liver transcriptome and gut microbial metagenome in the overfed vs. normally fed geese. An P < 0.05), while the levels of low density lipoprotein cholesterol (LDL-C) and fasting blood glucose were not significantly different between the two groups of geese (It is well known that a short period of overfeeding (2–3 weeks) can lead to dramatic increases in both body weight (BW) and liver weight (LW), as well as induce severe hepatic steatosis in geese10of geese . The eleof geese .de novo assembly of the clean reads were matched to 13,032 and 13,536 unigenes, respectively, from chicken and duck genome databases, or a total of 13,973 annotated unigenes without redundancy  and control groups (C) . A totalAs miRNAs regulate gene expression, we tested whether liver miRNAs responded to overfeeding in a way similar to the liver transcriptome. For this purpose, small RNA libraries constructed from 21 liver samples were deep sequenced . After dP-values are shown in vice versa  were identified between the C and T groups. A total of 30 (17 upregulated), 48 (36 upregulated) and 151 DEMs (114 upregulated) were identified at day 7, 14 and 19 of overfeeding, respectively . Five DEce versa . Pathwayce versa . This coFirmicutes was the most abundant phylum to which 36.60% of sequences were assigned, followed by Proteobacteria (27.24%), Bacteroidetes (9.78%), Cyanobacteria (6.34%), Actinobacteria (6.06%), Fusobacteria (4.07%), Spirochaetes (2.62%), Verrucomicrobia (1.93%), Acidobacteria (1.21%), Deferribacteres (0.63%) and the other phyla (3.52%). Firmicutes more densely inhabited the duodena, jejuna and ilea than caeca in the overfed geese, and its abundance was influenced by overfeeding. In regard to Bacteroidetes, the third most abundant phylum, it had a relatively stable occupancy in duodena and jejuna, but appeared to be negatively affected in ilea and positively affected in caeca by overfeeding. Actinobacteria, Verrucomicrobia and Acidobacteria all accounted for certain proportions of microbiota in duodena, jejuna and ilea, and they appeared to be negatively affected by overfeeding in duodena. Cyanobacteria and Deferribacteres had the most remarkable changes as a result of overfeeding. Although sequences assigned to Cyanobacteria only made up 1–2% of sequences in the control geese, it composed a much higher proportion of sequences in duodena, jejuna and ilea of the overfed geese . In contrast, 8.70% sequences were assigned to Deferribacteres in the caeca of the control geese, but less than 1% sequences were assigned to Deferribacteres in overfed geese. Moreover, the ratios of Firmicutes/Bacteroidetes varied with different intestinal segments, i.e., the ratios from the duodenum, jejunum and ileum were much larger than those from the caecum, especially in the overfed geese , Desulfovibrio, Gallibacterium, Zea and Bradyrhizobium were the main genera from the Proteobacteria phylum. Detailed information of the main genera are shown in OTUs were also clustered at the genus level for a deeper insight into the changes in the composition of gut microbiota. In total, 739 taxonomic groups were identified . AccordiP < 0.05) affected by overfeeding in at least one intestinal segment. For instance, 5 genera, Lactobacillus, Enterococcus, Sulfobacillus, Pasteurella and Halomonas, significantly increased in abundance in the duodena of the overfed versus control geese, while 6 genera, Staphylococcus, Sphingobacteriaceae/g__(genus unassigned), Nocardioides, Bacillus, Synergistes and Mucispirillum, decreased in abundance. Remarkably, the abundance of Lactobacillus and Enterococcus increased in all intestinal segments of the overfed versus control geese, whereas the abundance of Mucispirillum decreased. Moreover, the abundance of some bacteria varied with different intestinal segments. Typically, Geobacillus more densely inhabited the jejunum than other intestinal segments; in contrast, Bacillus, Bradyrhizobium and Clostridium less densely inhabited the duodenum, ileum, and cecum, respectively.After normalization, the relative abundance of a variety of genera and species were calculated and compared between the C and T groups at day 19 of overfeeding . In totastaphylococcus aureus infection, and carbohydrate digestion and absorption. Secondly, the synergetic effect of gut microbes varied with different intestinal segments. For example, the microbes in the duodenum appeared to be more closely related to ‘metabolism’ pathways than those in other intestinal segments as the microbes in the duodenum shared more signaling pathways with the liver transcriptome than those in other intestinal segments. Thirdly, a third-tier KEGG pathway analysis identified some gut microbes with known functions that could contribute to the changes in the liver transcriptome landscape  increased in the overfed geese. The increase in plasma butyric acid could be due to the increased amount of Butyricicoccus in the gut as previous study indicates that Butyricicoccus pullicaecorum is a butyrate producerButyricicoccus increased in abundance in the jejuna of the overfed geese (As generation of short chain fatty acids (SCFA) is a function of microorganism, we determined the levels of SCFA in the plasma of the overfed vs normally-fed geese at day 19 of overfeeding . Data shed geese . As butyC3, C4 and C5) in the livers at day 19 of overfeeding. Consistent with transcriptome analyses, they were all suppressed in goose fatty liver  suppressed in goose primary hepatocytes treated with 5 mM and 8 mM lactic acid versus control cells  in the liver was first determined by quantitative PCR and Western immunoblot analyses. Data showed that the suppression of C5 at both mRNA and protein levels was associated with the suppression of TNFα in goose fatty liver vs. normal liver , followed by prediction of HNF1α as a potential transcription factor of goose C5 . Quantitative PCR analysis indicated that HNF1α siRNA successfully reduced the expression of HNF1α by about 70% compared to NC siRNA treatment  or siRNA targeted to reatment . The redon of C5 . The resNAFLD presents a great challenge to public health around the world. Goose is a unique animal model with the discovery of a hepatic protective mechanism. In this study, we gained insight into the mechanism underlying overfeeding-induced goose fatty liver by integrating liver transcriptome and gut microbial metagenome analyses.Gpi, Pdh, Cs, Acly, Acc, Fasn, Scd and Dgat2, the key enzymes involved in fatty acid synthesis) and downregulated DEGs  retained the same expression pattern throughout the overfeeding period. During later stages of overfeeding, the ‘cell growth and death’ and the ‘immune diseases’ pathways jointly shaped the liver transcriptome landscape. When de novo synthesis of lipids surpassed the capacity of initial hepatocytes , hepatocyte enlargement or proliferation occurred to allow for more fat storage, which involved the ‘cell growth and death’ pathway , Proteobacteria (27.24%), and Bacteroidetes (9.78%) were the most abundant phyla in goose gut microbiota, and the abundance of Firmicutes was influenced by overfeeding and varied with different intestinal fragments. Although the increase of Proteobacteria is associated with the progression of NAFLD (inflammation and fibrosis) in human and mouse probably through production of endogenous ethanolProteobacteria was not an important player in the development of goose fatty liver as the average abundance of Proteobacteria were barely different between the control and overfeeding groups of geese (Firmicutes and Bacteroidetes can both produce SCFA through fermentation using high fat diets (for Firmicutes) or high plant fibers (for Bacteroidetes)Firmicutes was likely the primary producer of SCFAs promoting goose fatty liver, especially at later stages of overfeeding, as its abundance was increased. Moreover, recent studies showed that the ratio of Firmicutes/Bacteroidetes was associated with mammalian obesity, where NAFLD may occur. For example, Schwiertz et al. reported a decrease of this ratio in the gut of obese peopleet al. observed an increase of this ratio in the gut of obese mice and obese humansCyanobacteria, the microbes more densely inhabited the duodena, jejuna and ilea of overfed geese than control geese. Cyanobacteria may promote goose fatty liver via its products, cyanotoxins, as it is known that some microbial toxins, like tunicamycin, can induce fatty liver. In addition, gut microbiota may contribute to the regulation of ‘lipid metabolism’, ‘amino acid metabolism’, and ‘immune diseases’ pathways in goose fatty liver, as some pathways revealed by enriched microbial genes were shared by liver DEGs.In regard to gut microbiota, data indicated that of geese . This isLactobacillus, Akkermansia and Bifidobacterium increased in abundance, but Clostridium decreased in the overfed versus control geese. It is known that Lactobacillus is involved in carbohydrate metabolismLactobacillus also plays a protective role in the development of fatty liver2425Lactobacillus was indeed involved in the same pathways. We also demonstrated the increase of Lactobacillus contributed to suppression of the complement system in goose fatty liver via its metabolite, lactic acid, as blood lactic acid was significantly higher in the overfed geese than the control geese and that C5 was suppressed in the goose primary hepatocytes treated with 5 mM and 8 mM lactic acid compared to a control. Moreover, Akkermansia is associated with inflammation in fat tissues of patients with type 2 diabetesAkkermansia contributed to the suppression of the immune system pathway in goose fatty liver. Lastly, the decrease of Clostridium could reduce the risk of alcohol-induced steatohepatitis as it has been shown that Clostridium can produce alcohol in an animal’s intestineIn this study, we also noticed that Firmicutes) contributed to shaping the landscape via the gut-liver axis. The enriched phyla/genera varied in different intestinal segments, which is usually neglected in human studies due to limitations on sample collection. Remarkably, the complement system was suppressed in goose fatty liver, at least partially, due to increased blood lactic acid produced by the enriched Lactobacillus. This study thus provides an insight into goose liver capacity for and tolerance to severe hepatic steatosis.In conclusion, goose, like many other animals, is a complex system in which its symbiotic microbes coordinately respond to external stimuli, such as overfeeding. When geese are overfed, the liver transcriptome landscape gradually shifted from being characterized by the metabolism pathways to one characterized by more pathways including the ‘cell growth and death’ pathway and the ‘immune diseases’ pathway, in addition to the ‘metabolism’ pathways. Gut microbiota  of the Yangzhou University Animal Experiments Ethics Committee with permission number SYXK(Su) IACUC 2012–0029, and carried out in accordance with the approved guidelines. All efforts were made to minimize the suffering of the animals. The movement of birds was not restricted before the age of 60 days, but all the birds were restricted as they were moved to cages for the period of adaptation and overfeeding. The experimental geese were killed with an electrolethaler before harvesting their liver samples and intestinal contents. For isolation of goose primary hepatocytes, the embryos at 23 days of hatch were decapitated with a pair of scissors before harvesting their livers.A total of 42 healthy 65-day-old Landes geese were purchased from Rui Nong Farm  and randomly divided into a control group and an overfeeding group (or treatment group) . The geese were raised with a homemade feed before 65 days old . A 5-dayThe mRNA sequencing was performed as previously described with minor modificationsde novo assembly of transcripts by Trinity softwareGallus gallus, Galgal4 version) and duck  genomes retrieved from the following website: https://www.ensembl.org using NCBI Blast (NCBI Blast + v2.2.26), respectively. The mapping to the duck genome was a supplement to that to the chicken genome. The mapped reads of each gene were calculated and presented as Reads Per Kb per Million reads (RPKM)http://bioconductor.org/packages/release/bioc/html/DESeq.html). Genes with max RPKM value >2, fold change of treatment over control >2 or < 0.5, and P-value < 0.05 were assigned as differential expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) Automatic Annotation Server  was used to perform signaling pathway analysis.For mRNA analysis, the raw reads obtained from sequencing were filtered using Fast QC software. The clean reads were then used for the Bombyx mori/Bmo, Bos Taurus/Bta, Drosophila pseudoobscur/Dps, Gallus gallus/Gga, Homo sapiens/Has, Mus musculus/Mmu, Ornithorhynchus anatinus/Oan, Rattus norvegicus/Rno, Taeniopygia guttata/Tgu, and Zea mays/Zm) to identify goose miRNA homologs. The reads of miRNAs were calculated and presented as reads per million reads . To determine differential expressed miRNAs (DEMs), only the miRNAs with at least two RPM values >1 were used. The P-values were calculated between the overfeeding group and the control group using a two-tail t-test. The miRNAs with both fold change of the overfeeding group over the control group >1.5 or < 2/3 and P-value < 0.05 were considered DEMs. Target genes of the identified DEMs were predicted using miRanda with the TargetScan principlevice versa. KEGG Automatic Annotation Server  was used to perform signaling pathway analysis.The small RNA sequencing and miRNA analysis was performed as previously described with minor modificationsThe Metagenome sequencing and analysis was performed as previously described with minor modificationsThe primers  and conditions for PCR and amplicon purification were performed according to the protocols as previously describedhttp://www.genome.jp/tools/kaas/) was used to perform signaling pathway analysis.To gain the abundance of each taxon for gut microbes, the trimmed sequences were compared to the RDP database with the classification option ‘best hit’. The cutoffs of e-value, sequence identity, and the minimum alignment length were set at 8, 97%, and 120 bp, respectively. The abundance of gut microbes from each sample was calculated at family level, which was done by MGRAST. The abundance at genus level was transformed by log2 and normalized as previously describedPlasma samples obtained from the overfed geese and normally fed geese at day 7 and 14 of overfeeding were used for determination of plasma lactic acid, 6 each group). The concentration of lactic acid was measured with a Lactic Acid (LD) Detection Kit  according to the manufacture’s instruction. Plasma samples obtained from the overfed geese and normally fed geese at day 19 of overfeeding were used for SCFA determination 6 each group). The method for determination of plasma SCFA concentration was described in C5 was amplified and sequenced with primers that were designed according to the upstream sequence of duck C5 . The 2000 bp upstream sequence of human C5 was retrieved from Ensembl database. The prediction of transcription factor was performed with the ‘Match’ program (www.gene-regulation.com) using the default parameters.The upstream sequence of goose 6 cells/mL, plate 1 × 106 cells per well in 12-well dishes, followed by incubation in 5% CO2 incubator at 38 °C until treatment. The media was renewed at first 6 h of incubation.Hepatocytes were isolated from Landes goose embryos at 23 days of hatch. The preparation was performed as previously describedFor lactic acid treatment, the cultured goose primary hepatocytes were treated with complete culture media containing 0, 5 and 8 mM lactic acid  for 5 h. For lactic acid/ethanol treatment, goose primary hepatocytes were treated with 5 mM lactic alone, 6% ethanol alone , or 5 mM lactice plus 6% ethanol for 12 h, respectively. The cells treated with complete culture media were used as control.HNF1α siRNA  synthesized by GenePharma Co., Ltd, Shanghai, China) and negative control siRNA  were used to transfect goose primary hepatocytes using X-tremeGene siRNA Transfection Reagent  according to the manufacture’s instruction. The amount of 40 pmol each siRNA were used for each well of cells in 12-well dish. After 36 hr of transfection with the siRNAs,. the cells were harvested with TRIzol Reagent .C5 and TNFα, was determined by qRT-PCR as previously describedGAPDH) gene was used as an internal control. The primer sequences of the genes were listed in C5 genes were normalized to the control gene. The cycle threshold (Ct) was determined with the supplied software. The message RNA abundance of genes of interest was calculated using 2−ΔΔCt Total RNA were extracted from liver samples or primary hepatocytes and cDNA was synthesized with the purified RNA samples as previously describedC5 , TNFα  and β-Actin .Protein concentration of each liver sample was determined as previously describedt-test or one-way analysis of variance for statistical significance of differences between or among different treatments. A P < 0.05 was considered statistically significant.The data were expressed as the means ± SD. SPSS 16.0  was used to perform the Student’s How to cite this article: Liu, L. et al. Prosteatotic and Protective Components in a Unique Model of Fatty Liver: Gut Microbiota and Suppressed Complement System. Sci. Rep.6, 31763; doi: 10.1038/srep31763 (2016).