P. falciparum malaria and systemic lupus erythematosus (SLE) have been demonstrated. However, association of functional promoter variants with SLE and malaria is lacking in malaria endemic population. A total of 204 female SLE patients and 224 age and sex matched healthy controls were enrolled in the study. Three hundred fourteen P. falciparum infected patients with different clinical phenotypes were included. TNF-α polymorphisms (G-238A & G-308A) were genotyped by PCR-RFLP. Plasma levels of TNF-α was quantified by ELISA. Heterozygous mutants and minor alleles of TNF-α (G-238A and G-308A) polymorphisms were significantly higher in SLE patients compared to healthy controls and associated with development of lupus nephritis. In addition, both promoter variants were associated with severe P. falciparum malaria. SLE patients demonstrated higher levels of plasma TNF-α compared to healthy controls. TNF-α (G-238A and G-308A) variants were associated with higher plasma TNF-α. In conclusion, TNF-α (G-238A & G-308A) variants are associated with higher plasma TNF-α levels in SLE patients residing in malaria endemic areas and could be a contributing factor in the development of SLE and susceptibility to severe P. falciparum malaria.Tumor necrosis factor-α (TNF-α) is a proinflammatory cytokine associated with autoimmune and infectious diseases. Importance of TNF-α in  TNF-α is primarily produced as a trans-membrane protein that gets released from the membrane by a metalloprotease- TNF alpha converting enzyme (TACE), to form soluble 17 kDa protein2. TNF-α is a pleotropic cytokine with wide range of biological functions: it can initiate host defense against infectious diseases and along with it involved in toxicity and inflammatory processes1. TNF-α exerts its biological effect through specialized types of receptors viz. TNF receptor 1 (TNFR-1) and TNFR-23. Expression of TNF receptors is tissue specific. TNFR1 is normally observed in most tissues but TNFR2 is restricted to cells of the immune system3. TNF-α has both a beneficial and deleterious role and it has been linked with infectious diseases and autoimmune disorders7. The TNF-α gene is located in short arm of chromosome 6 at position 21.3 and spans about 12 kilobase (kb) length8. Till date, 43 single nucleotide polymorphisms (SNPs) at promoter region of TNF-α gene with minor allele frequency data have been reported (https://www.ncbi.nlm.nih.gov/SNP/snp_ref.cgi?locusId=7124). Although there are contradictory reports, some SNPs at promoter region of TNF-α have been shown to regulate TNF-α expression and/or soluble TNF-α levels viz. TNF-α G-238A (rs361525), TNF-α G-308A (rs1800629), TNF-α T-857C (rs1799724), and TNF-α T-1031C (rs1799964)9. However, large number of genetic association studies have focused on two common promoter polymorphisms of TNF-α gene (G-238A and G-308A) and these have shown a significant association with SLE as well as P. falciparum infection in different populations11.Tumor necrosis factor-alpha (TNF-α) is a pro-inflammatory cytokine produced by wide range of cells such as macrophages, B cells, T cells and mast cells12. This was true across the continents where malaria was endemic. Plasmodium falciparum infection is a life-threatening disease with diverse clinical manifestations15. TNF-α is an important molecule that works like a double-edged sword in malaria infection16. TNF-α can protect an individual against severe infection17 but when production is unregulated it could be damaging to the host. Low levels of TNF-α has been associated with susceptibility to P. falciparum infection. While various reports have demonstrated elevated plasma levels of TNF-α in severe malaria compared to uncomplicated infection19. Mortality in P. falciparum infection is also associated with very high plasma levels of TNF-α20. These observations collectively indicate the importance of TNF-α in P. falciparum malaria: optimum levels are essential for protection against infection. Recently, numerous studies have been carried out in different populations to established possible link between TNF-α gene polymorphisms and susceptibility/resistance to P. falciparum infection and/or clinical severity24. Most of the reports24 have included TNF-α promoter polymorphisms, that are believed to affect mRNA expression and alter plasma levels of protein molecule. TNF-α (G-308A) mutants have been associated with susceptibility to P. falciparum infection23, higher levels of parasitaemia22 and severe malaria25. However, an independent study on South-West Nigerian infected patients failed to demonstrate such association24. Another common TNF-α promoter (G-238A) variant is also linked to elevated parasitaemia22 and severe P. falciparum malaria24.Malaria infection is believed to be an important selection pressure during human evolution and subjects with possible survival advantage genotypes against lethal malaria are more prevalent in malaria endemic areas26. Lupus nephritis remains one of the severe clinical manifestations and contributes to significant morbidity and mortality28. About 50–60% of SLE patients present with kidney dysfunction and the rate of renal affection is higher in Asian population29. Although type I interferons have been shown to play an important role in the pathogenesis of lupus nephritis30, there are cumulative evidence to suggest that TNF-α may also have a crucial role in renal dysfunction31. This has been demonstrated in the mouse model of SLE (MRL/lpr): elevated levels have been reported in serum and kidney tissue such as glomeruli, vascular smooth muscle, perivascular infiltrating cells and tubular epithelial cells33. Furthermore, the severity of proteinuria has been found to correlate with the degree of TNF-α expression in the kidney32. There are several reports of elevated TNF-α in SLE patients37. In a study involving African American, European American and Hispanic American SLE patients, high levels of plasma TNF-α was observed and a positive correlation with IFN-α was demonstrated37. A significant positive correlation between plasma TNF-α, with clinical severity and anti-ds DNA has also been reported in several studies36. Interestingly, TNF-α expression was found to be high in the renal tissue of patients with lupus nephritis39. Defective clearance of apoptotic bodies has been suggested to be an important factor in the pathogenesis in SLE41. TNF-α has been shown to induce apoptosis44. Elevated TNF-α in SLE patients could be one of the reasons for increased apoptosis, elevated production of nuclear debris followed by defective clearance of dead or dying cells. However, anti TNF-α therapy has provided no therapeutic advantage in the treatment of SLE46.SLE is characterized by production of autoantibodies against self-antigens, formation of immune complexes, deposition of these complexes in tissues leading to organ damage and its failureP. falciparum malaria has been widely investigated48 and it has been demonstrated that TNF-α is an important molecule for parasite clearance49. However, uncontrolled production of this cytokine during P. falciparum infection can lead to clinical complications51. In malaria endemic areas, subjects with moderate TNF-α producing genotypes have survival advantage12. The association of TNF-α in mouse models of lupus52 and in the clinical manifestations in humans has been documented37. For instance, higher expression of TNF-α has been associated with lupus nephritis39. Since TNF-α appears to be important to some aspects of the pathogenesis in both SLE and P. falciparum malaria, we hypothesized a possible relationship between TNF-α promoter variants with predisposition to SLE, notably lupus nephritis, in patients residing in a malaria endemic area.Importance of TNF-α in 54, especially, in the malaria endemic belts, for possible association between TNF-α polymorphisms (G-238A and G-308A) and SLE. A recent study has shown a significant association between heterozygotes and minor allele to SLE10. A study from south of India demonstrated an association between TNF-α promoter haplotype and protection against SLE53. In our study, we have enrolled SLE patients and controls from malaria endemic areas of Eastern India and investigated the association of TNF-α promoter variants with SLE. Furthermore, we have quantified plasma levels of TNF-α to assess the genotype-phenotype relationship. The novelty of our study relies on the enrolment of SLE patients and P. falciparum infected cases from malarial endemic areas. The question we have addressed is whether individuals from malarial endemic areas are vulnerable to the development of SLE if genetically susceptible.There are limited studies in the Indian populationP. falciparum infected patients including 103 uncomplicated malaria (UM), 68 cerebral malaria (CM), eighty four multi organ dysfunctions (MODs) and 59 non-cerebral severe malaria (NCSM)  and 314 2 = 11.35, P value = 0.0007; G-238A: χ2 = 3.5, P value = 0.061).Prevalence of heterozygous (GA) and homozygous mutants (AA) for G-238A polymorphism was 12% and 1% respectively  showed significantly higher prevalence of A-G and A-A in SLE patients compared to healthy controls  (Supplementary Table +) compared to those patients without renal involvement (LN−) . However, distribution of TNF-α (G-308A) polymorphism was comparable among both groups.Since the study revealed a significant association between TNF-α promoter (G-238A and G-308A) polymorphisms and SLE, we analyzed the association of these polymorphisms with organ involvement. Lupus nephritis was the most important clinical phenotype observed and often associated with increased mortality in SLE. In our study, 41% of SLE patients had lupus nephritis. We categorized the patients into two broad groups: (1) Patients with lupus nephritis (LN+), and (2) patients without nephritis (LN−). As depicted in Table + and LN− by student’s t test and results are shown in Fig. − SLE patients was not statistically significant (P = 0.08).We quantified plasma TNF-α in 90 samples  by ELISA and mean TNF-α in each group was compared by unpaired ‘t’ test. SLE patients had significantly higher levels of TNF-α compared to healthy controls P < 0.0001). Plasma levels of TNF-α were compared between LN. Plasma Several studies have demonstrated a functional relevance of TNF-α promoter polymorphisms (G-238A and G-308A) with expression of TNF -α. We compared plasma levels of TNF-α among different genotypes of TNF-α (G-238A and G-308A). As shown in Fig. P. falciparum malaria have been well documented. In the present study, we enrolled 314 P. falciparum infected cases comprising of 103 uncomplicated cases and 211 severe malaria patients and genotyped for TNF-α (G-238A and G-308A) polymorphisms. As shown in Table Association between TNF-α (G-238A and G-308A) polymorphisms and susceptibility to Severe malaria patients were further sub-categorized in to CM, MOD and NCSM and distributions of genotypes and allele were compared with UM cases. Results are shown in Table P. falciparum infected patients (P = 0.003)  Fig. . Based o03) Fig. .Figure 3in silico. SNPs (rs1800629 and rs361525) were submitted to the FuncPred program and results obtained are shown in Supplementary Table We observed a significant correlation between TNF-α polymorphisms (G-238A and G-308A) and plasma levels of TNF-α. To validate the above findings, we analyzed functional relevance of these variants RegulomeDB database has divided both the SNPs into two distinct categories  were significantly associated with higher plasma levels. These observations provide evidence of a possible role for TNF-α in the pathogenesis of SLE but the precise mechanism(s) is not yet known55. TNF-α is a pleotropic cytokine and acts at multiple levels1. In genetically susceptible SLE individuals, malaria might be a trigger for increased production of TNF-α, besides other cytokines, triggering a cascade of events contributing to the development of SLE58.TNF-α is an important cytokine in the pathogenesis as well as control of P. falciparum malaria is predominantly endemic in the Eastern and Northeastern parts of India59. But it remains endemic in most parts of the country. Prevalence of TNF-α promoter polymorphisms (G-238A and G-308A) have been reported in Indian population. Distributions of TNF-α (G-238A and G-308A) genotypes were comparable with previous reports from different parts of the country60,- South-West61, North62 and North-West63 regions. In most of the earlier reports63 distribution of TNF-α promoter variants were compatible with HWE in healthy controls. In the present study distribution of TNF-α (G-308A) genotypes deviated from HWE in healthy females (P = 0.0007). The geographical area of Odisha is highly endemic for P. falciparum malaria which contributes to high mortality due to malaria in the country64. Deviation of genotype distribution has been attributed to several factors, and selection pressure remains one of the important causes65. The studied population is endemic to various infectious diseases other than malaria and could be the reason for increased selection pressure on host genome66. Interestingly, two independent studies from South67 and North India68 have reported higher prevalence of heterozygotes (GA) compared to homozygous (GG or AA). They have also shown a deviation of TNF-α G-308A genotypes from HWE. These abnormalities in observations could be due to genotyping methods (ARMS PCR/sequence specific primer PCR) which could give spurious results.11. In the present analysis, we observed higher prevalance of heterozygous (GA) and minor allele (A) in SLE patients compared to healthy females, suggesting a possible role of TNF-α (G-308A) polymorphism in susceptible to SLE. Similar observations have been reported in SLE patients from different geographical areas such as Brazil, Colombo, Mexico, North America, Spain, Taiwan11 and South India10. However, contradictory results have also been reported in Portugese, Thai, Chinese, Italian, African American, Japanese and Argentenian populations11. These discrepancies have been attributed to ethnicity of subjects enrolled for case-control studies and further supported by ethnicity related meta-analysis which revealed significant link between allele ‘A’ with predisposition to SLE in Europeans, Asians and South and North Americans but surprisingly not in African population11. In the present study, TNF-α (G-238A) heterozygous and minor allele (A) were also associated with susceptibility to SLE and it corroborated with other observations. Although the exact mechanism related to TNF-α polymorphism and SLE is yet to be understood, results of the present study and previous reports across the world indicates a strong association of TNF-α promoter variants, higher expression of TNF-α m-RNA and elevated levels of plasma TNF-α in SLE patients from malaria endemic regions.Role of TNF-α promoter variants in SLE have been widely investigated. A recent meta-analysis including 41 published studies worldwide, showed association of minor allele (A) and AA genotype of TNF-α (G-308A) polymorphism with susceptibility to development of SLE11. However it contradicts an observation from South Indian population10 and a recent meta-analysis11. Furthermore, patients with lupus nephritis had higher levels of plasma TNF-α than those without nephritis.We analysed the possible association of TNF-α polymorphisms with clinical manifestations of SLE, namely lupus nephritis which is one of the major clinical phenotypes linked to SLE mortality. We observed that heterozygous (GA) and minor allele ‘A’ of TNF-α (G-238A) polymorphism were significantly associated with lupus nephritis. These observations have been corroborated by a recent study on Chinese SLE patients69. In vitro stimulation of peripheral blood mononuclear cells (PBMC) derived from heterozygous subjects (GA) with lipopolysaccharide, displayed higher TNF-α than those of wild type individuals (GG)70. Furthermore, elevated plasma TNF-α has been associated with mutants for TNF-α (G-308A) polymorphism10. In the present study, we observed higher plasma levels of TNF-α in GA and AA genotypes compared to GG, corroborating earlier observations. Interestingly, other TNF-α promoter polymorphism (G-238A) also revealed similar results: mutants (GA and AA) were associated with higher plasma TNF-α than wild type (GG), which corroborates with an earlier report71. Furthermore, we performed in silico analysis which revealed regulatory effect in binding of transcription factors and enhanced expression of TNF-α gene. Results of the present investigation and earlier reports demonstrate signifcant regulatory role of promoter polymorphisms.Functional relevance of TNF-α promoter polymorphisms (G-308A and G-238A) have not been widely investigated. Minor allele for TNF-α (G-308A) polymorphism has been observed to enhance the binding of transcription factors and is associated with increase in mRNA production compared to major allele (G)72. However, in an earlier observation, we have demonstrated protection against severe malaria and malarial death in complement receptor 1 variants and concluded a possible reason for higher prevalence of CR1 mutants in malaria endemic areas14. We had also observed that CR-1 mutants are susceptible to development of SLE and lupus nephritis since they expressed lower surface CR1 which affects clearance of apoptotic debris73. Furthermore, similar association of FcγRIIb variant (codon 232) with susceptibility to SLE and protection against P. falciparum malaria has been reported74. Lower parasitaemia and minimal clinical severity has been reported in FcγRIIb deficient mice when infected with non-lethal murine plasmodium strain indicating protective nature of the truncated or deficient FcγRIIb against malaria74. This observation has been further supported by higher prevalence of FcγRIIb codon 232 mutant in African and Asian population when compared to other populations across the world where malaria is endemic. The results of the present study and earlier reports collectively demonstrate that certain genotypes are beneficial in protecting humans against P. falciparum malaria and are highly prevalent in malaria endemic areas. Unfortunately, subjects genetically susceptible to SLE and residing in malarial endemic areas have a greater chance to develop SLE compared to those residing in non-endemic areas.Investigations on possible link between malaria and SLE are limited and contradictory. Epidemiological data have shown lower prevalence of autoimmune diseases in areas where malaria incidence is high49 and people residing in malarial endemic areas often produce optimal levels of TNF-α19 which could be helpful in combating the infection. It could also be one of the contributory factors for inducing SLE in genetically susceptible individuals. Further studies from other malarial endemic areas in the world are important to validate our findings.In conclusion, elevated plasma TNF-α is observed in SLE patients and associated with clinical severity. Furthermore, promoter variants of TNF-α gene, associated with higher TNF-α expression, were more prevalent in SLE patients. TNF-α is essential for clearance of malarial parasites76. SLE is a chronic inflammatory autoimmune disorder and mostly prevalent in females77. In the present study, we enrolled 428 female subjects  to investigate possible association of TNF-α polymorphism in SLE. Patients of SLE were diagnosed based on the revised American College of Rheumatology (ACR) classification criteria78 and analyzed based on various clinical manifestations . About 5 ml blood was collected from each participant. Plasma was separated and stored at −80 degrees centigrade for later use. The study was approved by the Institutional Human Ethics Committee of Central University of Jharkhand, India and S.C.B. Medical College Cuttack, Odisha, India. Informed written consent was obtained from each patient. The study was conducted in accordance with methods approved by IHECs.Gender wise analysis has been recommended in numerous earlier reports of genetic association studiesns Table . In addiet al. 1998).Whole genomic DNA was purified from blood samples using Gen Elute Blood Genomic DNA mini Kit (Sigma-Aldrich) according to manufacturer’s instructions. TNF-α promoter polymorphisms (G-238A & G-308A) were genotyped by polymerase chain reaction followed by restriction fragment length polymorphism method as described earlier  kit (eBiosciences) according to manufacturer’s instructions.The plasma TNF-α levels in SLE patients, healthy controls and https://snpinfo.niehs.nih.gov/snpinfo/snpfunc.php) web server80, which helps in selecting SNPs for genetic association studies. For the current study, two SNPs (rs1800629 and rs361525) were uploaded for batch analysis with the default settings. The output information was a list of SNPs with possible functional effect.In order to recognize the effect of SNPs in non-coding regions, tools predicting probable functional effect of SNPs at transcription factor binding sites (TFBS), Intron/exon border consensus sequences (splice sites), Exonic splicing enhancers (ESEs), and miRNA binding were utilized. SNPinfo (FuncPred) and RegulomeDB offer a pool of functional information using series of tools. The SNPs functionality was defined by SNPinfo (FuncPred) (http://regulomedb.org/)81. RegulomeDB categorizes variants into six categories ranging from 1 to 6, where category 1 variants are ‘likely to affect binding and linked to expression of a gene target’, category 2 variants are ‘likely to affect binding’, Category 3 variants are ‘less likely to affect binding’, and Category 4, 5 and 6 variants have ‘minimal binding evidence’. RegulomeDB also allocates a score of 7 for variants with no annotation data available. dbSNP rsIDs were utilized as input for the current study.To supplement SNP ranking, SNPs were further analyzed by RegulomeDB  genotypes with plasma TNF-α levels were analyzed by unpaired ‘t’ test or ANOVA followed by an appropriate post-test. Graph Pad Prism 5.01 software was used for these statistical analyses. Haplotype analysis was performed by SNAP Stats online tool. Resampling analysis was performed by bootstrap method in Microsoft excel sheet attached as supplementary file-1.Genotype and allele distribution among different clinical categories was compared by Fisher’s exact test. P value less than 0.02 was taken as significant (Bonferroni correction for two SNPs 0.05/2 = 0.02). The mean plasma levels of TNF-α in SLE patients and healthy controls was compared by student’s t test and analysis of variance (ANOVA) was employed for study difference in plasma TNF-α in different clinical categories of Supplementary fileSupplementary Dataset-1


Single Nucleotide Polymorphic (SNP) variations of proinflammatory cytokines such as Tumor Necrosis Factor-α (TNF-α) have been reported to be closely associated with the major depressive disorder (MDD). However, it is unclear if proinflammatory genetic burden adversely affects the regional gray matter volume in patients with MDD. The aim of this study was to test whether rs1799724, an SNP of TNF-α, contributes to the neuroanatomical changes in MDD. In this cross-sectional study, a total of 144 MDD patients and 111 healthy controls (HC) well matched for age, sex and education were recruited from Shanghai Mental Health Center. Voxel-based morphometry (VBM) followed by graph theory based structural covariance analysis was applied to locate diagnosis x genotype interactions. Irrespective of diagnosis, individuals with the high-risk genotype (T-carriers) had reduced volume in left angular gyrus (main effect of genotype). Diagnosis x genotype interaction was exclusively localized to the visual cortex . The same region also showed reduced volume in patients with MDD than HC (main effect of diagnosis), with this effect being most pronounced in patients carrying the high-risk genotype. However, neither global nor regional network of structural covariance was found to have group difference. In conclusion, a genetic variation which can increase TNF-α expression selectively affects the anatomy of the visual cortex among the depressed subjects, with no effect on the topographical organization of multiple cortical regions. This supports the notion that anatomical changes in depression are in part influenced by the genetic determinants of inflammatory activity. Despite being a leading cause of global disease burden3, pharmacological strategies of MDD so far have been restricted to the manipulation of monoamine neurotransmission, with only partial effect on the symptom burden.Major depressive disorder (MDD) is associated with a high rate of morbidity, recurrence, disability and mortality4. Tumor necrosis factor-α (TNF-α) is a pro-inflammatory cytokine produced largely by macrophages5, and is involved in both neurotoxic effects as well as neuroprotective effects6. Overexpression of TNF-α is deleterious in the early stage of tissue damage, but it can aid recovery later7. Pathophysiologically, elevated TNF-α may arouse lessened neuronal synaptic plasticity, reduced neurotropic factors and declined neurogenesis9. It has been reported that patients with MDD have enhanced plasma levels TNF-α, and antidepressant treatments can decrease this levels11. Moreover, increasing evidence has shown anti-TNF-α therapy could help to relieve depressive symptoms and repair cognitive impairments12. Yang et al.13. have shown peripheral TNF-α can affect the brain structure via dendritic elimination independent of central inflammatory activity by using a preclinical mouse model. In particular, inhibition of peripheral TNF-α action prevents structural changes at the synaptic level. The peripherally produced cytokines are also able to act on the brain through deficient blood-brain-barrier, active transport via saturable transport molecules, activating endothelial cells to generate second messengers, and binding to receptors on afferent nerve fibers16.A growing evidence has suggested that peripheral and central inflammatory response may play an important role in the pathogenesis and development of MDD, especially cytokines17. The high-risk genotype (-857C/T) of rs1799724 has been found to give rise to higher levels of mRNA and protein than the low-risk genotype (−857C/C)17. It has been proved that rs1799724 is an important SNP closely associated with neurological disorders like Alzheimer’s disease19, stroke20 and depression after stroke21. In the presence of post-stroke depression, serum TNF-α concentration is higher in T-carriers (high-risk genotype) than in non-T carriers (low-risk genotype), indicating that 805 C/T genotype moderates serum TNF-a levels especially in the presence of depression21.The rs1799724 (-850 or 857 C/T) is a functional single nucleotide polymorphism (SNP) located in the promoter regions of TNF-α gene , which can affect the genetic transcriptional activity of TNF23. In particular, TNF-α has been found critical to the development of unimodal sensory cortex, especially visual24, auditory25 and somatosensory13 cortices. It has been proved by neuroimaging studies that peripheral TNF-α levels are negatively linked to regional volumes in the left occipitotemporal area, left superior occipital gyrus, left inferior parietal lobule and bilateral medial prefrontal cortices of healthy people26. Some other SNPs of TNF-α and its receptors have been revealed to affect brain volume of hippocampus, striatum and caudate in healthy people28.In recent times, several lines of evidence have implicated cytokines to have neurotrophic functions that help to both promote and prune neuronal synapses, thus serving as experience-dependent plasticity regulators both during development and in adult lifeIn this context, we aimed to evaluate the effects of functional TNF-α SNP, rs1799724, on brain structure in both MDD patients and healthy controls using voxel-based morphometry (VBM). We also sought diagnosis x genotype interaction and followed this up with graph analysis to determine the systemic impact of any localized changes.29, the minimum sample size in each group should be 80 to guarantee 80% voxel-based power for grey matter analysis, and 144 patients with MDD and 111 healthy controls were included in this study finally. The patients, who met Diagnostic and Statistical Manual of Mental Disorders (DSM)–IV-TR criteria for MDD, were recruited from the clinics of Shanghai Mental Health Center (SMHC). They were 20–40 years old, right-handed, and educated up to or above junior high school level. All patients were medication-free when they were scanned, including 80 drug-naïve first-episode patients, 27 drug-naïve multi-episode patients, and 37 multi-episode patients who were not medicated for at least one month before the scanning. Moreover, when assessed by Hamilton’s Depression Scale with 17 items, the patients included should be with total scores no less than 17 and scores of depressive mood item no less than 2. Those patients with other axes I disorders and debilitating general medical disorders were excluded. Age, sex, and education matched HCs, who could pass our screening and had no history of psychosis or debilitating general medical disorders, were also recruited. This study was approved by the Institutional Review Board of Shanghai Mental Health.According to a previous studyhttp://www.clinicaltrials.gov)Centre after strict inspection of the protocol, and all the participants have written informed consents. .The genomic DNA was isolated from the peripheral blood using Lifefeng Blood DNA Kit . The SNP rs1799724 of TNF-α was genotyped via the Multiplex SnaPshot technique . The PCR primer was rs9964_rs9724F/R. All the 255 subjects were successfully genotyped for this promoter polymorphism of TNF-α. Hardy–Weinberg equilibrium analysis for the single SNP was performed using Chi-squared Test with SPSS19.0 . The SNP rs1799724 genotype distribution of all the subjects was in Hardy–Weinberg equilibrium  had repetition time = 2530 ms, echo time = 3.65 ms, flip angle α = 7°, 224 sagittal slices, field of view = 256 × 256 mm, matrix = 256 × 256, thickness = 1 mm. Images were checked out for movement artifacts and homogeneity of image intensity immediately after scans and repeated if necessary. We also collected a clinical diagnostic MR sequence in the same session and excluded individuals who had ischemia, cavum septum pellucidum, radiologically notable cerebral leukomalacia as determined by a radiologist.30  toolbox based on Statistical Parametric Mapping  and Matlab . First, we reoriented the images manually to set their origins to the anterior commissure. Then the T1 image of every subject was segmented into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF)31. Meanwhile, the total volume of GM, WM, and CSF were estimated and reported by VBM8. After that, a high-dimensional non-linear DARTEL  algebra was performed for normalization and modulation of the GM and WM. The modulated GM maps were smoothed with an 8 mm full-width at half maximum Gaussian kernel.We used VBM8p < 0.001 (uncorrected) were reported. With DPABI33 software, AlphaSim program based on Monte Carlo simulation was applied for multiple comparison corrections34, and the current version has solved the bug raised by Eklund et al35 with the real smoothness in the three directions calculated from the residuals. 5000 simulations for every statistic map were conducted and strict threshold was applied . Anatomical regions emerging from VBM analysis were labeled according to Anatomical Automatic Labeling (AAL) atlas and visualized with BrainNet Viewer36. Additionally, we used xjView toolbox  together with Easy Volume toolbox (http://www.sbirc.ed.ac.uk/LCL/LCL_M1.html) to extract mean volumes of the clusters that had shown significant effects in VBM analysis.VBM statistics were conducted in SPM8 using a 2 × 2 full factorial model defining diagnosis  and genotype  as two factors, while using age, sex, years of education and total intracranial volume as covariates to remove their effects on variance. An explicit grey matter mask was used to prevent effects occurring outside grey matter. We assessed the main effect of diagnosis, the main effect of genotype and the interaction effect, the disease effects within low-risk or high-risk subgroup using F contrasts. All the significant results at 37) to implement graph analysis of the structural networks of MDD patients and HCs in the high-risk subgroup. First, 90 regions of interest (ROIs) based on the cerebral part of Anatomical Automatic Labeling (AAL) atlas were defined, masks of them were generated using WFU PickAtlas Toolbox38 and were resliced to the same dimension as modulated, normalized GM images from VBM preprocessing step. REX code (http://web.mit.edu/swg/software.htm) was used to extract the mean volume of every ROI. Second, the extracted volume data of 90 ROIs were used to construct structural correlation networks. A 90 × 90 correlation matrix (R) was generated in each group with each entry rij representing the Pearson correlation coefficient between the volume of ROI i and j. Then each R matrix was converted to a binary association matrix (A), with entry aij considered 1 If rij bigger than a specific threshold and zero otherwise. Thresholding and construction of structural networks were carried out at a range of network densities (Dmin: 0.24: 0.02: 0.5), across which also group comparison was conducted. The lower limit of the range was the calculated minimum density allowing all nodes to be fully connected with each other, and the upper limit of the range was set to 0.5, as densities above 50% are not sparse anymore and thus not biologically meaningful for brain networks. Accordingly, a graph (G) including 90 nodes was derived from A, and regions i and j were regarded as connected if gij is unity. Network degree (E) was equal to the number of edges, and the network density (D) was used to present the fraction of actually existent edges to all possible links. Third, topology of the global network, such as small-worldness, normalized clustering and normalized path length, were measured using codes in the Brain Connectivity Toolbox39 at both the network and regional level. The small-worldness of a network has two key measurements, clustering coefficient (C) and characteristic path length (L). The clustering coefficient is a measure of network segregation and is represented as the mean value of clustering coefficients, while the path length is a measure of network integration and is defined as the mean shortest path length between all pairs of nodes in the network. All the measurements were compared to the consistent mean values of a benchmark random graph so as to appraise the topology of the brain network, and m (the number) null networks were generated for normalization of C and L. Normalized C and normalized L were calculated as C/Crand and L/Lrand, and small-wordness was obtained as [C/Crand]/[L/Lrand] (Crand and Lrand were the mean clustering coefficient and the characteristic path length of the m random networks.). Compared to random network, small-world network is characterized by significantly higher clustering coefficient (C/Crand ratio greater than 1) as well as similar characteristic path length (L/Lrand ratio close to 1). In terms of regional network characteristics, nodal clustering, degree, and betweenness were estimated and compared at the minimal density for significant brain regions from VBM analyses. Nodal clustering quantifies how close its neighbors are to being a clique, nodal degree is defined as the number of the edges from a node to others, and nodal betweenness is represented as the proportion of all shortest paths in the network that pass through a given node. The regional measures were normalized by the mean network value respectively, and then compared between groups. Forth, the within-group difference of network topology was identified, the between-group difference of global and regional network measures were tested using non-parametric permutation test with 1000 repetitions.We primarily applied Graph Analysis Toolbox  and Chi-square test (gender and genotype).Statistical analyses of clinical data were conducted with SPSS19.0 . Normal distribution test was performed using One-Sample Kolmogorov–Smirnov Test in groups of MDD and HC separately, and Levene’s Tests were used to test the homogeneity of variances. , left angular gyrus, right precuneus gyrus, left inferior parietal gyrus and left supplementary motor area than low-risk HC (Table pAlphaSim < 0.05) and the orbital part of right middle frontal gyrus than HC in the high-risk subgroup  and compared within and between groups. In each group of high-risk MDD and HC, characteristic path length approached to 1, while clustering coefficient and small-worldness were higher than 1, indicating a small-world organization  has a predominant effect on the structure of the visual cortex in the presence of depression. Secondly, as there is no notable effect on the structural covariance networks, it is likely that the morphological aberration is late in onset and highly localized in nature. Thirdly, in medication-free MDD patients, grey matter changes are of small effect size and limited in distribution41 and occipital cortex abnormalities in MDD42. While gray matter reduction in occipital cortex has been reported inconsistently in MDD45, prior reports highlight reduced functional connectivity51, perfusion deficits53 and abnormal structure56 of occipital cortex in MDD. Given that our sample comprised largely of drug-naïve first episode MDD, and the fact that only high-risk group had the MDD-related reduction in occipital cortex volume, this association is unlikely to be explained by the use of antidepressants or duration of illness.Our findings demonstrate that a polymorphism, which is potentially linked to higher transcription of TNF-α, is associated with structural changes in the occipital cortex, especially in the presence of depression. These results add to the burgeoning literature implicating visual stimulus processing deficits17. Higher levels of TNF-α57 relates to depression-like symptoms58, thus indicating that the carriers of T form a high-risk group. Of interest to our findings, TNF-α has been showed to play an important role in the synaptic plasticity to contribute to the anatomy of visual cortex. In particular, in the absence of TNF-α, compensatory adjustment to monocular deprivation does not occur in the non-deprived eye59. TNF-α has been shown to mediate experience-dependent plasticity through homeostatic synaptic scaling24 as well as long-term potentiation59. Of further relevance to depression where diurnal variation in emotion, cognition, and motivation occurs in a prominent fashion, the notable diurnal variation has been reported in the expression of TNF-α receptors in the murine visual cortex, as a response to daylight60. As the visual system is used differently in day and night, the levels of some cytokines, including TNF-α, and the number of their receptor cells varies in different time of day60. TNF-α expression and receptor cells increased in the dark compared to the light. The alteration in visual cortex and related emotion and cognition of MDD patients may be explained by varying TNF-α and other cytokines partly. Taken together, our observation of MDD × genotype interaction indicates that in a subgroup of depressed subjects with the high-risk variant, the trophic effects of TNF-α on visual cortex may be disrupted.The T allele of rs1799724 has the higher transcriptional activity for TNF61. The lack of disruption in structural covariance in depressed subjects with the high-risk genotype suggests that the effect of TNF-α may be either temporally restricted  and/or spatially restricted to the occipital cortex. It is important to consider this in light of our observation that there was a small, statistically insignificant effect of diagnosis x genotype interaction in other brain regions in our sample. Such spatially limited grey matter deficits are in line with several VBM studies investigating a comparable sample 40.We studied structural covariance using graph theory, to detect the effect of TNF polymorphism on the coordinated maturation of distributed, large-scale morphometric networks. We observed no MDD × genotype interaction on the structural covariance across the entire brain. Morphometric networks with tightly co-varying patterns of brain anatomy are likely to have mutually shared trophic influences such as functional co-activation or expression of plasticity modulating factors19, stroke20 and depression after stroke21. We plan to undertake further neuroimaging studies with other SNPs of TNF-α, subsequent to appropriate approvals to study their individual effects as well as interactions among the various polymorphic variants. Secondly, we lacked functional data on task performance  and neuropsychological data relevant to visual processing, to further study the implications of the observed structural change. This is one of our goals for the future studies. Thirdly, it is possible that there are other potential confounding factors mediating the observed relationship between TNF polymorphism and brain structure in depression. We lacked sufficient quantitative data on smoking, alcohol and drug use, stress and childhood trauma, that may also influence the brain structure.There are several limitations that need to be considered when interpreting the results of this study. Firstly, as a transcriptional regulator, rs1799724 is not the only SNPs in the promoter region of TNF-α; nevertheless, studies have suggested a link between rs1799724 and neurodegenerative/neurovascular disorders such as Alzheimer’s diseaseIn conclusion, the TNF-α SNP, rs1799724 (TNF-850 or 857 C/T), has a notable effect on the brain structure in both patients with MDD and healthy controls, with disease-related effects localizable to the occipital cortex. Our observations raise questions regarding the disruptions in the trophic role played by pro-inflammatory cytokine system in depression. Our results are highly relevant to understanding the brain-basis of anti-inflammatory treatments in depression, as well as isolating sub-groups of depressed subjects who may differ in cortical anatomy, genotype as well as response to novel therapeutics.Supplementary Materials0703


Maternal mortality continues to be a global burden, with more than 200 million women becoming pregnant each year and a large number dying as a result of complications of pregnancy or childbirth. The World Health Organisation has recommended use of the partogram to monitor labour and delivery in order to improve healthcare and reduce maternal and foetal mortality rates.This study described factors affecting utilisation of the partogram among nurses and midwives in selected health facilities of Rwanda.A descriptive quantitative and cross-sectional research design was used. The population comprised 131 nurses and midwives providing obstetric care in 15 health institutions . Data collection was through a self-administered questionnaire, and a pre-test of the data collection instrument was carried out to enhance validity and reliability. The Statistical Package for Social Sciences (version 21) was used to capture and analyse data. Ethical clearance was obtained from the University of the Western Cape (Republic of South Africa) and from the Institutional Review Board of Kigali Health Institute (Rwanda). Patricia Benner’s model of nursing practice was used to guide the study.It was found that 36.6% of nurses and midwives did not receive any in-service training on how to manage women in labour. Despite fair knowledge of the partogram among nurses and midwives in this study, only 41.22% reported having used the partogram properly, while 58.78% reported not having done so.Nurses’ and midwives’ years of professional experience and training in managing pregnant women in labour were found to be predictors of the likelihood of proper use of the partogram. In-service training of obstetric caregivers in the Eastern Province of Rwanda is recommended to improve use of the partogram while managing women in labour. Maternal mortality continues to be a global burden, with at least 585 000 women dying each year from complications of pregnancy and childbirth  88.9% of deliveries are assisted by skilled service providers, while in the urban areas this rises to 94.5%  of the partogram by nurses and midwives in maternity wards in selected health facilities?This study adopted a descriptive quantitative and cross-sectional research design to gather information on utilisation of the partogram among nurses and midwives in selected public health facilities. A quantitative design is useful when wanting to describe and examine relationships and determine causality among variables  of the partogram by nurses and midwives in selected health facilities, while the independent variables are socio-demographic variables and other important variables under study. The questionnaire was translated from English into French by a professional translator; both languages are officially used in Rwanda. The data collection instrument was translated to facilitate respondents’ understanding of the tool by using the language with which they are most conversant. Translation from French back into English was done by an independent professional translator, to confirm that the meaning and content of the original copy had not been changed during translation. Verification of the translated instrument was also done to ensure its validity. The original instrument for data collection that was adapted to the present research had demonstrated a high degree of validity and reliability with a coefficient of 0.89 at an alpha level of 0.05  version 21. After data collection, the researcher proceeded with data entry, followed by data cleaning and data screening to ensure that there were no errors or missing data. Data were analysed in three steps: firstly, univariate analysis was used to summarise data in terms of frequency distributions of the variables under study. Secondly, bivariate analysis was used to determine the relationship between the dependent variable  and independent variables (sociodemographic and others). In this case, cross-tabulations together with the chi-squared test for independence were employed for categorical variables. Lastly, multivariate analysis was conducted to find out the extent to which independent variables affect dependent variables, using the logistic regression model. Captured and analysed data were reviewed by a statistician at the Department of Statistics at the University of the Western Cape.In undertaking this research, various sources were consulted to ensure that the study adhered to acceptable ethical guidelines. Participants in this study gave their consent to take part after receiving explanations about the purpose of the study as detailed in the information sheet. The original instrument for data collection that was adapted to the present research had demonstrated a high degree of validity and reliability with a coefficient of 0.89 at an alpha level of 0.05  self-administered questionnaires were analysed using SPSS version 21.A total of 140 questionnaires were distributed among nurses and midwives attending to pregnant women in labour in the selected health facilities and 131 questionnaires were fully completed, giving a response rate of 93.5%. One of the questionnaires had missing data and was excluded from analysis, and a further eight were not returned. Hence, data from 131 . The ages were put into six different groups with age intervals of 5 years. Most respondents were enrolled nurses (74.8%) with a secondary level of education. Only 9.9% of respondents were midwives. More than half of the participants (55.0%) had professional experience of 0–4 years, 28.2% had 5–9 years, 7.6% had 10–14 years and 9.2% had 15 years and above.It was found that more than half of the participants (63.4%) had received training in management of pregnant women in labour: 55.7% were trained in Emergency Obstetric and Neonatal Care (EmONC) and 7.6% were trained in Advanced Life Support in Obstetrics (ALSO). The remaining 36.6% of nurses and midwives declared that they had not received any in-service training on management of labour.Of the participants, 89.3% affirmed that they had been trained in using the partogram. The source of knowledge of using the partogram was given as the college or teaching institution by 51.1% of participants, while 48.9% did not respond.Only 19.8% were working in the hospital, while 80.2% were working in health centres; 51.1% of respondents were permanently working in labour wards. The remaining 48.1% participants were working in units affiliated to labour wards . All nurses and midwives who participated in this study were exposed to pregnant women in labour. Even though some participants were not found in the labour wards during the time of data collection, they rotate in different services and attend to pregnant women in labour, especially during night shifts and over the weekends. Forty-five per cent of participants revealed that while working in labour wards the shift is made up of only one staff member; 33.6% said there are two staff per shift, 20.6% that there are three staff per shift and just 0.8% said that the shift is made up of four persons.The results show that all 131 (100.0%) nurses and midwives have used the partogram previously, and 80.9% of them agreed that it is a simple graphic recording of progress of labour and salient conditions of the mother and foetus against time in hours. Of the 131 respondents, 79.4% knew the partogram was one of the tools to implement the Safe Motherhood programme, while 20.6% disagreed. A large percentage (90.1%) acknowledged use of the partogram in reducing maternal mortality, with 87.8% agreeing that this tool plays a key role in reducing newborn mortality. Of the respondents, 58.0% agreed that the action line of the partogram plot falls on the left of the alert line, while 42.0% disagreed.Less than half of the respondents (32.1%) agreed that the correct role of the action line on the partogram is to alert them to take appropriate action, while 67.9% disagreed. The majority of participants (78.6%) attributed the role of the action line to the wrong function – indicating that it allows time for the woman to be adequately assessed for appropriate intervention. Also, only 54.2% of respondents were of the view that in normal labour the minimum duration of a strong contraction is 40 seconds, while 45.8% opposed this view. Results further showed that 68.7% of respondents claimed that at least 10 minutes is required to assess adequacy of uterine contractions effectively.A large number of participants (92.4%) were of the view that it is a managerial policy that all women in labour should be monitored with a partogram in respective health facilities, whereas 3.82% disagreed and 3.82% revealed that they did not know. However, only 30 nurses and midwives (22.9%) considered the partogram useful in obstetric review, while 3.1% disagreed and 74.0% did not know. Most respondents failed to describe the two important lines on the partogram, namely the alert line and the action line. Only 58.0% of nurses and midwives agreed that in normal progress of labour the graph or plot on the partogram should fall on the left of the alert line, with 42.0% disagreeing. Of all participants, 32.1% agreed with the correct role of the action line, which is to indicate the appropriate action to be taken for a pregnant mother in labour.In addition to there being insufficient numbers of staff to monitor pregnant women in labour, it was found that the partogram is misused by most of the respondents. Only 41.2% were found to use the partogram properly, whereas 58.8% did not do so. Proper use of the partogram refers, in the current study, to monitoring of the pregnant mother in labour and recording findings at least once every 30 minutes. Nurses and midwives start completing the partogram when the woman enters the active phase of labour. In this regard, 41.2% of nurses and midwives monitored pregnant women and recorded every 30 minutes, 16.8% recorded every hour, 23.7% every 4 hours, 9.9% every 6 hours and 8.4% recorded the pregnant mother’s information after 12 hours.N = 131) agreed that the partogram is available in their health facility. Of the respondents, 93.9% agreed that there is a need to develop managerial guidelines or protocols for each maternity unit in their health facility to facilitate effective use of the partogram, while 6.1% disagreed. Almost all participants (93.9%) opted to be trained in the use of the partogram.All respondents  and participants’ demographic characteristics  and other selected variables under study (training received and knowledge of use of the partogram).In order to identify some of the factors that affect the use of the partogram, the chi-squared test for independence was used. The level of significance was set to 5%, with any 2(3) = 17.414, p = 0.001). Furthermore, among those with professional experience of 0–4 years, out of 72 nurses and midwives only 16% used the partogram properly, while 38.9% did not. Data show a significant association between number of years of professional experience and proper/not proper use of the partogram by nurses and midwives (χ2(3) = 10.547, p = 0.014).The results indicated that among the factors believed to affect the use of the partogram, those having a significant association are professional qualification, years of professional experience and in-service training received. Of the 13 (9.9%) registered midwives who responded in this study, 8.4% used the partogram properly, while 1.5% did not. Of 18 (13.7%) registered nurses, 8.4% used the partogram properly and 5.3% did not. The Pearson chi-squared test revealed a statistically significant association between proper/not proper use of the partogram and professional qualification of nurses and midwives (χ2(1) = 15.789; p = 0.000).With regard to in-service training received, of the nurses and midwives who received training in management of labour, 34.4% used the partogram properly while 29.0% did not. Among those trained in EmONC, 30.5% used the partogram properly while 25.2% did not. Among nurses and midwives trained in ALSO, 2.3% used the partogram properly and 5.3% did not. A statistically significant association was found between correct use of the partogram and training received in management of labour (χ2(3) = 6.479, p = 0.091). The results did not show a difference in proportions.A statistical association was not found between use of the partogram and number of staff per shift or place of work. Of 59 nurses and midwives (45.0%) who revealed that there is one staff member per shift in the labour ward, 15.3% used the partogram properly, whereas 29.8% did not. There was also no relationship found between use of the partogram and the shortage of nurses and midwives attending to pregnant women in labour . There was also no significant link between proper/not proper use of the partogram and knowing the role of the partogram in terms of reducing maternal and neonatal mortality.p-value is expected to be greater than 0.05  and number of years of experience (p = 0.050). Place of work did not contribute significantly.Binary logistic regression was performed to assess the impact of a number of factors on the likelihood that nurses and midwives would report properly or not properly using the partogram. The model contained various independent variables, but only two were found to be significant: number of years of professional experience and being trained in the management of pregnant women in labour. The full model containing these predictors was statistically significant, as shown by the Hosmer–Lemeshow goodness-of-fit test, with a chi-square value of 5.923 and a significance level of 0.432 at a degree of freedom of 6. With the Hosmer-Lemeshow goodness-of-fit test to support the logistic model, the  Pallant . ResultsThe strongest predictor of reporting proper use of the partogram was being trained in management of pregnant women in labour . This indicated that nurses and midwives trained in management of pregnant women in labour were over four times more likely to use the partogram properly than those who did not have this training. On the other hand, the odds ratios of 0.310 and of 0.745 for nurses with 0–4 and 5–9 years of experience were less than 1.000, indicating that respondents in these categories were, respectively, 0.310 and 0.745 times less likely to use the partogram properly than nurses and midwives with more experience. The primary aim of this study was to describe factors affecting use of the partogram among nurses and midwives in selected health facilities of Rwanda. The response rate of 93.5% implies that this study was needed in Rwanda. The discussion is organised according to the study’s specific objectives: knowledge and use of the partogram, challenges facing nurses and midwives during utilisation of the partogram and factors affecting utilisation of the partogramThe results indicate that 80.9% of all of respondents (131) knew what a partogram was and more than three-quarters (79.4%) knew its role as a tool to implement the Safe Motherhood programme. The data in terms of knowledge of nurses and midwives also confirm the results of Uwimana , who evaHowever, knowledge of the function of the alert line and the action line was poor; only 76 (58.0%) respondents could explain the function of the alert line and 42 (32.1%) the function of the action line. This may indicate the need for urgent steps to improve the knowledge of nurses and midwives on the partogram through training and seminars, in order to maximise proper use of this tool. This is confirmed by the findings of Yisma et al. , where 5These results are, however, higher than those found in a study carried out in Nigeria  of those who received training on the partogram. The low percentage of midwives (9.9%) who responded in this study might be why so few respondents reported having received pre-service training on the partogram (from school or teaching institution). The source of knowledge about the partogram in this study is similar to the findings of a study conducted in Ethiopia by Yisma et al. .In addition to education received from school, of all nurses and midwives who participated in this study, 73 (55.7%) were trained in EmONC and 10 (7.6%) in ALSO, while 48 (36.6%) did not receive any in-service training in management of the pregnant woman in labour. Similarly, a life-saving skills training workshop was reported as the primary source of knowledge by one-third of those who were aware of the partogram in a study in Nigeria  under the Ministry of Health of Rwanda, as stipulated by the third Health Sector Strategic Plan, which is to ensure availability of an adequate, equitably distributed, qualified, motivated and productive workforce responsive to the country’s changing needs and demands . This is in line with other literature confirming this relationship (Nyamtema et al. Results from the present study also revealed that there was a significant relationship between proper/not proper use of the partogram and whether the nurses and midwives had received in-service training (at a degree of freedom of 1, Number of years of professional experience was another predictor of proper use of the partogram: the more years of professional experience nurses and midwives have in practice, the more likely they are to use the partogram properly. This is similar to findings from Opiah et al. , who fouThe results of this study also reveal an association between the number of nurses and midwives per shift and proper use of the partogram or not. Shortage of staff was confirmed in the literature (Opiah et al. Ogwang et al.  found usAnother factor found to influence proper use of the partogram was professional qualification. This again is closely linked to the shortage in the midwifery workforce in Rwanda (Rwanda Ministry of Health The study was only conducted in 15 health facilities in one province of Rwanda. With that consideration, the findings cannot be generalised to the whole country because it is limited to some health facilities in the Eastern Province. Moreover, the methodology, especially the quantitative design used in this study to describe factors affecting the utilisation of partogram, generated data that could not assess the quality in documenting the partogram and determine the outcomes of the mother and the newborn. To this end, there is a need for qualitative study to improve delivery of care to pregnant women in labour.For many years, the partogram has been used as a standard for monitoring labour, the main reason being the assumption that it would guide in early identification of problems during labour and hence assist in taking appropriate action that could lead to reduction in complications of pregnancy and birth. Proper use of the partogram is an essential procedure in midwifery and also helps in clinical decision-making during labour. To this end, the purpose of this study was to describe factors affecting use of the partogram among nurses and midwives in the labour wards of selected public health facilities in the Eastern Province of Rwanda.In sum, a significant percentage of nurses and midwives in the selected health facilities have fair knowledge of the partogram and why it is necessary to use it in the management of labour. However, despite this, a large percentage of participants reported poor use of the partogram. Nurses’ and midwives’ years of professional experience as well as having received training on managing pregnant women in labour were both found to be predictors of proper use of the partogram.In addition to these two predictors, the numbers of staff members per shift as well as their professional qualifications demonstrate a significant influence on the proper use of the partogram.The findings of this study could be useful in designing professional continuing education programmes for nurses and midwives, as well as in formulating policies that may influence effective delivery of care to pregnant women in labour.


During median follow-up (1429 days), there were 67 composite events of all-cause death or hospitalization for heart failure  in HFpEF. Lower LAEF (below median) was associated with an increased risk of composite endpoints . In multivariable Cox regression analysis, LAEF  and indexed extracellular volume  were the only parameters that remained significant when added to a base prognostic model comprising age, prior HF hospitalization, diastolic blood pressure, lung disease, NYHA, six-minute-walk-test-distance, haemoglobin, creatinine and B-type natriuretic peptide. CMR-derived LAEF is lower in HFpEF compared to healthy controls and is a strong prognostic biomarker.The aim of this study was to determine whether left atrial ejection fraction (LAEF) quantified with cardiovascular magnetic resonance (CMR) was different between heart failure with preserved ejection fraction (HFpEF) and controls, and its relation to prognosis. As part of our single-centre, prospective, observational study, 188 subjects  underwent phenotyping with contrast-enhanced CMR, transthoracic echocardiography, blood sampling and six-minute walk testing. LAEF was calculated using the biplane method. Atrial fibrillation (AF) was present in 43 (31%) of HFpEF subjects. Overall, LAEF (%) was lower in HFpEF patients inclusive of AF (32 ± 16) or those in sinus rhythm alone (41 ± 12) compared to controls (51 ± 11), p < 0.0001. LAEF correlated inversely with maximal and minimal left atrial volumes indexed (The online version of this article (10.1007/s10554-019-01684-9) contains supplementary material, which is available to authorized users. Left atrial (LA) remodeling and dysfunction have been implicated in the pathophysiology of heart failure (HF) and are associated with poorer outcomes across a range of pathologies . To dateHeart failure with preserved ejection fraction (HFpEF) currently accounts for a significant proportion of all HF patients. Unlike heart failure with reduced ejection fraction (HFrEF), HFpEF still remains poorly understood and lacks proven, effective therapies . CurrentOne hundred and fifty five patients with HFpEF were recruited in an observational, cohort study conducted at a single tertiary cardiac centre. HFpEF inclusion criteria were clinical or radiographic evidence of HF, left ventricular ejection fraction (LVEF) > 50% on transthoracic echocardiography (TTE) and age ≥ 18 years. The exclusion criteria were as previously described .For comparison with HFpEF, 48 asymptomatic controls (age- and sex-matched) were recruited. Hypertensive subjects were included in this group (n = 22) since hypertension is highly prevalent in this age group of patients. The study was approved by the National Research Ethics Service (reference: 12/EM/0222). Written informed consent was obtained from all subjects prior to participation.All subjects underwent comprehensive clinical assessment and blood sampling, TTE and CMR during the same visit. A standardized six minute walk test (6MWT) was used to quantify exercise capacity .Blood was sampled for B-type natriuretic peptide , haematocrit, haemoglobin and renal function . Plasma samples were analysed in a single batch for N-terminal pro-atrial natriuretic peptide (NT-proANP), a marker of atrial stress/stretch, using a Luminex® bead-based multiplex assay as previously described .Echocardiography was performed by accredited sonographers in accordance with American Society of Echocardiography guidelines using an iE33 system  as previously reported , 10. LVEAll CMR scans were performed on a 3-Tesla scanner  with an 18-channel cardiac coil as previously detailed , 10. RetCVI42 software . Left ventricular volumes, EF and mass were calculated from the short-axis cine stack excluding papillary muscles and trabeculations ) and LA conduit function i.e. conduit volume ([LV stroke volume − LA reservoir volume]) were also calculated. LAVImax > 40 ml/m2 was used to define LA dilation [The biplane area-length method . Receiver operator characteristics (ROC) analyses were undertaken to assess the strength of the discriminatory capabilities of LAEF in distinguishing HFpEF from controls.Statistical tests were performed using SPSS v22. Normality for continuous data was assessed using histograms, Q–Q plots and the Shapiro–Wilk test. Summary data are presented as mean (± standard deviation) or median (25–75% interquartile range). Between group differences were compared using the unpaired t-test, Mann–Whitney U test and the Chi-square test as appropriate. BNP and creatinine were logKaplan–Meier analysis was undertaken to calculate event rates. Differences in survival curves were tested using the Log-Rank test. Cox proportional hazards analysis was undertaken to identify baseline variables associated with the composite endpoint. A base multivariable prognostic clinical model was created comprising clinical parameters shown to have historically strong prognostic importance in HF and univariable associations with the endpoint of p < 0.10. All remaining covariates associated with the endpoint at p < 0.10 were then entered into subsequent multivariable analysis to identify independent predictors using stepwise elimination methods. Continuous variables were Z-standardized to enable comparison of hazard ratios (HR) based upon one standard deviation increase in the predictor variable. The incremental prognostic benefit of LAEF beyond the base model was also assessed by comparing the area under the curves (AUCs) from ROC analysis.Following CMR, 15 HFpEF patients were diagnosed  with eitHFpEF and healthy controls were well matched for age (73 years) and sex. Approximately two-thirds of HFpEF patients had experienced prior hospital admissions for decompensated HF or had radiographic evidence of pulmonary congestion. Consistent with prior studies, HFpEF was frequently associated with co-morbidities including obesity, diabetes, hypertension and atrial fibrillation (AF). HFpEF patients had worse renal function and lower haemoglobin. A significant minority of HFpEF also had known ischaemic heart disease  and lung disease (17%). Furthermore, HFpEF patients had dramatically poorer exercise capacity (shorter 6MWT distance) and nearly one-third were in New York Heart Association (NYHA) III/IV.Indices of diastolic dysfunction as per European Society of Cardiology (ESC) guidelines i.e. BNP, E/E′, LAVImax, LV mass were significantly higher in HFpEF Tables , 2. CompHFpEF subjects had higher plasma NT-proANP levels, larger atria and lower LAEF 32 ± 16) compared to controls: overall (51 ± 11), with hypertension (49 ± 12) and without hypertension (52 ± 11); p < 0.0001 for all . There were further moderate to strong inverse correlations between LAEF, NTproANP (Spearman’s r =  − 0.367) and LA volumes  and LAVImin  are illustrated in Fig. r =  − 0.067; p = 0.527).LAEF correlated inversely with echocardiographic E/E′ .During median follow-up of 1429 days (1157–1657), there were a total of 67 composite events  in patients with HFpEF. The event rate was higher in the AF sub-group than in sinus rhythm . There were no events in the control group. No subjects were lost to follow-up.On univariable analysis comprising all HFpEF subjects, 18 parameters were associated with adverse outcomes Table . AF was Kaplan–Meier survival plots according to LAEF for all patients or sinus rhythm alone are shown in Fig. The AUCs  of the base model and LAEF for predicting outcomes were 0.790 (p < 0.0001) and 0.634 (p = 0.008) respectively. The combination of the base model and LAEF yielded a higher AUC of 0.806 (p < 0.0001). The AUC for iECV was 0.611 (p = 0.078).This study prospectively evaluated the prognostic relevance of CMR-derived LAEF in a well-phenotyped cohort of HFpEF and healthy subjects. The principal findings are that (a) LAEF is lower in HFpEF compared to age- and sex-matched healthy controls (b) LAEF is associated with LA volumes and plasma biomarkers of atrial stress/stretch (c) inclusive of AF or sinus rhythm alone, lower LAEF is associated with adverse outcomes in HFpEF and (d) CMR-LAEF is also an independent prognostic marker in HFpEF.Our work adds to a growing body of evidence implicating LA remodeling and dysfunction in HF . ImpaireCurrent ESC guidelines advocate measurement of LA volumes and LV mass in all subjects with suspected HFpEF . HoweverOur prospective study shows CMR-derived LAEF is an independent prognostic marker in HFpEF, both with and without AF. Previously, TTE-based observational studies  and HFpEThe potential value of LAEF as a prognostic biomarker may not be confined to HF alone. In a previous study of 312 subjects free of HF, who were in sinus rhythm and of similar age to our cohort, LAEF and LA strain were independent predictors of outcomes including future development of AF, HF and cardiovascular death . All of Beyond HF, CMR data also further support LA dysfunction as a marker of outcomes. Similar to our findings, the incremental prognostic value of LA function beyond LAVImax has previously been shown in a prospective study of asymptomatic subjects from the general population  and in cThe association between LA dilation and AF and their attendant cardiovascular risk is well recognized . In HF, Our study reaffirms the pathophysiological role of LA dysfunction in HFpEF. CMR-measured biplane LAEF is simple, reproducible and provides prognostic information which are strengths for consideration as a potential biomarker. CMR is becoming increasingly accessible and may more reliably discriminate breathless individuals with equivocal BNP levels and suboptimal echocardiographic imaging windows  , 17. RecThis is a single centre study and the results should be confirmed in additional HFpEF cohorts. We used a pragmatic approach to define our HFpEF population to reflect a real world setting as opposed to latest ESC guidelines . The preCMR-derived LAEF is lower in HFpEF compared to age- and sex-matched controls and independently predicts outcomes.Supplementary file1 (PDF 162 kb)Supplementary file2 (PDF 175 kb)Below is the link to the electronic supplementary material.