SMA) is an autosomal recessive neurodegenerative disease characterized by the selective death of lower motor neurons in the brain stem and spinal cord. SMA is caused by mutations in the survival motor neuron 1 gene (SMN1), leading to the reduced expression of the full‐length SMN protein. microRNAs (miRNAs) are small RNAs that regulate post‐transcriptional gene expression. Recent findings have suggested an important role for miRNAs in the pathogenesis of motor neuron diseases, including SMA. Motor neuron‐specific miRNA dysregulation in SMA might be implicated in their selective vulnerability. In this study, we discuss recent findings regarding the consequences of SMN defects on miRNAs and their target mRNAs in motor neurons. Taken together, these data suggest that cell‐specific changes in miRNAs are not only involved in the SMA motor neuron phenotype but can also be used as biomarkers and therapeutic targets.Spinal muscular atrophy ( Spinal muscular atrophy (SMA) is a severe neurodegenerative disease with autosomal recessive transmission SMN1, MIM#600354) which encodes the full‐length form of the SMN protein SMN1 paralogous gene, SMN2, predominantly encodes a truncated and unstable isoform through alternative splicing of exon 7. Only 10% of the transcript encodes a full‐length protein that can partially balance the SMN1 absence. The number of copies of SMN2 in the patient's genome largely determines the severity of the clinical presentation, spanning from SMA type I, the early onset and most severe form that is generally associated with two SMN2 copies, to the less severe SMN II‐IV forms, in which patients usually harbour multiple SMN2 copies in vitro loss of SMN leads to significant defects, not only in motor neuron survival but also in neurite extension SMA is determined by mutations (predominantly homozygous deletions) in the survival motor neuron 1 gene , an antisense oligonucleotide that modulates With all this in mind, a mechanism that seems to be implicated in the selective motor neuron vulnerability observed in SMA models is the alteration of the expression of motor neuron‐specific microRNAs (miRNAs). In fact, the SMN protein is likely involved in miRNA biogenesis miRNAs are small non‐coding RNAs that are approximately 22 nucleotides in length. They regulate gene expression at the post‐transcriptional level; in particular, they bind specific sequences in the 3′ UTR of target genes, inducing subsequent translational repression and/or decay of target mRNAs Fig. . As mentNumerous studies have suggested the importance of miRNAs in SMA disease.As mentioned above, SMN has a fundamental role in RNA processing. In fact, SMN binds directly to proteins relevant for miRNA generation and functionality, specifically fragile X mental retardation protein (FMRP), KH‐type splicing regulatory protein (KSRP) and fused in sarcoma/translocated in liposarcoma (FUS/TLS), which is one of the most frequent genetic causes of juvenile amyotrophic lateral sclerosis (ALS) Dicer function In spinal motor neurons, miRNAs are essential for the development, differentiation, acquisition and maintenance of identity, axonal growth, cytoskeletal structure, synapse formation and overall activity in vivo.Because of these essential roles, it is not unexpected that dysregulation of RNA processing and miRNA expression are emerging as mechanisms involved in motor neuron diseases Recently, it has been demonstrated that in ALS, the most common adult‐onset motor neuron disease, aberrant miRNA expression contributes to the disease pathophysiology and may represent a target for pharmacological intervention Increasing evidence also suggests that specific miRNAs can determine the selective vulnerability of motor neurons also in SMA Here, we present and discuss several of these specific miRNAs involved in SMA pathogenesis and their role as potential biomarkers and therapeutic targets Table .miR‐9 is one of the most abundant miRNAs in the CNS, with essential functions as a regulator of neuronal function, generation and differentiation. In particular, miRNA‐9 has different functions during different stages of development. Overall, miR‐9 is pivotal in both spinal motor neuron differentiation and correct positioning. During early stages of development, as demonstrated in chicken embryos, miR‐9 up‐regulation influences the differentiation of neural progenitor cells into spinal motor neurons through inhibition of the transcription factor onecut1 (OC1) The first evidence suggesting the importance of miRNA dysregulation, and specifically of miR‐9, in SMA came from a study by Hornstein group that was published in 2010. In that study, conditional ablation in spinal motor neurons in rodent models of Dicer1, a protein that is fundamental for miRNA processing and maturation, altered miRNA biogenesis and led to an SMA‐like phenotype in vivo and in vitroin vitro model represented by motor neurons derived from embryonic stem cells (ES) carrying a SMN1 mutant allele (SMN1mut). They used murine SMA ES cells from a transgenic mouse that also expressed a GFP reporter under the motor neuron‐specific promoter HB9 (Tg(Hlxb9‐GFP)1Tmj Tg(SMN2)89Ahmb Smn1tm1Msd/J); thus, they could monitor the correct differentiation of ES into motor neurons. The researchers analysed the RNA extracted from these SMN1mut motor neurons, purified with FACS according to the Hb9‐GFP expression, and compared these RNA profiles with those obtained from wild‐type (WT) motor neurons. The authors demonstrated through a quantitative PCR analysis that several specific miRNAs are significantly reduced in SMN1mut motor neurons. In particular, the expression levels of miR‐9 and miR‐9* (two miRNA species processed from the same hairpin) were reduced up to 15‐fold. miR‐9 is relevant to motor neuron pathology, as noted above and as demonstrated by the fact that it has neuron‐specific expression and that it is down‐regulated in SMN1‐deficient motor neurons. The mechanisms through which miR‐9 acts downstream of SMN1 and through which a specific subset of SMA phenotypes is regulated by miR‐9 should be further investigated.These animal models, which do not properly metabolize miRNA, showed a neuromuscular phenotype and neuropathological features that resemble those of SMA, including a loss of motor neurons, damage of the ventral horns of the spinal cord, alteration of the structure of the end plate, and atrophy and denervation of myofibres. The first modifications in animal function were detected at 2 months of age. At 4 months, both electromyography (EMG) and histopathological analysis demonstrated motor neuron cell loss. Interestingly, the neurofilament heavy subunit (NEFH), which is involved in the degeneration of motor neurons in other motor neuron diseases such as ALS, was overexpressed in the miRNA‐deficient motor neurons, supporting its key role in determining the development of the SMA phenotype. Intriguingly, this subunit is a target of miR‐9, one of the most abundant miRNAs in the CNS, and a key regulator of axonal extension and branching in neurons et al. Wang et al. et al. SMN2 splicing to allow production of a large quantity of full‐length protein, normalized miR‐9 levels in skeletal muscle but not in the spinal cord, further supporting miR‐9's potential utility as a biomarker. Higher levels of miR‐9 were also detected in the serum of SMA mice, and were reduced by morpholino treatment that up‐regulated SMN; these miRNA level changes occurred much earlier than the changes in level in the spinal cord and skeletal muscle. miR‐9 levels were also shown to be increased in the serum of SMA type II and, to a lesser extent, in type III patients, who showed levels that were intermediate between SMA type II patients and healthy controls.Catapano Overall, the studies concerning miRNA‐9 expression in SMA suggest that miR‐9 levels are significantly altered by the reduction of the SMN full‐length protein. miR‐9 expression can be down‐ or up‐regulated depending on the SMA cells or tissues; it is likely down‐regulated in the CNS/motor neurons and up‐regulated in other non‐neuronal cells and in the blood. However, knockdown of SMN in a motor neuronal cell line resulted in miR‐9 up‐regulation Muscle involvement in SMA patients is related not only to skeletal muscle denervation secondary to spinal motor neuron defects but also to disruption of the myogenic program determined by SMN deficiency miR‐206 regulates the processes of motor axonal growth and muscle connection after acute nerve injury by influencing the expression of fibroblast growth factors (FGFs) and brain‐derived neurotrophic factor (BDNF), which are key elements of motor neuron regeneration.HDAC4), with consequent increase of fibroblast growth factor binding protein (FGFBP1) After acute nerve injury in mice, miR‐206 is up‐regulated and promotes distal axon regrowth and muscle reinnervation through inhibition of the mRNA of histone deacetylase 4  In SMA models, interestingly, the increase in miR‐206 levels in muscle delays neurodegeneration, despite not being able to completely rescue the integrity of motor neurons The authors of this study used the SMNΔ7 mouse model to analyse the correlation between miRNA‐206 levels and NMJ architecture. They demonstrated that the quadriceps, a muscle affected earlier in this SMA model, shows a morphological pattern characterized by an increase in atrophic fibres, a fibre type disproportion with a reduction of type II fibres, and an accumulation of neurofilaments in the pre‐synaptic terminal of the NMJs. Furthermore, molecular investigation showed that miRNA‐206 also has an effect in regulating the HDAC4‐FGFBP1 pathway. In fact, as mentioned above for wild‐type rodents, miRNA‐206 up‐regulation determines the HDAC4 protein reduction and consequent increase in FGFBP1 mRNA. This pathway has a neuroprotective effect and increases re‐innervation of muscle endplates. Overall, miR‐206 may play a significant protective role in NMJs and muscle and could represent a possible as yet unexplored therapeutic target for SMA.Treatment with oligonucleotides to increase SMN does not significantly modify miRNA‐206 levels in SMA I mice, either in the spinal cord or in skeletal muscle, but does normalize its serum levels It is intriguing that miRNA‐206 is commonly dysregulated in both SMA and ALS. In both of these disorders, miR‐206 has been shown to be able to partially delay the neurodegeneration process. miRNA 206 is capable of modulating the expression of several target genes that could represent several common molecular pathways underlying both ALS and SMA, thus representing potential therapeutic targets for these diseases.in vitro and might interfere with radial neuronal migration in the embryonic mouse neocortex in vivoet al. Another miRNA highly represented in the CNS and with a putative role in SMA disease is miR‐132. Its role is mainly in the modulation of neuronal dendritic outgrowth and synaptic function Studies of miRNA expression demonstrate a different miRNA profile in primary SMA cortical neurons with respect to control tissues Specifically, researchers have found high levels of miR‐183 in neurites of SMN‐deficient neurons and demonstrated how miR‐183 up‐regulation is able to suppress axonal growth Moreover, it has been demonstrated that the translation of mechanistic target of rapamycin (mTOR) is regulated by miR‐183 through its direct binding to the 3′ UTR In vivo experiments have demonstrated the possibility of restoring it by inhibiting miR‐183. This inhibition also has functional consequences, as demonstrated by the fact that inhibition of miR‐183 in the spinal cord in a SMA mouse model resulted in an increase in median survival as well as motor function improvement In SMN‐deficient neurons, the local axonal translation of mTOR appears to be reduced. Recently, it has been demonstrated that miR‐335‐5p, which is known to be able to control differentiation and self‐renewal of mouse ES SMNΔ7 SMA mouse model, comparing them to WT‐derived NSCs. While several characteristics remained the same, such as the ability to form neurospheres and the expression of specific regional and self‐renewal markers, SMNΔ7 NSCs had an altered cell cycle distribution as well as an increased proliferation rate compared to WT‐NSCs. These differences in proliferation may be observed because in SMNΔ7 NSCs, the expression of certain miRNAs, such as miR‐100‐5p and miR‐335‐5p, is reduced, further highlighting the potential role of miRNAs in SMA pathology Luchetti and his group in vitro model for genetic disorders, because they offer the important possibility of studying genetic diseases directly in human cells that are not accessible in live patients, such as motor neurons.In the past decade, there has been growing interest in utilizing induced pluripotent stem cells (iPSCs) as an In vitro models of SMA using human iPSCs have already been described et al. In a recent study, Murdocca Using quantitative reverse transcription PCR (qRT‐PCR), it was possible to demonstrate that while the expression of miR‐335‐5p is almost equivalent between SMA and WT iPSCs, it begins to significantly differ at both 14 and 22 days of differentiation. After 14 days, miR‐335‐5p appears to be down‐regulated more than twofold in SMA versus WT cells, and after 22 days, the difference is even more pronounced. This evidence suggests that miR‐335‐5p may be involved in the process of differentiation of iPSCs towards early motor neurons These new results regarding the correlation between down‐regulation of miR‐335‐5p in differentiating cells and SMA are important, as they suggest an involvement of this specific miRNA in SMA pathology specifically in cells that are differentiating towards motor neurons.As previously reported, at the iPSC stage there is no difference in miR‐335‐5p expression, while the difference becomes more significant after 2 and 3 weeks of differentiation. This evidence deserves further in‐depth analysis in order to better understand how miR‐335‐5p down‐regulation is involved in SMA precursor differentiation and, most importantly, its possible correlation with SMA phenotype.in vitro model was created using wild‐type embryonic rat spinal motor neurons infected with lentiviral shRNA specific for down‐regulating SMN (shSMN). Both Western blot and qRT‐PCR analyses were used to evaluate SMN knockdown. After 6 days, these methods demonstrated an 80% and 75% reduction, respectively, in SMN protein levels The Sahin group n = 17) with increase in several of their putative mRNA targets. The expression of miR‐431 was very high, while a number of its putative target mRNAs were considerably down‐regulated in motor neurons with reduced SMN levels. It has been previously described that miR‐431 is expressed in the brain as well as in the spinal cord during embryonic development Through the integration of miRNA/mRNA profiles, it was possible to detect a number of dysregulated miRNAs , which was also increased, it was possible to establish that the mechanisms underlying the miR‐431 increase may include its augmented primary transcription. Moreover, Wertz wth Fig. . TherefomiR‐375 has two important functions: it contributes to the promotion of the acquisition of a motor neuron phenotype and protects neurons from apoptosis after DNA damage.et al. investigated which miRNAs were regulated by REST using Rest‐null mouse ESC, in which normally suppressed miRNAs should be highly activated in vitro model of spinal motor neuron development, Bhinge et al. discovered that miR‐375 is highly activated during spinal motor neurogenesis and that its expression is specific to MNs, indicating an essential role for miR‐375 in motor neuron development.During development, miR‐124 promotes neurogenesis through RE1‐silencing transcription factor (REST) silencing miR‐375 promotes motor neuron differentiation through silencing PAX6 and cyclin D2 (CCND2) transcript expression, both of which are direct targets of miR‐375. This silencing enhances motor neuron differentiation The timing of REST silencing is fundamental. In fact, in order to allow the formation of post‐mitotic spinal motor neurons, miR‐124 must silence REST activity and miR‐375 must suppress PAX6 at specific time‐points The second major function of miR‐375, the protection from apoptosis, is mediated by reduction of tumour suppressor p53 protein levels p53‐mediated neuronal apoptosis has been described in various neurodegenerative disorders, including ALS and SMA et al. observed that in SMA motor neurons, p53 levels were remarkably high while miR‐375 levels were extremely low Bhinge The possible role of miR‐2 in SMA pathogenesis has recently been demonstrated.In mice, miR‐2 acts as a negative regulator of m2R (a muscarinic acetylcholine receptor important for neurons) and as an inhibitor of cholinergic MN synaptic release et al., using a C. elegans model, reported that the reduction of SMN levels can cause neuromuscular junction (NMJ) dysfunction in motor neurons and suggested that dysregulation of neurotransmission may represent another pathological mechanism in SMA Recently, Patrick O'Hearn C. elegans SMN orthologue SMN‐1 causes mir‐2 and consequently GAR‐2 (C. elegans m2R orthologue), miR‐2 dysregulation and NMJ defects. Increasing in C. elegans the Gemin3 orthologue MEL‐46 modifies miR‐2 expression and ameliorates NMJ defects.According to their model, loss of the GAR‐2 and m2R are functionally conserved, as activation of these pre‐synaptic receptors by acetylcholine in different species results in hyperpolarization and decreased NMJ acetylcholine release across species, and several treatments that block m2R are currently available to treat other conditions.In a SMA mouse model, m2R levels showed an increase of 50% compared to controls, and pharmacological inhibition of m2R by methoctramine was able to rescue MN phenotype and to overcome MN axon outgrowth defects.Collectively, these results suggest that m2R up‐regulation in SMA at early stages may contribute to MN dysfunction, resulting in overactive neurotransmission and that therapies that target miR‐2 expression can modify disease evolution.et al. specifically investigated miRNA expression and secretory profiles in SMA astrocyte models, and they demonstrated that miR‐146a was the only miRNA that was up‐regulated in vitro with synthetic miR‐146a molecules can mimic SMA pathogenesis and induce motor neuron loss. Moreover, miR‐146a inhibition rescues the SMA phenotype The precise mechanisms that lead to selective motor neuron loss in SMA are currently under investigation, but it is well known that extrinsic influences, such as those arising from astrocytes, may also contribute to SMA pathogenesis. Among the different mechanisms suggested, altered expression of miRNAs in astrocytes has recently been highlighted. Sison The critical role of the SMN protein in miRNA biogenesis and processing confirms the importance of miRNAs in SMA pathogenesis Overall, miRNAs have multiple functions and appear to be fundamental for neuronal survival. However, the expression of miRNA is highly variable in different neuronal cells and in different stages of cell development. In fact, each neuronal subtype is characterized by a specific miRNA profile that changes over the course of the development, maintenance and regeneration phases. Their highly specialized morphology and function make motor neurons strictly dependent on precise miRNA functioning and regulation.One of the main questions in the miRNA/SMA field is how to interpret miRNA specificity for diseases, as miRNAs are involved in several functions related to neuronal involvement. The link between miRNA disruption and selective motor neuron death likely resides in their targets.For example, miR‐9 alteration leads to reduced down‐regulation of heavy neurofilaments, a pathogenic process that specifically involves motor neurons. In fact, neurofilament accumulation has been supported by several studies as one of the more likely causes of selective motor neuron degeneration. The neurons that are most prominently affected by the accumulation of neurofilaments are the largest neurons with the longest axons, which normally contain abundant neurofilaments. Indeed, cytoskeletal abnormalities may augment the susceptibility of neurons to other insults, for example excitotoxicity, so that multiple elements culminate in the disease The miR‐183/mTOR pathway regulates local axonal translation and axonal growth, which are fundamental in motor neurons. Interestingly, miR‐183 partially rescues the neuronal phenotype induced by SMN loss, and can be an additional target besides the modulation of the mTOR pathway.Also miRNAs which are specifically altered in astrocytes, such as mi‐146, can influence motor neuron development due to their high dependence on extrinsic influences.Current knowledge confirms the importance of changes in miRNA expression, especially in early disease stages in the miRNA–mRNA regulatory network in the pathogenesis of SMA. Although several pathways, targets and intersections have now been determined, a more detailed understanding of the transcriptome networks in both healthy and diseased motor neurons is fundamental to establishing further understanding of the pathogenesis and mechanisms that lead to selective motor neuron susceptibility.Despite significant progress in the understanding of SMA pathogenesis, definition of the biomarkers for this disease is still lacking. With promising therapies progressing through clinical development, there is an urgent need for the definition of molecular biomarkers that could be fundamental to performing patient classification, following disease evolution and better defining the efficacy of therapeutic approaches using minimally invasive procedures.Overall, miRNAs hold an interesting diagnostic and prognostic potential as non‐invasive biomarkers for SMA. In fact, miRNAs are relatively stable in accessible biofluids, such as blood and CSF, and can be detected with accessible and feasible laboratory methods. Moreover, multiple samples can be captured in order to follow disease evolution over time.Among the miRNAs highlighted in this review, miR‐9, miR‐132, miR‐206, miR‐183 and miR‐375 could represent possible biomarkers for SMA, while miR‐183 and miR‐375 may play additional roles in contributing to the specificity of SMA determination, based on the data presented above in each miRNA subchapter. The major critical challenges remain the possible inconsistencies in the results due to human subject variability and technical issues related to the relative fragility of miRNAs. In general, one of the critical aspects is the specificity of this kind of biomarker.The recruitment of large cohorts of patients could increase the power of biomarker studies and promote the advancement of the field.i) overexpressing them with miRNA mimics or (ii) down‐regulating them through antisense oligonucleotides (anti‐miRNAs) Over the last several years, given their specific ability as broad transcriptomic regulators, miRNAs have been proposed as promising therapeutic targets for neurodegenerative diseases, including motor neuron disorders. Schematically, there are two possible approaches to modulating miRNAs: , or with the use of delivery tools such as nanocapsules Among the miRNAs presented in this review, miR‐9, miR‐206, miR‐183 and miR‐375 could potentially be explored as therapeutic targets for SMA.via gene/molecular therapy. However, miR‐9 is a key player in many processes within many cells. Its expression is tightly regulated and can vary significantly between each phase of motor neuron regeneration, being first up‐regulated and later down‐regulated. Thus, artificially mimicking these complex variations with pharmacological or gene therapy without inducing significant off‐target effects may be difficult. Indeed, the findings of miR‐9 down‐regulation are not consistent in all data sets in the literature, and conflicting results have been observed depending on the SMA model/cell type considered. In any case, the testing of miR‐9 as a therapeutic target warrants further investigation in pre‐clinical SMA models.miR‐9 represents one of the most interesting targets because it is the one with the most relevance to motor neuron function. The vast majority of experimental evidence suggests that miR‐9 is generally down‐regulated in SMA spinal cords. Thus, one possible therapeutic strategy could be its up‐regulation miR‐206 may play a significant protective role in NMJs and muscles and represents a potential unexplored therapeutic target for SMA.Regarding miR‐183, its expression in the spinal cord of an SMA mouse prolonged survival and improves motor function of Smn‐mutant mice via inhibition of p53, from increased susceptibility to DNA damage‐induced apoptosis Finally, miR‐375 can confer motor neuron protection by shielding motor neurons, miRNA therapeutic strategies can also be used to directly up‐regulate SMN levels.zebrafish that the expression of anti‐smn1 miRNAs in motor neurons reproduced most of the hallmarks observed previously in the ubiquitous knockdown model. In addition, smn1 knockdown in zebrafish motor neurons is sufficient to induce late‐onset motor neuron degeneration It has been recently demonstrated in SMN1 or SMN2 miRNAs in mammalian motor neurons is the first step to further developing this idea.The demonstration of the expression of anti‐miRNA dysregulation likely has an important role in SMA pathogenesis and in determining the selective vulnerability of motor neurons. In particular, miRNA activity seems to be fundamental for the survival and function of post‐mitotic spinal motor neurons. miRNA homeostasis disruption in murine spinal motor neurons contributes to the appearance of typical hallmarks of SMA. Different studies have shown altered expression of specific miRNAs in SMA, and several of these experiments have highlighted the same miRNAs in different SMA models. The miRNAs related to neuronal function are those most frequently identified as aberrantly expressed, even if the exact molecular mechanisms in which they are involved are largely undefined. Further investigations of this perspective will allow increased understanding of how miRNAs intervene in SMA pathogenic mechanisms. The expression profile of each miRNA can vary in different tissues, such as muscle, serum and spinal cord, and can even reflect the severity of SMA, being more altered in SMA I than SMA II and SMA III.in vitro and in vivo experiments have demonstrated the neuroprotective potential of certain miRNAs, this would be an important topic to be assessed in subsequent studies for implementing novel SMA therapies. For instance, miRNA can be modified by RNA therapy, including antisense oligonucleotides, miRNA mimics and antagomirs, and could represent a promising potential therapeutic target for SMA in association with SMN‐targeted therapies.Therefore, miRNAs can be used not only as biomarkers of pathology but also as markers of disease severity and progression, as well as of response to effective experimental therapies in future clinical trials. Furthermore, the therapeutic potential of miRNAs must be thoroughly explored. Given that The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in this manuscript.The authors confirm that there are no conflict of interests.


Achieving World Health Organization (WHO) recommendations for postnatal care (PNC) within the first few weeks of life is vital to eliminating early mother–to–child transmission of HIV (MTCT) and improving infant health. Almost half of the annual global deaths among children under five occur during the first six weeks of life. This study aims to identify uptake of three PNC visits within the first six weeks of life as recommended by WHO among South African mother–infant pairs, and factors associated with uptake.We analyzed data from three facility–based, nationally representative surveys  primarily designed to determine the effectiveness of the South African program to prevent MTCT. This analysis describes the proportion of infants achieving the WHO recommendation of at least 3 PNC visits. Interviews from 27 699 HIV–negative and HIV–positive mothers of infants aged 4–8 weeks receiving their six week immunization were included in analysis. Data were analyzed using STATA 13.0 and weighted for sample ascertainment and South African live births. We fitted a multivariable logistic regression model to estimate factors associated with early PNC uptake.Over half  = 59.0–60.3) of mother–infant pairs received the recommended three PNC visits during the first 6 weeks; uptake was 63.1% (95% CI = 61.9–64.3) amongst HIV exposed infants and 58.1% (95% CI = 57.3–58.9) amongst HIV unexposed infants. Uptake of early PNC improved significantly with each survey, but varied significantly by province. Multivariable analysis of the pooled data, controlling for survey year, demonstrated that number of antenatal visits (4+ vs <4 Adjusted odds ratio (aOR) = 1.13, 95% CI = 1.04–1.23), timing of initial antenatal visits , place of delivery , and infant HIV exposure  were the key factors associated with receiving recommended PNC visits.Approximately 40% of neonates did not receive three or more postnatal care visits in the first 6 weeks of life from 2010–2013. To improve uptake of early PNC, early antenatal booking, more frequent antenatal care attendance, and attention to HIV negative women is needed. Global efforts to improve the health of children under one year of age have succeeded in reducing preventable infant deaths, yet infant mortality remains high in sub–Saharan Africa, especially in settings of high HIV prevalence ,2. NeonaSouth Africa, as a country with slowly reducing infant mortality and static perinatal mortality, within the context of the greatest HIV epidemic in the world, suffers in the dual and associated burdens of child mortality and HIV . AlthougWhile South Africa demonstrates commitment to adopting and implementing prevention of mother to child transmission (PMTCT) guidelines –12, therNational statistics regarding early PNC focus on attendance to the PNC visit timed before 6 days post–delivery. Estimates from 2014–2015 indicate that about 74.3% of mothers and infants achieved this visit, falling slightly short of the national target of 80% [This paper aims to describe the current status of population–level achievement of at least three PNC facility–based visits during the first six weeks postpartum among infants achieving the 6–week immunization visit in South Africa, and to identify associated factors. This analysis identifies areas of potential intervention to improve progress toward achieving the global WHO recommendation in the interest of optimizing neonatal health.Data for this secondary data analysis were collected through the “Evaluation of the effectiveness of the national Prevention of Mother–to–Child Transmission programme on infant HIV in South Africa” surveys conducted in 2010 (June–December 2010), 2011/12 (August 2011–March 2012), and 2012/13 (October 2012–May 2013). Public sector health facilities were sampled using multi–stage, probability proportional to size methodology, and the study was powered to produce nationally–representative results of MTCT. More detailed information about the survey is available in previous publications .For this study, mother/caregiver–infant pairs were enrolled during the infant’s first postpartum immunization visit at six weeks since national coverage of this visit is known to be very high in South Africa . InfantsTrained fieldworkers (nurses) interviewed mothers and caregivers about socio–demographic information, infant health and feeding practices, and postnatal care. Mothers were also interviewed about their HIV status and testing practices, and care received during the antenatal and intrapartum periods. Infant dried blood spot samples (iDBS) were taken at the time of the interview (4–8 weeks postpartum) to detect the presence of maternal HIV antibodies and infant HIV infection. Responses to the question on facility–based PNC were based on maternal recall; however, fieldworkers cross–checked information recalled by the mother with information documented in the infant’s Road to Health booklet. Gestational age was abstracted from the infant Road to Health booklet.This particular analysis was restricted to 27 699 mothers (not other caregivers) with available PNC information, regardless of the availability of infant HIV test results . Data were weighted to adjust for sampling methods, sample ascertainment, and South African live births. We performed frequencies to assess the proportion of infants who achieved at least 3 PNC visits in a facility within the first six weeks post–delivery vs those who had fallen short of the recommended visits. The six–week immunization visit was included as a PNC visit.We performed frequencies to describe socio–demographic characteristics of the mother–infant pairs, as well as frequencies to examine factors related to antenatal and delivery care. HIV exposure was defined by maternal self–reported HIV status during pregnancy and labor. To determine whether variables predicting uptake of early PNC were different by HIV exposure status, we tested the associations between each variable of interest and the PNC outcome variable separately among HIV exposed infants and among HIV unexposed infants. When it was established that the same associations were seen regardless of HIV exposure status, we pooled these data. Justification was also established to pool the data from all survey years when significant changes were not seen among independent variables over time.To estimate uptake of early PNC as an odds ratio adjusted for all covariates, we fitted a multivariable logistic regression model using purposeful selection of variables . ParametThe protocol for the cross–sectional survey was approved by Human Subjects Division at the United States Centers for Disease Control and Prevention within the Center for Global Health and the institutional review board of the South African Medical Research Council. Mothers provided written informed consent prior to the onset of the interview.Within the population included for this analysis, one third  of infants were HIV exposed based on maternal self–reported HIV status (The mean age of mothers was 26.1 years (standard deviation: 6.3) and the majority of them were single . Most women reported that their highest level of education attended was grades 8–12 . Over half of the women were multiparous . Over half of the women  were able to correctly identify all modes of MTCT.About 60%  of those included in the survey achieved at least 3 PNC visits in the first 6 weeks of life, with a median of 3 PNC visits per infant .A higher proportion of infants who were HIV exposed achieved 3 PNC , compared to HIV unexposed infants   were at least 30% more likely to receive 3 or more early PNC visits compared to infants in Gauteng Province, with those in Free State Province almost seven times more likely to receive recommended PNC  compared with Gauteng Province residents.Mothers who delivered in a clinic vs a hospital, who achieved at least four ANC visits, or who booked an ANC appointment before 12 weeks gestation were far more likely to achieve at least 3 recommended early PNC visits . However, those who received support during pregnancy and delivery from a community health worker (CHW) were less likely than those who did not receive this support to have at least 3 early PNC visits . Those who delivered via Caesarean section had lower achievement of early PNC visits than those with vaginal delivery .Infants who required hospitalization during the first six weeks of life were more likely than those who were not hospitalized to have 3 early PNC visits . Similarly, those born prematurely  were more likely to achieve the recommended 3 PNC visits than those born at full term . Infants classified as Non–Black  were more likely to achieve 3 early PNC visits compared with infants classified as Black .The WHO recommends that all mother–infant pairs should receive three postnatal care visits during the first 6 weeks of life. Our analysis of data from three nationally representative population–based surveys demonstrated that approximately 60% of infants achieving the 6–week immunization visit access the WHO recommended number of postnatal care visits in the first six weeks of life. Access to early postnatal care visits significantly increased between 2010 and 2012.This study was the first of its kind to assess achievement of the WHO recommendation for early PNC at a national level in South Africa, and to track changes in access to early PNC over time (2010–2013).Our findings are consistent with the levels of early PNC uptake documented by the 2014–15 District Health Barometer which, using routine data, demonstrated 74.3% achievement of the first PNC visit within the first 6 days post–delivery [Although approximately 40% of infants did not receive the required number of early PNC visits, our finding that the majority (59.6%) of infants received three or more PNC visits indicates a much higher early PNC coverage in South Africa, an upper middle income country, compared with rural Tanzania and Ghana, low income and lower middle income countries respectively . These cAchievement of recommended interactions with the health system along the continuum of care has been shown to arise from a combination of health system, community, household, and individual–level determinants –26. ThisAdherence to WHO recommended early PNC was highly influenced by province of residence, with those residing in Gauteng Province less likely than those in almost every other province to achieve at least 3 early PNC visits. Eastern Cape Province was the only province that had lower achievement of at least 3 PNC visits than Gauteng Province. Populations in Gauteng and Eastern Cape Provinces are highly mobile and thus may demonstrate reduced consistency in attendance to health visits ,27,28. PAn infant’s exposure to HIV was found to be predictive of meeting recommended early PNC visits, with HIV exposed infants being more likely to receive at least three PNC visits than HIV unexposed infants. Since the early 2000s, South Africa has aggressively adopted each updated WHO recommendation for PMTCT, and has update postnatal care guidelines –35. ProgOur findings show that a woman’s compliance with antenatal recommendations were predictive of early PNC uptake for her infant, as seen in similar studies ,20. UptaReceipt of support by a CHW during pregnancy, delivery, and/or postnatal care had the opposite effect on uptake of early PNC. CHW have been increasingly adopted in South Africa as a method to improve access to important health messages and services through lower–level cadres of health workers who are more mobile within the community ,39. ResuWomen who delivered in a clinic were more likely than those who delivered in a hospital or outside of a facility to achieve three early PNC visits. While any facility delivery  has been observed in similar studies as a predictor of PNC ,20 compaInfants delivered through Caesarean section vs vaginal delivery were less likely to achieve 3 early PNC visits. This is surprising due to the high risk nature of Caesarean delivery, yet may be explained by longer duration in the hospital reducing the need for early PNC visits. This further supports the finding that hospital delivery was associated with lower uptake of early PNC visits.The positive relationship between health knowledge and health seeking behavior by mothers has been shown in multiple studies ,44 and wContrarily, mothers with a high level of education  were less likely than those with a low achievement of education (grade 1–7) to seek at least 3 PNC visits during the first 6 weeks. Studies examining relationships between knowledge, risk perception, and health behaviors indicate that low understanding of a disease may influence perception of high risk and, in turn, perception of high risk motivates health seeking behavior –47. ThisPremature infants are at higher risk for adverse health in early infancy and thus are recommended to receive more than three early PNC visits, so this finding that premature infants achieve at least 3 visits at a higher frequency than full–term infants is consistent with expectations . Our finWomen aged 25–34 were more likely than adolescent women (19 and younger) to achieve recommended PNC. Related literature is inconclusive about the relationship between maternal age and health seeking behavior, however our finding is reflective of observations from studies in similar settings indicating that younger and less experienced women are less likely to adhere to recommended health care ,51. AtteRespondents from the 2011/12 and 2012/13 survey years were much more likely to succeed in reaching the recommendation for early PNC than the 2010 survey year. This suggests a pattern of improvement in compliance with WHO recommended early PNC over time, likely due to the influence of non–governmental organizations partnering with the South African government to implement the PMTCT program. From 2008 to 2010 South Africa revised national PMTCT guidelines, adding specification of a postnatal visit within 3 days of delivery in addition to the 6 week visit specified within guidelines from 2008 and prior. This change may have enhanced health messaging focused on the postnatal period to influence an increase in attendance to early PNC.Our results highlighted the need to reinforce messages about the importance of completing all health behavior and health visit recommendations along the continuum of care, regardless of infant HIV exposure status. Lessons should be taken from provinces achieving higher uptake of PNC (such as Free State Province and North West Province) to improve uptake in lower performing provinces (such as Gauteng Province and Eastern Cape Province). Messages about the importance of PNC should target those who do not attend at least four ANC, those who initiate ANC after 12 weeks gestation, those who deliver outside of the clinic setting, and those with demographic characteristics predictive of lower PNC utilization.As a secondary data analysis, the original survey was not designed to specifically answer the question addressed by this analysis. By the nature of this study design, responses to the questions about health behavior were retroactive and may have introduced information bias; however there is no reason to believe that maternal memory was affected differentially between the group who met the recommended number of PNC visits and those who did not. Infants that died before 4–8 weeks and those who were severely ill were excluded from the study based on the survey sampling method, even though their cases could have been some of the most informative regarding the importance of PNC.Only the responses of mothers were included in this study (excluding responses from other caregivers (3.2% of survey participants). Mothers were excluded from this analysis if they did not provide information about number of PNC visits, however the proportion missing PNC responses was only 6.93% of mothers. . The potential effects of missing data were accounted for in the process of developing weights to analyze this data set as representative of the national population of mothers in South Africa. For some variables, the proportion of “Do not know” or “No answer” responses was greater than 10%, thus interpretability is limited. We did not ascertain information regarding the timing, contents, and quality of PNC visits, thus limiting the extent to which we could assess the productiveness of the care received. The location where ANC, delivery care, and PNC were received was not collected within this study, thus our ability to explain patterns in PNC uptake by district were limited to province of residence. This study focused on health care received in the formal health system and did not include information about home care or traditional care.While South Africa has not yet officially adopted the WHO recommendation for 3 early PNC visits as the national standard of practice, uptake of these important visits is high and coverage appears to have increased between 2010 and 2013. Uptake of at least 2 PNC visits, the current national standard in South Africa, is very high (over 94%), indicating strong implementation of this guideline—an encouraging prospect for potential implementation of the WHO recommendation for 3 early PNC visits. South Africa seen only mild improvements in infant survival over the past decade and has not seen improvements in neonatal survival. Adoption of the global postnatal guideline for 3 early PNC visits, or adoption of more community–based postnatal care, may be the next necessary step toward achieving optimal neonatal and infant health outcomes. Our findings suggest that efforts to encourage a woman’s compliance with global recommendations along the continuum of care–such as facility–based delivery, timely initiation of ANC, and achieving 4 or more ANC visits–increase the likelihood of her infant completing the recommended number of early PNC. Messages from the health system should be strengthened during ANC, labor and delivery, and PNC to ensure that all expectant and breastfeeding mothers understand the minimum recommended visits along the continuum of care and work with health care providers to achieve them. These messages should specifically target women who have been non–adherent to at least one recommended health behavior or interaction with a facility.As HIV prevention moves toward elimination of maternal to child HIV transmission and reduction in neonatal mortality, South Africa must strengthen the implementation of policies and programs aimed at achieving high utilization of early PNC in order to ensure the health and well–being of new generations during the postnatal period and beyond.


The development of therapeutics is often characterized by promising animal research that fails to translate into clinical efficacy; this holds for the development of gene therapy in glioma. We tested the hypothesis that this is because of limitations in the internal and external validity of studies reporting the use of gene therapy in experimental glioma.We systematically identified studies testing gene therapy in rodent glioma models by searching three online databases. The number of animals treated and median survival were extracted and studies graded using a quality checklist. We calculated median survival ratios and used random effects meta‐analysis to estimate efficacy. We explored effects of study design and quality and searched for evidence of publication bias.CI 1.53–1.67). Study quality was low and the type of gene therapy did not account for differences in outcome. Study design characteristics accounted for a significant proportion of between‐study heterogeneity. We observed similar findings in a data subset limited to the most common gene therapy.We identified 193 publications using gene therapy in experimental glioma, including 6,366 animals. Overall, gene therapy improved median survival by a factor of 1.60 (95% As the dysregulation of key molecular pathways is characteristic of gliomas, gene therapy remains a promising treatment for glioma. Nevertheless, we have identified areas for improvement in conduct and reporting of studies, and we provide a basis for sample size calculations. Further work should focus on genes of interest in paradigms recapitulating human disease. This might improve the translation of such therapies into the clinic. The prognosis for patients with malignant glioma remains poor despite extensive experimental and clinical research.However, as is the case in many areas of biomedical research, the promising results from preclinical animal models have failed to be translated effectively into the clinic.Several narrative reviews have described the promise of gene therapy in malignant gliomaWe hypothesized that limitations in the internal and external validity in animal modelling lead to an overstatement of efficacy of gene therapy in animal models of glioma. Here we use systematic review and meta‐analysis to describe the relationship between study design, study quality and the reported improvements in median survival, and the fidelity with which limitations in the animal data were taken into account in the design of human clinical trials.Relevant full publications and meeting abstracts were identified by electronic searching of three online databases  using the search terms: <gene therapy> AND <<glioma> OR <brain tumour> OR <brain tumour> OR <brain neoplasm> OR <glioblastoma> OR <ependymoma> OR <astrocytoma> OR <oligodendroglioma>>. Results were limited to animal studies with no language or date limits. Following comments raised in the review, we tested whether the term <gene therapy> was overly restrictive by searching for <glioma> and <thymidine kinase> to determine whether additional studies would be identified.The inclusion criteria were adapted from previously published criteriain vitro, and whether the study provided evidence of infection, replication and expression in the tumour in vivo.A 9‐item quality checklist was adapted from the CAMARADES  published criteriaWe extracted data for median survival time, the number of animals in both the treatment and control groups and details of study design characteristics ). We grouped gene therapy into broad categories of angiogenesis, DNA repair, immunomodulation, oncolytic and “other”. We calculated an effect size for each comparison by dividing the median survival in the treatment group by the median survival in the control group to give a median survival ratio.A preliminary stratification identified that studies that used a prodrug in the treatment group (to activate the gene therapy) but not in the control group were associated with significantly larger effects than those using prodrug in both groups, suggesting biological activity of the prodrug alone. Therefore, studies using a prodrug were only included where the same prodrug was also used in the control group. Some studies reported more than one control group. We considered the most appropriate control group to be the one that was most similar to the treatment group, while offering no functional gene therapy, according to a hierarchy that prodrug with non‐functioning vector was preferred to prodrug with saline, which was preferred to prodrug only. Where a prodrug was not used, the hierarchy was non‐functioning vector in preference to saline‐only in preference to no treatment. For studies in which more than 50% of animals survived till the end of the experiment, we used the last time point at which survival was reported to give a conservative measure of median survival.Individual study effect sizes were weighted by the number of animals for that comparison, as there is no inherent measure of variance available for median survival data. Where a control group served more than one treatment group we corrected the weighting of the study by dividing the number of animals in the control group by the number of treatment groups served. Effect sizes were calculated on log‐transformed data2 distribution with n − 1 degrees of freedom (where n is the number of strata). We performed stratified analyses on the complete dataset that included all gene therapies reported. We also performed analyses on a more homogenous subset of data that consisted of only the most common gene therapy—herpes simplex virus thymidine kinase activated by ganciclovir (GCV). To allow for multiple comparisons  we adjusted our significance level to p < 0.0019 using Bonferroni correction for 26 tests of statistical significance in the same dataset. We used funnel plotting,We used stratified meta‐analysis to estimate the significance of differences between groups of studies by partitioning heterogeneity and using the χhttp://doi.org/10.5061/dryad.bs8c4.To estimate the statistical power of a typical experiment, we calculated the median observed values for median survival in the control and treatment groups and the median numbers in each group and used the “stpower exponential” functional in Stata. Data extracted from studies included in the review and the results of meta‐analysis and publication bias assessment are available from the Dryad Digital Repository: We identified 3,860 publications, of which 208 met our inclusion criteria . While the approaches to gene therapy were diverse, the broad category of gene therapy used did not account for a significant proportion of the observed heterogeneity . Thymidine kinase was the most common gene therapy  followed by IL‐4 (23 comparisons), IL‐2 (21 comparisons) and tumour necrosis factor‐related apoptosis inducing ligand . Across all 127 gene therapies there was a significant improvement in the median survival time , and there was significant between‐study heterogeneity (χin vitro and 90 (46.6%) provided evidence of infection, replication or expression in the tumour in vivo. No publication reported a sample size calculation and the median number of animals in each of the control and treatment groups was eight (IQR 6–10). In 90 publications it was reported that animals were killed when they manifested signs reflecting disease of a certain severity , and in the remainder of studies the circumstances of death (euthanasia or spontaneous) were not reported.The median number of quality checklist items reported was three of a possible nine (interquartile range (IQR) 3–4; Appendix S4); 193 (100%) publications were in peer‐reviewed journals, 170 (88.1%) reported the number of tumour cells implanted, 23 (12.4%) randomly allocated animals to group, 7 (3.6%) blinded the assessment of outcome, 133 (68.9%) had a statement of compliance with animal welfare regulations, 15 (7.8%) had a statement of a potential conflict of interest, 24 (12.4%) reported the number of animals originally inoculated with the tumour and 41 (21.1%) gave an explanation of any treated animals excluded from the survival analysis. A total of 139 studies (72.0%) provided evidence of successful transduction and gene expression The aggregate number of quality checklist items scored or the reporting of randomized group allocation did not account for between‐study heterogeneity Figure A. Only sBias introduced by an excess of small, imprecise studies was suggested with asymmetry in the funnel plot Figure B and Egg2 = 24.1, df = 3, p < 0.0019; Figure 2 = 53.0, df = 3, p < 0.0019). The greatest estimates of effect were observed where retroviruses and adeno‐associated viruses were used. Similarly, selection of cellular delivery system also accounted for significant between‐study heterogeneity . Bone marrow‐derived stem cells and neural stem cells were associated with the largest effect sizes.The method of gene delivery  had a significant impact on the reported effect size. Cells and virus‐producing cells were associated with the largest treatment effects  with median survival ratio being 50% higher (95% CI 35 –65%). A further 17 comparisons involved prodrugs not usually associated with the gene therapy used . The most commonly used prodrugs were GCV (40 comparisons) and 5‐FC .Several gene therapy paradigms were reported that usually included the concomitant use of a prodrug; 67 comparisons reported such combinations, for instance thymidine kinase with GCV, cytosine deaminase (CD) with 5‐fluorocystine (5‐FC). Furthermore, these same gene therapies were sometimes used without the appropriate prodrug (35 comparisons). Gene therapies using a prodrug were associated with an increased effect size if that prodrug was used  when compared with the same gene therapies where no prodrug was used  also accounted for a significant proportion of the between‐study heterogeneity. We observed a direct relationship between the number of doses and effect size where up to five doses were given followed by a fall in efficacy where six or seven doses were administered , and the timing of treatment had a significant impact on reported efficacy  than mice , and a convention of seeking power of 80 to 90% in well‐conducted clinical trials. As a guide for future investigators in Appendix S5, we present the relationship between statistical power and number needed per group for the above comparison and for a range of median survival ratios that might be sought for in future experiments.2 = 49.9, df = 29, p < 0.0019; I2 = 69%).We performed a sensitivity analysis for the most common gene therapy paradigm . Thymidine kinase gene therapy was associated with a significant increase in median survival  and between‐study heterogeneity comparable with the complete dataset  and we did not find an association between the number of study quality checklist items scored and efficacy Figure A. Small Only one study used more than one dose of gene therapy, only three used a route of delivery other than intracranial inoculation and only three reported efficacy in animals with co‐morbidity; these data were not analysed further. There was no effect of the method of gene delivery, the vector used Figure D, the ti2 = 40.4, df = 7, p < 0.0019; Figure 2 = 24.4, df = 2, p < 0.0019), with largest effect observed in studies reporting spontaneous death  (95% CI 1–15%) higher compared with studies killing animals when they became symptomatic).The tumour line itself did however account for some of the observed heterogeneity in this dataset . Our threshold for significance testing was conservative (Bonferroni correction for 26 stratifications), and while testing for an effect of study quality on treatment efficacy did not reach this significance threshold (p = 0.024), an association is likely. Only 12% of studies reported randomization and less than 4% reported the blinded assessment of outcome. As two thirds of studies met either three or four checklist items and none met more than seven, we have not been able to ascertain whether high‐quality studies give lower estimates of efficacy. This contrasts with findings from other models of neurological disease, where the prevalence of reporting of such factors is higher and where there is evidence that high‐quality studies report lower estimates of efficacy.We found no differences between broad categories of gene therapies so we analysed all therapies together, with a sensitivity analysis using only the most commonly used therapy. It is likely that certain individual therapies were substantially more or less effective than the overall estimate but 79% of these were tested in fewer than four experiments (Appendix S3), and in these circumstances meta‐analysis contributes little that cannot be gleaned from an examination of primary data. Nonetheless, thymidine kinase was more efficacious than average . While this supports there being differences in efficacy between treatments there are alternative explanations—for instance differences in the animal and glioma models used. We found differences in efficacy associated with different vector‐delivery mechanisms, routes of gene therapy delivery, numbers of doses and delays to treatment. Delivery of gene therapy using stem cells was associated with greatest efficacy in both datasets, and this might relate to more effective delivery to the required site of action, more sustained gene expression or other factors. In the complete dataset, intracranial delivery  and multiple dosing (particularly four or more doses) were most effective. In contrast to the difficulties of transfecting tumours in humans with glioma, we were surprised that, taken together, systemic therapies were as efficacious as those delivered intracranially.We also found that features of the disease models used were widely variable and significantly affected the observed efficacy. A total of 40 different glioma cell lines were used, originating from humans, mice and rats. No studies used mice with spontaneously occurring or induced glioma cells and only one reported the use of cells recently extracted from human glioma specimens. Median survival ratios for different cell lines ranged from 1 to 8.56 . This suggests that cell line selection is one of the most important factors for investigators to consider during experimental design. As prominent were the species used and their immune status. Rats and mice were used in both datasets, and roughly one third of the animals used were immune‐suppressed; this was associated with greater efficacy. The immune system plays an important role in the body's response to glioma, so the immune‐compromised mouse may not be an ideal model of human disease.Consistent with the modelling of other neurological conditions, these data suggest that the efficacy of gene therapies in glioma is characterized by heterogeneity in both the disease model used and the treatment delivery. Further, we observed a low prevalence of reporting of measures to reduce the risk of bias (see Appendix S4 for details), possible overstatement of efficacy in studies at risk of bias, and publication bias.There are a number of potential weaknesses to this approach. Foremost, meta‐analysis is essentially an observational technique. When we stratify by various study design characteristics and measures of study quality or bias, it may be that there are other unknown differences that are the cause of observed differences. For this reason we have been rigorous in only investigating sources of heterogeneity that we prespecified in a protocol. Our findings demonstrate association rather than causality; the observation that treatments delivered using cellular vectors are more effective than those using viruses or molecular approaches may be due to differences in gene delivery efficiency between these routes, or alternatively it may be that different types of interventions are more suited to different vector systems, and that these interventions differ as a class in their efficacy, or a difference in other study design characteristics shown to be associated with heterogeneity. For this reason our findings should be considered hypothesis‐generating only. However, further high‐quality preclinical studies can be used directly to test any hypothesis of interest.Secondly, summarizing a field of research (as we have attempted here) requires by necessity the combination of data from experiments that are, to a greater or lesser extent, dissimilar. In these circumstances, the meaning of a summary estimate of efficacy across a range of studies has limited relevance other than to provide a yardstick of the magnitude of effect that might be expected of an intervention. However, we believe the statistical explanation of the differences between studies, especially in the face of the substantial heterogeneity observed here, is valid and important. This rationale is the basis on which we have deemed it appropriate, corroborated by the evidence that broad groups do not differ in efficacy, to collate all gene therapies into a single analysis—following this, heterogeneity was accounted for by measures of study design rather than the gene therapy paradigm itself. In support of these findings, we ran a separate analysis on the most commonly used gene therapy paradigm, thymidine kinase with GCV; in general we found that the same factors relating to study design and internal and external validity of these experiments had a significant impact on efficacy. Given the presence of such diversity in study design, our findings on study quality, randomization, controlling, experimental design and the consistency of these between the two datasets provide validation of our approach.Our findings are only as reliable as the data on which they are based, and we have shown that this is likely to be confounded by poor study quality and by publication bias. However, our search strategy was broad, accepting conference abstracts and publications in languages other than English, so our approach is likely to provide a better summation of what is known than narrative reviews—which are subject to the same potential biases—and the impact of selection bias is likely to have reduced to the minimum possible. We used the term “gene therapy” in our search rather than detailing specific genes so that we might identify the largest number of studies, not just those where the use of that gene was already widely known. The term “gene therapy” may have been unduly restrictive, but searching for “thymidine kinase” and “glioma” in Pubmed—without further limitations—identified only one additional study, inclusion of data from which had no impact on the overall efficacy estimate of efficacy. Finally, we have attempted to minimize false positives in our statistical tests by adjusting for multiple comparisons.The use of meta‐analysis to summarize median survival data is not well established. Because we did not have access to data for individual animals we could not pool hazard ratios as has been suggested for clinical studies,In this systematic review and meta‐analysis, we have presented substantial evidence that features relating to the risk of bias and experimental design of animal studies significantly affect the observed efficacy of gene therapy for experimental glioma. However, another issue yet to be addressed is that of construct validity; there is evidence from these data that translation of gene therapy from experimental to clinical glioma has failed because the experimental models do not recapitulate human disease.in vitro cultures. These models may be more characteristic of human disease and provide genetic heterogeneity not seen with traditional glioma models;The optimized conditions that are generally created for animal studies do not recapitulate the heterogeneity of human glioma patients, as these studies are all undertaken on homogeneous rodent populations. While techniques such as meta‐analysis seek to counteract this homogeneity, the breadth achieved still does not reflect that of the human population. For example, of these animals, many are immune‐compromised, a feature that is uncommon in clinical practice. We have observed a wide variety of glioma models used, but those most commonly selected GL261, U87 and C6) tend to grow quickly and relatively non‐invasively into large discreet spheres,7 and C6 The large between‐study heterogeneity observed in our data suggests that the efficacy of gene therapy is very variable, depending at least in part on the features we have described and perhaps to a greater degree than is observed in other glioma treatments.The statistical power of the experiments included in this meta‐analysis was low, and no study reported a formal sample size calculation. Improving the statistical power of gene therapy experiments may help to reduce heterogeneity by reducing the chances of type II  errors and also the predictive value of positive studies where the prior probability of success was low.In spite of these limitations, gene therapy treatment for experimental glioma appears to be effective when initiated at later time points, and efficacy was observed against cells of human origin. Both these features are pertinent to successful treatment for human disease, as tumours are only discovered after a period of growth. Gene therapy was effective when given either intracranially or systemically although this does not seem to correlate with clinical experience. Efficacy appeared to be highest when five doses of the gene therapy were given, but—given the difficulties of systemic administration in humans—it may not be practicable to implant locally more than once. Exploration of the most effective number of treatments was not addressed in any of the included publications and is an important topic for further animal study.As such, we recommend that future preclinical research focuses on genes ratified in both animal and human glioma cell biology, using orthotopic tumours and intracranial gene delivery over one or more doses; they should ideally use stem‐like cancer cells or patient‐derived xenografts, or at least provide a rationale for tumour model selection, in non‐immune‐compromised animals where possible. These studies should be registered, randomized, blind assessment of outcome and provide a sample size calculation in all but hypothesis‐generating experiments in accordance with ARRIVE guidelines.Gene therapies are associated with substantial increases in median survival in animal models of cerebral glioma, but because of concerns about the internal , external (study design) and particularly construct (recapitulation of human disease) validity of this literature, these findings should be interpreted with caution. Our analysis suggests that a strategy based on multiple treatments with viral or cellular vectors expressing genes of interest delivered locally, tested in the potentially more relevant tumour models described recently, represents a plausible approach to developing gene therapies for glioma. However, the issues of study quality and construct validity of existing models that we have identified here should be addressed in further animal studies if such strategies are to have the best chance of success.The authors disclose no potential conflicts of interest for this article.Appendix S1. References used in systematic review.Click here for additional data file.Appendix S2. Study characteristics.Click here for additional data file.Appendix S3. Collated gene therapies.Click here for additional data file.Appendix S4. Study quality scores.Click here for additional data file.Appendix S5. Number of animals per group needed to achieve a set statistical power.Click here for additional data file.


Myelin‐Nets). The Myelin‐Nets were built from quantitative Magnetization Transfer data—an in‐vivo magnetic resonance imaging (MRI) marker of myelin content. The synchronicity of the variations in myelin content between anatomical regions was measured by computing the Pearson's correlation coefficient. We were especially interested in elucidating the effect of age on the topological organization of the Myelin‐Nets. We therefore selected two age groups: Young‐Age (20–31 years old) and Old‐Age (60–71 years old) and a pool of participants from 48 to 87 years old for a Myelin‐Nets aging trajectory study. We found that the topological organization of the Myelin‐Nets is strongly shaped by aging processes. The global myelin correlation strength, between homologous regions and locally in different brain lobes, showed a significant dependence on age. Interestingly, we also showed that the aging process modulates the resilience of the Myelin‐Nets to damage of principal network structures. In summary, this work sheds light on the organizational principles driving myelination and myelin degeneration in brain gray matter and how such patterns are modulated by aging.Networks of anatomical covariance have been widely used to study connectivity patterns in both normal and pathological brains based on the concurrent changes of morphometric measures  between brain structures across subjects Evans, . However Despite myelin density being sparser in gray matter compared to white matter, this tissue component plays an important role in insulating local axons that connects neighboring and distant areas. It introduces a boost in axonal conduction velocities making it possible for brain areas to interchange information in optimal synchrony. It has been proved that the impaired cognitive ability, disorganized thinking, mood disorders or hallucinations associated with psychiatric illness  might result from slowed or desynchronized impulse conduction between cortical regions due to deficiencies of myelin wrapping the axons Fields, . ExperimThe analysis of the covariance between regional estimates of morphometric features derived from magnetic resonance images (MRI) is well established . A recent study has shown that microscopic changes within brain tissue could lead to the spurious detection of apparent morphological change  . Based on the graph theory framework we explore, for the first time, the topological organization of the Myelin‐Nets and its modulation by age. Two age groups  were compared to describe age‐related Myelin‐Nets topological changes in an elapsed time of 40 years. The continuous aging trajectory of the topology of the Myelin‐Nets was also investigated after the fifth decade of life. This approach could be considered as another step for revealing basic principles of gray matter organization, and how these are modified by aging processes.In this study, we use in vivo measures of MT to investigate patterns of correlations in myelination change between gray matter regions. In particular, we aim to study how myelination, a key microstructural feature of brain tissue, changes synchronously among spatially distant regions to form characteristic networks of myelin covariance , using a 64‐channel RF receive head coil and body coil for transmission. On visual inspection study participants showed neither macroscopic brain abnormalities, that is, major atrophy, nor signs of overt vascular pathology  of grade 2 or more by the Scheltens rating scale  acquisitions with predominantly Magnetization Transfer‐weighted (MTw: TR/α = 24.5 ms/6°), proton density‐weighted (PDw: TR/α = 24.5 ms/6°) and T1‐weighted (24.5 ms/21°) contrast  and Matlab 7.11 . The MT maps were computed as described in Helms, Dathe, and Dechent  maps from the acquired data was implemented with the Voxel‐Based Quantification toolbox . These data were released under the Creative Commons Attribution‐Non‐Commercial (CC BY‐NC) with no end date. The anatomical T1‐weigthed MRI scans originate from the OASIS project (http://www.oasis-brains.org/) and the labeled data were provided by Neuromorphometrics, Inc. (http://Neuromorphometrics.com/) under academic subscription.At every gray matter voxel (in subject space), the probability of belonging to a specific anatomical structure is provided. From above, a maximum probability label maps are calculated at all gray matter voxels (in subject space) which are labeled according to the structure of maximum probability. Finally  and different sliding windows (p > .05) in the aging trajectory study . Therefore, the global MT was not regressed out as confounding variable. Global MT effect subtraction in principle may highlight interregional differences but at the same time will affect genuine covariance patterns  without the possibility of estimating the introduced bias  being the number of gray matter regions)—or Myelin correlation matrix—contains elements ijC that are the value of the Pearson's correlation between regions i and j. Self‐connections were excluded, implying zeros in the diagonal of this symmetric matrix.We defined a connection as the statistical association in MT values (a surrogate measure of myelin) between each pair of brain regions for a parcellation scheme of 114 anatomical structures. The statistical similarity or synchronized co‐variations in myelination between two regions was measured by computing the Pearson's correlation coefficient across subjects Figure . Hence, It is important to point out that a partial correlation analysis could not be used in our case because the sample size was not large enough for a robust estimation of this measure .kR were calculated for each of the 2000 correlation matrices so that their elements ijC were set to 1 when |ijC| > kR and 0 otherwise. This procedure normalizes the networks to have the same number of nodes and edges, enabling the examination of the relative network properties obtained for each group.In the next step, we obtained for each age group Nboot = 2000 bootstrap samples of the connectivity matrix by selecting a random subset of subjects with replacement using the classical bootstrapping procedure described in , the relations or connections between them  are based on anatomical data, they can be taken as possible biomarkers of underlying biophysical mechanisms. These Myelin‐Nets are unweighted because all edges are assumed to indicate relations of equivalent strength between nodes, and undirected, simply summarizing symmetric relations (such as correlations) between nodes.It is important to note here that this is a mathematically derived network, whose connections do not explicitly reflect anatomical or physiological mechanisms in the brain. However, because these “Networks of myelin covariance” (Myelin‐Nets architecture and how efficiently the information of myelin fluctuations is “exchanged” over the network (in terms of the graph theory). Importantly, these networks cannot be interpreted in terms of temporal causality. First, because myelination co‐variations are assessed across subjects and second, because we are using Pearson correlations, measures that do not provide directional/causal information on the interactions between pairs of nodes.We used graph theory to study the myelin co‐variation networks in the Young‐Age and Old‐Age groups. This mathematical treatment allows us to characterize the age‐related changes of global and local phenomena observed when myelination in any structure fluctuates concurrently with myelination in its neighborhoods and other distant brain regions of the network. In other words, graph theory gives us a framework to explore the Myelin‐Nets when the most important regions (hubs) are virtually attacked. In the following, these measures will be defined with the traditional interpretation of general networks. However, their usefulness as relevant descriptors of anatomical brain states will become apparent in the next sections.In particular, we analyzed the following global network attributes: cluster index, local and global efficiency, and characteristic path length. To describe the nodal properties of the network we computed the betweenness centrality attribute that allowed us to identify the network hubs. Additionally we carried out a “Targeted Attack” study to evaluate the resilience of the 2.7Ci of a node “i” is defined as the number of existing connections between the node's neighbors divided by all their possible connections. It is a measure of the inherent tendency of nodes to cluster into strictly connected neighborhoods  i and j, and it is defined as the mean of geodesic lengths dij over all pairs of nodes.The characteristic path length dij is defined as the number of edges along the shortest path connecting nodes i and j  between age groups across brain lobes we used the anatomical subdivision of the brain in lobes proposed by Tzourio‐Mazoyer et al. . We asse2.12Network properties (NP) of the myelination correlation matrices were computed for each sparsity degree values and different bootstrap samples in each age group. Thus, we had a set of Nboot = 2000 NP curves for each network property showing the change in NP with the sparsity degree. The area under the curve was computed for each network attribute to contrast the global behavior of these attributes  construction of the empirical bootstrapped distribution of differences by subtracting the corresponding bootstrap samples between groups; (b) definition of the statistical significance level: a 95% confidence interval (CI) (biased corrected percentile bootstrap CI) Efron,  of the e2.13Myelin‐Nets properties was applied to explore network robustness differences between groups.We calculated a surrogate measure of the resilience of the Myelin‐Nets against targeted attack. In a simulated targeted attack study, network hubs are removed one by one in order of betweenness centrality (NBC). Each time a node was removed from the network, the size of the largest connected component was recomputed. We defined the robustness parameter as the area under the curve showing the size of the relative largest connected component versus the number of nodes removed  AAL atlas with N = 90 structures  Gordon atlas  using a weighted contribution of the data points in the windows to the correlation coefficient at the age window centers  and the maximum was 0.6 . The maximum age difference between the youngest and oldest subjects within a window was 9.16 years (around the “window age” = 74 years old), the minimum 3.29 years and the mean 5.3 years.To uncover dynamical properties of the Myelin‐Nets: clustering index, characteristic path length, local and global efficiency, global connectivity, and the connectivity strength between homologous regions. Additionally a study of the aging trajectory of the normalized betweenness centrality (NBC), as nodal network property, was performed.We focused our attention on the main global network attributes of the Myelin‐Nets attributes were fitted as a function of the “window age” using a polynomial model. The order of the polynomial fitting was determined by the Akaike's Information Criterion (AIC) . Aging was found to have a heterogeneous effect on myelination across gray matter regions . The peak in myelination was found to take place between 40 and 50 years of age for most of brain anatomical regions . The modeled age‐dependence of the regional MT values was detrended from the original values before calculation of the correlation matrices.This motivated the use of a second‐order polynomial model to fit the age dependence of the MT data for the detrending (using “polyfit.m” subroutine implemented in MATLAB 2015a), with significant coefficients (3.2p < .05) higher correlations than the Young‐Age group. However no statistical difference in global connectivity was found between groups   and Precentral Gyrus (PrG.R) for the Young and Old Age groups respectively. The structures common to both groups were left superior parietal lobule (SPL.L), left and right supplementary motor cortex , right superior frontal gyrus (SFG.R), and the middle frontal gyrus (MFG.R). Interestingly, the most connected region in each group is not present in the other.3.5Myelin‐Nets, defined as having a Normalized Betweenness Centrality  over 1.5  values for the characteristic path length, clustering index Figure , and locIn contrast, the Young‐Age group depicted higher global efficiency Figure , panel a3.7Myelin‐Nets increases with age: the Old‐Age group showed higher resilience after “simulated attacks” to the Myelin‐Net hubs  for a period of 27 years from 48 years old to 75 years old. The best polynomial fit of the age trajectories was obtained with order n = 3, (based on AIC) for all NPs. In each case the polynomial coefficients were statistically significant (p < .05). The clustering index and local efficiency showed , with two principal maxima between 50–55 years and 65 years old  with maxima around 50 and 65 years for PCgG.R right and PCgG.L, respectively.On the other hand, PCgG.R and PCgG.L  and Old‐Age (panel B) groups and the different gray matter parcellations .Figure Table 4Myelin‐Net). The Myelin‐Net showed well‐structured topological patterns strongly modulated by age. Our findings can be summarized as follows: (a) Aging modulates the correlation strength between homologous regions but not the global myelin correlation strength. (b) The topological attributes of the Myelin‐Nets depict a strong aging modulation. (c) Aging shapes the distribution of the central regions (hubs) of the Myelin‐Nets. (d) The aging process increases the resilience of the Myelin‐Nets to damage to the network's hubs. These findings are discussed in the following subsections.In this study, we provide empirical evidence that myelination processes in gray matter are spatially correlated, irrespective of the distance between brain regions. When pooling together all possible covariations between pairs of structures, a nonrandom network of concurrent changes emerged: the network of myelination covariance  common normal/pathological vulnerabilities; (b) neurodevelopment; (c) genetic factors  and theoretical modelling need to be conducted to support or disprove the impact of these putative factors and mechanisms on correlations in myelination between gray matter regions.4.2The study of myelination processes is crucial to understand brain anatomy and function. Here we extended the standard analysis of exploring myelin distributions across the gray matter  to a second order approach, where the amount of myelin in each anatomical region is no longer relevant . It is this approach that allows the estimation of the interactions between structures by the Pearson correlation coefficients. It has been proven that such type of analysis reveals hidden organizational properties of brain anatomy that are difficult to detect through classical univariate approaches  onwards showed a minimum at 48 years Figure , panel EIt is important to point out the observed strong age modulation in myelination covariance between homologous regions. The covariance of homologous structures was found to increase significantly with age. This suggests that interindividual differences in myelination due to neurodevelopmental factors are less coordinated than the putative compensatory, demyelination/remyelination and shared vulnerability processes that become prominent in later life. Myelination changes in old age are noticeably more synchronized and spatially extended than in young age, in line with the scaffolding hypothesis of the STAC theory of aging  and left superior parietal lobe (SPL.L)). The presence of SMC as a network hub has been described previously at different ages. In the case of the elderly connectome (76–94 years), this structure is preserved as a hub  in Precuneus Left (PCu.L) and Left Posterior cingulate gyrus (PCgG.L) structures . The NBC of PCu.L/PCgG.L was lower/higher in the Old‐Age group. Both regions are part of the Default Mode Network and impose high metabolic demand on the brain . According to the graph theory, this increase could be generated by the establishment of new densely connected local clusters which may generate an uncontrolled “flow of information” through the entire network. This measure is related to the local efficiency of the “information flow” of the networks and its abnormal performance could be attributed to shared vulnerability and compensatory mechanisms. The increased intralobe myelin covariation in 4 out of 7 lobes might explain the larger clustering index in old age.The increasing “local efficiency” was accompanied by a “global efficiency” decline in Old‐Age. In terms of the graph theory, these changes affect network performance pointing to a higher “wiring cost” for parallel “information transfer” between anatomical regions. The weakening of the global efficiency is explained by the larger characteristic path length present in old age.Myelin‐Nets.The aging trajectory in both “clustering index” and “local efficiency” showed a minimum at 48 years old that is related to global myelin correlation strength changes and the cause producing that this attribute has a minimum value at the same age. The maxima of these two network properties and the maximum/minimum in characteristic‐path‐length/global‐efficiency are synchronized in some extend revealing an unbalance between segregation and integration processes in Myelin‐Nets. Networks were “attacked” at key nodes of the highest betweenness centrality (network hubs). We found that the Old‐Age group showed higher resilience to these simulated attacks. A possible explanation for this finding may rest on the observed increase in symmetry and the presence of aberrant local circuits leading to increased “local efficiency” with age. Also the redistribution and the higher number of hubs in the Old‐Age group favored a higher resilience to target damage. Attacks to hub regions in the Young‐Age group produced devastating consequences in the integrity and stability of the network, where regional specialization is well defined.In our “Targeted Attack” analysis, we attempted to further investigate the age‐associated changes in the resilience of the Myelin‐Nets and Networks of anatomical covariance have common topological features. For both brain networks, correlations between homologous regions are the highest and are modulated by age. Also, the global network attributes—characteristic path length, clustering index, and local efficiency—share the same age modulation across networks  would shed light on the common principles driving the correlated myelination processes and anatomical  connectivity. A separate study, preferably based on Myelin‐ and WM‐Nets extracted from the same cohort, is necessary to highlight the interplay between these processes. However, some similarities and differences can be highlighted in light of the main anatomical connectivity findings reported in the literature. First, in both myelin and anatomical networks, the precuneus and posterior cingulate gyrus are observed as centrally connected regions, independently of age  some of the identified age‐related differences in 5In this article, we provide empirical evidence that myelination processes are spatially correlated across cortical gray matter. The patterns of myelination covariance show specific topological organization revealed using a graph theoretical approach. A number of specific correlated myelination phenomena were strongly modulated by age. In particular, we brought evidence that aging increases synchronicity between homologous regions. Our results are an important step toward elucidating the organizational principles behind the dynamics of the human brain anatomy across the lifespan. In particular, myelination processes are at the cross‐way of several psychiatric and neurodegenerative brain diseases and are therefore crucial for their understanding.The authors have declared that no conflict of interests exists.Additional Supporting Information may be found online in the supporting information tab for this article.Supporting InformationClick here for additional data file.