Nos1, as well as alteration in IGF-1 pathway including decreased circulating and brain IGF-1, decreased circulating IGFBP3, and increased Igfbp3 brain mRNA expression. This study suggests that growth-associated microbiota can influence early neuron and oligodendrocyte development and that this effect may be mediated by effects on neuroinflammation and circulating IGF-1.Poor growth in the Neonatal Intensive Care Unit is associated with an increased risk for poor neurodevelopmental outcomes for preterm infants, however the mechanism is unclear. The microbiome has increasingly been recognized as a modifiable environmental factor to influence host development. Here we explore the hypothesis that the microbiome influences both growth phenotype and brain development. A germ free mouse transfaunation model was used to examine the effects of preterm infant microbiotas known to induce either high growth or low growth phenotypes on postnatal brain development. The microbiome which induced the low growth phenotype was associated with decreases in the neuronal markers NeuN and neurofilament-L as well as the myelination marker MBP when compared to the microbiome associated with the high growth phenotype. Additionally, poor growth phenotype-associated microbiota was associated with increased neuroinflammation marked by increased  The early assembly of microbiota has been shown to shape host development of the gut3, endocrine system4, lung5, liver7, bone8 and brain10. More specifically, this window of early gut microbiota development parallels nervous system development across prenatal and early postnatal stages. Brain development such as neurogenesis, neuronal migration, axonal and dendritic growth, synaptogenesis, and myelination begins early in prenatal life and continues postnatally11. The concurrent, early, postnatal window of both microbiome and brain development is a critical time period for investigation to determine whether an interplay between these developmental processes exists.Around the time of birth and thereafter, newborns are rapidly colonized with a community of microbes that starts the process of gut microbiota assembly and continues during the first 2–3 years of life13. These deficits are considered to be the consequence of complications associated with prematurity which impairs brain development14. Furthermore, while critical development for full term infants occurs in utero under limited influence of microbiota, for preterm infants it largely occurs ex utero shaped by environmental influences including the development of the microbiome. The microbiome of the preterm infant is shaped by the NICU environment including instrumentation, frequent antibiotic use, multiple care givers, and a hospital environment. The combination of postnatal insults and developmental immaturity of both the gut microbiota and the nervous system makes preterm infants a unique population in which to study the impact of initial microbiota colonization and development on brain development.Preterm infants, particularly those born at less than 32-week of gestational and/or with a birth weight less than 1500 g, are at risk for adverse neurological outcomes including later cognitive and behavioral deficits15. We and others have previously demonstrated that the microbiome of preterm infants changes over time with distinct clustering at less than 2 weeks of life17. Thus, to study the effects of these early microbial colonization patterns on host development, samples chosen for transfaunation were from human preterm infants prior to two weeks of life with different growth rates. Our data showed that a preterm infant growth phenotype could be transferred to mice via the microbiota. Mice colonized with microbiota from a preterm infant with good growth ) had significantly more weight gain (20%) postnatally than mice colonized with microbes from a preterm infant with poor postnatal growth ). We demonstrated that MPI-L mice had increased intestinal inflammation using nuclear factor-kappa beta (NF-κB) activation as a marker and by investigating production of NF-κB-mediated inflammatory cytokines at both the intestinal and serum level when compared to MPI-H mice. These differences were seen at baseline, even without a secondary insult and demonstrated that the gut microbiota not only has local intestinal effects, but also has systemic effects including inducing a systemic inflammatory response and influencing overall growth.Recently, our group demonstrated that germ free (GF) mice colonized with two different human preterm infant fecal samples yielded distinct growth phenotypes20. We hypothesized that early microbiota development also influences brain development contributing to long term neurodevelopmental potential. Specifically, we postulated that microbiota associated with impaired growth phenotypes adversely influence brain development. We thus investigated several potential mechanisms including growth factors, neuroinflammation, brain fatty acid compositions, and microbial metabolites by which microbiota may influence both growth and neurodevelopment.Poor early postnatal growth after preterm birth is clinically associated with short term morbidities in the neonatal intensive care unit as well as long-term adverse neurological outcomes. Although the mechanism is not fully understood, contributing independent factors include severity of illness and nutritional delivery24. Patients with mutations in the igf-1 gene or in the igf1r gene have severe somatic growth failure, microcephaly, and severe cognitive impairment25. Specifically in preterm infants, IGF-1 circulating levels are positively correlated with birth weight, length, and head circumference26. Furthermore, circulating IGF-1 has specifically been shown to be an important regulator of brain cell proliferation, apoptosis, myelination, neurogenesis, maturation and differentiation27. Studies in GF mice have reported that microbiota-regulated IGF-1 levels in mice drive juvenile growth28. Since IGF-1 regulates brain development and microbiota-mediated IGF-1 has been shown to regulate growth, we hypothesized that the two growth phenotype associated-microbiomes could regulate both somatic growth and brain development through IGF-1.Deficits in growth hormones such as circulating insulin-like growth factor 1(IGF-1) contribute to adverse outcomes in preterm infants including poor postnatal growth29. Neuroinflammation can give rise to common neonatal brain injuries such as periventricular leukomalacia (PVL) and hypoxic-ischemic encephalopathy30. These neuroinflammation-related brain injuries are associated with neurological disorders such cerebral palsy, autism and schizophrenia32 and can contribute to long term adverse neurological outcomes such as motor and cognitive deficits34. Gut microbial cell wall components continually interact with the innate immune system to induce the secretion of cytokines. In our previous study15, pro-inflammatory mediators such as IL-1β, TNF, and IFNγ were elevated in the serum of mice colonized with microbes from the poor growth infant, reflecting a systemic effect by the microbiome. However, the effect of the microbiota on neuroinflammation such as IL-1β and TNF was not investigated at the time.Preterm infants are at high risk for neuroinflammation resulting from exposure to maternal, fetal, and neonatal infection and non-infectious insults35. Brain accumulation of monounsaturated fatty acids such as oleic acid (C18:1) and tetracosenoic acid (24:1), which is elongated from C18:1 ω-9, is very high during the early postnatal period when myelin is being formed most rapidly36. The incorporation of these fatty acids in the fetal brain occurs mainly during the last trimester of pregnancy and continues to the end of two years of life38 thus preterm infants are at high risk for PUFA deficiency and this deficit-related impaired visual and cognitive functions42.Long-chain polyunsaturated fatty acids (PUFA) such as arachidonic acid (AA) and docosahexaenoic acid (DHA) are essential structural and functional constituents of cell membranes and are required for the growth and function of the brain and vascular systems43. SCFAs have been implicated in the pathogenesis of several neurodegenerative diseases44, with perhaps the strongest evidence that SCFAs have roles in the gut-brain axis coming from a study demonstrating that SCFA-producing bacteria or butyrate itself can decrease the blood-brain barrier (BBB) permeability in GF mice45.Other trajectories of microbiota-originated communication with the brain might involve their metabolites such as short chain fatty acids (SCFAs) generated by enteric bacterial fermentation48. However, its impact on early postnatal brain development remains elusive. The cause of poor neurodevelopmental outcome in preterm infants is certainly multifactorial; however a key distinctive of the microbiome is that it is modifiable for an individual infant in a time frame parallel to brain development. In this study, we introduced two growth phenotype-associated microbiotas to pregnant GF mice and investigated the influence of these two distinct microbial communities on the postnatal brain development of the offspring. We further investigated multiple potential mechanisms by which microbiota can affect brain development and demonstrated that the microbiota’s effects may be partially mediated by circulating IGF-1 levels and markers of neuroinflammation.The microbiome has increasingly become a focus of studies of host development and functions49. Increased expression of neurofilament proteins (NFs), which provide support for axonal growth, is closely associated with continued growth of axons and axon diameter50. To examine whether microbial colonization impacts early neuronal development, we measured the expression levels of NeuN and NF, markers of early development in the brain. In our study, we colonized pregnant GF mice at E15 with the human microbiome of interest, and the newborn pups were not separated from the colonized mother until weaning thus the offspring acquired a microbiota reflecting the human microbiome of interest from contact with the mother15. The fecal samples were from the first two postnatal weeks in human preterm infants with two different growth rates (MPI-H and MPI-L) during their NICU course, and resulted in corresponding high and low growth phenotypes in the pup offspring15. In this study, western blot analysis of cerebral cortex homogenates with anti-NeuN antibody showed significantly increased levels of NeuN expression in MPI-H mice colonized with microbiota from a preterm infant with good growth compared with GF pups at two weeks of age  where OL-specific transcription factors such as Olig2 drive the transcription of genes required for differentiation52. Differentiated OLs myelinate axons of neurons to ensure rapid propagation of action potentials and provide metabolic support for axons. Myelin basic protein (MBP) is the major structural element of myelin and is essential for axon myelination, compacting, and wrapping and is developmentally regulated53. Protein expression levels tested by western blot demonstrated that cerebral cortex expression of NG2 was not statistically different among the three experimental groups at two weeks of age  is expressed by oligodendrocyte precursor cells (OPC) but not by any other mature neural cell-typeage Fig. . Expressage Fig. . NG2 andPI-L demonstrated significantly reduced MBP expression when compared to MPI-H mice  are the main excitatory and inhibitory neurotransmitters in the central nervous system, respectively. Together they are involved in over 85% of the synapses that underlie learning and memory, motor activity, sensory and many other functions in the mammalian cortex56. Serotonergic and dopamine signaling control mood, sleep, concentration, and motivation. Dysfunction and imbalance of these pathways can contribute to cognitive deficits58. It has been suggested that changes in serotonergic signaling may contribute to the altered anxiety phenotype in GF mice59. Since previous molecular and behavioral studies have implicated the gut microbiota in the development of neuronal circuits60, we studied the expression of synaptic transmission plasticity-related genes by quantitative RT-PCR  and decreased serotonin and dopamine pathway expression levels (blue) in Fig. PI-H.Glutamate and PCR Fig. . Microbi62. Neuronal nitric oxide synthase (NOS1) is a key enzyme implicated in neurotoxicity in the perinatal cortex64. As a potential mechanism by which different microbiota can affect brain development, we examined the overt inflammatory status in the developing brain. Our data showed that at two weeks of age, GF mice had significantly higher Il-1β and Tnf mRNA expression in the brain when compared to MPI-L and MPI-H mice   Fig. , C22:6 (AA) Fig.  and C18:AA) Fig.  at both 65. We found that fecal contents of acetic acid . At four weeks of age, MPI-L mice still had significantly lower circulating IGF-1 compared to MPI-H mice . In serum, the majority of the IGFs exist in a 150-kDa complex including the IGF molecule, IGF binding protein 3 (IGFBP-3), and the acid labile subunit (ALS). This complex prolongs the half-life of serum IGFs and facilitates their endocrine actions. We found that there was no difference in serum IGFBP3 levels among the mice at two weeks of age . These data suggest that poor growth-phenotype related microbiota is associated with reduced circulating IGF-1 and IGFBP3 levels in mouse pups.To understand the mechanisms by which different growth phenotype related-microbiota colonization resulted in different brain development phenotypes, we tested whether the effect of microbiota is mediated through circulating levels of IGF-1. Serum levels of IGF-1 measured by ELISA were significantly lower in GF and Mage Fig. , but at PI-L and MPI-H pups (at least p < 0.05) at two weeks of age . These data demonstrate that poor growth phenotype-associated microbiota resulted in decreased circulating and brain IGF-1, decreased circulating IGFBP3 and increased IGFBP3 brain levels when compared to good growth phenotype-associated microbiota.IGFBP3 antagonizes the local biologic effects of IGF-1 by having higher affinity for IGF-1 than the IGF-1 receptorups Fig. . At fourPI-L mice compared to GF mice  at four weeks of age. Liver Igf1 transcript levels were not affected by the different microbiota , providing direct evidence that there is a critical window in early life during which microbiota can influence brain development.Our study extends the growing body of research to support the view that normal gut microbiota plays a critical role in shaping brain functions77. Thus our data also suggests that early microbiota colonization associated with a poor growth outcome might pose neurological disadvantages for neonates by affecting neurotransmission pathways.Other impacts of microbiota on brain development observed in this study includes the complex and diverse alterations in gene expression in multiple neurotransmission pathways, including glutamatergic, GABAergic, serotonin and dopamine pathways as well as neurotransmitter transporters and ion channels. Even though the mechanisms by which microbiota affect these pathways are beyond the scope of this study, these findings provide evidence that microbiota can have diverse impacts on the brain. For instance, developmental changes in NMDA receptor composition at early postnatal ages may influence the balance of plasticity and stability that is critical for information processing and storage and precedes the associative learning79. A persistent systemic inflammatory response during a sensitive period of postnatal life in a hospital setting influences critical phases of myelination and cortical plasticity30. Our previous study demonstrated a systemic proinflammatory profile in mice colonized with microbiota from a preterm infant with poor growth15. Elevated proinflammatory cytokines have been associated with brain injuries in the developing neonatal brain81. However, even though phenotypic changes in brain development have been linked to systemic changes of proinflammatory cytokines, the underlying mechanisms that transfer systemic inflammation to the brain remains elusive29. Possible mechanisms by which peripheral cytokines might influence brain inflammation include the immature development of the BBB82 and interaction between TLR ligands and brain endothelial TLR receptors followed by activation of the downstream signaling to induce inflammation in the brain83. Perinatal neuroinflammation has been associated with neurotoxicity63 and dysfunctions of synaptic organization in the developing brain29. In animal models of neonatal meningitis, cerebral cortex and hippocampal expression of TNF, IL-1β and IL-6 were upregulated after S. Pneumonie or S. agalactiae infection in the neonatal rats84. We demonstrate that, even without induced active infection, different baseline microbiota colonization patterns result in distinct inflammatory profiles in the brain as evidenced by the elevated expression levels of Nos1 in MPI-L mice and Il-1β and Tnf in GF mice. Our data suggest that the effects of microbiota on neuroinflammation can be another mechanism by which microbiota affect brain development.Extremely preterm infants exposed to a prolonged systemic inflammatory response are at an increased risk for impaired neurodevelopment85. Homozygous Igf1 −/− mice at two months of age had reduced brain weights, white matter size and spinal cord due to the decreased numbers of axons and oligodendrocytes. Myelinated axons, the volume of the dentate gyrus granule cell layer, and the number of striatal parvalbumin-containing cells were also reduced86. Moreover, IGF-1 is very important in prenatal and early postnatal neurogenesis87 as increased IGF-1 levels result in increased numbers of total neurons in the cerebral cortex. In this study, we have demonstrated that colonization of microbiota from a human preterm infant with poor growth resulted in reduced serum levels and liver production of IGF-1. However, microbiota did not affect the local brain production of IGF-1 evidenced by the similar Igf1 transcripts in the brain across groups. Our data suggest that serum IGF-1, not locally produced IGF-1, may be the main contributor to the different brain IGF-1 levels in our three experimental groups. Furthermore, microbiota also affected the brain level of Igfbp3 mRNA, suggesting that microbiota may influence brain IGF-1 bioavailability.The effect of microbiota on serum IGF-1 levels could also contribute to the altered brain development. IGF-1 has been shown to play prominent roles in CNS development and maturationPI-L mice since the liver expression levels of Igf1 in MPI-L mice were significantly lower than that of GF mice. Modulation of liver production of IGF-1 by microbiota has been shown in several studies; however the extent of the influence is inconclusive. Schwarzer et al. report higher liver Igf1 transcripts in SPF mice compared with GF mice28. Yan et al. observed higher liver production of IGF1 in GF mice colonized with adult SPF microbiota but no transcript difference was detected8. Our study demonstrates that liver production of IGF-1 at early postnatal ages can be modulated by early microbial colonization. The associated reduced circulating IGF-1 levels contribute to the reduced brain IGF-1 levels in MPI-L mice and correlates with the delayed neuronal development and myelination in the cortex in these pups. Thus, early alteration of microbial colonization may modulate systemic IGF-1 levels that in turn might impact postnatal brain development.The effect of microbiota on liver production of IGF-1 may contribute to the decreased IGF-1 circulating levels in MIn conclusion, this study builds on our previous findings demonstrating that early microbiome colonization patterns influence growth trajectories, and suggests that colonization of different microbial communities influences brain development. The initial colonization of microbiota can therefore be a modifiable factor that affects brain development. Future studies on specific involvement of certain microbial communities and their metabolites in altering brain development and functions in early postnatal age are warranted and of clinical importance. Early optimization of microbial colonization at an early postnatal stage might benefit preterm infants to shape brain development and enhance long-term neurological outcomes.This study was designed to investigate the influence of early microbiota on the brain development using gnotobiotic mice transplanted with early microbiota from preterm infants. Subjects were recruited from the neonatal intensive care unit (NICU) at The Comer Children’s Hospital of the University of Chicago. The procedures were approved by the Institutional Review Board (IRB) at University of Chicago (protocol #14991B) and written informed consent was obtained from all patient parents. All methods in the study on humans were performed in accordance with the guidelines and regulations of the University of Chicago.15. Briefly, eight to nine week old pregnant GF mice were transfaunated with fecal samples of the preterm human infant donors on E15. Pups were born naturally and nursed by respective mothers until weaning. Early (<two weeks of life) preterm human infant microbiota as representative of the first microbiota to encounter the host were used in the transfaunation since our previous study showed distinct clustering of microbial samples prior to two weeks of life16. Corresponding to the growth phenotype, pups from GF dams transfaunated with fecal samples from an infant with poor growth were identified in this study as MPRETERM INFANT-Low (MPI-L), and pups from GF dams transfaunated with fecal samples from an infant with good growth were identified as MPRETERM INFANT-High (MPI-H).All animal procedures were approved by the Institutional Animal Care and Use Committee under the animal protocol No. 71703 and performed strictly in accordance with approved Animal Care and Use Protocols (ACUPs) at The University of Chicago. Germ free (GF) C57BL/6 J mice were maintained in the gnotobiotic facility of the Knapp Center for Biomedical Discovery at the University of Chicago and are routinely tested for microbes and parasites by the facility’s staff to ensure germ-free conditions. Colonization experiments were carried out as previously described® BCA assays  for protein concentration measurement. Equal amount of protein lysate was subjected to SDS-PAGE electrophoresis using Bio-Rad Criterion™ XT 4–12% Bis-Tris precast gels  and transferred to PVDF membranes using a semi-dry transfer system (Bio-Rad). The membranes were blocked with 5% nonfat milk (Bio-Rad) in Tris-buffered saline  with 0.1% Tween-20 (TBST) for an hour on a shaker at room temperature. The membranes were cut into pieces depending on the molecular weights of the proteins of interest and then incubated with respective primary antibodies in 5% NFM in TBST overnight at 4 °C. The membranes were washed four times for 10 min each time with TBST and then incubated with secondary antibodies for 1 h at room temperature. The chemiluminescent signal was developed using SuperSignal West Femto maximum sensitivity substrate (Thermo Scientific) and captured using a Molecular Imager® ChemiDoc™ XRS + imaging system (Bio-Rad). The density of each band was quantified with ImageJ  and normalized to GAPDH and presented as fold change relative to the control.Brain tissues were homogenized in ice-cold 1× RIPA lysis buffer , 0.5% (wt/vol) Sodium deoxycholate, 0.1% (wt/vol) SDS with protease inhibitors  and spun at 12,000 × g for 10 mins. Tissue lysates were then subjected to PierceBrains were obtained from mice at postnatal age of two weeks (pre-wean) and four weeks (post-wean) and embedded in OCT. Eight µm sections were cut with a cryostat and the sections were fixed in ice-cold methanol at −20 °C for 20 minutes. After washing with 1 × PBS for three times, the samples were permeabilized with PBS with 0.1% triton (PBST) for 15 mins at room temperature. The samples were then incubated with blocking solution (5% goat serum) in PBST for one hour at room temperature. Before primary antibody application, the tissues were circled using a hydrophobic barrier pen. The tissue sections were incubated with respective 50 µl of primary antibody dilution solution overnight at 4 °C. After wash with PBST for three times for 15 mins, the sections were then incubated with respective fluorophore-conjugated secondary antibodies for one hour at room temperature. The sections were counterstained with DAPI antifade mounting medium (Invitrogen) before coverslips were applied.® Plus Mini Kit . 500 ng of isolated total RNA was used to synthesize cDNA using RT2 First Strand Kit from QIAGEN. TaqMan probes and primers (Thermo Scientific) were used for gene of interests and the housekeeping gene Gapdh. Gene expression was normalized to the housekeeping gene and expressed as fold change of experimental controls.Total RNA from snap frozen brains and livers were isolated using the RNeasyNeuronal nuclei (NeuN), Oligodendrocyte transcription factor 2 (Olig2) and Neural/glial antigen 2 (NG2) antibodies were purchased from EMD Millipore . Myelin basic protein (MBP), neurofilament-Light chain (NFL), and GAPDH antibody were purchased from Cell Signaling Technology . Secondary anti-mouse-HRP and anti-rabbit-HRP antibodies were purchased from Santa Cruz Biotechnology, Inc. .® BCA assays (Thermo Scientific). All ELISAs were read with a Multiskan™ GO Microplate Spectrophotometer (Thermo Scientific) with PathCorrection protocol.Serum, brain, and liver samples were collected and processed for IGF-1and IGFBP3 measurement using Mouse IGF-I or IGFBP3 Quantikine ELISA Kit from R&D Systems Inc.  according to the manufacturer’s instructions, respectively. Equal amount of tissue lysates of brain, and liver were applied to ELISA plates after protein concentration measured by Pierce89. Briefly, after the addition of an internal standard (30 μg of heptadecanoic acid), the sample was mixed with 3 ml of chloroform: methanol (2:1 v/v) and vortexed. The sample was then incubated on ice for 10 min, vortexed and centrifuged at 2500 rpm for 10 min. The bottom infranatant was removed and completely dried under nitrogen gas vapors. The dried sample was then methylated by addition of 0.5 ml 0.0.5 M methanolic NaOH and incubated for 3 min at 100 °C. Once cooled, 0.5 ml of BF3-methanol was added, and the sample was incubated at 100 °C for an additional minute. After cooling, the sample was mixed with 1 ml of hexane, followed by 6.5 mL saturated NaCl solution. The sample was vortexed and centrifuged at 1700 rpm for 4 min and the upper hexane phase was transferred to a fresh vial and quantified by gas chromatography-mass spectroscopy (GC-MS). Fatty acids are expressed as a percent of the total fatty acid mass (mol %).Brain tissues were collected freshly at two and four weeks of age and snap frozen until analysis. Approximately 50 mg segments of brain were homogenized in 1.0 mL of Phosphate- Buffered Saline solution using a Fisher PowerGen 125 homogenizer. Five hundred microliters of the aliquot was removed and lipids were extracted using a modified Folch methodFecal contents were collected freshly at two and four weeks of age, frozen immediately and stored at −80 °C until analysis. Short chain fatty acids were analyzed at OmegaQuant  by gas chromatography (GC) with flame ionization detection. Samples were transferred to a screw-cap glass vial which contained heptanoic acid as an internal standard (C7:0 FFA) (Nu-Chek Prep). De-Ionized Water and 50% Sulfuric Acid Solution  was added to each vial. Each sample was homogenized with a homogenizer cleaned between each sample. After homogenization anhydrous ethyl ether (Fisher Scientific) was added to each vial and vortexed for 1 minute. Samples were then centrifuged at 4 °C for 10 minutes at 3800 rpm. An aliquot of the ethyl ether layer was transferred to a GC vial. GC was carried out using a GC2010 Plus Gas Chromatograph equipped with an AOC-5000 autosampler with stack cooler , and a HP-INNOWAX 30 m column . The stack cooler was kept below 10 °C while samples were kept on an autosampler. Fatty acids were identified by comparison with a standard mixture of short chain fatty acids  which was also used to determine individual fatty acid calibration curves. The 7:0 FFA was used to calculate recovery efficiency of the assay and applied to all fatty acids. Fatty acid composition was expressed as a percent of total identified fatty acids and concentrations as µg/mg sample.hoc tests were used if there was an overall significance. P < 0.05 was considered to be significantly different.All data are presented as the mean ± s.e.m. One and two-way ANOVA were used for overall comparisons using GraphPad Prism 6 . Kruskal-Wallis test was used for nonparametric data. Corresponding post-The data generated during the current study are available from the corresponding author on reasonable request.Supplementary information


Activation of the renin-angiotensin-aldosterone-system (RAAS) has been proposed to contribute to development of vascular complications in type 2 diabetes (T2D). The aim of the present study was to determine if plasma renin levels are associated with the severity of vascular changes in subjects with and without T2D.n = 985) and without (n = 515) T2D participating in the SUMMIT (SUrrogate markers for Micro- and Macro-vascular hard endpoints for Innovative diabetes Tools) study and in 205 carotid endarterectomy patients. Vascular changes were assessed by determining ankle-brachial pressure index (ABPI), carotid intima-media thickness (IMT), carotid plaque area, pulse wave velocity (PWV) and the reactivity hyperemia index (RHI).Renin was analyzed by the Proximity Extension Assay in subjects with (Plasma renin was elevated in subjects with T2D and demonstrated risk factor-independent association with prevalent cardiovascular disease both in subjects with and without T2D. Renin levels increased with age, body mass index, HbA1c and correlated inversely with HDL. Subjects with T2D had more severe carotid disease, increased arterial stiffness, and impaired endothelial function. Risk factor-independent associations between renin and APBI, bulb IMT, carotid plaque area were observed in both T2D and non-T2D subjects. These associations were independent of treatment with RAAS inhibitors. Only weak associations existed between plasma renin and the expression of pro-inflammatory and fibrous components in plaques from 205 endarterectomy patients.Our findings provide clinical evidence for associations between systemic RAAS activation and atherosclerotic burden and suggest that this association is of particular importance in T2D. Activation of the renin-angiotensin-aldosterone-system (RAAS) has been implicated in the development of vascular complications in type 2 diabetes (T2D) , 2. ApprTo further explore the relation between activation of RAAS and vascular complications in diabetes we analyzed the association between plasma renin levels and markers of atherosclerosis, arterial stiffness and endothelial dysfunction in 1500 subjects with and without T2D matched for age, gender and prevalence of CVD participating in the SUMMIT (SUrrogate markers for Micro- and Macro-vascular hard endpoints for Innovative diabetes Tools) study. Furthermore to determine if plasma levels of renin were related with atherosclerotic plaque phenotype we analyzed their association with markers of inflammation and fibrous components in 205 carotid plaques obtained at endarterectomy.The SUrrogate markers for Micro- and Macro-vascular hard endpoints for Innovative diabetes Tools (SUMMIT) study cohort consisted of 4 groups; (1) subjects with T2D and clinically manifest CVD, (2) subjects with T2D but without clinical signs of CVD, (3) subjects with CVD but no diabetes and (4) subjects without both CVD and diabetes recruited from existing population cohorts and hospital registers at the university hospitals in Malmö (Sweden), Pisa , Dundee and Exeter (UK) between December 2010 and April 2013 . DiabeteCarotid intima media thickness (IMT) was measured both in common carotid artery (CCA) and in the bulb as previously described . To calcEndothelial function was measured using EndoPat  to estimate the endothelium-dependent vasodilation following post-ischemic hyperemia .The reactive hyperemia index (RHI) was calculated as a post-occlusion to pre-occlusion ratio of the signal amplitudes. Thirty-one subjects were excluded from the RHI analysis due to incomplete occlusion  or time of occlusion was > or < 5 mins.Arterial stiffness was assessed by calculating pulse wave velocity (PWV) using a Sphygmocor device . The carotid and femoral pulses were captured. PWV (m/s) was automatically calculated as the measured distance divided by the differences in time between the R wave of the ECG to the foot of the carotid and femoral pulse curves as previously described .The ankle brachial pressure index (ABPI) was calculated as the ratio between the highest systolic blood pressure values from each foot respectively and the blood pressure from the arm giving the highest value. Values given represent the mean of the left and right ABPI.Two hundred and five human carotid plaques were collected at carotid endarterectomy. The indications for surgery were plaques associated with ipsilateral symptoms  and stenosis >70 % or plaques not associated with symptoms and stenosis >80 %, measured by duplex. Patients were preoperatively assessed by a neurologist. Blood samples were collected one day before endarterectomy. Informed consent was given by each patient. The study was approved by the local ethical committee. Plaques were snap-frozen in liquid nitrogen immediately after surgical removal. Plaque homogenates were prepared as previously described . One mm Finally aliquots of 50 μL of plaque homogenate were centrifuged at 13,000 g for 10 min. Twenty-five μL of the supernatant was removed and used for measuring different cytokines and growth factors. The procedure was performed according to the manufacturer’s instructions  and analyzed with Luminex 100 IS 2.3 . Elastin and collagen in plaque homogenates were measured using the Fastin Elastin and Sircol soluble Collagen assays as previously described . Renin l96×96 reagents kit  at the Clinical Biomarkers Facility, Science for Life Laboratory, Uppsala. Oligonucleotide-labeled antibody probe pairs were allowed to bind to their respective targets present in the plasma sample and addition of a DNA polymerase led to an extension and joining of the two oligonucleotides and formation of a PCR template. Universal primers were used to pre-amplify the DNA templates in parallel. Finally, the individual DNA sequences were detected and quantified using specific primers by microfluidic real-time quantitative PCR chip . The chip was run with a Biomark HD instrument. The mean coefficients of variance for intra-assay variation and inter-assay variation are 7 and 13 % for renin, and 8 and 10 % for IL-6, respectively. All samples were analyzed in the same run. Data analysis was performed by a preprocessing normalization procedure using Olink Wizard for GenEx . All data are presented as arbitrary units (AU). General calibrator curves to calculate the approximate concentrations as well as technical information about the assays are available on the Olink homepage (http://www.olink.com).Plasma levels of renin and IL-6 were analyzed by the Proximity Extension Assay (PEA) technique using the Proseek Multiplex CVDp-value of the renin coefficient.Statistical analyses were performed based on log2-transformed renin levels to approximate normal distribution. Assessment of association with other markers was done via Pearson correlation coefficient and linear regression models adjusted to study center and the individual factors from the Framingham risk score . Statistical significance of the association in the linear regression model is judged by the For assessing associations of renin levels with CVD risk logistic regression models were used, and adjustment for factors of the Framingham risk score and study center were done. Spearman correlations were used to determine associations between plasma renin levels and components of endarterectomy specimens. Statistical analyses of the SUMMIT study were done using the R version 3.1.1 and the IBM SPSS (version 22) software was used for the carotid endarterectomy study.The design of the SUMMIT study has previously been reported . BrieflyThe levels of renin in plasma increased with age, body mass index (BMI), HbA1c and triglycerides, and showed inverse associations with LDL cholesterol, HDL cholesterol and renal function as assessed by the eGFR. Notably, these associations were at least as strong in non-T2D subjects as in the T2D group Table . There wWe next analyzed if renin levels were related to the severity of vascular changes. Peripheral artery disease was determined by the ankle-brachial pressure index (ABPI), carotid disease by the intima-media thickness (IMT) in the common carotid artery (CCA) and the carotid bulb as well as by carotid plaque area, arterial stiffness by measuring pulse wave velocity (PWV) and endothelial function by determining the Reactivity Hyperemia Index (RHI). Subjects with T2D had more severe carotid disease, increased arterial stiffness, and impaired endothelial function while there was no difference in ABPI between subjects with and without T2D Table . Renin lIn an additional approach to explore the role of RAAS activation in vascular complications to T2D we analyzed if ongoing treatment with RAAS inhibitors (e.g. ACE inhibitors ARBs or renin inhibitors) was associated with any difference in markers of atherosclerosis, arterial stiffness and endothelial dysfunction. Subjects with or without prevalent CVD were analyzed separately since prevalent CVD has been shown to be associated with more severe vascular pathologies . Seventyn = 68) were excluded from these analyses as these do not have the same increasing effect on plasma renin as ACE inhibitors and ARBs. Moreover, since only 41 subjects in the non-CVD, non-T2D group were treated with ACE inhibitors and ARBs we restricted the analyses to the T2D group. In T2D subjects treated with RAAS inhibitors those with CVD (n = 313) had higher plasma renin than those without CVD  versus 271 AU (167–465), p = 9.2E-06). Also in T2D subjects without RAAS inhibition higher renin levels was observed in the CVD group (n = 150) than in the non-CVD group  versus 167 AU (108–253), p = 3.3E-05). The odds-ratio for CVD risk with increased plasma renin levels was 1.45 (95 % C.I. 1.19–1.76) for T2D subjects treated with RAAS inhibitors and 1.41 (95 % C.I. 1.04–1.93) for those not treated with RAAS inhibitors when controlling for age, gender, total cholesterol, HDL, systolic blood pressure, smoking and study center. The pattern of renin associations with measures of atherosclerosis burden, arterial stiffness and endothelial function were also similar in T2D subjects with or without treatment with RAAS inhibitors  and TNF-α , but there were no significant associations with plaque content of collagen, elastin, IL-6, monocyte chemotactic protein-1, vascular endothelial growth factor or immunostaining for macrophages or smooth muscle cells (data not shown). Renin levels in plaque homogenates were analyzed using the Proximity Extension Assay. There was a strong correlation between the levels of renin in plasma and atherosclerotic plaque tissue . However, with the exception of a trend for a correlation with the plaque content of platelet-derived growth factor  there were correlations between the plaque renin content and other plaque components.Since previous experimental data have shown that RAAS activation can stimulate inflammation, expression of fibrous proteins and smooth muscle cell growth we investigated if plasma levels of renin were related to atherosclerotic plaque content of these factors in a cohort of 205 carotid endarterectomy patients. The clinical characteristics of this cohort have been reported previously . Weak buThere is evidence from clinical trials that treatment with RAAS inhibitors slows the onset of T2D and reduces the risk of renal complications in manifest T2D . MoreoveIn spite of the association between renin and markers of atherosclerotic burden we found no evidence for reduced atherosclerosis in subjects treated with RAAS-inhibitors. There are several possible explanations to this finding. First, it cannot be excluded that RAAS activation has no direct effect on atherosclerosis development in humans and that the association between renin and disease severity observed here is caused by association of renin with another atherogenic factor. However, the fact that renin remained significantly associated to atherosclerotic burden when adjusting for other cardiovascular risk factors, as well as renal function argues against this. Second, it could be that vascular changes caused by increased RAAS activation over many years are not easily reversible by providing RAAS inhibition in different time-frames. Third, it is possible that RAAS inhibition when given alone may be sufficient to reduce or inhibit the progression of disease but when co-administered with other potent anti-atherogenic drugs, such as statins, the effect of RAAS inhibition may become too small to be of clinical significance. In line with the latter possibility treatment with ACE-inhibition reduced myocardial events in the HOPE study in which only about 20 % received lipid-lowering therapy  while noExperimental studies have shown that angiotensin II induces vascular oxidative stress leading to decreased endothelial relaxation and endothelial dysfunction . In accoThere are some limitations of the present study that should be considered. Most importantly, the observational design of the study does not allow for conclusions regarding cause and effect relations. Thus, our findings do not provide clinical evidence for an atherogenic role of renin and RAAS activation. They are, however, well in line with experimental data suggesting that RAAS activation exuberate several biological processes involved in plaque development. The finding that treatment with RAAS-inhibitors does not affect atherosclerosis severity also needs to be interpreted with caution since this is an observational study and information regarding length of treatment is unfortunately lacking. Another important limitation is that RAAS activation was only assessed indirectly through analysis of renin levels.Our findings provide clinical evidence for an association between RAAS activation and atherosclerotic burden both in subjects with and without T2D. Plasma renin and atherosclerosis are concomitantly increased in subjects with T2D as compared to age and sex-matched subjects without T2D suggesting that these associations may be of particular importance in vascular complication of diabetes. Importantly, the association between renin and atherosclerotic burden was independent of blood pressure and other major cardiovascular risk factors suggesting involvement of a direct effect of RAAS activation on the vascular wall. However, our findings also suggest that treatment with RAAS inhibitors may have limited effectiveness in counteracting the atherogenic effects of RAAS activation.


We investigated the influence of genetic variants on atherosclerosis using whole exome sequencing in cases and controls from the autopsy study “Pathobiological Determinants of Atherosclerosis in Youth (PDAY)”. We identified a PDAY case group with the highest total amounts of raised lesions (n = 359) for comparisons with a control group with no detectable raised lesions (n = 626). In addition to the standard exome capture, we included genome-wide proximal promoter regions that contain sequences that regulate gene expression. Our statistical analyses included single variant analysis for common variants (MAF > 0.01) and rare variant analysis for low frequency and rare variants (MAF < 0.05). In addition, we investigated known CAD genes previously identified by meta-analysis of GWAS studies. We did not identify individual common variants that reached exome-wide significance using single variant analysis. In analysis limited to 60 CAD genes, we detected strong associations with COL4A2/COL4A1 that also previously showed associations with myocardial infarction and arterial stiffness, as well as coronary artery calcification. Likewise, rare variant analysis did not identify genes that reached exome-wide significance. Among the 60 CAD genes, the strongest association was with NBEAL1 that was also identified in gene-based analysis of whole exome sequencing for early onset myocardial infarction. More recently, genetic studies of CAD have relied on genome wide association studies (GWAS) that test millions of genetic variants (single nucleotide polymorphisms) across the genome for associations in large case-control studies2.Coronary artery disease (CAD) due to atherosclerosis remains a major health burden across the globe. Atherosclerosis is a life-long process that involves accumulation of lipids, inflammatory cells, and smooth muscle cells in the intima of the arterial wall to form atherosclerotic lesions that can block blood circulation required for transport of oxygen and critical nutrients to the heart. Population-based epidemiological studies identified important risk factors for CAD such as elevated low density lipoprotein cholesterol (LDL-C) and reduced high density lipoprotein cholesterol (HDL-C). Genetic factors also influence CAD risk, but the identity of the responsible genes still remains unclear. Attempts to identify genes that influence CAD began with association studies of DNA variants in biological candidate genes from metabolic pathways with known involvement in atherosclerosis like cholesterol transport and metabolism3.Despite these efforts, the identification of genes that influence CAD has remained elusive. A major reason is that clinical CAD is a heterogenous disease, resulting from many different pathophysiologic mechanisms. In addition, important subclinical measures of CAD like extent of atherosclerosis are difficult to measure in human populations. To address these problems, a multicenter autopsy study was established to provide direct measurements of atherosclerotic lesions called “Pathobiological Determinants of Youth (PDAY)”. PDAY obtained arterial measurements of subclinical atherosclerosis in young persons (15–34 years of age) who died of external causes unrelated to heart disease . Results of PDAY studies directly demonstrated the atherogenic effects of exposure to risk factors such as elevated plasma levels of cholesterol and LDL levels, as well as smoking and hypertension4.In this study, we are employing PDAY to find genetic variants that are associated with a quantitative measure of subclinical CAD, the involvement of arterial surfaces with complicated raised lesions. We selected a case group with the highest amounts of arterial raised lesions for comparisons with a control group with no detectable raised lesions. Our goal was to identify genetic variants that are enriched in the case group  or the control group . To identify genetic variants, we are using whole exome sequencing by isolation of protein coding regions from individual genomes, followed by next generation sequencing. While GWAS examines associations of relatively common genetic variants, whole exome sequencing can detect low frequency and rare variants that are specific to the study population and may have larger effects on disease phenotypes. A novel aspect of this whole exome sequencing study is the inclusion of genome-wide proximal promoter regions that contain sequence elements that regulate gene expression5. Likewise, we investigated known genes that have previously shown strong and replicable associations with CAD from GWAS studies2. These CAD-associated genes represent numerous physiological and molecular processes, including well known pathways such as lipoprotein transport and metabolism, as well as pathways that have not been previously implicated in CAD risk.In addition to using whole exome sequencing for variant discovery in PDAY, we were also interested in relating our results for subclinical CAD with other population-based genetic studies of clinical CAD. In particular, we compared our results with whole exome sequencing for early onset myocardial infarction (NIH Exome Sequencing Project) to provide replication of their results, and to identify genes that are unique to each studyTable 4. Association tests for single variants were used for relatively common variants with minor allele frequencies greater than 0.01 (MAF > 0.01). These association tests used linear mixed-model regression with covariates including age, gender, race, sequencing platform, and the top three principal components. Figure −7). Supplementary Figure −6). We also selected single variant association results for the variants in proximal promoter regions only .For low-frequency and rare variants with MAF < 0.05, we performed gene-based tests to assess contributions of rare variants within the same gene. In gene-based tests, variants residing in the same gene are grouped together to assess whether they are collectively associated with a phenotype. We used two commonly used methods for gene-based tests: a collapsing method (CMC)2. Figure −6 that reached the Bonferroni significance threshold of 4.3 × 10−5). Table 2) with the index variant (rs72657934). We performed conditional analyses on selected variants to test for independence of the association with rs72657934 in COL4A2. Conditioning on rs3742207 (Gln1134His) or rs1562173 (our top hit in COL4A1) did not weaken p-values for rs72657934 , indicating that association with our top significant variant (rs72657934) is independent of previously identified GWAS variants. We also used gene-based analysis for low frequency and rare variants (MAF < 0.05) in the 60 CAD GWAS genes. Table To investigate whether genes that have previously shown consistent associations with coronary artery disease (CAD) are associated with atherosclerosis in young persons, we selected 60 genes from published meta-analysis of GWAS of CAD2. In this study, we are using PDAY for genetic studies to reduce the phenotypic heterogeneity inherent in clinical CAD, and to provide quantitative measures of subclinical CAD (raised atherosclerotic lesions) that accumulate over time and can eventually result in clinical CAD. We performed whole exome sequencing in 626 controls and 359 cases with raised lesions as directly measured by pathologists in arterial specimens in the PDAY study  across the exome to identify associations with arterial raised lesions. However, we did not identify any variants that achieved exome-wide significance after adjustments for multiple testing Fig. . This re10. The VAX2 transcription factor is a dominant/negative regulator of expression of Wnt signaling antagonists like TCF7L210. Therefore, VAX2 would likely act to regulate gene expression in atherogenesis via pathways like Wnt signaling, rather than as a structural protein in lesion development. Interestingly, TCF7L2 has been associated with Type 2 diabetes in several GWAS, and was subsequently found to be associated with CAD severity in diabetic and non-diabetic subjects11. Wnt signaling is involved in heart valve development, regulating genes from osteogenesis pathways that are also important in coronary artery calcification12. Perhaps VAX2 is also involved in development of other anatomic structures like the arterial wall. Our results suggest that the significant gene-based association for VAX2 relied on inclusion of rs557150817 (C/A) in the upstream promoter region. The rare A variant was found in 8 cases and one control. This variant may alter VAX2 expression via disruption of transcription factor binding sites located in this region (Egr1 and SP1), potentially altering expression of downstream targets of VAX2 transcription factor activities.In addition to standard whole exome sequencing, we used custom probes to capture genome-wide proximal promoter regions (200 bp upstream). However, single variant analysis of promoter regions did not find strong evidence for associations  was prominent in common variant analysis as shown in the Q-Q plot . This COL4A2 variant also showed the second lowest p-value in exome-wide single variant analysis  appears to act independently in single variant tests, since conditional analysis with other variants in COL4A1/COL4A2 did not decrease the significance levels for rs72657934 associations. Furthermore, linkage disequilibrium does not appear to be responsible for rs72657934 associations, since linkage disequilibrium values are low among the COL41/COL4A2 variants as shown in the regional plot  of WDR12 also showed associations with raised lesions, although p-values did not reach statistical significance. NBEAL1 is comprised of 25 exons spanning chromosome 2q, and encodes the neurobeachin-like 1 protein that was first isolated from a brain cDNA library20. NBEAL1 is highly expressed in glioma, with potential involvement in membrane-processing signals. NBEAL1 also is expressed in heart and artery, but little is known about any functional role in these tissues. The distribution of rare variants did not offer any substantive clues concerning their functional effects, since potentially deleterious variants were found among both cases and controls.In addition, we performed separate analyses to investigate rare variants that may underlie associations of CAD genes but that were not included in GWAS with common variants. The results differed between CMC and SKAT analyses, with lower p-values emerging from CMC. Our top gene from CMC was NBEAL1, a gene that showed associations in the previous NHLBI Exome Sequencing ProjectWhile the PDAY study provides direct measurements of atherosclerosis in arterial specimens, the unique nature of these measures hinders direct comparisons of our results with other cohorts. Therefore, we have compared our results with genetic studies of clinical sequelae of atherosclerosis like myocardial infarct and early onset myocardial infarction, and other subclinical measures such as coronary artery calcification. Interestingly, of the 60 CAD genes identified by meta-analysis of GWAS, we only found significant association with COL4A1/COL4A2 encoding alpha-1 and alpha-2 subunits of type IV collagen. Perhaps the effects of COL4A1/COL4A2 variation occur early in development of atherosclerosis, setting the stage for effects of other genetic variants in subsequent phases of atherogenesis.18. These data emphasize the potential causal contributions of genetic variation in NBEAL1 and COL4A1/COL4A2 to the pathogenesis of premature atherosclerosis.In summary, we used whole exome sequencing of PDAY cases with raised atherosclerotic lesions and controls, but did not find novel associations with exome-wide significance for either common variants with MAF > 0.01 or low frequency and rare variants with MAF < 0.05. This result may be due to a truly polygenic basis of inheritance for atherosclerosis, requiring very large studies to achieve exome-wide significance for multiple variants with only small additive effects. Addition of proximal promoter regions to coding sequences did not substantially alter our findings, except for VAX2 that showed associations in gene-based analysis only with inclusion of the promoter region. In separate analyses of 60 CAD genes identified by meta-analysis of GWAS, we confirmed previously reported associations only with common variants in COL4A1/COL4A2 on chromosome 13. Likewise, in rare variant analysis of CAD genes, we found associations with NBEAL1 on chromosome 2 that was initially detected by GWAS associations with WDR12 that contains an e-QTL for NBEAL1 expression in aortic media, and that was independently identified in gene-based analyses from the NIH Exome Sequencing Project for early onset myocardial infarction21. The 626 controls were selected from PDAY subjects with no arterial raised lesions with frequency matching for age, race, and gender. All methods and experimental studies were carried out in accordance with relevant guidelines and regulations after approval by the Committee for the Protection of Human Subjects (IRB) at the University of Texas Health Science Center at Houston. The PDAY subjects were not consented since the post-mortem samples were collected at autopsy by County Coroners’ Offices after death due to external causes 21.Cases and controls were selected from autopsied PDAY subjects (15–34 years of age) who died of non-CAD related causes such as accident, homicide, and suicide. The subjects included male and female European Americans and African Americans , and intractable repeat regions (polynucleotides and Alu repeats). After capture, we used automated library construction  with addition of barcodes for multiplexed sequencing. We began sequencing with the oligonucleotide ligation-based SOLiD 5500xl platform  that performs massively parallel sequencing of individual DNA molecules amplified on beads affixed to glass slides (288 subjects). For the remaining 697 subjects, we used the Ion Proton platform , based on proton assays for polymerase sequencing of individual DNA molecules in wells of modified semiconductor chips. For both platforms, we sequenced each case with their corresponding controls in the same sequencing run . We constructed BAM files  for variant calling using Freebayes algorithms, and annotated the resulting VCF files using VEP. We created a single VCF by merging the calls from each sequencing platform, and filled in the reference sequences (non-variable positions) using a jointly called VCF from the two platforms.Genomic DNA samples were purified from archived PDAY liver tissues using an automated paramagnetic bead based extraction system (Promega Magnasil). The genomic DNA samples were used for exome capture with TargetSeq reagents  based on high density oligonucleotide hybridization of GENCODE annotated coding exons, NCBI CCDS, exon flanking sequences (including intron splice sites), small non-coding RNAs  and a selection of miRNA binding sites. We also designed custom probes to capture promoter regions located within ~200 bp upstream from transcriptional start sites that typically contain the majority of transcription factor binding siteshttp://genome.sph.umich.edu/wiki/EPACTS) to adjust for population stratification and to minimize batch effects from sequencing platforms by calculating the kinship matrix between samples from the exome VCF file. EPACTS supports linear mixed-model based tests for both single variant tests (common variants) and gene-based tests (low frequency and rare variants). Age, gender, and race were used as covariates in all statistical tests. First, we evaluated association signals of individual common variants with minimum minor allele frequencies (MAF) of 0.01 and with minimum minor allele count of 5. We used the ‘q.emmax’ test in the EPACTS pipeline, which is an implementation of the linear mixed-model22. We treated case/control status as a quantitative trait after adjusting for covariates. We then tested associations of low frequency and rare variants (MAF < 0.05) using mixed-model gene-based tests to find whether functional rare variants in each gene are jointly associated with the phenotype. Variants were annotated by Variant Effect Predictor (VEP)23 with gene symbols and functional effects, and only missense, nonsense, and splice variants with MAF less than 0.05 were included in the gene-based tests. We used two different EMMAX-based rare variant tests: the collapsing test (emmaxCMC) and the kernel-based test (mixed model SKAT) to test different hypotheses. The collapsing test assumes all functional rare variants in the gene would have effects of the same direction6, while the kernel-based test assumes that each variant can have either positive or negative effect to the phenotype7. Single-variant and gene-based test results were then sub-selected using the list of candidate genes from CAD GWAS2. For single-variant results, we also ran conditional analysis to evaluate dependence of our top hit from the candidate region (rs4773144) to known GWAS variants in COL4A1/COL4A2. All statistical tests used Bonferroni corrections to account for multiple testing.For all association analyses, we used linear mixed-model analyses from the EPACTS software pipeline (Supplemental Materials


The highly virulent rabbit hemorrhagic disease virus (RHDV) has been widely used in Australia and New Zealand since the mid-1990s to control wild rabbits, an invasive vertebrate pest in these countries. In January 2014, an exotic RHDV was detected in Australia, and 8 additional outbreaks were reported in both domestic and wild rabbits in the 15 months following its detection. Full-length genomic analysis revealed that this virus is a recombinant containing an RHDVa capsid gene and nonstructural genes most closely related to nonpathogenic rabbit caliciviruses. Nationwide monitoring efforts need to be expanded to assess if the increasing number of different RHDV variants circulating in the Australian environment will affect biological control of rabbits. At the same time, updated vaccines and vaccination protocols are urgently needed to protect pet and farmed rabbits from these novel rabbit caliciviruses. Lagovirus causing acute hepatic necrosis in European rabbits (Oryctolagus cuniculus), leading to disseminated intravascular coagulation and death in >90% of susceptible animals (Rabbit hemorrhagic disease virus (RHDV) is a calicivirus in the genus –Conversely, in Australia and New Zealand, the European rabbit is a major vertebrate pest, threatening the survival of native plants and animals, facilitating erosion through burrowing and grazing, and causing massive economic losses to agricultural sectors. In 1991, a strain of RHDV from Czechoslovakia (CAPM V-351) was imported into Australia for assessment of its suitability as a rabbit biocontrol agent; it has been used for this purpose since 1995, resulting in substantial benefits for both the economy and the environment  comprising 2 open reading frames (ORFs)  (1). Nin,,,,,12; reviewed in 1). In some geographic regions, it was suggested that RHDVa had replaced previous enzootic viruses . RCVs have been reported from various geographic locations; in contrast to the pathogenic hepatotropic lagoviruses, most RCVs mainly cause a nonclinical infection of the small intestine   or to CSIRO  by veterinarians or NSW Local Land Service rangers. Samples were collected during December 1, 2013–April 30, 2015. No animal ethics permit is required in Australia for sampling of rabbits that are found dead.For serologic analysis of healthy wild rabbits, we collected 20 wild rabbits from the ACT; these animals were shot from a vehicle using a 0.22-caliber rifle targeting the head or chest. We collected samples  postmortem; all sampling was conducted according to the Australian Code for the Care and Use of Animals for Scientific Purposes as approved by the CSIRO Ecosystem Sciences animal ethics committee .Liver samples submitted to EMAI were prepared by homogenizing ≈1 g of tissue in 5 mL of phosphate-buffered saline and centrifuging at 3,000 rpm for 10 minutes. Supernatant was tested in the RHDV antigen-capture ELISA as previously reported . We applied sterile cotton swabs to the freshly cut surface of liver samples and transferred them to 5-mL vials containing 3 mL of sterile phosphate-buffered gelatin saline, then extracted viral RNA from 50-µL samples from these vials using the MagMAX-96 Viral Isolation System  on a Kingfisher 96 magnetic particle handling system .We tested purified viral RNA (5 µL) in an RHDV-specific Taqman rRT-PCR assay using the AgPath-ID One-Step RT-PCR kit (ThermoFisher Scientific), based on detection of a conserved sequence of the VP60 gene with modifications  (34). We>1 isolate from each outbreak) using the universal lagovirus RT-PCR, as described previously ; the Maxwell 16 LEV simplyRNA Tissue Kit ; or the Invitrogen Purelink viral RNA/DNA Mini Kit (ThermoFisher Scientific) following the manufacturers’ instructions. We performed first-strand cDNA synthesis from 5 μL of RNA with 500 ng of OligodT (18mer)  using Invitrogen Superscript III  following the manufacturer’s directions. We conducted initial detection and typing of RHDV samples submitted to CSIRO . Sequencing was performed on an Illumina MiSeq using the 300 cycle paired-end MiSeq Reagent Kit v2 (Illumina), as described previously  and the VP60 gene  using PhyML  for recombination using the RDP, GENECONV, MaxChi, and BootScan methods available in the RDP4 package  and IgA (15/20), indicating a recent virus outbreak , and SanWe also detected Australian field strains (RHDV G2) during the same sampling period on 3 occasions, 2 from wild rabbits , we recovered RHDVa RNA from a healthy shot rabbit following an observed decline in rabbit numbers. Subsequent serologic analyses from a sample of healthy shot rabbits suggests that high levels of cross-reacting isotype antibodies , in combination with low or negative test results for specific competition ELISAs for RHDV and RCV-A1, may be used as a tool to infer previous exposure of a rabbit population to RHDVa. This particular serologic profile may prove useful for large-scale field epidemiology studies attempting to track the spread and impact of RHDVa in the Australian landscape, even in the absence of a specific serologic test. Furthermore, our study demonstrates that PCR analysis of bile in recovering, recently RHDV-infected (IgM-positive) rabbits can be an additional tool to determine to which virus a wild rabbit population had been exposed.Several of the RHDVa cases in domestic rabbits were reported to have occurred in previously vaccinated rabbits, although details about the vaccination regimens and intervals were difficult to retrieve. The RHDVa variant JN165234/XA/China/2010, which closely resembles the VP60 sequence of the RHDVa from Australia we describe, was reported to be able to partially overcome protection induced by vaccination against classic RHDV (,,–Before the detection of RHDVa, the deliberately released CAPM V-351 and its descendants were the only RHDV variants circulating in Australia, despite both RHDVa and RHDV2 circulating overseas since 1997 and 2010, respectively (


There was a significant increase in the change scores for estimated VO2max of the Spin group when compared to the Balance group. Semantic verbal fluency output within the scanner was also improved in the Spin group as compared to controls at postassessment. Group fMRI comparisons of IFG activity showed lower activity in the right IFG following the intervention in the aerobic Spin group when compared to the Balance group. Regression analysis of imaging data with change in both estimated VO2max and semantic verbal fluency was negatively correlated with activity in right IFG. The current work is registered as clinical trial with NCT01787292 and NCT02787655.Previous work has shown that older adults who evidence increased right inferior frontal gyrus (IFG) activity during language tasks show decreased sematic verbal fluency performance. The current study sought to evaluate if an aerobic exercise intervention can alter patterns of brain activity during a semantic verbal fluency task assessed by functional magnetic resonance imaging (fMRI). Thirty-two community-dwelling, sedentary older adults were enrolled to a 12-week aerobic “Spin” exercise group or a 12-week nonaerobic exercise control condition . Thirty participants completed their assigned intervention  with pre- and postintervention assessments of a semantic verbal fluency task during fMRI and estimated VO Over the past few decades considerable attention has been devoted to examining the benefits of aerobic exercise on central nervous system plasticity. Aging research suggests that the positive effects of aerobic exercise involve higher order cognitive-executive processes, which are subserved largely by the frontal lobes –3. SigniAerobic exercise has been increasingly associated with improvements in memory, executive function, and patterns of neural activity as assessed by fMRI –4, 7–11.The aims of the present study were to test the effect of a 12-week aerobic exercise intervention against a nonaerobic control condition to investigate changes in semantic verbal fluency and its underlying neural activity in previously sedentary older adults. We hypothesize that increased aerobic capacity brought on by the aerobic exercise intervention will be associated with decreased blood oxygenation level dependent (BOLD) activity in right lateral frontal regions (Broca's homologue). Specifically, we hypothesize that the aerobic intervention would result in a decrease in recruitment of Broca's homologue which would correlate with behavioral improvement in a semantic verbal fluency language task.n = 17) or a nonaerobic control group  to equalize contact and monitoring. Study personnel explained the purpose, potential risks of the experiment and completed the informed consent process with each participant following protocols approved by the Emory University's Institutional Review Board (IRB) in compliance with the Helsinki Declaration.In this 12-week randomized controlled trial, 32 participants were divided into an aerobic, Spin exercise group . To meet inclusion criteria participants had to (1) be between 60 and 89 years of age, (2) report being sedentary, defined as not engaging in structured physical activity and/or not accumulating 30 minutes or more of moderate physical activity most days of the week, (3) have no history of depression, neurological disease, including Parkinson's disease, Alzheimer's disease, and multiple sclerosis or stroke, (4) report being right-handed, (5) report being a native English speaker, and (6) obtain physician's approval that it was safe for them to participate in the study. Exclusion criteria included (1) conditions that would contraindicate an MRI scan, (2) failure to provide informed consent, (3) hospitalization within the past 6 months, (4) inability to walk 400 meters, and (5) significant cognitive-executive impairment, defined as a score on the Montreal Cognitive Assessment (MoCA) of <24.Consistent with our previous study , the groThe Spin intervention took place in a climate controlled fitness facility. The instructor guided the participants through a 5-minute warm-up and then a work out phase that included steady up-tempo cadences, sprints, and climbs. During the workout phase the target HRR reserve was maintained by averaging increases and decreases in intensity/HR. The goal was to maintain a 10% offset from the HRR goal during the workout phase. Thus, participants were within target HRR on average across the session. All participants wore HR monitors (FT7 Polar® Heart Rate monitor) and were instructed each day of their target HR range. Staff members also monitored and tracked the HR to ensure adequate intensity throughout each session. Weekly meetings in which each participant's HR was reviewed served as a way to encourage those with low attendance or HR to improve their performance for the next week.Participants in the control group were equalized (frequency and duration) to the Spin group for contact and monitoring. As such they reported the same facility with the same interventionist; however, instead of progressive aerobic exercise they engaged in group balance, stretching, and light muscle toning exercises. Similar to the aerobic group, the Balance intervention began with an initial 20-minute session steadily progressing to 45 minutes over the course of the 12-week intervention. Heart rate was consistently monitored to assess general intensity during each session.All assessments were done no more than 10 days before the start of or 10 days after the conclusion of the 12-week intervention period. Assessment sessions did not exceed two hours to alleviate participant fatigue.2max) prior to and after the intervention period. The selected submaximal test is much better tolerated than a maximum exertion treadmill test in the selected population (sedentary older adults). The YMCA test uses an extrapolation method in which heart rate workload values are obtained at 2–4 points during stages of increasing resistance and extrapolated to predict workload at the estimated maximum heart rate . Estimated VO2max is then calculated from the predicted maximum workload. Prior to beginning the test, the procedures were briefly explained and participants completed a 2-minute warm-up consisting of pedaling without load so that they could adapt to the ergometer for the first minute and then pedaling with a 0.5 kg·m load during the second minute. The YMCA submax test has an R = 0.86 with VO2max and a SEE = 10% of the predicted VO2max [To validate that the Spin exercise was effective at increasing cardiovascular fitness when compared to control, participants performed a YMCA submaximal fitness test on a cycle ergometer. This submaximal test was used to estimate the participant's maximal oxygen uptake  test (Letter and Semantic Fluency), the Hopkins Verbal Learning Test (HVLT), and forward and reverse digit span.During fMRI semantic verbal fluency acquisition, the participant's task was to overtly generate different exemplars of the respective category.Similar to our previous work examining the neural underpinnings of semantic verbal fluency , a sparsError analysis on scanner response proceeded as follows. Correct responses consisted of a semantically related member of the provided category . Two raters scored the responses and inconsistencies were resolved by interrater agreement. Incorrect responses were semantically unrelated utterances , filler words , or no response given. Failure to respond comprised 80% of errors in the test sample.Functional images were obtained on a 3T Siemens Trio  platform with a whole-brain, 1-shot gradient EPI scan using a 12-channel RF receive coil with the following parameters: 240 × 240 mm FOV, 64 × 64 matrix (3.75 × 3.75 mm in-plane resolution), TR = 5830 ms, time of acquisition (TA) = 1830 ms, echo time (TE) = 25 ms, and flip angle (FA) = 70°. Image voxels were isotropic using a 3.75 mm slice thickness (no gap) with 32 slices acquired per image. A high-resolution T1-weighted 3D rapid acquisition gradient echo (MP-RAGE) scan  was obtained to provide anatomic reference. A laser position system was used to align the participants within the bore of the magnet. Head motion was minimized using foam padding and careful instructions were given to the participant about avoiding motion.t-test. To evaluate pre-post-differences between groups, change scores for behavioral data were computed using the convention: change = pre − post. Intervention effects were examined by independent sample t-test on change scores to determine between-group differences for the variables of interest: cognitive battery, cardiovascular fitness assessment, and in-scanner semantic verbal fluency performance.Statistical analyses were conducted using Microsoft Excel and JMP 12 . Potential group differences at baseline on demographic and psychometric parameters were evaluated using a between-subjects For fMRI image processing, Analysis of Functional NeuroImages (AFNI) software and FMRIB Software Library (FSL) were used. Images were skull-stripped using a BASH shell optimized version of FSL Brain Extraction Tool (optiBET) . After rn to be evaluated using a GLM. The specified generalized linear tests (GLT) afforded between and within group comparisons, as well as interaction effects while controlling for sphericity due to within-subjects comparisons. We used AFNI's 3dClustSim (compiled September 2015) program to correct for multiple comparisons with a voxel-wise threshold level p < .01 holding alpha at .01 for a minimum cluster size of 101 voxels at 2 × 2 × 2 mm3 (MNI space). We selected this conservative threshold in light of recent work discussing random field theory in cluster correction [q ≤ .02 for all reported differences.To evaluate group differences as a result of the interventions, we performed a split-plot (2 between × 2 within) ANOVA as implemented in AFNI's 3dMVM  with intrrection . We addi2max in prediction of BOLD activity in the postsession. As above, statistical thresholds were set to p < .01, alpha = .02 with a minimum cluster size of 101 voxels in MNI space using 3dClustSim.We additionally performed regression analyses using AFNI's 3dRegAna application to test for significant correlations between change scores in both semantic verbal fluency and change in estimated VOμ = 69.45 ± 6.12 years). The Spin and Balance group did not differ significantly at baseline in any characteristics  of the Spin group (μ = 3.85 ± 2.58) and the Balance group (μ = −0.05 ± 1.05); t(29) = 4.63, p < .01 (There was a significant difference between the change scores for the cardiovascular fitness assessment (estimated VO p < .01 . Particit(29) = 1.94, p = .06) and the Hopkins Verbal Learning Test (t(29) = 1.93, p = .06). Group differences in postintervention comparisons were not significant for tests of forward digit span and reverse digit span.Cognitive Test Battery: A trend was shown for better performance in the Spin group after intervention on both semantic verbal fluency outside the scanner (t(29) = 2.6, p = .01) (t(29) = 1.2, ns). However, during postintervention assessments, participants in the aerobic Spin training group showed fewer errors of omission (no response) than the Balance group (t(29) = 2.78, p < .01).In-scanner performance: in-scanner semantic verbal fluency performance improved after intervention in the Spin group as compared to the Balance control group (p = .01) . Error at-test on presession regression coefficients to test if there were differences at baseline between the two participant groups. Negligible group differences were evident at the selected threshold in this comparison on whole-brain analysis. No differences were evident in language eloquent cortices.We performed a between-subjects 2 with right inferior frontal activity during fMRI. As shown in the figure, change in VO2 was correlated with altered activity in right inferior frontal activity.Groups showed significant differences when comparing BOLD activity in postsession see . Brain r2 change data relating to postsession imaging results across participants are presented in 2 at postsession was correlated with decreased activity in right inferior frontal activity (indicated in blue) but increased left lateralized activity (indicated in orange).Results from regression analysis on VOResults from regression analysis of postsession semantic fluency performance within the scanner with fMRI activity are presented in The goal of the present study was to examine changes in brain activity during a semantic verbal fluency task in a previously sedentary cohort of older adults following 12 weeks of aerobic Spin exercise when compared to a nonaerobic, Balance control group. Consistent with our hypothesis, participants completing the aerobic Spin exercise condition improved their cardiovascular fitness level and showed improved semantic verbal fluency performance during a category member generation within the MR scanner as compared to the Balance control group. Additionally, when comparing group imaging data in the postsession controlling for variance between groups in the presession, the aerobic Spin group showed less positive BOLD activity in right lateral frontal, right superior temporal, and right angular gyrus.As expected, the older adults exhibited positive BOLD activity in the right frontal operculum during the preintervention fMRI. These findings corroborate our previous findings indicating higher bilateral positive BOLD in older adults while performing an fMRI semantic verbal fluency paradigm. This increased bilateral activity is indicative of worse performance when compared to individuals who evidenced more left lateralized inferior frontal activity , 19. In The finding of decreased activity in right inferior frontal regions being correlated with stronger semantic verbal fluency in older adults is, at face, seemingly at odds with a dominant model of hemispheric activity change respective of aging. The hemispheric asymmetry reduction in older adults (HAROLD) model has shown evidence that bilateral activity in older persons may be compensatory in nature . This inThe exact physiological mechanism responsible for the demonstrated changes in this exercise intervention study has yet to be determined. However, several candidates exist that need to be investigated to truly understand the mechanisms driving the changes evidenced in our exercise sample. Though beyond the scope of the present study, these mechanistic parameters may include, but are not limited to, an increase in brain-derived neurotrophic factor and other nerve growth factors , 8, chanAn impressive finding of the current study is the relatively short amount of time (12 weeks) in which functional recruitment during a semantic verbal fluency task can be positively impacted by an exercise intervention. Baker et al. (2010) enrolled 33 participants with mild cognitive impairment over a 6-month span in which the participants engaged in 4 bouts of exercise per week. The participants followed a similar exertion schedule (though primarily treadmill-based) as the present study with heart rate targeted at 75–85% of HRR for the exercise sessions. After the 6-month training program semantic verbal fluency (measured by the DKEFS category fluency) significantly improved in females within the study cohort. Given this study was with patients diagnosed with mild cognitive impairment, the current findings may have clinical implications denoting the importance of beginning an aerobic exercise regimen prior to the onset of significant cognitive difficulties in older adults.n = 44) reported improvements in executive function  while showing reductions in recruitment of prefrontal regions during fMRI acquisition during related tasks. The group interpreted the reduced activation as an increase in processing efficiency within the prefrontal regions. However, their exercise program was relatively low intensity (~60% HR peak within age group) and involved 30–45 minutes of walking for 12 months. With inflexible exercise targets respective of duration and HR intensity, it is possible that participants may have acquired peak effects earlier in the intervention and then maintained a plateau with respect to their aerobic performance. As such the current intervention is modeled as a progressive and adaptive protocol that may offer consistent performance gains throughout the duration of the exercise program.While Baker et al. (2010) did not use neuroimaging, numerous studies investigating the effects of aerobic exercise on executive functions have. In a seminal investigation, Colcombe et al.  demonstrThere are notable limitations to the current work that should be addressed. Most immediately, the sample size is somewhat low in the present report. While this is problematic from a data extensibility standpoint, it also is exciting given the fact that we were able to detect changes in a small number of individuals . Given this, however, additional work is clearly warranted to attempt to better characterize neural activity changes as a result of aerobic interventions. Secondly, the present study cannot easily characterize the nature of how the BOLD signal changes. As such, it is difficult to differentiate vascular effects from the intervention as compared to neural changes. While it is impossible to completely dissociate one from the other using the present modality, we must acknowledge that improvements in vascular flow dynamics as a result of increased physical activity may better characterize the BOLD changes shown in the present study. Again, future work is needed with alternate methodologies to identify the focal mechanism of change presented here. Finally, as a methodological note, pre/postassessments using MRI introduce sensitivity/specificity variation due to differences in MR field characteristics. We utilized B0 field maps to assess changes between sessions in MR scanner function. While these did not reveal a gross overall change, physiological characteristics of repeated scans could not be accounted for. Statistically, we attempted to compensate for sensitivity differences by using a consistent and reasonable threshold for functional activity.In conclusion, the present study shows that a 12-week aerobic exercise intervention (Spin) alters brain activity in language networks and may be associated with the improvement in sematic verbal fluency. Additional work is warranted to further evaluate the effects of aerobic exercise on the neural substrates of language production in aging.


The neuroimaging-based model was significantly more accurate than a model involving patient-related and medical variables (p = 0.005). Hub regions belonging to several distinct functional networks were the most important predictors of cognitive outcome. Characteristics of these hubs indicated potential spread of brain injury from default mode to other networks over time. These findings suggest that resting state fMRI is a promising tool for predicting future cognitive impairment associated with breast cancer. This information could inform treatment decision making by identifying patients at highest risk for long-term cognitive impairment.We aimed to determine if resting state functional magnetic resonance imaging (fMRI) acquired at pre-treatment baseline could accurately predict breast cancer-related cognitive impairment at long-term follow-up. We evaluated 31 patients with breast cancer (age 34–65) prior to any treatment, post-chemotherapy and 1 year later. Cognitive testing scores were normalized based on data obtained from 43 healthy female controls and then used to categorize patients as impaired or not based on longitudinal changes. We measured clustering coefficient, a measure of local connectivity, by applying graph theory to baseline resting state fMRI and entered these metrics along with relevant patient-related and medical variables into random forest classification. Incidence of cognitive impairment at 1 year follow-up was 55% and was predicted by classification algorithms with up to 100% accuracy ( Breast cancer and its treatments can have neurotoxic effects in some patients, resulting in acute, persistent and/or late onset cognitive impairments such as difficulties with attention, memory, processing speed, executive function and verbal fluency , which is one of the most sensitive neuroimaging techniques currently available, is non-invasive and simple to acquire Kesler, . RestingWe recently demonstrated subtle disruption of intrinsic functional network organization in patients newly diagnosed with breast cancer who were evaluated prior to any treatment, including surgery  from baseline intrinsic functional network characteristics obtained prior to treatment initiation. There are many different characteristics of intrinsic functional connectivity that can be measured from resting state fMRI. Based on our prior studies of breast and other cancers , cyclophosphamide, doxorubicin and fluorouracil (N = 2), cyclophosphamide and paclitaxel (N = 9), doxorubicin, carboplatin and paclitaxel (N = 2), fluorouracil, epirubicin and cyclophosphamide (N = 2). The Stanford University Institutional Review Board approved this study and all procedures performed were in accordance with the ethical standards of the Declaration of Helsinki. Written informed consent was obtained from all participants included in the study.As part of our ongoing, prospective longitudinal study of breast cancer and cognition, we enrolled 31 newly diagnosed patients with primary breast cancer age 34–65 years and 43 frequency matched healthy control females  for verbal learning and verbal memory retention Schmidt, , Comprehz-scores based on the control group’s mean and standard deviation. Cognitive impairment was defined as having any two z-scores of −1.5 or lower or any one z-score of −2.0 or lower, based on the ICCTF recommendations , suggesting further ecological validity.Test scores were converted to Neuroimaging data were acquired using a GE Discovery MR750 3.0 Tesla whole body scanner  on the same day as the cognitive testing session (see Supplementary Methods for further details). Functional connectivity preprocessing was performed with Statistical Parametric Mapping 8 (SPM8) and CONN Toolboxes as previously described . Change in CAD and Adjustment Index scores were evaluated using paired For random forest classification, the square root of the number of features were split at each node and an ensemble of 500 trees was grown by bootstrapping the features with replacement. Feature selection/reduction was conducted on a training set (A + B) consisting of a 75% random sample of the breast cancer group obtained after stratified class sampling. Recursive feature elimination was used to remove minimally contributing features and optimize the models. Recursive feature elimination was conducted on this set with A = training data and B = testing data with leave-one-out cross-validation across 100 random partitions of A and B. Features that provided the best accuracy across these partitions were used to re-train a model on A + B with out-of-bag error estimation  in addition to patient/medical features.We tested three different models Figure . Model 1The significance of model accuracy was evaluated using a two-sided exact binomial test in addition to the area under the curve (AUC) of the receiver operating characteristic (ROC). Feature importance was determined using mean decrease in Gini index  including the “randomForest”, “caret” and “pROC” libraries.Because there is no standard definition of cognitive impairment, we supplemented classification analysis with random forest regression to determine if features identified by classification could accurately predict individual cognitive test N = 17/31) incidence of cognitive impairment and healthy controls demonstrated 26% (N = 11/43). The difference in incidence was significant . Of those impaired in the breast cancer group, 59% (N = 10/17) had persistent impairment while 41% (N = 7/17) had late onset impairment. Depression, anxiety and fatigue decreased over time based on patients’ self-ratings, but not significantly (p > 0.725) and was not clinically elevated at any time point. Self-rating of functional capacity decreased over time but not significantly (p > 0.193). Cognitive testing and self-report data are presented in Table Patients with breast cancer demonstrated 55%  and 2 . Models 1 and 2 were not significantly different .The AUC of Model 3 was significantly greater than the AUCs of Models 1 (R2 = 0.79 (p < 0.0001). RAVLT verbal retention scores were predicted with an adjusted R2 = 0.78 (p < 0.0001). The model for CTMT Trail 1 scores had an adjusted R2 = 0.70 (p < 0.0001). CTMT Trail 5 scores were predicted at adjusted R2 = 0.75 (p < 0.0001). The model for COWA scores had an adjusted R2 = 0.64 (p < 0.0001). The relative contributions of the five clustered connectivity features to these regression models are provided in Supplementary Table S2.Using the five brain regions from Model 3 above, individual RAVLT verbal learning scores were accurately predicted with an adjusted As shown in Table a priori regions, and Model 3 included the entire brain with patient/medical variables.The aim of this study was to determine if baseline, pre-treatment resting state fMRI could be used to accurately predict long-term cognitive outcome in chemotherapy-treated patients with breast cancer. Based on our prior work, we measured clustering coefficient, a characteristic of brain network connectivity obtained from resting state fMRI data. We observed that most patients (55%) demonstrated cognitive impairment at 1 year post-chemotherapy follow-up. This incidence is consistent with previous studies  accuracy in machine learning applications is rare but not unprecedented when neuroimaging features are included (Gothelf et al., Model 1 results indicated that patient and medical factors, particularly age and CAD score, were independently useful at predicting impairment with 71% accuracy, although specificity was suboptimal and the overall model was not significant. The addition of clustered connectivity data improved accuracy to 85% with increased specificity, though this improvement was not significant. Model 3 performed with perfect sensitivity and specificity and included only clustered connectivity of brain regions selected in a data driven manner. Model 3 was significantly more accurate than Models 1 and 2. Further, regression models using Model 3 features were associated with significant adjusted RMany of the regions selected in Models 2 and 3 have been noted to be altered in prior studies of breast cancer as well as other conditions that affect cognitive function (Kaiser et al., Modularity analysis indicated that all Model 2 regions were part of the default mode network, consistent with prior studies (Fox et al., The regions in Model 3 most accurately predicted outcome but had no overlap with those in Model 2; we did not previously observe them to be different between patients with breast cancer and healthy controls at pre-treatment baseline (Kesler et al., The main limitation of this study is the small sample size which can result in model over-fitting. We conducted random forest modeling using a conservative approach that included cross-validation and careful separation of training and testing samples. However, further evaluation of our models’ validity requires a new, unseen and larger sample of patients to which we can apply our algorithms. We are currently acquiring such a sample and have also made our algorithms available for others to apply to their own data as appropriatePatients undergoing chemotherapy tend to be monitored for various toxicities including cardiac, hepatic and hematologic problems, among others. Given the high incidence of cognitive impairments, it seems reasonable that neurologic monitoring be included as well. We have demonstrated that this impairment can potentially be predicted from baseline, pre-treatment data. Resting state fMRI may be a particularly promising tool for this purpose, improving our ability to identify patients at risk for long-term cancer-related brain injury. If inclusion of resting state fMRI data continues to result in the most accurate predictions of future cognitive outcome, we have already demonstrated that it is feasible to obtain these data from patients pre-treatment. Connectome metrics derived from resting state fMRI show good to excellent test-retest reliability (Braun et al., SRK designed the study, wrote the Matlab code for graph theoretical analysis and the R code for random forest analysis, conducted the statistical analyses and prepared the manuscript. AR assisted with R code and statistical analyses and edited the manuscript. IAO-G and MK edited the manuscript. DWB provided oncology consultation, assisted with participant recruitment and edited the manuscript. OP supervised participant recruitment, study coordination and data acquisition and edited the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.