Slope of the intracranial pressure waveform after traumatic brain injury.

BackgroundThe measurement and treatment of ICP within the management of TBI generally focuses on keeping the mean ICP to less than 20 mm Hg. More sophisticated analysis of the intracranial pressure waveform has yielded important relationships, but those methods have not gained widespread use. Prior analysis of the slope of the ICP waveform during inspiration and expiration in patients with hydrocephalus has provided valuable information that has never been applied to patients with TBI. This study used digital methods to examine ICP and the slope of the ICP waveform in relation to the respiratory cycle in subjects with TBI.MethodsIntracranial pressure was monitored in 6 randomly selected patients admitted with acute TBI. In the first 3 subjects, a single 5-minute recording was analyzed. In 3 subsequent subjects, 4 nonsequential 5-minute epochs were analyzed during periods of varying ICP. The systolic slope of the ICP waveform was compared during inspiration and expiration, and then evaluated in relation to simultaneous mean ICP.ResultsThe slope of the systolic ICP waveform was significantly greater during inspiration than during expiration (P < .0001 for 5 subjects and P < .03 for 1 subject). Within each subject, the ICP slope was positively correlated with simultaneous ICP (P < .0001 in all 6 cases).ConclusionGreater systolic ICP waveform slope during inspiration has not been described previously after TBI and is consistent with prior observations in subjects with hydrocephalus. The strong correlation between ICP slope and simultaneous mean ICP suggests that increasing ICP slope might indicate loss of intracranial compliance after TBI

Retroperitoneal Transdiaphragmatic Robotic-Assisted Laparoscopic Resection of a Left Thoracolumbar Neurofibroma

ObjectiveRobotic technology has been used in a variety of surgical procedures for its 3D magnification and precision. Minimally invasive techniques have already become common in neurosurgery; however, robotic-assisted procedures in neurosurgery are still a relatively new frontier. This report describes the first use of robotic technology to resect a left thoracolumbar neurofibroma.Case reportA 19-year-old male with a family history of neurofibromatosis was diagnosed with a suspected 3-cm x 4-cm neurofibroma in the T12-L1 left paraspinal area. His only complaint was back pain requiring narcotic analgesics. He had no other findings on physical examination or laboratory/radiologic workup.MethodsAfter consulting urologic robotic surgeons, it was agreed to use the da Vinci robot (Intuitive Surgical, Sunnyvale, CA) for the resection of this mass. Following retroperitoneal laparoscopic access, the urologic surgeons opened the diaphragm and began the initial mobilization of the mass laparoscopically. The robot was docked, and the neurosurgeon operated the robot at the console to resect the mass from its nerve origin. There were no complications, and the mass, a confirmed neurofibroma, was completely removed. The patient was discharged on postoperative day 2; his back pain resolved, requiring no analgesia by the end of the first postoperative week.ConclusionThis case provides early evidence that robotic assistance can be successfully used for the resection of a paraspinal neurofibroma

Primary leptomeningeal oligodendrogliomatosis

Primary leptomeningeal oligodendrogliomas (PLOs) are rare intracranial malignancies where tumors grow in the subarachnoid space without an obvious connection to the brain or spinal cord parenchyma. Adding to the three previously reported cases of PLO with no parenchymal involvement we report a fourth case of the same in this paper in a 50-year-old woman presenting with unrelenting headaches. CT scan of her head revealed hydrocephalus and MRI revealed diffuse enhancement of her leptomeninges throughout her brain and spine, prominent over the basilar region. Biopsy obtained using a frameless stereotactic biopsy showed sharply defined cell borders, clear cytoplasm, and rounded nuclei consistent with an oligodendroglioma. Our case suggests that PLO can mimic diffuse forms of granulomatous meningitis and should be suspected in patients that clinically and radiographically present like granulomatous meningitis but without blood or CSF markers for the same

The Association of PNPLA3 Variants with Liver Enzymes in Childhood Obesity Is Driven by the Interaction with Abdominal Fat

BACKGROUND AND AIMS: A polymorphism in adiponutrin/patatin-like phospholipase-3 gene (PNPLA3), rs738409 C->G, encoding for the I148M variant, is the strongest genetic determinant of liver fat and ALT levels in adulthood and childhood obesity. Aims of this study were i) to analyse in a large group of obese children the role of the interaction of not-genetic factors such as BMI, waist circumference (W/Hr) and insulin resistance (HOMA-IR) in exposing the association between the I148M polymorphism and ALT levels and ii) to stratify the individual risk of these children to have liver injury on the basis of this gene-environment interaction. METHODS: 1048 Italian obese children were investigated. Anthropometric, clinical and metabolic data were collected and the PNPLA3 I148M variant genotyped. RESULTS: Children carrying the 148M allele showed higher ALT and AST levels (p = 0.000006 and p = 0.0002, respectively). Relationships between BMI-SDS, HOMA-IR and W/Hr with ALT were analysed in function of the different PNPLA3 genotypes. Children 148M homozygous showed a stronger correlation between ALT and W/Hr than those carrying the other genotypes (p: 0.0045) and, therefore, 148M homozygotes with high extent of abdominal fat (W/Hr above 0.62) had the highest OR (4.9, 95% C. I. 3.2-7.8, p = 0.00001) to develop pathologic ALT. CONCLUSIONS: We have i) showed for the first time that the magnitude of the association of PNPLA3 with liver enzymes is driven by the size of abdominal fat and ii) stratified the individual risk to develop liver damage on the basis of the interaction between the PNPLA3 genotype and abdominal fat

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Genome-Wide Association Analysis of Autoantibody Positivity in Type 1 Diabetes Cases

The genetic basis of autoantibody production is largely unknown outside of associations located in the major histocompatibility complex (MHC) human leukocyte antigen (HLA) region. The aim of this study is the discovery of new genetic associations with autoantibody positivity using genome-wide association scan single nucleotide polymorphism (SNP) data in type 1 diabetes (T1D) patients with autoantibody measurements. We measured two anti-islet autoantibodies, glutamate decarboxylase (GADA, n = 2,506), insulinoma-associated antigen 2 (IA-2A, n = 2,498), antibodies to the autoimmune thyroid (Graves') disease (AITD) autoantigen thyroid peroxidase (TPOA, n = 8,300), and antibodies against gastric parietal cells (PCA, n = 4,328) that are associated with autoimmune gastritis. Two loci passed a stringent genome-wide significance level (p<10(-10)): 1q23/FCRL3 with IA-2A and 9q34/ABO with PCA. Eleven of 52 non-MHC T1D loci showed evidence of association with at least one autoantibody at a false discovery rate of 16%: 16p11/IL27-IA-2A, 2q24/IFIH1-IA-2A and PCA, 2q32/STAT4-TPOA, 10p15/IL2RA-GADA, 6q15/BACH2-TPOA, 21q22/UBASH3A-TPOA, 1p13/PTPN22-TPOA, 2q33/CTLA4-TPOA, 4q27/IL2/TPOA, 15q14/RASGRP1/TPOA, and 12q24/SH2B3-GADA and TPOA. Analysis of the TPOA-associated loci in 2,477 cases with Graves' disease identified two new AITD loci (BACH2 and UBASH3A)

A Genome-Wide Association Scan on the Levels of Markers of Inflammation in Sardinians Reveals Associations That Underpin Its Complex Regulation

Identifying the genes that influence levels of pro-inflammatory molecules can help to elucidate the mechanisms underlying this process. We first conducted a two-stage genome-wide association scan (GWAS) for the key inflammatory biomarkers Interleukin-6 (IL-6), the general measure of inflammation erythrocyte sedimentation rate (ESR), monocyte chemotactic protein-1 (MCP-1), and high-sensitivity C-reactive protein (hsCRP) in a large cohort of individuals from the founder population of Sardinia. By analysing 731,213 autosomal or X chromosome SNPs and an additional ∼1.9 million imputed variants in 4,694 individuals, we identified several SNPs associated with the selected quantitative trait loci (QTLs) and replicated all the top signals in an independent sample of 1,392 individuals from the same population. Next, to increase power to detect and resolve associations, we further genotyped the whole cohort (6,145 individuals) for 293,875 variants included on the ImmunoChip and MetaboChip custom arrays. Overall, our combined approach led to the identification of 9 genome-wide significant novel independent signals—5 of which were identified only with the custom arrays—and provided confirmatory evidence for an additional 7. Novel signals include: for IL-6, in the ABO gene (rs657152, p = 2.13×10−29); for ESR, at the HBB (rs4910472, p = 2.31×10−11) and UCN119B/SPPL3 (rs11829037, p = 8.91×10−10) loci; for MCP-1, near its receptor CCR2 (rs17141006, p = 7.53×10−13) and in CADM3 (rs3026968, p = 7.63×10−13); for hsCRP, within the CRP gene (rs3093077, p = 5.73×10−21), near DARC (rs3845624, p = 1.43×10−10), UNC119B/SPPL3 (rs11829037, p = 1.50×10−14), and ICOSLG/AIRE (rs113459440, p = 1.54×10−08) loci. Confirmatory evidence was found for IL-6 in the IL-6R gene (rs4129267); for ESR at CR1 (rs12567990) and TMEM57 (rs10903129); for MCP-1 at DARC (rs12075); and for hsCRP at CRP (rs1205), HNF1A (rs225918), and APOC-I (rs4420638). Our results improve the current knowledge of genetic variants underlying inflammation and provide novel clues for the understanding of the molecular mechanisms regulating this complex process

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk.

Blood pressure is a heritable trait influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (≥140 mm Hg systolic blood pressure or  ≥90 mm Hg diastolic blood pressure). Even small increments in blood pressure are associated with an increased risk of cardiovascular events. This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention