Automated profiling of spontaneous speech in primary progressive aphasia and behavioral-variant frontotemporal dementia: An approach based on usage-frequency.

Language production provides important markers of neurological health. One feature of impairments of language and cognition, such as those that occur in stroke aphasia or Alzheimer's disease, is an overuse of high frequency, "familiar" expressions. We used computerized analysis to profile narrative speech samples from speakers with variants of frontotemporal dementia (FTD), including subtypes of primary progressive aphasia (PPA). Analysis was performed on language samples from 29 speakers with semantic variant PPA (svPPA), 25 speakers with logopenic variant PPA (lvPPA), 34 speakers with non-fluent variant PPA (nfvPPA), 14 speakers with behavioral variant FTD (bvFTD) and 20 older normal controls (NCs). We used frequency and collocation strength measures to determine use of familiar words and word combinations. We also computed word counts, content word ratio and a combination ratio, a measure of the degree to which the individual produces connected language. All dementia subtypes differed significantly from NCs. The most discriminating variables were word count, combination ratio, and content word ratio, each of which distinguished at least one dementia group from NCs. All participants with PPA, but not participants with bvFTD, produced significantly more frequent forms at the level of content words, word combinations, or both. Each dementia group differed from the others on at least one variable, and language production variables correlated with established behavioral measures of disease progression. A machine learning classifier, using narrative speech variables, achieved 90% accuracy when classifying samples as NC or dementia, and 59.4% accuracy when matching samples to their diagnostic group. Automated quantification of spontaneous speech in both language-led and non-language led dementias, is feasible. It allows extraction of syndromic profiles that complement those derived from standardized tests, warranting further evaluation as candidate biomarkers. Inclusion of frequency-based language variables benefits profiling and classification.

Climate teleconnections and recent patterns of human and animal disease outbreaks.

BACKGROUND: Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Although Rift Valley fever outbreaks have been known to follow periods of above-normal rainfall, the timing of the outbreak events has largely been unknown. Similarly, there is inadequate knowledge on climate drivers of chikungunya outbreaks. We analyze a variety of climate and satellite-derived vegetation measurements to explain the coupling between patterns of climate variability and disease outbreaks of Rift Valley fever and chikungunya. METHODS AND FINDINGS: We derived a teleconnections map by correlating long-term monthly global precipitation data with the NINO3.4 sea surface temperature (SST) anomaly index. This map identifies regional hot-spots where rainfall variability may have an influence on the ecology of vector borne disease. Among the regions are Eastern and Southern Africa where outbreaks of chikungunya and Rift Valley fever occurred 2004-2009. Chikungunya and Rift Valley fever case locations were mapped to corresponding climate data anomalies to understand associations between specific anomaly patterns in ecological and climate variables and disease outbreak patterns through space and time. From these maps we explored associations among Rift Valley fever disease occurrence locations and cumulative rainfall and vegetation index anomalies. We illustrated the time lag between the driving climate conditions and the timing of the first case of Rift Valley fever. Results showed that reported outbreaks of Rift Valley fever occurred after ∼3-4 months of sustained above-normal rainfall and associated green-up in vegetation, conditions ideal for Rift Valley fever mosquito vectors. For chikungunya we explored associations among surface air temperature, precipitation anomalies, and chikungunya outbreak locations. We found that chikungunya outbreaks occurred under conditions of anomalously high temperatures and drought over Eastern Africa. However, in Southeast Asia, chikungunya outbreaks were negatively correlated (p<0.05) with drought conditions, but positively correlated with warmer-than-normal temperatures and rainfall. CONCLUSIONS/SIGNIFICANCE: Extremes in climate conditions forced by the El Niño/Southern Oscillation (ENSO) lead to severe droughts or floods, ideal ecological conditions for disease vectors to emerge, and may result in epizootics and epidemics of Rift Valley fever and chikungunya. However, the immune status of livestock (Rift Valley fever) and human (chikungunya) populations is a factor that is largely unknown but very likely plays a role in the spatial-temporal patterns of these disease outbreaks. As the frequency and severity of extremes in climate increase, the potential for globalization of vectors and disease is likely to accelerate. Understanding the underlying patterns of global and regional climate variability and their impacts on ecological drivers of vector-borne diseases is critical in long-range planning of appropriate disease and disease-vector response, control, and mitigation strategies.

Genetic mapping and exome sequencing identify variants associated with five novel diseases.

The Clinic for Special Children (CSC) has integrated biochemical and molecular methods into a rural pediatric practice serving Old Order Amish and Mennonite (Plain) children. Among the Plain people, we have used single nucleotide polymorphism (SNP) microarrays to genetically map recessive disorders to large autozygous haplotype blocks (mean = 4.4 Mb) that contain many genes (mean = 79). For some, uninformative mapping or large gene lists preclude disease-gene identification by Sanger sequencing. Seven such conditions were selected for exome sequencing at the Broad Institute; all had been previously mapped at the CSC using low density SNP microarrays coupled with autozygosity and linkage analyses. Using between 1 and 5 patient samples per disorder, we identified sequence variants in the known disease-causing genes SLC6A3 and FLVCR1, and present evidence to strongly support the pathogenicity of variants identified in TUBGCP6, BRAT1, SNIP1, CRADD, and HARS. Our results reveal the power of coupling new genotyping technologies to population-specific genetic knowledge and robust clinical data.

Anatomy and development of the meninges: implications for subdural collections and CSF circulation.

The dura is traditionally viewed as a supportive fibrous covering of the brain containing the dural venous sinuses but otherwise devoid of vessels and lacking any specific function. However, review of the embryology and anatomy reveals the dura to be a complex, vascularized and innervated structure, not a simple fibrous covering. The dura contains an inner vascular plexus that is larger in the infant than in the adult, and this plexus likely plays a role in CSF absorption. This role could be particularly important in the infant whose arachnoid granulations are not completely developed. Although subdural hemorrhage is frequently traumatic, there are nontraumatic conditions associated with subdural hemorrhage, and the inner dural plexus is a likely source of bleeding in these nontraumatic circumstances. This review outlines the development and age-specific vascularity of the dura and offers an alternative perspective on the role of the dura in homeostasis of the central nervous system.

Clinical application of DNA microarrays: molecular diagnosis and HLA matching of an Amish child with severe combined immune deficiency.

Amish and Mennonite children with severe combined immune deficiency (SCID) often die without treatment as a result of delayed diagnoses and prohibitive costs of therapy. In this detailed case report, we describe the novel use of DNA microarrays to improve the diagnosis and management of an Amish infant with SCID. Using 10,000 single nucleotide polymorphism (SNP) genotypes from the patient, her parents, and seven siblings, we identified the recombinase activating genes for diagnostic sequencing, and then characterized a novel pathogenic variant in RAG1 (c.2974A>G). The same genotype data were used to identify a sibling stem cell donor who was haplo-identical at human leukocyte antigen (HLA) and blood group (ABO) loci. Autozygosity and linkage analysis of SNP genotypes within a family narrows the search for SCID candidate genes and provides a relatively simple and inexpensive way to identify potential tissue donors among biological siblings.

Abdominal mucinous cystic neoplasm in a male child.

Mucinous cystic neoplasms (MCNs) make up a morphologic family of similar appearing tumors arising in the ovary and various extraovarian sites, including the pancreas, hepatobiliary tract, paratesticular soft tissues, and mesentery. Other than the uncommon mucinous cystadenoma of the ovary presenting in adolescence, MCNs are rarely seen by the pediatric pathologist. The present case is a 5-year-old boy with an abdominal mass appearing to arise in the mesentery of the small intestine. Because of its unresectability, a generous biopsy was performed and disclosed a MCN with focal complex papillary architecture in the absence of appreciable cytologic atypia or invasion into the wall. Like other MCNs, this tumor had an inhibin-positive, ovarian-like stroma that was nonreactive for estrogen and progesterone receptors. Only 1 other case of a mesenteric MCN has been reported to date in a child and none in a male. The MCN of the mesentery joins other, somewhat more common cystic lesions of the omentum and mesentery presenting in childhood.