Multimodal characterization of the late effects of traumatic brain injury: a methodological overview of the Late Effects of Traumatic Brain Injury Project

Epidemiological studies suggest that a single moderate-to-severe traumatic brain injury (TBI) is associated with an increased risk of neurodegenerative disease, including Alzheimer’s and Parkinson’s disease (AD and PD). Histopathological studies describe complex neurodegenerative pathologies in individuals exposed to single moderate-to-severe TBI or repetitive mild TBI, including chronic traumatic encephalopathy (CTE). However, the clinicopathological links between TBI and post-traumatic neurodegenerative diseases such as AD, PD, and CTE remain poorly understood. Here we describe the methodology of the Late Effects of TBI (LETBI) study, whose goals are to characterize chronic post-traumatic neuropathology and to identify in vivo biomarkers of post-traumatic neurodegeneration. LETBI participants undergo extensive clinical evaluation using National Institutes of Health TBI Common Data Elements, proteomic and genomic analysis, structural and functional MRI, and prospective consent for brain donation. Selected brain specimens undergo ultra-high resolution ex vivo MRI and histopathological evaluation including whole mount analysis. Co-registration of ex vivo and in vivo MRI data enables identification of ex vivo lesions that were present during life. In vivo signatures of postmortem pathology are then correlated with cognitive and behavioral data to characterize the clinical phenotype(s) associated with pathological brain lesions. We illustrate the study methods and demonstrate proof of concept for this approach by reporting results from the first LETBI participant, who despite the presence of multiple in vivo and ex vivo pathoanatomic lesions had normal cognition and was functionally independent until her mid-80s. The LETBI project represents a multidisciplinary effort to characterize post-traumatic neuropathology and identify in vivo signatures of postmortem pathology in a prospective study

Canine models of Duchenne muscular dystrophy and their use in therapeutic strategies

Duchenne muscular dystrophy (DMD) is an X-linked recessive disorder in which the loss of dystrophin causes progressive degeneration of skeletal and cardiac muscle. Potential therapies that carry substantial risk, such as gene and cell-based approaches, must first be tested in animal models, notably the mdx mouse and several dystrophin-deficient breeds of dogs, including golden retriever muscular dystrophy (GRMD). Affected dogs have a more severe phenotype, in keeping with that of DMD, so may better predict disease pathogenesis and treatment efficacy. We and others have developed various phenotypic tests to characterize disease progression in the GRMD model. These biomarkers range from measures of strength and joint contractures to magnetic resonance imaging. Some of these tests are routinely used in clinical veterinary practice, while others require specialized equipment and expertise. By comparing serial measurements from treated and untreated groups, one can document improvement or delayed progression of disease. Potential treatments for DMD may be broadly categorized as molecular, cellular, or pharmacologic. The GRMD model has increasingly been used to assess efficacy of a range of these therapies. While some of these studies have largely provided general proof-of-concept for the treatment under study, others have demonstrated efficacy using the biomarkers discussed. Importantly, just as symptoms in DMD vary among patients, GRMD dogs display remarkable phenotypic variation. While confounding statistical analysis in preclinical trials, this variation offers insight regarding the role that modifier genes play in disease pathogenesis. By correlating functional and mRNA profiling results, gene targets for therapy development can be identified

A Morphometric Assessment of the Intended Function of Cached Clovis Points

A number of functions have been proposed for cached Clovis points. The least complicated hypothesis is that they were intended to arm hunting weapons. It has also been argued that they were produced for use in rituals or in connection with costly signaling displays. Lastly, it has been suggested that some cached Clovis points may have been used as saws. Here we report a study in which we morphometrically compared Clovis points from caches with Clovis points recovered from kill and camp sites to test two predictions of the hypothesis that cached Clovis points were intended to arm hunting weapons: 1) cached points should be the same shape as, but generally larger than, points from kill/camp sites, and 2) cached points and points from kill/camp sites should follow the same allometric trajectory. The results of the analyses are consistent with both predictions and therefore support the hypothesis. A follow-up review of the fit between the results of the analyses and the predictions of the other hypotheses indicates that the analyses support only the hunting equipment hypothesis. We conclude from this that cached Clovis points were likely produced with the intention of using them to arm hunting weapons

Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. Video Abstract [Figure presented] Keywords: type 2 diabetes (T2D); genetics; disease mechanism; SLC16A11; MCT11; solute carrier (SLC); monocarboxylates; fatty acid metabolism; lipid metabolism; precision medicin

Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development

The stigma turbine:A theoretical framework for conceptualizing and contextualizing marketplace stigma

Stigmas, or discredited personal attributes, emanate from social perceptions of physical characteristics, aspects of character, and “tribal” associations (e.g., race; Goffman 1963). Extant research emphasizes the perspective of the stigma target, with some scholars exploring how social institutions shape stigma. Yet the ways stakeholders within the socio-commercial sphere create, perpetuate, or resist stigma remain overlooked. We introduce and define marketplace stigma as the labeling, stereotyping, and devaluation by and of commercial stakeholders (consumers, companies and their employees, stockholders, institutions) and their offerings (products, services, experiences). We offer the Stigma Turbine (ST) as a unifying conceptual framework that locates marketplace stigma within the broader sociocultural context, and illuminates its relationship to forces that exacerbate or blunt stigma. In unpacking the ST, we reveal the critical role market stakeholders can play in (de)stigmatization, explore implications for marketing practice and public policy, and offer a research agenda to further our understanding of marketplace stigma and stakeholder welfare

Economy and Divorces: Their Impact Over Time on the Self-Employment Rates in Spain

The paper used time-series data and examined the effect of economic and social variables on the male and female self-employment rates in Spain. We also employed cointegration analysis (with and without) structural breaks. We thus find strong evidence that long run relationships exist among the variables. More precisely, we find that the unemployment rates and the ratio of self-employment to employees’ earnings have a positive effect on self-employment, whereas, economic development and divorce rates have a negative effect. Importantly, we find that the economic variables have equal or stronger long run impact on females than males, with both groups reacting to changes in family circumstances. Finally, we show that the short run family circumstances are better predictors of self-employment choices rather than economic factors, with self-employment being a means of adjustment to new personal circumstances and economic needs

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p

Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson’s r=0.77 and 0.76, respectively, across SNPs with p &lt; 4.4 × 10−4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45×10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p &gt; 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec