A Class Representative Model for Pure Parsimony Haplotyping under Uncertain Data

The Pure Parsimony Haplotyping (PPH) problem is a NP-hard combinatorial optimization problem that consists of finding the minimum number of haplotypes necessary to explain a given set of genotypes. PPH has attracted more and more attention in recent years due to its importance in analysis of many fine-scale genetic data. Its application fields range from mapping complex disease genes to inferring population histories, passing through designing drugs, functional genomics and pharmacogenetics. In this article we investigate, for the first time, a recent version of PPH called the Pure Parsimony Haplotype problem under Uncertain Data (PPH-UD). This version mainly arises when the input genotypes are not accurate, i.e., when some single nucleotide polymorphisms are missing or affected by errors. We propose an exact approach to solution of PPH-UD based on an extended version of Catanzaro et al. [1] class representative model for PPH, currently the state-of-the-art integer programming model for PPH. The model is efficient, accurate, compact, polynomial-sized, easy to implement, solvable with any solver for mixed integer programming, and usable in all those cases for which the parsimony criterion is well suited for haplotype estimation

A path toward precision medicine for neuroinflammatory mechanisms in Alzheimer's disease

Neuroinflammation commences decades before Alzheimer's disease (AD) clinical onset and represents one of the earliest pathomechanistic alterations throughout the AD continuum. Large-scale genome-wide association studies point out several genetic variants—TREM2, CD33, PILRA, CR1, MS4A, CLU, ABCA7, EPHA1, and HLA-DRB5-HLA-DRB1—potentially linked to neuroinflammation. Most of these genes are involved in proinflammatory intracellular signaling, cytokines/interleukins/cell turnover, synaptic activity, lipid metabolism, and vesicle trafficking. Proteomic studies indicate that a plethora of interconnected aberrant molecular pathways, set off and perpetuated by TNF-α, TGF-β, IL-1β, and the receptor protein TREM2, are involved in neuroinflammation. Microglia and astrocytes are key cellular drivers and regulators of neuroinflammation. Under physiological conditions, they are important for neurotransmission and synaptic homeostasis. In AD, there is a turning point throughout its pathophysiological evolution where glial cells sustain an overexpressed inflammatory response that synergizes with amyloid-β and tau accumulation, and drives synaptotoxicity and neurodegeneration in a self-reinforcing manner. Despite a strong therapeutic rationale, previous clinical trials investigating compounds with anti-inflammatory properties, including non-steroidal anti-inflammatory drugs (NSAIDs), did not achieve primary efficacy endpoints. It is conceivable that study design issues, including the lack of diagnostic accuracy and biomarkers for target population identification and proof of mechanism, may partially explain the negative outcomes. However, a recent meta-analysis indicates a potential biological effect of NSAIDs. In this regard, candidate fluid biomarkers of neuroinflammation are under analytical/clinical validation, i.e., TREM2, IL-1β, MCP-1, IL-6, TNF-α receptor complexes, TGF-β, and YKL-40. PET radio-ligands are investigated to accomplish in vivo and longitudinal regional exploration of neuroinflammation. Biomarkers tracking different molecular pathways (body fluid matrixes) along with brain neuroinflammatory endophenotypes (neuroimaging markers), can untangle temporal–spatial dynamics between neuroinflammation and other AD pathophysiological mechanisms. Robust biomarker–drug codevelopment pipelines are expected to enrich large-scale clinical trials testing new-generation compounds active, directly or indirectly, on neuroinflammatory targets and displaying putative disease-modifying effects: novel NSAIDs, AL002 (anti-TREM2 antibody), anti-Aβ protofibrils (BAN2401), and AL003 (anti-CD33 antibody). As a next step, taking advantage of breakthrough and multimodal techniques coupled with a systems biology approach is the path to pursue for developing individualized therapeutic strategies targeting neuroinflammation under the framework of precision medicine.Sorbonne University Foundation and sponsored by la Fondation pour la Recherche sur Alzheimer. HH is an employee of Eisai Inc. During his previous work (until April 2019), he was supported by the AXA Research Fund, the Fondation partenariale Sorbonne Université and the Fondation pour la Recherche sur Alzheimer, Paris, Franc

Twins Lead to the Prevention of Atherosclerosis: Preliminary Findings of International Twin Study 2009

ABSTRACT Introduction.—Atherosclerosis is an infl ammatory process in which the artery wall thickens as a result of plaque deposition, but this process may be preceded by increased arterial stiffness. We sought to evaluate the infl uence of genetics and shared and unshared environmental components on the onset of atherosclerosis. Methods.—A total of 135 monozygotic (MZ) and 70 dizygotic (DZ) twin pairs (mean age 49 ± 16 years) underwent carotid intima media thickness (IMT; carotid analyzer) and arterial stiffness (augmentation index on brachial artery [Aixbra], pulse wave velocity on aorta [PWVao]; TensioMed Arteriograph) measurements. Results.—Age-adjusted intraclass correlations were greater in MZ than in DZ pairs for proximal right common carotid artery (CCA; MZ = 0.19, DZ = 0.06), proximal and distal left CCA (MZ = 0.27, DZ = 0.06; MZ = 0.27, DZ = 0.13, respectively), and proximal left internal carotid artery (ICA; MZ = 0.39, DZ = −0.54), suggesting a moderate genetic effect. Heritability was estimated to be 18% (95% confi dence interval [CI] = 3–33) for proximal right CCA, 26% and 27% for proximal and distal left CCA, respectively, and 38% (95% CI = 26–49) for proximal left ICA. Regarding distal right CCA and proximal right ICA, no genetic effects were detected. Age-adjusted intraclass correlation of Aixbra and PWVao were 0.65 (95% CI = 0.55–0.72) and 0.46 (95% CI = 0.33–0.57) in MZ, 0.42 (95% CI = 0.24–0.57) and 0.28 (95% CI = 0.08–0.47) in DZ pairs; heritability 45% (95% CI = 12–71%) and 42% (95% CI = 2–57%) adjusted by age, respectively. Conclusions.—The investigated parameters appeared to be only moderately infl uenced by genetic factors. Environmental factors of relevance for these measures appeared not to be shared within family but related to individual experience (e.g., smoking habits, diet, and physical activity). Atherosclerosis detection at an early stage is necessary for treatment to prevent serious complications such as stroke and heart attack

Genetic and environmental factors on the relation of lung function and arterial stiffness

SummaryBackgroundAn association between reduced lung function and increased cardiovascular risk has been reported, but the underlying mechanisms are unknown. The aim of this study was to assess the heritability of lung function and to estimate its genetic association with arterial stiffness.Methods150 monozygotic and 42 dizygotic healthy Hungarian and American Caucasian twin pairs (age 43 ± 17 years) underwent spirometry (forced vital capacity/FVC/, forced expiratory volume in 1 s/FEV1/; MIR Minispir, USA); and their brachial and central augmentation indices (AIx), and aortic pulse wave velocity (PWV) were measured by oscillometric Arteriograph (TensioMed Ltd, Budapest, Hungary). Phenotypic correlations and bivariate Cholesky decomposition models were applied.ResultsAge-, sex-, country- and smoking-adjusted heritability of FEV1, percent predicted FEV1, FVC and percent predicted FVC were 73% (95% confidence interval /CI/: 45–85%), 28% (95% CI: 0–67%), 68% (95% CI: 20–81%) and 45% (95% CI: 0–66%), respectively. Measured and percent predicted FVC and FEV1 values showed no significant phenotypic correlations with AIx or aortic PWV, except for phenotypic twin correlations between measured FEV1, FVC with brachial or aortic augmentation indices which ranged between −0.12 and −0.17. No genetic covariance between lung function and arterial stiffness was found.ConclusionsLung function is heritable and the measured FVC and FEV are phenotypically, but not genetically, associated with augmentation index, a measure of wave reflection. This relationship may in turn reveal further associations leading to a better mechanistic understanding of vascular changes in various airway diseases