Dataset Information

Network Analysis Identifies Sex-Specific Gene Expression Changes in Blood of Amyotrophic Lateral Sclerosis Patients.

ABSTRACT: Understanding the molecular mechanisms underlying the pathogenesis of amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disease, is a major challenge. We used co-expression networks implemented by the SWitch Miner software to identify switch genes associated with drastic transcriptomic changes in the blood of ALS patients. Functional analyses revealed that switch genes were enriched in pathways related to the cell cycle, hepatitis C, and small cell lung cancer. Analysis of switch genes by sex revealed that switch genes from males were associated with metabolic pathways, including PI3K-AKT, sphingolipid, carbon metabolism, FOXO, and AMPK signaling. In contrast, female switch genes related to infectious diseases, inflammation, apoptosis, and atherosclerosis. Furthermore, eight switch genes showed sex-specific gene expression patterns. Collectively, we identified essential genes and pathways that may explain sex differences observed in ALS. Future studies investigating the potential role of these genes in driving disease disparities between males and females with ALS are warranted.

SUBMITTER: Santiago JA

PROVIDER: S-EPMC8269377 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Network Analysis Identifies Sex-Specific Gene Expression Changes in Blood of Amyotrophic Lateral Sclerosis Patients.

Santiago Jose A JA Quinn James P JP Potashkin Judith A JA

International journal of molecular sciences 20210701 13

Understanding the molecular mechanisms underlying the pathogenesis of amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disease, is a major challenge. We used co-expression networks implemented by the SWitch Miner software to identify switch genes associated with drastic transcriptomic changes in the blood of ALS patients. Functional analyses revealed that switch genes were enriched in pathways related to the cell cycle, hepatitis C, and small cell lung cancer. Analysis of swi ...[more]

PMID: 34281203

Similar Datasets

Project description:Multiple sources of evidence suggest that changes in metabolism may precede the onset of motor symptoms in amyotrophic lateral sclerosis. This study aimed to seek evidence for alterations in the levels of blood indices collected routinely in the primary care setting prior to the onset of motor symptoms in amyotrophic lateral sclerosis. Premorbid data, measured as part of routine health screening, for total cholesterol, high-density and low-density lipoprotein cholesterol, triglyceride, glycated haemoglobin A1c and creatinine were collected retrospectively from (i) a cohort of amyotrophic lateral sclerosis patients attending a specialist clinic (n = 143) and (ii) from primary care-linked data within UK Biobank. Data were fitted using linear mixed effects models with linear b-splines to identify inflection points, controlling for age and sex. In specialist amyotrophic lateral sclerosis clinic cases, models indicated decreasing levels of total and low-density lipoprotein cholesterol prior to an inflection point in the years before symptom onset (total cholesterol 3.25 years, low-density lipoprotein cholesterol 1.25 years), after which they stabilized or rose. A similar pattern was observed in amyotrophic lateral sclerosis cases within UK Biobank, occurring several years prior to diagnosis (total cholesterol 7 years, low-density lipoprotein cholesterol 7.25 years), differing significantly from matched controls. High-density lipoprotein cholesterol followed a similar pattern but was less robust to sensitivity analyses. Levels of triglyceride remained stable throughout. Glycated haemoglobin temporal profiles were not consistent between the clinic and biobank cohorts. Creatinine level trajectories prior to amyotrophic lateral sclerosis did not differ significantly from controls but decreased significantly in the symptomatic period after an inflection point of 0.25 years after symptom onset (clinic cohort) or 0.5 years before diagnosis (UK Biobank). These data provide further evidence for a pre-symptomatic period of dynamic metabolic change in amyotrophic lateral sclerosis, consistently associated with alterations in blood cholesterols. Such changes may ultimately contribute to biomarkers applicable to population screening and for pathways guiding the targeting of preventative therapy.

Project description:BackgroundFew genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysisResultsAdvanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis. An unexpected discovery of a strong genetic background in sporadic ALS using a DNA multiarray panel and analytical processing of the data with advanced artificial neural networks was found. The predictive accuracy obtained with Linear Discriminant Analysis and Standard Artificial Neural Networks ranged from 70% to 79% (average 75.31%) and from 69.1 to 86.2% (average 76.6%) respectively. The corresponding value obtained with Advanced Intelligent Systems reached an average of 96.0% (range 94.4 to 97.6%). This latter approach allowed the identification of seven genetic variants essential to differentiate cases from controls: apolipoprotein E arg158cys; hepatic lipase -480 C/T; endothelial nitric oxide synthase 690 C/T and glu298asp; vitamin K-dependent coagulation factor seven arg353glu, glycoprotein Ia/IIa 873 G/A and E-selectin ser128arg.ConclusionThis study provides an alternative and reliable method to approach complex diseases. Indeed, the application of a novel artificial intelligence-based method offers a new insight into genetic markers of sporadic ALS pointing out the existence of a strong genetic background.

Project description:Magnetic resonance imaging measures have been proposed as objective markers to study upper motor neuron loss in motor neuron disorders. Cross-sectional studies have identified imaging differences between groups of healthy controls and patients with amyotrophic lateral sclerosis (ALS) or primary lateral sclerosis (PLS) that correlate with disease severity, but it is not known whether imaging measures change as disease progresses. Additionally, whether imaging measures change in a similar fashion with disease progression in PLS and ALS is unclear. To address these questions, clinical and imaging evaluations were first carried out in a prospective cross-sectional study of 23 ALS and 22 PLS patients with similar motor impairment and 19 age-matched healthy controls. Clinical evaluations consisted of a neurological examination, the ALS Functional rating scale-revised, and measures of finger tapping, gait, and timed speech. Age and ALSFRS score were not different, but PLS patients had longer duration of symptoms. Imaging measures examined were cortical thickness, regional brain volumes, and diffusion tensor imaging of the corticospinal tract and callosum. Imaging measures that differed from controls in a cross-sectional vertex-wise analysis were used as regions of interest for longitudinal analysis, which was carried out in 9 of the ALS patients (interval 1.26 ± 0.72 years) and 12 PLS patients (interval 2.08 ± 0.93 years). In the cross-sectional study both groups had areas of cortical thinning, which was more extensive in motor regions in PLS patients. At follow-up, clinical measures declined more in ALS than PLS patients. Cortical thinning and grey matter volume loss of the precentral gyri progressed over the follow-up interval. Fractional anisotropy of the corticospinal tracts remained stable, but the cross-sectional area declined in ALS patients. Changes in clinical measures correlated with changes in precentral cortical thickness and grey matter volume. The rate of cortical thinning was greater in ALS patients with shorter disease durations, suggesting that thickness decreases in a non-linear fashion. Thus, cortical thickness changes are a potential imaging marker for disease progression in individual patients, but the magnitude of change likely depends on disease duration and progression rate. Differences between PLS and ALS patients in the magnitude of thinning in cross-sectional studies are likely to reflect longer disease duration. We conclude that there is an evolution of structural imaging changes with disease progression in motor neuron disorders. Some changes, such as diffusion properties of the corticospinal tract, occur early while cortical thinning and volume loss occur later.

Dataset Information

Network Analysis Identifies Sex-Specific Gene Expression Changes in Blood of Amyotrophic Lateral Sclerosis Patients.

Publications

Network Analysis Identifies Sex-Specific Gene Expression Changes in Blood of Amyotrophic Lateral Sclerosis Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets