A putative Alzheimer's disease risk allele in PCK1 influences brain atrophy in multiple sclerosis

A Method for Bridging Population-Specific Genotypes to Detect Gene Modules Associated with Alzheimer's Disease

BACKGROUND

Genome-wide association studies have successfully identified variants associated with multiple conditions. However, generalizing discoveries across diverse populations remains challenging due to large variations in genetic composition. Methods that perform gene expression imputation have attempted to address the transferability of gene discoveries across populations, but with limited success.

METHODS

Here, we introduce a pipeline that combines gene expression imputation with gene module discovery, including a dense gene module search and a gene set variation analysis, to address the transferability issue. Our method feeds association probabilities of imputed gene expression with a selected phenotype into tissue-specific gene-module discovery over protein interaction networks to create higher-level gene modules.

RESULTS

We demonstrate our method's utility in three case-control studies of Alzheimer's disease (AD) for three different race/ethnic populations (Whites, African descent and Hispanics). We discovered 182 AD-associated genes from gene modules shared between these populations, highlighting new gene modules associated with AD.

CONCLUSIONS

Our innovative framework has the potential to identify robust discoveries across populations based on gene modules, as demonstrated in AD.

Genetic Variability in Molecular Pathways Implicated in Alzheimer's Disease: A Comprehensive Review

Alzheimer's disease (AD) is a complex neurodegenerative disease, affecting a significant part of the population. The majority of AD cases occur in the elderly with a typical age of onset of the disease above 65 years. AD presents a major burden for the healthcare system and since population is rapidly aging, the burden of the disease will increase in the future. However, no effective drug treatment for a full-blown disease has been developed to date. The genetic background of AD is extensively studied; numerous genome-wide association studies (GWAS) identified significant genes associated with increased risk of AD development. This review summarizes more than 100 risk loci. Many of them may serve as biomarkers of AD progression, even in the preclinical stage of the disease. Furthermore, we used GWAS data to identify key pathways of AD pathogenesis: cellular processes, metabolic processes, biological regulation, localization, transport, regulation of cellular processes, and neurological system processes. Gene clustering into molecular pathways can provide background for identification of novel molecular targets and may support the development of tailored and personalized treatment of AD.

HLA in Alzheimer's Disease: Genetic Association and Possible Pathogenic Roles

Alzheimer's disease (AD) is commonly considered as the most prominent dementing disorder globally and is characterized by the deposition of misfolded amyloid-β (Aβ) peptide and the aggregation of neurofibrillary tangles. Immunological disturbances and neuroinflammation, which result from abnormal immunological reactivations, are believed to be the primary stimulating factors triggering AD-like neuropathy. It has been suggested by multiple previous studies that a bunch of AD key influencing factors might be attributed to genes encoding human leukocyte antigen (HLA), whose variety is an essential part of human adaptive immunity. A wide range of activities involved in immune responses may be determined by HLA genes, including inflammation mediated by the immune response, T-cell transendothelial migration, infection, brain development and plasticity in AD pathogenesis, and so on. The goal of this article is to review the recent epidemiological findings of HLA (mainly HLA class I and II) associated with AD and investigate to what extent the genetic variations of HLA were clinically significant as pathogenic factors for AD. Depending on the degree of contribution of HLA in AD pathogenesis, targeted research towards HLA may propel AD therapeutic strategies into a new era of development.

Intricate Regulation of Phosphoenolpyruvate Carboxykinase (PEPCK) Isoforms in Normal Physiology and Disease

BACKGROUND

The phosphoenolpyruvate carboxykinase (PEPCK) isoforms are considered as rate-limiting enzymes for gluconeogenesis and glyceroneogenesis pathways. PEPCK exhibits several interesting features such as a) organelle-specific isoforms (cytosolic and a mitochondrial) in vertebrate clade, b) tissue-specific expression of isoforms and c) organism-specific requirement of ATP or GTP as a cofactor. In higher organisms, PEPCK isoforms are intricately regulated and activated through several physiological and pathological stimuli such as corticoids, hormones, nutrient starvation and hypoxia. Isoform-specific transcriptional/translational regulation and their interplay in maintaining glucose homeostasis remain to be fully understood. Mounting evidence indicates the significant involvement of PEPCK isoforms in physiological processes (development and longevity) and in the progression of a variety of diseases (metabolic disorders, cancer, Smith-Magenis syndrome).

OBJECTIVE

The present systematic review aimed to assimilate existing knowledge of transcriptional and translational regulation of PEPCK isoforms derived from cell, animal and clinical models.

CONCLUSION

Based on current knowledge and extensive bioinformatics analysis, in this review we have provided a comparative (epi)genetic understanding of PCK1 and PCK2 genes encompassing regulatory elements, disease-associated polymorphisms, copy number variations, regulatory miRNAs and CpG densities. We have also discussed various exogenous and endogenous modulators of PEPCK isoforms and their signaling mechanisms. A comprehensive review of existing knowledge of PEPCK regulation and function may enable identification of the underlying gaps to design new pharmacological strategies and interventions for the diseases associated with gluconeogenesis.

Prediction of Alzheimer's Disease-Associated Genes by Integration of GWAS Summary Data and Expression Data

Alzheimer's disease (AD) is the most common cause of dementia. It is the fifth leading cause of death among elderly people. With high genetic heritability (79%), finding the disease's causal genes is a crucial step in finding a treatment for AD. Following the International Genomics of Alzheimer's Project (IGAP), many disease-associated genes have been identified; however, we do not have enough knowledge about how those disease-associated genes affect gene expression and disease-related pathways. We integrated GWAS summary data from IGAP and five different expression-level data by using the transcriptome-wide association study method and identified 15 disease-causal genes under strict multiple testing (α < 0.05), and four genes are newly identified. We identified an additional 29 potential disease-causal genes under a false discovery rate (α < 0.05), and 21 of them are newly identified. Many genes we identified are also associated with an autoimmune disorder.

A systems medicine approach reveals disordered immune system and lipid metabolism in multiple sclerosis patients

Identification of autoimmune processes and introduction of new autoantigens involved in the pathogenesis of multiple sclerosis (MS) can be helpful in the design of new drugs to prevent unresponsiveness and side effects in patients. To find significant changes, we evaluated the autoantibody repertoires in newly diagnosed relapsing-remitting MS patients (NDP) and those receiving disease-modifying therapy (RP). Through a random peptide phage library, a panel of NDP- and RP-specific peptides was identified, producing two protein data sets visualized using Gephi, based on protein--protein interactions in the STRING database. The top modules of NDP and RP networks were assessed using Enrichr. Based on the findings, a set of proteins, including ATP binding cassette subfamily C member 1 (ABCC1), neurogenic locus notch homologue protein 1 (NOTCH1), hepatocyte growth factor receptor (MET), RAF proto-oncogene serine/threonine-protein kinase (RAF1) and proto-oncogene vav (VAV1) was found in NDP and was involved in over-represented terms correlated with cell-mediated immunity and cancer. In contrast, transcription factor RelB (RELB), histone acetyltransferase p300 (EP300), acetyl-CoA carboxylase 2 (ACACB), adiponectin (ADIPOQ) and phosphoenolpyruvate carboxykinase 2 mitochondrial (PCK2) had major contributions to viral infections and lipid metabolism as significant events in RP. According to these findings, further research is required to demonstrate the pathogenic roles of such proteins and autoantibodies targeting them in MS and to develop therapeutic agents which can ameliorate disease severity.

Cardiac transcriptome profiling of diabetic Akita mice using microarray and next generation sequencing

Although diabetes mellitus (DM) causes cardiomyopathy and exacerbates heart failure, the underlying molecular mechanisms for diabetic cardiomyopathy/heart failure are poorly understood. Insulin2 mutant (Ins2+/-) Akita is a mouse model of T1DM, which manifests cardiac dysfunction. However, molecular changes at cardiac transcriptome level that lead to cardiomyopathy remain unclear. To understand the molecular changes in the heart of diabetic Akita mice, we profiled cardiac transcriptome of Ins2+/- Akita and Ins2+/+ control mice using next generation sequencing (NGS) and microarray, and determined the implications of differentially expressed genes on various heart failure signaling pathways using Ingenuity pathway (IPA) analysis. First, we validated hyperglycemia, increased cardiac fibrosis, and cardiac dysfunction in twelve-week male diabetic Akita. Then, we analyzed the transcriptome levels in the heart. NGS analyses on Akita heart revealed 137 differentially expressed transcripts, where Bone Morphogenic Protein-10 (BMP10) was the most upregulated and hairy and enhancer of split-related (HELT) was the most downregulated gene. Moreover, twelve long non-coding RNAs (lncRNAs) were upregulated. The microarray analyses on Akita heart showed 351 differentially expressed transcripts, where vomeronasal-1 receptor-180 (Vmn1r180) was the most upregulated and WD Repeat Domain 83 Opposite Strand (WDR83OS) was the most downregulated gene. Further, miR-101c and H19 lncRNA were upregulated but Neat1 lncRNA was downregulated in Akita heart. Eleven common genes were upregulated in Akita heart in both NGS and microarray analyses. IPA analyses revealed the role of these differentially expressed genes in key signaling pathways involved in diabetic cardiomyopathy. Our results provide a platform to initiate focused future studies by targeting these genes and/or non-coding RNAs, which are differentially expressed in Akita hearts and are involved in diabetic cardiomyopathy.

Statistical Evidence Suggests that Inattention Drives Hyperactivity/Impulsivity in Attention Deficit-Hyperactivity Disorder

Background

Numerous factor analytic studies consistently support a distinction between two symptom domains of attention-deficit/hyperactivity disorder (ADHD), inattention and hyperactivity/impulsivity. Both dimensions show high internal consistency and moderate to strong correlations with each other. However, it is not clear what drives this strong correlation. The aim of this paper is to address this issue.

Method

We applied a sophisticated approach for causal discovery on three independent data sets of scores of the two ADHD dimensions in NeuroIMAGE (total N = 675), ADHD-200 (N = 245), and IMpACT (N = 164), assessed by different raters and instruments, and further used information on gender or a genetic risk haplotype.

Results

In all data sets we found strong statistical evidence for the same pattern: the clear dependence between hyperactivity/impulsivity symptom level and an established genetic factor (either gender or risk haplotype) vanishes when one conditions upon inattention symptom level. Under reasonable assumptions, e.g., that phenotypes do not cause genotypes, a causal model that is consistent with this pattern contains a causal path from inattention to hyperactivity/impulsivity.

Conclusions

The robust dependency cancellation observed in three different data sets suggests that inattention is a driving factor for hyperactivity/impulsivity. This causal hypothesis can be further validated in intervention studies. Our model suggests that interventions that affect inattention will also have an effect on the level of hyperactivity/impulsivity. On the other hand, interventions that affect hyperactivity/impulsivity would not change the level of inattention. This causal model may explain earlier findings on heritable factors causing ADHD reported in the study of twins with learning difficulties.

Genes and Environment in Multiple Sclerosis project: A platform to investigate multiple sclerosis risk

The Genes and Environment in Multiple Sclerosis project establishes a platform to investigate the events leading to multiple sclerosis (MS) in at-risk individuals. It has recruited 2,632 first-degree relatives from across the USA. Using an integrated genetic and environmental risk score, we identified subjects with twice the MS risk when compared to the average family member, and we report an initial incidence rate in these subjects that is 30 times greater than that of sporadic MS. We discuss the feasibility of large-scale studies of asymptomatic at-risk subjects that leverage modern tools of subject recruitment to execute collaborative projects.

Concise review: modeling multiple sclerosis with stem cell biological platforms: toward functional validation of cellular and molecular phenotypes in inflammation-induced neurodegeneration

In recent years, tremendous progress has been made in identifying novel mechanisms and new medications that regulate immune cell function in multiple sclerosis (MS). However, a significant unmet need is the identification of the mechanisms underlying neurodegeneration, because patients continue to manifest brain atrophy and disability despite current therapies. Neural and mesenchymal stem cells have received considerable attention as therapeutic candidates to ameliorate the disease in preclinical and phase I clinical trials. More recently, progress in somatic cell reprogramming and induced pluripotent stem cell technology has allowed the generation of human "diseased" neurons in a patient-specific setting and has provided a unique biological tool that can be used to understand the cellular and molecular mechanisms of neurodegeneration. In the present review, we discuss the application and challenges of these technologies, including the generation of neurons, oligodendrocytes, and oligodendrocyte progenitor cells (OPCs) from patients and novel stem cell and OPC cellular arrays, in the discovery of new mechanistic insights and the future development of MS reparative therapies.

Relationship between Helicobacter pylori infection and multiple sclerosis

BACKGROUND

Recent data indicate the presence of immunomodulating properties of Helicobacter pylori (Hp) (Hp Sydney Strain-1 antigen) in an experimental model of multiple sclerosis (MS), and there are limited contradictory epidemiologic data regarding Hp serology in MS patients.

METHODS

The aim of this prospective, comparative study was to validate the incidence of active Hp infection by histology and the endoscopic abnormalities, in 44 patients with relapsing-remitting MS and 20 anemic controls.

RESULTS

The overall prevalence of histologically confirmed active Hp infection in 44 MS patients was 86.4% vs. 50% in 20 matched anemic control participants (P=0.002, odds ratio 6.33, 95%CI 1.85-21.64). Concomitant diseases of autoimmune origin including hypothyroidism and ulcerative colitis were exclusively present in MS patients. Moreover, a trend of increased presence of pathological endoscopic findings such as hiatus hernia, Barrett's esophagus and duodenal ulcer disease was observed in MS patients compared with controls; Barrett's esophagus and duodenal ulcers were exclusively observed in MS patients. Likewise, Hp (+) MS patients showed exclusive presence of hiatus hernia, esophagitis and duodenal ulcer disease compared with Hp (-) MS patients.

CONCLUSION

Hp infection appears to be more frequent in MS patients. If confirmed, this might indicate either a common factor that causes susceptibilities to both MS and Hp infection or that Hp might be a causal factor for developing MS. If a causal link between Hp infection and MS is confirmed in the future, this may have a major impact on the pathophysiology and management of MS.

CLU genetic variants and cognitive decline among elderly and oldest old

The CLU gene is one of the prime genetic candidates associated with Alzheimers disease. In the present study CLU genotypes and haplotypes were associated with baseline cognition and the rate of cognitive decline in two cohorts, the Danish 1905 birth cohort (93 years of age in 1998) and the Longitudinal Study of Aging Danish twins (LSADT) (73-83 year old twins in 1997). Both Mini Mental State Examination (MMSE) and a cognitive composite score was attained up to six times for up to 10 years and analysed using random effects models and vital status. The rs11136000 T allele was associated with better baseline cognitive performance both in the LSADT (effect on intercept: 0.41 95% CI [-0.04; 0.87]) and the 1905 birth cohort (effect on intercept: 0.28 95% CI [0.01; 0.55]), although it did not reach significance in the LSADT cohort. However, the rs11136000 T allele was significantly associated with a steeper decline (effect on slope: -0.06 95% CI [-0.11; -0.01]) in the LSADT cohort, but not in the 1905 birth cohort. Haplotype analyses revealed that carriers of the common rs11136000, rs1532278 and rs9331888 TTC haplotype (36%) in the CLU gene performed cognitively better than non-carriers in the 1905 birth cohort (effect on intercept: 0.50 95% CI [0.12; 0.91]) and carriers of a rare TCC haplotype (1%) performed worse on the cognitive composite score (effect on intercept: -1.51 95% CI [-2.92; -0.06]). The association between the TTC haplotype and better cognitive composite score was higher among those surviving past the age of 98 (p = 0.014), and among these the TTC haplotype was borderline associated with a steep decline (effect on slope: -0.13 95% CI [-0.27; 0.00]). In summery CLU genetic variants associate with cognition in two cohorts, but the genetic effect of CLU seems to regress toward the mean when aging.

Modeling disease severity in multiple sclerosis using electronic health records

Objective

To optimally leverage the scalability and unique features of the electronic health records (EHR) for research that would ultimately improve patient care, we need to accurately identify patients and extract clinically meaningful measures. Using multiple sclerosis (MS) as a proof of principle, we showcased how to leverage routinely collected EHR data to identify patients with a complex neurological disorder and derive an important surrogate measure of disease severity heretofore only available in research settings.

Methods

In a cross-sectional observational study, 5,495 MS patients were identified from the EHR systems of two major referral hospitals using an algorithm that includes codified and narrative information extracted using natural language processing. In the subset of patients who receive neurological care at a MS Center where disease measures have been collected, we used routinely collected EHR data to extract two aggregate indicators of MS severity of clinical relevance multiple sclerosis severity score (MSSS) and brain parenchymal fraction (BPF, a measure of whole brain volume).

Results

The EHR algorithm that identifies MS patients has an area under the curve of 0.958, 83% sensitivity, 92% positive predictive value, and 89% negative predictive value when a 95% specificity threshold is used. The correlation between EHR-derived and true MSSS has a mean R² = 0.38±0.05, and that between EHR-derived and true BPF has a mean R² = 0.22±0.08. To illustrate its clinical relevance, derived MSSS captures the expected difference in disease severity between relapsing-remitting and progressive MS patients after adjusting for sex, age of symptom onset and disease duration (p = 1.56×10⁻¹²).

Conclusion

Incorporation of sophisticated codified and narrative EHR data accurately identifies MS patients and provides estimation of a well-accepted indicator of MS severity that is widely used in research settings but not part of the routine medical records. Similar approaches could be applied to other complex neurological disorders.

Multiple sclerosis susceptibility loci do not alter clinical and MRI outcomes in clinically isolated syndrome

It has not yet been established whether genetic predictors of multiple sclerosis (MS) susceptibility also influence disease severity and accumulation of disability. Our aim was to evaluate associations between 16 previously validated genetic susceptibility markers and MS phenotype. Patients with clinically isolated syndrome verified by positive magnetic resonance imaging (MRI) and cerebrospinal fluid findings (n=179) were treated with interferon-β. Disability and volumetric MRI parameters were evaluated regularly for 2 years. Sixteen single-nucleotide polymorphisms (SNPs) previously validated as predictors of MS susceptibility in our cohort and their combined weighted genetic risk score (wGRS) were tested for associations with clinical (conversion to MS, relapses and disability) and MRI disease outcomes (whole brain, grey matter and white matter volumes, corpus callosum cross-sectional area, brain parenchymal fraction, T2 and T1 lesion volumes) 2 years from disease onset using mixed-effect models. We have found no associations between the tested SNPs and the clinical or MRI outcomes. Neither the combined wGRS predicted MS activity and progression over 2-year follow-up period. Power analyses confirmed 90% power to identify clinically relevant changes in all outcome variables. We conclude that the most important MS susceptibility loci do not determine MS phenotype and disease outcomes.