Alzheimer’s disease (AD) is a progressive neurodegenerative disease characterized by the formation of amyloid plaques implicated in neuronal death. Genetics, age, and sex are the risk factors attributed to AD. Though omics studies have helped to identify pathways associated with AD, an integrated systems analysis with the available data could help to understand mechanisms, potential biomarkers, and therapeutic targets. Analysis of transcriptomic data sets from the GEO database, and proteomic and metabolomic data sets from literature was performed to identify deregulated pathways and commonality analysis identified overlapping pathways among the data sets. The deregulated pathways included those of neurotransmitter synapses, oxidative stress, inflammation, vitamins, complement, and coagulation pathways. Cell type analysis of GEO data sets showed microglia, endothelial, myeloid, and lymphoid cells are affected. Microglia are associated with inflammation and pruning of synapses with implications for memory and cognition. Analysis of the protein-cofactor network of B2, B6, and pantothenate shows metabolic pathways modulated by these vitamins which overlap with the deregulated pathways from the multi-omics analysis. Overall, the integrated analysis identified the molecular signature associated with AD. Treatment with anti-oxidants, B2, B6, and pantothenate in genetically susceptible individuals in the pre-symptomatic stage might help in better management of the disease.

Acute-on-Chronic Liver Failure (ACLF) is associated with innate immune dysfunction and high short-term mortality. Neutrophils have been identified to influence prognosis in ACLF. Neutrophil biology is under-evaluated in ACLF. Therefore, we investigated neutrophil-specific genes and their association with ACLF outcomes. This is an observational study. Enriched granulocytes, containing neutrophils, isolated from study participants in three groups- ACLF(n = 10), chronic liver disease (CLD, n = 4) and healthy controls (HC, n = 4), were analysed by microarray. Differentially expressed genes were identified and validated by qRT-PCR in an independent cohort of ACLF, CLD and HC (n = 30, 15 and 15 respectively). The association of confirmed overexpressed genes with ACLF 28-day non-survivors was investigated. The protein expression of selected neutrophil genes was confirmed using flow cytometry and IHC. Differential gene expression analysis showed 1140 downregulated and 928 upregulated genes for ACLF versus CLD and 2086 downregulated and 1091 upregulated genes for ACLF versus HC. Significant upregulation of neutrophilic inflammatory signatures were found in ACLF compared to CLD and HC. Neutrophil enriched genes ELANE, MPO and CD177 were highly upregulated in ACLF and their expression was higher in ACLF 28-day non-survivors. Elevated expression of CD177 protein on neutrophil surface in ACLF was confirmed by flow cytometry. IHC analysis in archival post mortem liver biopsies showed the presence of CD177+ neutrophils in the liver tissue of ACLF patients. Granulocyte genes ELANE, MPO and CD177 are highly overexpressed in ACLF neutrophils as compared to CLD or HC. Further, this three-gene signature is highly overexpressed in ACLF 28-day non-survivors.

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Huntington's disease (HD) is a neurodegenerative disease associated with polyglutamine expansion in the protein Huntingtin. Though the polyglutamine repeat length correlates with the age of onset and severity, the complication points to disease modifiers. Mitochondrial dysfunction and metabolic deregulation are associated with the disease. Despite multi-omic characterization of patients and model systems, the mechanisms have remained elusive. Systems analysis of multi-omics data and its validation using yeast model could help to elucidate pathways that modulate protein aggregation. Metabolomic analysis of HD patients and yeast model of HD was carried out. Our analysis shows a considerable overlap of deregulated metabolic pathways. Further, our multi-omic analysis shows deregulated pathways that are common to human, mice and yeast model systems and those that are unique to them. The deregulated pathways include metabolism of various amino acids, glutathione metabolism, longevity, autophagy and mitophagy. Addition of selected metabolites and gene knockout from the deregulated pathways in yeast model system shows that they modulate protein aggregation. Taken together our results show modulation of deregulated pathways influences protein aggregation in HD with implications for progression and prognosis.

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Amyotrophic lateral sclerosis (ALS) is a multi-systemic, incurable, amyloid disease affecting the motor neurons, resulting in the death of patients. The disease is either sporadic or familial with SOD1, C9orf72, FUS, and TDP-43 constituting the majority of familial ALS. Multi-omics studies on patients and model systems like mice and yeast have helped in understanding the association of various signaling and metabolic pathways with the disease. The yeast model system has played a pivotal role in elucidating the gene amyloid interactions. We carried out an integrated transcriptomic and metabolomic analysis of the TDP-43 expressing yeast model to elucidate deregulated pathways associated with the disease. The analysis shows the deregulation of the TCA cycle, single carbon metabolism, glutathione metabolism, and fatty acid metabolism. Transcriptomic analysis of GEO datasets of TDP-43 expressing motor neurons from mice models of ALS and ALS patients shows considerable overlap with experimental results. Furthermore, a yeast model was used to validate the obtained results using metabolite addition and gene knock-out experiments. Taken together, our result shows a potential role for the TCA cycle, cellular redox pathway, NAD metabolism, and fatty acid metabolism in disease. Supplementation of reduced glutathione, nicotinate, and the keto diet might help to manage the disease.