Pandey, Akhilesh

Abstract Alzheimer's disease (AD) is the most common cause of dementia and is associated with serious neurologic sequelae resulting from neurodegenerative changes. Identification of markers of early-stage AD could be important for designing strategies to arrest the progression of the disease. The brain is rich in lipids because they are crucial for signal transduction and anchoring of membrane proteins. Cerebrospinal fluid (CSF) is an excellent specimen for studying the metabolism of lipids in AD because it can reflect changes occurring in the brain. We aimed to identify CSF lipidomic alterations associated with AD, using untargeted lipidomics, carried out in positive and negative ion modes. We found CSF lipids that were significantly altered in AD cases. In addition, comparison of CSF lipid profiles between persons with mild cognitive impairment (MCI) and AD showed a strong positive correlation between the lipidomes of the MCI and AD groups. The novel lipid biomarkers identified in this study are excellent candidates for validation in a larger set of patient samples and as predictive biomarkers of AD through future longitudinal studies. Once validated, the lipid biomarkers could lead to early detection, disease monitoring and the ability to measure the efficacy of potential therapeutic interventions in AD.

Abstract A data-independent acquisition (DIA) approach is being increasingly adopted as a promising strategy for identification and quantitation of proteomes. As most DIA data sets are acquired with wide isolation windows, highly complex MS/MS spectra are generated, which negatively impacts obtaining peptide information through classical protein database searches. Therefore, the analysis of DIA data mainly relies on the evidence of the existence of peptides from prebuilt spectral libraries. Consequently, one major weakness of this method is that it does not account for peptides that are not included in the spectral library, precluding the use of DIA for discovery studies. Here, we present a strategy termed Precursor ion And Small Slice-DIA (PASS-DIA) in which MS/MS spectra are acquired with small isolation windows (slices) and MS/MS spectra are interpreted with accurately determined precursor ion masses. This method enables the direct application of conventional spectrum-centric analysis pipelines for peptide identification and precursor ion-based quantitation. The performance of PASS-DIA was observed to be superior to both data-dependent acquisition (DDA) and conventional DIA experiments with 69 and 48% additional protein identifications, respectively. Application of PASS-DIA for the analysis of post-translationally modified peptides again highlighted its superior performance in characterizing phosphopeptides (77% more), N-terminal acetylated peptides (56% more), and N-glycopeptides (83% more) as compared to DDA alone. Finally, the use of PASS-DIA to characterize a rare proteome of human fallopian tube organoids enabled 34% additional protein identifications than DDA alone and revealed biologically relevant pathways including low abundance proteins. Overall, PASS-DIA is a novel DIA approach for use as a discovery tool that outperforms both conventional DDA and DIA experiments to provide additional protein information. We believe that the PASS-DIA method is an important strategy for discovery-type studies when deeper proteome characterization is required.

AbstractBackgroundGene expression profiling is emerging as a tool for tuberculosis diagnosis and treatment response monitoring, but limited data specific to Indian children and incident tuberculosis infection (TBI) exist.MethodsSixteen pediatric Indian tuberculosis cases were age- and sex-matched to 32 tuberculosis-exposed controls (13 developed incident TBI without subsequent active tuberculosis). Longitudinal samples were collected for ribonucleic acid sequencing. Differential expression analysis generated gene lists that identify tuberculosis diagnosis and tuberculosis treatment response. Data were compared with published gene lists. Population-specific risk score thresholds were calculated.ResultsSeventy-one genes identified tuberculosis diagnosis and 25 treatment response. Within-group expression was partially explained by age, sex, and incident TBI. Transient changes in gene expression were identified after both infection and treatment. Application of 27 published gene lists to our data found variable performance for tuberculosis diagnosis (sensitivity 0.38–1.00, specificity 0.48–0.93) and treatment response (sensitivity 0.70–0.80, specificity 0.40–0.80). Our gene lists found similarly variable performance when applied to published datasets for diagnosis (sensitivity 0.56–0.85, specificity 0.50–0.85) and treatment response (sensitivity 0.49– 0.86, specificity 0.50–0.84).ConclusionsGene expression profiles among Indian children with confirmed tuberculosis were distinct from adult-derived gene lists, highlighting the importance of including distinct populations in differential gene expression models.

AbstractContextInactivating germline mutations in the aryl hydrocarbon receptor interacting protein (AIP) gene are linked to pituitary adenoma predisposition. Here, we present the youngest known patient with AIP-related pituitary adenoma.Case DescriptionThe patient presented at the age of 4 years with pituitary apoplexy and left ptosis with severe visual loss following a 1-year history of abdominal pain, headaches, and rapid growth. His IGF-1 level was 5× the upper limit of normal, and his random GH level was 1200 ng/mL. MRI showed a 43 × 24 × 35‒mm adenoma with suprasellar extension invading the left cavernous sinus (Knosp grade 4). After transsphenoidal surgery, histology showed a grade 2A sparsely granulated somatotropinoma with negative O6-methylguanine-DNA methyltransferase and positive vascular endothelial growth factor staining. Genetic testing identified a heterozygous germline nonsense AIP mutation (p.Arg81Ter). Exome sequencing of the tumor revealed that it had lost the entire maternal chromosome-11, rendering it hemizygous for chromosome-11 and therefore lacking functional copies of AIP in the tumor. He was started on octreotide, but because the tumor rapidly regrew and IGF-1 levels were unchanged, temozolomide was initiated, and intensity-modulated radiotherapy was administered 5 months after surgery. Two months later, bevacizumab was added, resulting in excellent tumor response. Although these treatments stabilized tumor growth over 4 years, IGF-1 was normalized only after pegvisomant treatment, although access to this medication was intermittent. At 3.5 years of follow-up, gamma knife treatment was administered, and pegvisomant dose increase was indicated.ConclusionMultimodal treatment with surgery, long-acting octreotide, radiotherapy, temozolomide, bevacizumab, and pegvisomant can control genetically driven, aggressive, childhood-onset somatotropinomas.

Abstract Primary immunodeficiencies (PIDs) are a rare and heterogeneous group of inherited genetic disorders that are characterized by an absent or impaired immune system. In this report, we describe the use of next-generation sequencing to investigate a male infant with clinical and immunological manifestations suggestive of a PID. Whole-exome sequencing of the infant along with his parents revealed a novel nucleotide variant (cytosine to adenine substitution at nucleotide position 252) in the coding region of the interleukin 2 receptor subunit gamma ( IL2RG ) gene. The mother was found to be a carrier. These findings are consistent with a diagnosis of X-linked severe combined immunodeficiency and represent the first such reported mutation in an Indian family. This mutation leads to an asparagine to lysine substitution ( p.Asn84Lys ) located in the extracellular domain of IL2RG, which is predicted to be pathogenic. Our study demonstrates the power of next-generation sequencing in identifying potential causative mutations to enable accurate clinical diagnosis, prenatal screening, and carrier female detection in PID patients. We believe that this approach, which is not a current routine in clinical practice, will become a mainstream component of individualized medicine in the near future.

Abstract Understanding the molecular profile of every human cell type is essential for understanding its role in normal physiology and disease. Technological advancements in DNA sequencing, mass spectrometry, and computational methods allow us to carry out multiomics analyses although such approaches are not routine yet. Human umbilical vein endothelial cells (HUVECs) are a widely used model system to study pathological and physiological processes associated with the cardiovascular system. In this study, next‐generation sequencing and high‐resolution mass spectrometry to profile the transcriptome and proteome of primary HUVECs is employed. Analysis of 145 million paired‐end reads from next‐generation sequencing confirmed expression of 12 186 protein‐coding genes (FPKM ≥0.1), 439 novel long non‐coding RNAs, and revealed 6089 novel isoforms that were not annotated in GENCODE. Proteomics analysis identifies 6477 proteins including confirmation of N ‐termini for 1091 proteins, isoforms for 149 proteins, and 1034 phosphosites. A database search to specifically identify other post‐translational modifications provide evidence for a number of modification sites on 117 proteins which include ubiquitylation, lysine acetylation, and mono‐, di‐ and tri‐methylation events. Evidence for 11 “missing proteins,” which are proteins for which there was insufficient or no protein level evidence, is provided. Peptides supporting missing protein and novel events are validated by comparison of MS/MS fragmentation patterns with synthetic peptides. Finally, 245 variant peptides derived from 207 expressed proteins in addition to alternate translational start sites for seven proteins and evidence for novel proteoforms for five proteins resulting from alternative splicing are identified. Overall, it is believed that the integrated approach employed in this study is widely applicable to study any primary cell type for deeper molecular characterization.

Abstract The pituitary function is regulated by a complex system involving the hypothalamus and biological networks within the pituitary. Although the hormones secreted from the pituitary have been well studied, comprehensive analyses of the pituitary proteome are limited. Pituitary proteomics is a field of postgenomic research that is crucial to understand human health and pituitary diseases. In this context, we report here a systematic proteomic profiling of human anterior pituitary gland (adenohypophysis) using high-resolution Fourier transform mass spectrometry. A total of 2164 proteins were identified in this study, of which 105 proteins were identified for the first time compared with high-throughput proteomic-based studies from human pituitary glands. In addition, we identified 480 proteins with secretory potential and 187 N-terminally acetylated proteins. These are the first region-specific data that could serve as a vital resource for further investigations on the physiological role of the human anterior pituitary glands and the proteins secreted by them. We anticipate that the identification of previously unknown proteins in the present study will accelerate biomedical research to decipher their role in functioning of the human anterior pituitary gland and associated human diseases.