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A proteomic profiling in Alzheimer's Disease to identify the disregulation of proteins and pathology

ABSTRACT: The discovery of blood-based proteomics biomarkers is recently a popular topic in AD studies due to its advantage to relate external environmental factors with the development of AD. In this study, a proteomic study based on Malaysian Chinese and Malay prospects was conducted. Differentially expressed proteins (DEPs) in AD patients and normal controls for Chinese and Malays were identified. The dissimilarities of dysregulated proteins identified in Chinese and Malays samples suggested the differences of pathways involved in this pathological condition for each respective ethnicity: the Chinese group was involved to Aβ/tau protein-related, oxidative stress and inflammation whereas neuroinflammation was related to the Malays. These findings served as a preliminary understanding in the molecular studies of AD especially in multi-ethnic population.

INSTRUMENT(S): Q Exactive HF-X

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Cell, Blood Serum

DISEASE(S): Alzheimer's Disease

SUBMITTER: Siow-Wee Chang

LAB HEAD: Siow-Wee Chang

PROVIDER: PXD040566 | Pride | 2024-06-10

REPOSITORIES: Pride

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			Action	DRS
	211013_P32213_HFX_GlobalTMT_HpH_Fraction_1.raw	Raw
	211013_P32213_HFX_GlobalTMT_HpH_Fraction_2.raw	Raw
	211013_P32213_HFX_GlobalTMT_HpH_Fraction_3.raw	Raw
	P32213_peptide.xlsx	Xlsx
	checksum.txt	Txt

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Project description:The 'Thin on the Outside Fat on the Inside' TOFI_Asia study found Asian Chinese to be more susceptible to Type 2 Diabetes (T2D) compared to European Caucasians matched for gender and body mass index (BMI). This was influenced by degree of visceral adipose deposition and ectopic fat accumulation in key organs, including liver and pancreas, leading to altered fasting plasma glucose, insulin resistance, and differences in plasma lipid and metabolite profiles. It remains unclear how intra-pancreatic fat deposition (IPFD) impacts TOFI phenotype-related T2D risk factors associated with Asian Chinese. Cow’s milk whey protein isolate (WPI) is an insulin secretagogue which can suppress hyperglycemia in prediabetes. In this dietary intervention, we used untargeted metabolomics to characterize the postprandial WPI response in 24 overweight women with prediabetes. Participants were classified by ethnicity (Asian Chinese, n=12; European Caucasian, n=12) and IPFD (low IPFD < 4.66%, n=10; high IPFD ≥ 4.66%, n=10). Using a cross-over design participants were randomized to consume three WPI beverages on separate occasions; 0 g (water control), 12.5 g (low protein, LP) and 50 g (high protein, HP), consumed when fasted. An exclusion pipeline for isolating metabolites with temporal (T0-240mins) WPI responses was implemented, and a support vector machine-recursive feature elimination (SVM-RFE) algorithm was used to model relevant metabolites by ethnicity and IPFD classes. Metabolic network analysis identified glycine as a central hub in both ethnicity and IPFD WPI response networks. A depletion of glycine relative to WPI concentration was detected in Chinese and high IPFD participants independent of BMI. Urea cycle metabolites were highly represented among the ethnicity WPI metabolome model, implicating a dysregulation in ammonia and nitrogen metabolism among Chinese participants. Uric acid and purine synthesis pathways were enriched within the high IPFD cohort’s WPI metabolome response, implicating adipogenesis and insulin resistance pathways. In conclusion, the discrimination of ethnicity from WPI metabolome profiles was a stronger prediction model than IPFD in overweight women with prediabetes. Each models’ discriminatory metabolites enriched different metabolic pathways that help to further characterize prediabetes in Asian Chinese women and women with increased IPFD, independently.

Project description:BACKGROUND: Babies born at lower gestational ages or smaller birthweights have a greater risk of poorer health in later life. Both the causes of these sub-optimal birth outcomes and the mechanism by which the effects are transmitted over decades are the subject of extensive study. We investigated whether a transcriptomic signature of either birthweight or gestational age could be detected in umbilical cord RNA. METHODS: The gene expression patterns of 32 umbilical cords from Singaporean babies of Chinese ethnicity across a range of birthweights (BW, 1698-4151g) and gestational ages (GA, 35-41 weeks) were determined. We confirmed the differential expression pattern by gestational age for 12 genes in a series of 127 umbilical cords of Chinese, Malay and Indian ethnicity. RESULTS: We found that the transcriptome is substantially influenced by gestational age; but less so by birthweight. We show that some of the expression changes dependent on gestational age are enriched in signal transduction pathways, such as Hedgehog and in genes with roles in cytokine signalling and angiogenesis. We show that some of the gene expression changes we report are reflected in the epigenome. CONCLUSIONS: We studied the umbilical cord which is peripheral to disease susceptible tissues. The results suggest that soma-wide transcriptome changes, preserved at the epigenetic level, may be a mechanism whereby birth outcomes are linked to the risk of adult metabolic and arthritic disease and suggest that greater attention be given to the association between premature birth and later disease risk. 8 umbilical cords form low birth weight babies, 8 umbilical cords from high birth weight babies, 14 umbilical cords from normal birth weigth babies, 7 matching the gestational ages of the low birth weigth group (norm1) and 7 matching the getsational ages of the high birth weight group (norm2). Replicates for array, cRNA and slide spotting REPLICATES: biological replicate: LBW_1, LBW_2, LBW_3A, LBW_3B, LBW_3C, LBW_4, LBW_5, LBW_6, LBW_7, LBW_8A, LBW_8B biological replicate: HBW_1, HBW_2A, HBW_2B, HBW_2C, HBW3, HBW4, HBW5, HBW6, HBW7, HBW8 biological replicate: norm1_1, norm1_2, norm1_3, norm1_4, norm1_5, norm1_7A, norm1_7B, norm1_7C, norm1_7D biological replicate: norm2_1, norm2_2, norm2_3, norm2_4, norm2_5, norm2_6A, norm2_6B, norm2_7 technical replicate: HBW_2A, HBW_2B, HBW_2C technical replicate: LBW_3A, LBW_3B, LBW_3C technical replicate: LBW_8A, LBW_8B techical replicate: norm1_7A, norm1_7B, norm1_7C, norm1_7D technical repliacte: norm2_6A, norm2_6B

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A proteomic profiling in Alzheimer's Disease to identify the disregulation of proteins and pathology

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