Introduction: A critical and as-yet unmet need in Alzheimer’s disease (AD) is the discovery of peripheral small molecule biomarkers. Given that brain pathology precedes clinical symptom onset, we set out to test whether metabolites in blood associated with pathology as indexed by cerebrospinal fluid (CSF) AD biomarkers. Methods: This study analyzed 593 plasma samples selected from the European Medical Information Framework for Alzheimer’s Disease Multimodal Biomarker Discovery study, of individuals who were cognitively healthy (n = 242), had mild cognitive impairment (n = 236), or had AD-type dementia (n = 115). Logistic regressions were carried out between plasma metabolites (n = 883) and CSF markers, magnetic resonance imaging, cognition, and clinical diagnosis. Results: Eight metabolites were associated with amyloid b and one with t-tau in CSF, these were primary fatty acid amides (PFAMs), lipokines, and amino acids. From these, PFAMs, glutamate, and aspartate also associated with hippocampal volume and memory. Discussion: PFAMs have been found increased and associated with amyloid b burden in CSF and clinical measures.

NFAT5 is induced and translocates to the nucleus in HLECs undergoing hyperosmolar stress through activation of p38. IL-1 beta and TNF-alpha are induced via NFAT5 activation. Our data collectively indicate that NFAT5 may be an important gene regulator and survival factor in hyperosmolar stressed HLECs.

We recently showed that Alzheimer's disease patients have lower plasma concentrations of the phosphatidylcholines (PC16:0/20:5; PC16:0/22:6; and PC18:0/22:6) relative to healthy controls. We now extend these findings by examining associations between plasma concentrations of these PCs with cognition and brain function (measured by regional resting state cerebral blood flow; rCBF) in non-demented older individuals. Within the Baltimore Longitudinal Study of Aging neuroimaging substudy, participants underwent cognitive assessments and brain (15)O-water positron emission tomography. Plasma phosphatidylcholines concentrations (PC16:0/20:5, PC16:0/22:6, and PC18:0/22:6), cognition (California Verbal Learning Test (CVLT), Trail Making Test A&B, the Mini-Mental State Examination, Benton Visual Retention, Card Rotation, and Fluencies-Category and Letter), and rCBF were assessed. Lower plasma phosphatidylcholine concentrations were associated with lower baseline memory performance (CVLT long delay recall task-PC16:0/20:5: -2.17-1.39-0.60 p = 0.001 (β with 95% confidence interval subscripts)) and lower rCBF in several brain regions including those associated with memory performance and higher order cognitive processes. Our findings suggest that lower plasma concentrations of PC16:0/20:5, PC16:0/22:6, and PC18:0/22:6 are associated with poorer memory performance as well as widespread decreases in brain function during aging. Dysregulation of peripheral phosphatidylcholine metabolism may therefore be a common feature of both Alzheimer's disease and age-associated differences in cognition.

Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current study is to investigate the etiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic (N = 12,828), metabolomic (N = 2,945), lipidomic (N = 2,593), and proteomic (N = 1,170) data were obtained in plasma. For each data type, each cluster was compared with the other four clusters as the reference. The insulin-resistant cluster showed the most distinct molecular signature, with higher branched-chain amino acid, diacylglycerol, and triacylglycerol levels and aberrant protein levels in plasma were enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher levels of cytokines. The mild diabetes cluster with high HDL showed the most beneficial molecular profile with effects opposite of those seen in the insulin-resistant cluster. This study shows that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease.