Background: Early detection and diagnosis are very important for autism. Current diagnosis of autism relies mainly on some observational questionnaires and interview tools that may involve a great variability. We performed a metabolomics analysis of serum to identify potential biomarkers for the early diagnosis and clinical evaluation of autism. Methods: We analyzed a discovery cohort of patients with autism and participants without autism in the Chinese Han population using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF MS/MS) to detect metabolic changes in serum associated with autism. The potential metabolite candidates for biomarkers were individually validated in an additional independent cohort of cases and controls. We built a multiple logistic regression model to evaluate the validated biomarkers. Results: We included 73 patients and 63 controls in the discovery cohort and 100 cases and 100 controls in the validation cohort. Metabolomic analysis of serum in the discovery stage identified 17 metabolites, 11 of which were validated in an independent cohort. A multiple logistic regression model built on the 11 validated metabolites fit well in both cohorts. The model consistently showed that autism was associated with 2 particular metabolites: sphingosine 1-phosphate and docosahexaenoic acid. Limitations: While autism is diagnosed predominantly in boys, we were unable to perform the analysis by sex owing to difficulty recruiting enough female patients. Other limitations include the need to perform test–retest assessment within the same individual and the relatively small sample size. Conclusion: Two metabolites have potential as biomarkers for the clinical diagnosis and evaluation of autism.

Background: Lipoprotein lipase (LPL) and serum 25-hydroxyvitamin D [25(OH)D] play important roles in the regulation of lipid metabolism. Although dyslipidemia is associated with insulin resistance (IR) and type 2 diabetes (T2D), there are limited data available regarding the relationship of LPL and 25(OH)D to IR and T2D at a population level. The objective of the present study is to investigate the associations of LPL and 25(OH)D with IR and T2D in a Chinese population. Methods: The study cohort consisted of 2708 subjects (1326 males, 1382 females; mean age 48.5 ± 12.6 years) in main communities of Harbin, China. Serum 25(OH)D, LPL, free fatty acids (FFAs), fasting glucose (FG), fasting insulin, lipid profile, apoA and apoB concentrations were measured. Results: Serum 25(OH)D concentration was positively associated with LPL (β = 0.168, P < 0.001). LPL was inversely associated with IR and T2D. Subjects in the lowest quartile of LPL had the highest risk of IR [odds ratio (OR) = 1.85, 95% CI = 1.22-2.68] and T2D (OR = 1.65, 95% CI = 1.14-2.38). Serum 25(OH)D was also inversely associated with IR and T2D. Vitamin D deficiency [25(OH)D < 20 ng/ml] was associated with an increasing risk of IR (OR = 1.91, 95% CI = 1.23-2.76) and T2D (OR = 2.06, 95% CI = 1.37-3.24). The associations of 25(OH)D with IR and T2D were attenuated by further adjustment for LPL. Conclusions: LPL is associated with serum 25(OH)D, IR and T2D in the Chinese population. These results suggest a potential mediating role of LPL in the associations of 25(OH)D with IR and T2D.

Alzheimer disease (AD) can be diagnosed by clinical and neuropsychologic tests and at autopsy, but there are no simple effective diagnostic methods fo