Targeted Metabolomic Profiling of Total Fatty Acids in Human Plasma by Liquid Chromatography-Tandem Mass Spectrometry

• Main Authors: Anas Al Aidaros, Charu Sharma, Claus-Dieter Langhans, Jürgen G. Okun, Georg F. Hoffmann, Majed Dasouki, Pranesh Chakraborty, Fatma Aljasmi, Osama Y. Al-Dirbashi
• Format: Article
• Language: English
• Published: MDPI AG 2020-10-01
• Series: Metabolites
• Subjects: plasma fatty acids; targeted metabolomics; liquid chromatography-tandem mass spectrometry; derivatization; inborn errors of metabolism
• Online Access: https://www.mdpi.com/2218-1989/10/10/400

This article reports a targeted metabolomic method for total plasma fatty acids (FAs) of clinical or nutritional relevance. Thirty-six saturated, unsaturated, or branched-chain FAs with a chain length of C8-C28 were quantified using reversed-phase liquid chromatography-tandem mass spectrometry. FAs in plasma (10 μL) were acid-hydrolyzed, extracted, and derivatized with DAABD-AE (4-[2-(<i>N</i>,<i>N</i>-Dimethylamino)ethylaminosulfonyl]-7-(2-aminoethylamino)-2,1,3-benzoxadiazole) at 60 °C for 1 h. Derivatization resulted in a staggering nine orders of magnitude higher sensitivity compared to underivatized analytes. FAs were measured by multiple-reaction monitoring using stable isotope internal standards. With physiological and pathological analyte levels in mind, linearity was established using spiked plasma. Intra-day (n = 15) and inter-day (n = 20) imprecisions expressed as variation coefficient were ≤10.2% with recovery ranging between 94.5–106.4%. Limits of detection and limit of quantitation ranged between 4.2–14.0 and 15.1–51.3 pmol per injection, respectively. Age-stratified reference intervals were established in four categories: <1 month, 1–12 month, 1–18 year, and >18 year. This method was assessed using samples from patients with disorders affecting FAs metabolism. For the first time, C28:0 and C28:0/C22:0 ratio were evaluated as novel disease biomarkers. This method can potentially be utilized in diagnosing patients with inborn errors of metabolism, chronic disease risk estimation, or nutritional applications.