Patent Application
20250180508
The present disclosure relates to the field of lipidomics, and in particular, to a novel derivatization strategy for quantitative lipid methylation. The present disclosure further relates to phospholipid biomarkers for assessing Omega-3 Index status in a subject and uses thereof.
The human lipidome comprises a vast number of lipid molecular species present in tissues, cells, exosomes and biofluids, which are defined by their specific polar head group, chemical linkage, fatty acid carbon chain length, number of double bond equivalents, oxygenated fatty acyls, and regio-/stereochemistry.1,2 As lipid homeostasis plays an important role in energy metabolism, membrane structure, and cell signalling, dysregulation in lipid metabolism has long been associated with inflammation and the etiology of cardiometabolic disorders, including obesity, type 2 diabetes, cardiovascular and neurodegenerative diseases.3,4 Lipidomic studies have also gained traction in nutritional epidemiology as objective indicators of food exposures since essential dietary fats and fat-soluble vitamins relevant to human health5 are not accurately assessed from self-reports.6 For these reasons, new advances in untargeted lipid profiling by high resolution mass spectrometry (MS)7 provide a hypothesis-generating approach for gaining new insights into complex disease mechanisms.8 However, several technical hurdles impede the progress in lipidomics given the lack of chemical standards and reference MS/MS spectra that limit comparative quantitative reporting and the unambiguous identification of unknown lipids of clinical significance.9 Recent efforts have focused on developing consensus guidelines in lipid classification and annotation,10,11 using internal standards for data normalization,12 applying automated data processing with open-access software tools,13,14 as well as implementing standardized lipidomic protocols and inter-laboratory ring trials using reference and quality control samples.15-17 Nevertheless, lipidomics workflows require careful method optimization to avoid bias and false discoveries depending on the specific biospecimen type and instrumental platform, including sample pretreatment protocols.18
Nutritional epidemiological studies have relied on food frequency questionnaires to estimate omega-3 FA dietary fat intake for chronic disease risk assessment (71). Alternatively, biomarkers may offer a more reliable way to assess nutritional status (72) given between-subject differences in n3-LCPUFA bioavailability and metabolism, the variable content of omega-3 FAs in marine foods, and memory recall bias. In this case, the omega-3 index (O3I), defined as the erythrocyte EPA+DHA content from the phospholipid (PL) fraction as a mole percent to total fatty acids, represents a novel biomarker of coronary heart disease risk and sudden cardiac death independent of traditional risk factors (20). Although PL erythrocytes reflect habitual n3-LCPUFA intake patterns over a longer time interval (˜120 days) as compared to other more dynamic PL class pools in circulation (77), a moderate to strong correlation of the O3I with EPA and DHA PL content measured in plasma or whole dried blood has been reported previously (74,78). The disadvantages of the existing O3I index include the need to access erythrocytes, which are not widely available in biorepositories unlike other blood specimens (79,80). Also, gas chromatography (GC) requires complicated sample handling procedures for O3I status determination after off-line PL fractionation by thin layer chromatography and their subsequent saponification into FA methyl esters, which is time consuming and less amenable to large-scale epidemiological studies (81). Also, there is a lack of standardization when reporting the O3I as varying number of FAs are measured by GC methods complicating comparative studies. Therefore, there is currently a need for improved methods to assess O3I that are more amenable to routine screening.
The background herein is included solely to explain the context of the disclosure. This is not to be taken as an admission that any of the material referred to was published, known, or part of the common general knowledge as of the priority date.
Herein, a novel two-step chemical derivatization strategy is introduced for the quantitative methylation of PLs based on 9-fluorenylmethyoxycarbonyl chloride (FMOC) followed by 3-methyl-1-p-tolyltriazene (MTT) that offers a practical way to expand lipidome coverage in mass spectrometry, such as MSI-NACE-MS. For the first time, it is demonstrated that this procedure enables the rapid identification and quantification of phosphatidylcholines (PCs) and sphingomyelins (SMs) as their cationic phosphate methyl esters, which was validated on a standard reference human plasma sample previously analyzed in an inter-laboratory harmonization study.15
This two-stage FMOC/MTT lipid methylation derivatization strategy can also be applied to improve the resolution and detection of other classes of lipids when using complementary liquid chromatography-mass spectrometry, direct infusion-mass spectrometry and ion mobility-mass spectrometry methods.
An accelerated data workflow using a sub-group analysis of serum extracts from placebo and high-dose fish oil (FO) treatment participants confirmed that dietary omega-3 fatty acids were predominately uptaken as their phosphatidylcholines (PCs) in comparison to other serum phospholipid pools. Consistently in both FO (5.0 g/day) and docosahexaenoic acid (DHA) or eicosapentaenoic acid (EPA)-specific (3.0 g/day) intervention studies, serum PC (16:0_20:5) was most responsive (>7-fold change from baseline) to supplementation (>28 days) as compared to various DHA containing PCs, notably PC (16:0_22:6) (>2-fold change from baseline), reflective of preferential incorporation of EPA into these circulating lipid pools. It was also demonstrated that the sum of serum PC (16:0_20:5) and PC (16:0_22:6) was positively correlated to 031 measurements when using FO (r=0.717, p=1.62×10−11, n=69), as well as DHA or EPA (r=0.764, p=3.00×10−33, n=167) with most participants improving their O3I status >8.0%. However, DHA was more efficacious in improving O3I (ΔO3I=4.90+1.33) compared to EPA (ΔO3I=2.99+1.19) that was dose dependent with large between-subject variability. It was concluded that MSI-NACE-MS offers a promising multiplexed separation platform for more convenient assessment of O3I status using specific PCs derived from widely available serum or plasma specimens.
Other instrumental methods can also be used for rapid screening of the 031 status based on these circulating PLs with or without chemical labeling, including direct infusion-tandem mass spectrometry, liquid chromatography-mass spectrometry, and ion mobility-mass spectrometry. This work can support nutritional epidemiological studies exploring the role of essential dietary fats in human health while optimizing individual responses to dietary or pharmacological interventions based on specific omega-3 fatty acid formulations. Accordingly, the present disclosure describes the identification of circulating phospholipid species that may serve as surrogate biomarkers of O3I status using the novel derivatization strategy described herein.
Accordingly, an aspect of the disclosure is a method of generating a lipid profile using mass spectrometry (MS), the method comprising:
In some embodiments, the amine protecting reagent is 9-fluorenylmethyoxycarbonyl chloride (FMOC).
In some embodiments, separating, in step e) comprises capillary electrophoresis, liquid chromatography or ion mobility.
In some embodiments, extracting the lipid fraction in step a) comprises incubating the sample with methyl tert butyl ether (MTBE), hexane, chloroform, methanol or acetonitrile.
In some embodiments, extracting the lipid fraction in step a) comprises incubating the sample with methyl tert butyl ether (MTBE).
In some embodiments, step b) further comprises drying the one or more protected lipids under nitrogen.
In some embodiments, the one or more lipids is a phospholipid, glycerolipid, glycerophospholipid, sphingolipid, sterol, steroid, isoprenoid, glycolipid, polyketide, saccharolipid, prenol lipid, bile acid, fatty acid, a lipid containing a reactive amino, carboxyl, phenol, thiol, hydroxyl, or phosphate functionality (e.g., acylcarnitines, acyl-coenzyme A) or combinations thereof.
In some embodiments, the one or more lipids is a phospholipid.
In some embodiments, the phospholipid is sphingomyelin (SM), phosphatidylcholine (PC), phosphatidylserine (PS), phosphatidylinositol (PI), phosphatidylethanolamine (PE), phosphatidic acid (PA), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), cardiolipin (CL) lysophosphatidic acid (LPA), or combinations thereof.
In some embodiments, the method further comprises in step e) introducing a known amount of one or more methylated lipids as a reference sample for calibration of lipid quantity.
In some embodiments, the one or more lipids in the lipid fraction in step b) are cationic or zwitterionic. In some embodiments, the one or more methylated lipids are cationic or zwitterionic, optionally the one or more methylated lipids are zwitterionic or cationic phospholipids.
In some embodiments, step c) has a reaction time of about 20 minutes to about 100 minutes, about 20 minutes to about 40 minutes, about 40 minutes to about 60 minutes, about 60 minutes to about 100 minutes, about 60 minutes to about 80 minutes, or about 40 minutes to about 80 minutes, optionally the reaction time is about 60 minutes.
In some embodiments, the concentration of MTT in step c) is about 50 mM to about 900 mM, optionally, the MTT is at a concentration of about 450 mM.
In some embodiments, step c) has a reaction temperature of about 20° C. to about 100° C., optionally the reaction temperature is about 60° C.
In some embodiments, step b) has a reaction time of about 1 minute to about 30 minutes.
In some embodiments, step b) has a reaction time of about 5 minutes.
In some embodiments, the concentration of the amine protecting reagent in step b) is about 0.10 mM to about 10 mM.
In some embodiments, the concentration of the amine protecting reagent in step b) is about 0.85 mM.
In some embodiments, in step f) the mass spectrometer comprises multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry (MSI-NACE-MS), direct infusion-MS, desorption ionization (DESI)-MS, gas chromatography (GC)-MS, ion mobility (IM)-MS liquid chromatography (LC)-MS or supercritical fluid chromatography (SFC)-MS (SFC)-MS/MS.
In some embodiments, in step f) the mass spectrometer is multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry (MSI-NACE-MS).
In some embodiments, the sample is of animal, plant or human origin.
In some embodiments, the sample is from human blood, optionally plasma or serum.
In some embodiments, in step b) the amine protecting reagent is added in excess and the excess amine protecting reagent reacts with p-toluidine and/or phosphatidylethanolamine (PE).
In some embodiments, back extracting the one or more methylated lipids in step d) comprises back extracting with hexane.
In some embodiments, back extracting the one or more methylated lipids in step d) comprises back extracting with methyl tert butyl ether (MTBE).
In some embodiments, the lipid profile is untargeted.
In some embodiments, the lipid profile is targeted.
In some embodiments, the method further comprises separating a portion of the lipid fraction obtained in step a) for mass spectrometry in negative ion mode.
In some embodiments, negative ion mode is for detecting anionic lipids and a mass spectrum chart is generated and results are combined with the lipid profile of the sample in g).
Another aspect of the disclosure is a method of assessing omega-3 index (O3I) status in a subject, the method comprising:
In some embodiments, the one or more omega-3 containing phospholipid biomarkers comprises one or more phosphatidylcholines (PCs) selected from the group consisting of PC 38:6 (16:0_22:6), PC 36:5 (16:0_20:5), PC 38:5, PC 40:6, PC 36:6, and PC 40:5.
In some embodiments, the one or more PCs comprise one PC, two PCs, three PCs, four PCs, five PCs or six PCs.
In some embodiments, the one or more PCs comprise PC 36:5 (16:0_20:5) and PC 38:6 (16:0_22:6).
In some embodiments, the one or more omega-3 containing phospholipid biomarkers consist of two PCs, and wherein the two PCs consist of PC 36:5 (16:0_20:5) and PC 38:6 (16:0_22:6).
In some embodiments, the one or more omega-3 containing phospholipid biomarkers comprise PCs comprising omega-3 fatty acids containing eicosapentaenoic acid (EPA, 20:5). docosahexaenoic acid (DHA, 22:6), docosapentaenoic acid (DPA) and/or alpha-linolenic acid (ALA) together with other fatty acyl chains (e.g., 18:0). In some embodiments, the PCs comprise EPA and/or DHA.
In some embodiments, the sample comprises serum, plasma, whole blood or dried blood.
In some embodiments, the method further comprises repeating the method of assessing O3I status for a second sample taken from the same subject at a second time point to assess O3I status and monitor change from the first time point to the second time point.
In some embodiments, assessing the level of one or more omega-3 containing phospholipid biomarkers comprises a method of chemical derivatization, the method comprising:
In some embodiments, the method further comprises introducing the one or more methylated lipids to a mass spectrometer under positive-ion mode and acquiring a mass spectrum chart of the one or more methylated lipids to generate the lipid profile of the sample.
Another aspect of the disclosure is a method of assessing cardiovascular risk in a subject, the method comprising: assessing omega-3 index (O3I) status in a subject using the methods described herein,
wherein if the level of the one or more omega-3 containing phospholipid biomarkers is similar to a control of less than 4% O3I the subject is determined to be at high cardiovascular risk, if the level of the one or more omega-3 containing phospholipid biomarkers is similar to a control of 4% to 8% O3I the subject is determined to be at intermediate cardiovascular risk, and if the level of the one or more omega-3 containing phospholipid biomarkers is similar to a control of more than 8% O3I the subject is determined to be at low cardiovascular risk.
In some embodiments, if the subject has a high or intermediate cardiovascular risk, the method further comprises treating the subject by administering omega-3 fatty acid supplementation.
In some embodiments, the omega-3 fatty acid supplementation comprises fish oil, eicosapentaenoic acid (EPA) and/or docosahexaenoic acid (DHA).
The preceding section is provided by way of example only and is not intended to be limiting on the scope of the present disclosure and appended claims. Additional objects and advantages associated with the compositions and methods of the present disclosure will be appreciated by one of ordinary skill in the art in light of the instant claims, description, and examples. For example, the various aspects and embodiments of the disclosure may be utilized in numerous combinations, all of which are expressly contemplated by the present description. These additional advantages objects and embodiments are expressly included within the scope of the present disclosure. The publications and other materials used herein to illuminate the background of the disclosure, and in particular cases, to provide additional details respecting the practice, are incorporated by reference, and for convenience are listed in the appended reference section.
Further objects, features and advantages of the disclosure will become apparent from the following detailed description taken in conjunction with the accompanying figures showing illustrative embodiments of the disclosure, in which:
The following is a detailed description provided to aid those skilled in the art in practicing the present disclosure. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used in the description herein is for describing particular embodiments only and is not intended to be limiting of the disclosure. All publications, patent applications, patents, figures and other references mentioned herein are expressly incorporated by reference in their entirety.
Further, the definitions and embodiments described in particular sections are intended to be applicable to other embodiments herein described for which they are suitable as would be understood by a person skilled in the art. For example, in the following passages, different aspects of the disclosure are defined in more detail. Each aspect so defined may be combined with any other aspect or aspects unless clearly indicated to the contrary. In particular, any feature described herein may be combined with any other feature or features described herein.
In understanding the scope of the present disclosure, the term “comprising” and its derivatives, as used herein, are intended to be open ended terms that specify the presence of the stated features, elements, components, groups, integers, and/or steps, but do not exclude the presence of other unstated features, elements, components, groups, integers and/or steps. The foregoing also applies to words having similar meanings such as the terms, “including”, “having” and their derivatives.
The term “consisting” and its derivatives, as used herein, are intended to be closed terms that specify the presence of the stated features, elements, components, groups, integers, and/or steps, but exclude the presence of other unstated features, elements, components, groups, integers and/or steps. The term “consisting essentially of”, as used herein, is intended to specify the presence of the stated features, elements, components, groups, integers, and/or steps as well as those that do not materially affect the basic and novel characteristic(s) of features, elements, components, groups, integers, and/or steps.
Terms of degree such as “substantially”, “about” and “approximately” as used herein mean a reasonable amount of deviation of the modified term such that the end result is not significantly changed. These terms of degree should be construed as including a deviation of at least ±5% of the modified term if this deviation would not negate the meaning of the word it modifies. In addition, all ranges given herein include the end of the ranges and also any intermediate range points, whether explicitly stated or not.
As used in this disclosure, the singular forms “a”, “an” and “the” include plural references unless the content clearly dictates otherwise. Thus, for example, a composition containing “a compound” includes a mixture of two or more compounds.
In embodiments comprising an “additional” or “second” component, the second component as used herein is chemically different from the other components or first component. A “third” component is different from the other, first, and second components, and further enumerated or “additional” components are similarly different.
The term “and/or” as used herein, should be understood to mean “either or both” of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and/or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the “and/or” clause, whether related or unrelated to those elements specifically identified.
As used herein, “or” should be understood to have the same meaning as “and/or” as defined above. For example, when separating items in a list, “or” or “and/or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of” or “exactly one of” or, when used in the claims, “consisting of” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e., “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of.”
As used herein, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from anyone or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified.
The abbreviation, “e.g.” is derived from the Latin exempli gratia and is used herein to indicate a non-limiting example. Thus, the abbreviation “e.g.” is synonymous with the term “for example.”
The recitation of numerical ranges by endpoints herein includes all numbers and fractions subsumed within that range (e.g. 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.90, 4, and 5). It is also to be understood that all numbers and fractions thereof are presumed to be modified by the term “about.”
The present description refers to a number of chemical terms and abbreviations used by those skilled in the art. Nevertheless, definitions of selected terms are provided for clarity and consistency.
It will be understood that any component defined herein as being included may be explicitly excluded by way of proviso or negative limitation, such as any specific compounds or method steps, whether implicitly or explicitly defined herein.
All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms.
Further, the definitions and embodiments described in particular sections are intended to be applicable to other embodiments herein described for which they are suitable as would be understood by a person skilled in the art. For example, in the following passages, different aspects of the disclosure are defined in more detail. Each aspect so defined may be combined with any other aspect or aspects unless clearly indicated to the contrary.
Provided herein is a method of generating a lipid profile using mass spectrometry (MS), the method comprising:
As used herein, “mass spectrometry” or “MS” refers to an analytical technique used to identify the chemical composition and structure of a sample by measuring the mass-to-charge ratio (m/z) of its ionized particles. The method involves ionizing chemical compounds to generate charged molecules or molecular fragments, separating these ions based on their mass-to-charge ratios, and detecting them to produce a spectrum. This spectrum serves as a molecular fingerprint that can be analyzed to determine the identities and quantities of the components in a sample. Mass spectrometry techniques include a variety of ionization methods and mass analyzer types which may be combined. Examples of ionization methods include, without limitation, Electron Impact Ionization (EI), Chemical Ionization (CI), Electrospray Ionization (ESI), Matrix-Assisted Laser Desorption/Ionization (MALDI), Atmospheric Pressure Chemical Ionization (APCI), Atmospheric Pressure Photoionization (APPI), Fast Atom Bombardment (FAB), Desorption Electrospray Ionization (DESI), Secondary Ion Mass Spectrometry (SIMS), Field Ionization (FI), Field Desorption (FD) and multi-segment injection (MSI). Examples of mass analyzer types include, without limitation, Quadrupole Mass Analyzer, Time-of-Flight (TOF), Orbitrap, Magnetic Sector Analyzer, Ion Trap (including 3D and linear ion traps), Fourier Transform Ion Cyclotron Resonance (FT-ICR), Double-Focusing Mass Analyzer, Quadrupole Ion Trap (QIT), Hybrid Ion Trap-Orbitrap Systems, Dynamic Reaction Cell (DRC) for ICP-MS. Hybrid techniques include, for example, tandem mass spectrometry (MS/MS), including triple quadrupole and quadrupole time of flight (TOF), gas chromatography mass spectrometry (GS-MS), liquid chromatography mass spectrometry (LC-MS), inductively coupled plasma mass spectrometry (ICP-MS), capillary electrophoresis-mass spectrometry (CE-MS), MALDI-TOF, MALDI-TOF/TOF, and nonaqueous capillary electrophoresis-mass spectrometry (NACE-MS).
The term “positive ion mode” as used herein refers to a mass spectrometry technique in which the instrument detects and analyzes positively charged ions, such as amines, peptides, proteins and small organic compounds.
In some embodiments, in step e) separating comprises capillary electrophoresis, liquid chromatography or ion mobility
In some embodiments, extracting the lipid fraction in a) comprises incubating the sample with methyl tert butyl ether (MTBE) or related organic solvents, such as hexane, chloroform, methanol, acetonitrile.
As used herein, the term “lipid fraction” refers to the lipid portion of a sample, such as a blood sample (e.g., whole blood, dried blood spot, plasma, serum), as well as other specimens, such as cell or tissue extract. Methods of obtaining a lipid fraction are known to the skilled person and include, for example, the Bligh and Dyer method and the Folch method.
In some embodiments, step b) further comprises drying the one or more protected lipids under nitrogen.
The term “protecting” as used herein refers to a chemical modification to mask a functional group on a molecule, preventing it from reacting under certain conditions in a multi-step synthesis. Examples of amine protecting groups include, tert-butyloxycarbonyl (BOC), carbobenzoxy (Cbz) and FMOC. In some embodiments, the amine protecting reagent is 9-fluorenylmethyoxycarbonyl chloride (FMOC).
The terms “methylated” or “methylating” as used herein refers to a chemical modification in which a methyl (—CH3) group is added to a molecule.
In some embodiments, the one or more methylated lipids is a cationic phosphate methyl ester lipid.
In some embodiments, the one or more lipids includes various lipid classes that can undergo methylation, such as phospholipids, glycerophospholipids, sphingolipids, glycerolipids, sterols, fatty acids, bile acids, steroids, isoprenoids, glycolipids, polyketides, saccharolipids, prenol lipids, sterols, a lipid containing a reactive amino, carboxyl, phenol, thiol, hydroxyl, or phosphate functionality (e.g., acylcarnitines, acyl-coenzyme A) or combinations thereof.
In some embodiments the one or more lipids is a phospholipid.
In some embodiments, the phospholipid is sphingomyelin (SM), phosphatidylcholine (PC), phosphatidylserine (PS), phosphatidylinositol (PI), phosphatidylethanolamine (PE), phosphatidic acid (PA), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), lysophosphatidic acid (LPA), cardiolipin (CL) or combinations thereof.
In some embodiments, the method further comprises in step e) introducing a known amount of one or more methylated lipids as a reference sample for calibration of lipid quantity, optionally the method further comprises generating an external calibration curve using a serial dilution of the reference sample.
In some embodiments, the PLs are quantified with improved resolution, sensitivity, and throughput compared to methylation using diazomethane.
In some embodiments, the one or more lipids in the lipid fraction in step b) are cationic or zwitterionic. In some embodiments, the one or more methylated lipids are cationic or zwitterionic, optionally the one or more methylated lipids are zwitterionic or cationic phospholipids.
In some embodiments, step c) has a reaction time of about 20 minutes to about 100 minutes, about 20 minutes to about 40 minutes, about 40 minutes to about 60 minutes, about 60 minutes to about 100 minutes, about 60 minutes to about 80 minutes, or about 40 minutes to about 80 minutes, optionally the reaction time is about 60 minutes.
In some embodiments, the concentration of MTT in step c) is about 50 mM to about 900 mM, optionally, the MTT is at a concentration of about 450 mM.
In some embodiments, MTT represents a safer and more convenient alternative to diazomethane.
In some embodiments, step c) has a reaction temperature of about 20° C. to about 100° C., optionally the reaction temperature is about 60° C.
In some embodiments, step b) has a reaction time of about 1 minute to about 30 minutes.
In some embodiments, step b) has a reaction time of about 5 minutes.
In some embodiments, the concentration of the amine protecting reagent, optionally FMOC, in step b) is about 0.10 mM to about 10 mM.
In some embodiments, the concentration of the amine protecting reagent, optionally FMOC, in step b) is about 0.85 mM.
In some embodiments, the mass spectrometer comprises multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry (MSI-NACE-MS), direct infusion-MS, desorption ionization (DESI)-MS, gas chromatography (GC)-MS, ion mobility (IM)-MS and liquid chromatography (LC)-MS and supercritical fluid chromatography (SFC)-MS.
In some embodiments, the mass spectrometer is multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry (MSI-NACE-MS).
In some embodiments, the sample is of animal, plant or human origin. In some embodiments, the sample is from human blood, optionally plasma or serum.
In some embodiments, in step b) the amine protecting reagent, optionally FMOC, is added in excess and the excess amine protecting reagent reacts with p-toluidine and/or phosphatidylethanolamine (PE).
In some embodiments, the amine protecting reagent, optionally FMOC, reduces isobaric interferences and ion suppression effects. In some embodiments, the back extracting in d) reduces isobaric interferences and ion suppression effects.
In some embodiments, back extracting the one or more methylated lipids in d) comprises back extracting with hexane. In some embodiments, back extracting the one or more methylated lipids in d) comprises back extracting with methyl tert butyl ether (MTBE).
In some embodiments, the lipid profiling is targeted. In some embodiments, the lipid profiling is untargeted.
The term “untargeted”, as used herein refers to a comprehensive profile of the entire lipidome of a sample without prior knowledge of the lipids present.
The term “targeted” as used herein refers to the identification and quantification of a specific set of known lipids of interest. This technique may be used for absolute or relative quantification using standards or internal references.
In some embodiments, the method further comprises separating a portion of the lipid fraction obtained in step a) for mass spectrometry in negative ion mode. In some embodiments, negative ion mode is for detecting anionic lipids and a mass spectrum chart is generated and results are combined with the lipid profile of the sample in g).
The term “negative ion mode” as used herein refers to a mass spectrometry technique in which the instrument detects and analyzes negatively charged ions, such as carboxylic acids, phenols and phosphates.
Another aspect of the disclosure is a method of assessing omega-3 index (O3I) status in a subject, the method comprising:
As used herein, the omega-3 index (O3I), is defined as the erythrocyte (red blood cells (RBCs)) EPA+DHA content from the phospholipid (PL) fraction as a mole percent to total fatty acids, and represents a novel biomarker of coronary heart disease risk and sudden cardiac death independent of traditional risk factors (75). The O3I status can be stratified based on clinically defined cut-off values, where <4% is considered high risk, 4-8% being intermediate risk, and low risk >8% for mortality from coronary heart disease (76), as confirmed in a meta-analysis from 10 cohort studies (77). For example, the mean O3I index for Canadian adults has been reported as 4.5% with less than 3% classified as having high cardioprotection (i.e., O3I>8%) that was dependent on age, ethnicity, fish consumption, supplement use, smoking status and obesity (78). The O3I is calculated using the formula 1:
The term “docosahexaenoic acid” or “DHA”, as used herein, refers to an omega-3 fatty acid 22:6 (n−3). DHA is commonly found in cold water fish, such as salmon, or can be taken as a dietary supplement. DHA has the following chemical structure:
The term “eicosapentaenoic acid” or “EPA”, as used herein, refers to an omega-3 fatty acid 20:5 (n−3). EPA is commonly found in oily fish, such as herring, mackerel, salmon or in edible algaes, or can be taken as a dietary supplement. EPA has the following chemical structure:
The term “control”, as used herein refers to a comparative sample, such as a blood sample, taken from a subject with a known O3I status, or a specific value or dataset that can be used to prognose or classify the value e.g., phospholipid biomarker level or reference phospholipid biomarker value obtained from a test sample or samples associated with a known O3I status. In one embodiment, the dataset may be obtained from samples of a group of subjects known to have an O3I of less than 4%, an O3I of 4%-8%, and/or an O3I of greater than 8%. The level of the phospholipid biomarkers in the dataset can be used to create a “control value” that is used in testing samples from new subjects. A control value may be obtained from historical phospholipid biomarker levels for a subject or pool of subjects with a known O3I status.
The term “subject” as used herein includes all members of the animal kingdom including mammals, and suitably refers to humans. Optionally, the term “subject” includes healthy mammals. In some embodiments, the term “subject” includes mammals that are taking dietary fish oil, docosahexaenoic acid (DHA) or eicosapentaenoic acid (EPA) supplementation or other dietary long-chain omega-3 fatty acids, including docosapentaenoic acid (DPA) and a-linolenic acid (ALA), as well as various natural lipids or synthetic analogs, such as ethyl eicosapentaenoic acid. In one embodiment, the term “subject” refers to a human having, or suspected of having, cardiovascular disease.
In some embodiments, the subject is a healthy subject. In some embodiments, the subject has, is suspected of having or is at risk of developing a cardiovascular disease. In some embodiments, the subject has, is suspected of having or is at risk of developing a cardiometabolic disorder. In some embodiments, the subject has, is suspected of having or is at risk of developing a neurodegenerative disorder. In some embodiments, the subject has, is suspected of having or is at risk of developing a mental health disorder. In some embodiments, the subject has, is suspected of having or is at risk of developing an autoimmune disorder. In some embodiments, the subject is, is suspected of being, or will become pregnant.
In some embodiments, the method is for monitoring O3I status in a pregnant subject. In some embodiments, the method is for monitoring prenatal supplementation and nutrition in a pregnant subject or in a subject who is planning to become pregnant.
The term “cardiometabolic disorder” as used herein refers to a condition or group of conditions characterized by one or more abnormalities in cardiovascular and/or metabolic systems, including but not limited to hypertension, dyslipidemia, obesity, insulin resistance, impaired glucose tolerance, diabetes, and associated systemic inflammation.
The term “neurodegenerative disorder”, includes any and all disorders and conditions of the central nervous system that involve neural degeneration and/or neural cell loss, including but not limited to Alzheimer's disease (AD), Parkinson's disease (PD), Amyotrophic Lateral Sclerosis (ALS), Huntington's disease (HD), Multiple Sclerosis (MS), cognitive decline and mild cognitive impairment (MCI).
The term “mental health disorder” refers to a condition characterized by disturbances in a person's cognition, emotional regulation or behavior, reflecting a dysfunction in psychological, biological, or developmental processes underlying mental function. Mental disorder includes, without limitation, mood disorders, depression, anxiety disorders, psychotic disorders, post-traumatic stress disorder, eating disorders, neurodevelopmental disorders and personality disorders.
The term “autoimmune disorder” refers to conditions where the immune system mistakenly attacks the body's own tissue leading to chronic or acute inflammation. Examples of autoimmune disorders associated with inflammation include, rheumatoid arthritis, systemic lupus erythematosus, Sjogren's Syndrome, Mixed Connective Tissue Disease, Hashimoto's Thyroiditis, Type 1 Diabetes, Inflammatory Bowel Disease (e.g. Crohn's disease and ulcerative colitis), multiple sclerosis, neuromyelitis optica, vasculitis, psoriasis, vitiligo, ankylosing spondylitis, dermatomyositis, polymyositis, and autoimmune hepatitis.
In some embodiments, the one or more omega-3 containing phospholipid biomarkers that correlate to O3I status comprise one or more phosphatidylcholines (PCs). In some embodiments, the one or more PCs are selected from the group consisting of PC 38:6(16:0_22:6), PC 36:5 (16:0_20:5), PC 38:5, PC 40:6, PC 36:6, and PC 40:5.
In some embodiments, the one or more PCs comprise one PC, two PCs, three PCs, four PCs, five PCs or six PCs.
In some embodiments, the one or more PCs comprise PC 36:5 (16:0_20:5) and PC 38:6 (16:0_22:6). In some embodiments the one or more PCs comprise PC 36:5 (16:0_20:5) and PC 38:6 (16:0_22:6) with chemical derivatization. In some embodiments, the one or more PCs comprise PC 36:5 (16:0_20:5) and PC 38:6 (16:0_22:6) without chemical derivatization.
In some embodiments, the one or more omega-3 containing phospholipid biomarkers that correlate to O3I status consist of two PCs, wherein the two PCs consist of PC 36:5 (16:0_20:5) and PC 38:6 (16:0_22:6).
In some embodiments, the one or more omega-3 containing phospholipid biomarkers that correlate to O3I status are PCs comprising omega-3 fatty acids containing eicosapentaenoic acid (EPA, 20:5) docosahexaenoic acid (DHA, 22:6), docosapentaenoic acid (DPA) and/or alpha-linolenic acid (ALA) together with other fatty acyl chains (e.g., 18:0).
In some embodiments, the omega-3 fatty acids comprise DHA and/or EPA.
In some embodiments, the levels of omega-3 containing PCs in circulating phospholipids are correlated with omega-3 index when adjusted for relative abundances between omega-3 containing circulating PCs compared to red blood cell membrane omega-3 index measurements
In some embodiments, the method further comprises repeating the method of assessing omega-3 index (O3I) status in a subject for a second sample from the same subject taken at a second time point to assess O3I status and monitor change from the first time point to the second time point.
In some embodiments, the first sample and/or the second sample comprises serum, plasma, whole blood or dried blood.
In some embodiments, assessing the level of one or more omega-3 containing phospholipid biomarkers may be measured by any suitable method known to the skilled person, such as immunoassays, including for example, enzyme linked immunosorbent assay (ELISA).
In some embodiments, assessing the level of one or more omega-3 containing phospholipid biomarkers comprises a method of chemical derivatization using the methods described herein.
Another aspect of the disclosure is a method of assessing cardiovascular risk in a subject, the method comprising: assessing omega-3 index (O3I) status in a subject using the methods described herein, wherein if the level of the one or more omega-3 containing phospholipid biomarkers is similar to a control of less than 4% O3I the subject is determined to be at high cardiovascular risk, if the level of the one or more omega-3 containing phospholipid biomarkers is similar to a control of 4% to 8% O3I the subject is determined to be at intermediate cardiovascular risk, and if the level of the one or more omega-3 containing phospholipid biomarkers is similar to a control of more than 8% 031 the subject is determined to be at low cardiovascular risk.
Methods of determining the similarity between profiles are well known in the art. Methods of determining similarity may in some embodiments provide a non-quantitative measure of similarity, for example, using visual clustering. In other embodiments, similarity may be determined using methods which provide a quantitative measure of similarity.
In some embodiments, if the subject has a high or intermediate cardiovascular risk, the method further comprises treating the subject by administering omega-3 fatty acid supplementation.
In some embodiments, the method further comprises re-assessing the cardiovascular risk in a subsequent sample following omega-3 fatty acid supplementation.
In some embodiments, the omega-3 fatty acid supplementation comprises fish oil, eicosapentaenoic acid (EPA) and/or docosahexaenoic acid (DHA).
In some embodiments, the subsequent sample is obtained about 1 day to about 90 days after initiation of supplementation. The timing of obtaining the subsequent sample can be determined by the skilled person and may be determined based on the formulation of the supplementation, the frequency of dosing and the dosage.
In some embodiments, the subsequent sample is obtained about 28 days after initiation of supplementation.
In some embodiments, the method further comprises adjusting the omega-3 fatty acid supplementation based on the change in level of the one or more phospholipid biomarkers that correlate to O3I status from the first time point to the second time point.
In some embodiments, adjusting the omega-3 fatty acid supplementation comprises increasing the omega-3 fatty acid supplementation if the subject is determined to be at high cardiovascular risk or at intermediate cardiovascular risk.
In some embodiments, adjusting the omega-3 fatty acid supplementation comprises maintaining or discontinuing the omega-3 fatty acid supplementation if the subject is determined to be at low cardiovascular risk.
The term “treating” or “treatment” as used herein and as is well understood in the art, means an approach for obtaining beneficial or desired results, including clinical results. Beneficial or desired clinical results can include, but are not limited to, alleviation or amelioration of one or more symptoms or conditions, diminishment of extent of disease, stabilized (i.e. not worsening) state of disease (e.g. maintaining a subject in remission), preventing disease or preventing spread of disease, delay or slowing of disease progression, amelioration or palliation of the disease state, diminishment of the reoccurrence of disease, and remission (whether partial or total), whether detectable or undetectable. “Treating” and “treatment” can also mean prolonging survival as compared to expected survival if not receiving treatment. “Treating” and “treatment” as used herein can also mean mitigating the risk of or the risk of developing cardiovascular in a subject.
Another aspect of the disclosure is a method of treating and/or preventing a mental health disorder, an autoimmune disorder, or a neurodegenerative disorder in a subject, the method comprising:
In some embodiments the mental health disorder is depression.
In some embodiments, the omega-3 fatty acid supplementation comprises fish oil, eicosapentaenoic acid (EPA) and/or docosahexaenoic acid (DHA).
In some embodiments, the method further comprises repeating the method of assessing O3I status for a second sample from the same subject taken at a second time point following omega-3 fatty acid supplementation.
In some embodiments, the subsequent sample is obtained about 1 day to about 90 days after initiation of supplementation. The timing of obtaining the subsequent sample can be determined by the skilled person, and may be determined based on the formulation of the supplementation, the frequency of dosing and the dosage
In some embodiments, the second sample is obtained about 28 days after initiation of supplementation.
In some embodiments, the method further comprises adjusting the omega-3 fatty acid supplementation based on the change in level of the one or more phospholipid biomarkers that correlate to O3I status from the first time point to the second time point.
In some embodiments, the impact of changes in omega-3 fatty acid intake through diet or supplements can be monitored over time, as well as risk assessment for incidence of clinical events (e.g., heart failure, stroke, cognitive decline).
The preceding section is provided by way of example only and is not intended to be limiting on the scope of the present disclosure and appended claims. Additional objects and advantages associated with the compositions and methods of the present disclosure will be appreciated by one of ordinary skill in the art in light of the instant claims, description, and examples. For example, the various aspects and embodiments of the disclosure may be utilized in numerous combinations, all of which are expressly contemplated by the present description. These additional advantages, objects and embodiments are expressly included within the scope of the present disclosure. The publications and other materials used herein to illuminate the background of the disclosure, and in particular cases, to provide additional details respecting the practice, are incorporated by reference, and for convenience are listed in the appended reference section.
The following non-limiting examples are illustrative of the present disclosure:
Classical methods for lipid profiling of biological samples have relied on the analysis of esterified fatty acids from lipid hydrolysates using gas chromatography (GC)-MS.19 However, comprehensive analysis of intact phospholipids (PLs) was first achieved by MS when using soft ionization methods based on matrix-assisted laser desorption/ionization and electrospray ionization (ESI).20 Although shotgun lipidomics enables the direct analysis of lipid extracts by direct infusion (DI)-MS,21 high efficiency separations are often needed to improve method selectivity while reducing ion suppression effects, isobaric interferences and/or various other mass ambiguities.22 To date, liquid chromatography (LC)-MS remains the separation platform of choice in lipidomics.23 However, LC-MS protocols vary substantially in terms of operation conditions (e.g., column types, elution conditions etc.) used to resolve different lipid classes primarily by reversed-phase, normal-phase and/or hydrophilic interaction chromatography (HILIC).24,25 For instance, greater sample throughput, separation resolution and/or reproducibility can be achieved in reversed-phase LC-MS lipidomic analyses using core shell particles,26 vacuum jacked columns,27 capillaries operated under ultra-high pressure conditions,28 and via multidimensional separations.29 Alternatively, supercritical fluid chromatography-MS can resolve lipids that vary widely in their polarity with better robustness than HILIC-MS.30 Also, ion mobility-MS enables the ultra-fast separation of PLs as compared to chromatographic methods with adequate selectivity to generate a lipidome atlas.31 On the other hand, nonaqueous capillary electrophoresis-mass spectrometry (NACE-MS) is largely an unrecognized separation technique in lipidomics likely due to a paucity of published studies limited to certain ionic lipids, such as saturated fatty acids32 lipid A isomers33 and glycerophospholipids.34,35 Indeed, a lack of robust NACE-MS protocols, limited vendor support, and sparse method validation relative to existing chromatographic methods have deterred its use as a viable separation platform in untargeted lipid profiling.
Recently, multisegment injection (MSI)-NACE-MS was introduced as a multiplexed separation platform for the quantitative determination of fatty acids from blood specimens,6,36,37 which can also resolve other classes of anionic lipids under negative ion mode detection, such as phosphatidic acids and phosphatidylinositols.38 Serial injection of seven or more samples within a single capillary allows for higher sample throughput39 together with temporal signal pattern recognition in ESI-MS40 for rigorous molecular feature selection and lipid authentication when performing nontargeted screening.38 However, separation resolution and selectivity is currently limited for phosphatidylcholines (PC) and other classes of zwitter-ionic lipids that migrate close to the electroosmotic flow (EOF). Pre-column chemical derivatization strategies have been developed to introduce or switch charge states on specific lipid classes to modify their chromatographic retention, reduce isobaric interferences, and improve ionization efficiency with lower detection limits in ESI-MS.41 For instance, Smith et al.42-44 have used diazomethane for charge inversion on modified cationic PLs via quantitative methylation. However, given the explosive and toxicity hazards of diazomethane that is generated in-situ,45 safer methylating agents are required in routine MS-based lipidomic workflows without blast shields and other personal protective equipment.
Ultra LC-MS grade methanol, acetonitrile, water and 2-propanol were used to prepare the sheath liquid and the background electrolyte (BGE). Ammonium formate, formic acid, 1,2-distearoyl-d70-sn-glycero-3-phosphocholine (PC 36:0[D70]), 1,2-dipalmitoyl-d62-sn-glycero-3-phosphocholine (PC 32:0[D62]), methyl-tert-butyl ether (MTBE), MTT, FMOC and all other chemical standards were purchased from Sigma-Aldrich Inc. (St. Louis, MO, USA) unless otherwise stated. All lipid standards purchased were either as a powder or dissolved in solution (1:1) of chloroform and methanol. Stock solutions for lipids were then diluted in chloroform and methanol and stored at −80° C. prior to further use. Reference material from the National Institute of Standards and Technology (NIST) SRM-1950 pooled human plasma was purchased from the NIST (Gaithersburg, ML, USA). While certified reference values for NIST SRM-1950 have been reported for several polar metabolites, plasma PLs measured in this study were compared to the median of mean concentrations reported for NIST SRM-1950 in an international study across 31 laboratories that adopted various LC-MS/MS lipidomic workflows. In this case, consensus plasma PL concentrations required measurements from a minimum of 5 laboratories having a sample coefficient of dispersion (COD)<40%.15
Plasma samples and lipid calibrant solutions were extracted using a modified MTBE-based liquid extraction procedure previously described for fatty acids and anionic lipids using MSI-NACE-MS in negative ion mode.36,38 Briefly, 50 μL of a NIST SRM-1950 plasma aliquot was mixed with 100 μL of methanol containing PC 32:0[D62] as a recovery standard and shaken for 10 min. Then, 250 μL of MTBE was added and the mixture was subject to vigorous shaking for 10 min. To induce phase separation, 100 μL of deionized water was then added prior to centrifugation at 10 min at 4000 g. Next, 200 μL of the lipid-rich MTBE upper layer was transferred into another vial and dried down at room temperature using an Organomation MULTIVAP® nitrogen evaporator (Berlin, MA, USA). For underivatized lipids, dried plasma extracts were then reconstituted to a volume of 50 μL containing acetonitrile/isopropanol/water (70:20:10) with 10 mM ammonium formate containing internal standards PC 36:0[D70] (5 μM), benzyltriethylammoniumchloride (BTA) (1 μM), and of PC 32:0[D62] (5 μM) prior to analysis by MSI-NACE-MS.
All plasma ether extracts and PL calibrants were subject to a two-step chemical labeling procedure using FMOC and MTT. In 2 mL amber glass vials, 100 μL of 0.85 mM FMOC in chloroform was added to dried ether plasma extracts and shaken vigorously for 5 min. Then, samples were blown down to dryness using nitrogen at room temperature prior to reconstitution in 50 μL of MTBE containing 450 mM of MTT. Vials were next sealed with Teflon tape and vortexed for 30 s prior to derivatization at 60° C. for 60 min (unless otherwise stated). Afterwards, 100 μL of MeOH, 250 μL of hexane and 200 μL of deionized water was added to back extract polar by-products of the reaction (e.g., p-toluidine). After centrifuging for 10 min at 4000 g, 200 μL of hexane as the supernatant was transferred out to a separate glass vial and then evaporated to dryness under nitrogen. Lastly, derivatized extracts were then reconstituted in 50 μL of acetonitrile/isopropanol/water (70:20:10) with 10 mM ammonium formate containing internal standards PC 36:0[D70] (5 μM), BTA (1 μM), and of PC 32:0[D62] (5 μM) prior to analysis by MSI-NACE-MS. Derivatization yields for methylated PLs from plasma extracts were calculated based on the integrated relative peak area (RPA) for each native (unlabelled) PL relative to PC 36:0[D70] as an internal standard using equation (1):
An Agilent 6230 time-of-flight (TOF) mass spectrometer with a coaxial sheath liquid electrospray (ESI) ionization source equipped with an Agilent G7100A CE unit was used for all experiments (Agilent Technologies Inc., Mississauga, ON, Canada). An Agilent 1260 Infinity isocratic pump and a 1260 Infinity degasser were utilized to deliver an 80:20 MeOH-water with 0.1% vol formic acid at a flow rate of 10 μL/min using a CE-MS coaxial sheath liquid interface kit. For mass correction in real-time, the reference ions purine and hexakis (2,2,3,3-tetrafluoropropoxy) phosphazine (HP-921) were spiked into the sheath liquid at 0.02% vol to provide constant mass signals at m/z 121.0509 and 922.0098, which were utilized for monitoring ion suppression and/or enhancement effects. During sample introduction into the capillary, the nebulizer gas was turned off to prevent siphoning effects that may contribute to air bubbles and current errors upon voltage application.36 This was subsequently turned on at a low pressure of 4 psi (27.6 kPa) following voltage application with the ion source operating at 300° C. with a drying gas of nitrogen that was delivered at 4 L/min. The TOF-MS was operated in 2 GHz extended dynamic range under positive mode detection. A Vcap was set at 3500 V while the fragmentor was 120 V, the skimmer was 65 V and the octopole rf was 750 V. All separations were performed using bare fused-silica capillaries with 50 μm internal diameter, a 360 μm outer diameter, and 100 cm total length (Polymicro Technologies Inc., AZ). A capillary window maker (MicroSolv, Leland, NC) was used to remove 7 mm of the polyimide coating on both ends of the capillary to prevent polyimide swelling with organic solvents in the background electrolyte (BGE) or aminolysis under alkaline nonaqueous buffer conditions.46 An applied voltage of 30 kV was used for CE separations at 25° C. together while using a forward pressure of 5 mbar (0.5 kPa). The BGE was 35 mM ammonium formate in 70% vol acetonitrile, 15% vol methanol, 10% vol water and 5% vol isopropanol with an apparent pH of 2.3 adjusted with the addition of formic acid. Derivatized plasma extracts and lipid standards were introduced in-capillary hydrodynamically at 50 mbar (5 kPa) alternating between 5 s for each sample plug and 40 s for the BGE spacer plug for a total of seven discrete samples analyzed within a single run.38 Prior to first use, capillaries were conditioned by flushing at 950 mbar (95 kPa) with methanol, 0.1 M sodium hydroxide, deionized water, and BGE sequentially for 15 min each. The BGE and sheath liquid were degassed prior to use. For analysis of NIST SRM-1950 by MSI-NACE-MS in negative ion mode to verify acidic lipids not amenable by the FMOC/MTT labelling, an alkaline BGE with the same organic solvent composition was used, but with ammonium acetate and ammonium hydroxide as the BGE and pH modifier respectively as described elswhere.36 In this case, the same MTBE extraction protocol was applied for the direct analysis of fatty acids and anionic lipids, but the extract was concentrated two-fold without FMOC/MTT chemical derivatization. Plasma PLs were annotated by MSI-NACE-MS based on their sum composition, mass error and relative migration times (RMTs) or apparent electrophoretic mobilities (Table 1, 2) with select PLs from NIST SRM-1950 ether extracts further characterized by MS/MS for confirmation of molecular PC and SM species.
A two-step chemical labeling strategy using FMOC/MTT was first developed to generate a positive charge on methylated PLs to increase their electrophoretic mobility as depicted in
MTT was previously introduced as a methylation agent for esterification of carboxylic acids47 that allowed for the analysis of acidic metabolites in urine by GC-MS.48 Similarly, Furukawa et al.49 reported using MTT to methylate oligosaccharides containing sialic acid residues in glycoblotting experiments prior to MALDI-MS analyses. However, this reagent remains unexplored to date with sparse information related to its reaction mechanism and applicability to routine lipidomic analyses. Initial studies were performed to optimize reaction conditions for the formation of methylated PCs as a function of three experimental factors, namely reaction time (0 to 180 min), MTT concentration (50 to 900 mM) and reaction temperature (20 to 100° C.). A maximum yield for methylated PCs was achieved using 450 mM of MTT with a reaction time of 60 min at 60° C. corresponding to an average yield of ˜70%. This apparent reaction yield was lower than first anticipated without the use of FMOC due to ion suppression effects from p-toluidine formed as a by-product when using excess MTT (data not shown). A kinetic study was next performed to determine the minimum reaction time needed when using a two-step chemical derivatization strategy based on FMOC/MTT, where the reaction progress was reflected by a more intense golden/amber hue color as shown in
Similar to the use of collisional cross-section areas for classifying lipid structures as gas-phase ions in IMS,31 the electrophoretic mobility represents an intrinsic physicochemical parameter for characterizing ionic lipids in solution by MSI-NACE-MS.38 Zwitter-ionic PC species that migrate close to the EOF under alkaline BGE conditions overlap substantially resulting in a narrow separation window as compared to acidic lipid classes, such as PEs, phosphatidylinositols (PIs), lysophosphatidic acids (LPAs), and free/nonesterified fatty acids (FAs). This scenario was suboptimal for PCs and SMs as it can contribute to false discoveries from isobaric interferences when performing untargeted lipidomics.
Characterization of Consensus mPLs from Reference Plasma Sample:
Previously, Bowden et al.15 reported the use of NIST SRM-1950 as a reference sample when comparing the performance of untargeted lipidomic platforms across 31 international laboratories, each using their own analysis data workflows, LC-MS methodology and hardware/software configuration. Although 1527 unique lipid features were measured quantitatively across all sites, only 339 of these plasma lipids were reported consistently from at least 5 or more laboratories with adequate precision based on a minimum coefficient of dispersion threshold (COD <40%). Next, the two-stage chemical derivatization protocol using MSI-NACE-MS was validated for a panel of methylated PCs and SMs measured consistently from NIST-SRM-1950 plasma extracts as compared to various standardized LC-MS protocols. Overall, 75 plasma PLs reported in the harmonization study were annotated based on their sum composition from NIST SRM-1950 ether extracts in a targeted manner, including 48 PCs and 27 SMs as their cationic phosphate methyl esters (Table 1; Table 2). Overall, MSI-NACE-MS was able to measure 90% of reported consensus PCs (48 out of 53) and SMs (27 out of 30) from NIST SRM-1950, respectively based on the combined PL annotations used by Bowden et al.15, which also included mass resolvable plasmanyl and plasmenyl species. However, the latter lipid species were confirmed to not be detected in this case. An analysis of acidic lipids from NIST SRM-1950 was also performed when using MSI-NACE-MS under negative ion mode without chemical derivatization to expand lipidome coverage to include more polar classes of acidic lipids under alkaline conditions.38 This also includes LPCs that have a poor recovery after hexane back extraction and PEs that generate isobaric interferences with PCs after methylation if FMOC was not included as a protecting agent. In this case, it was possible to reliably measure 11/14 (79%) bile acids (BAs), 19/25 (76%) of LPCs, but only 24/35 (69%) PE and 7/13 (54%) PI species from the consensus plasma lipids reported by five or more laboratories in Bowden et al.15 The reduced coverage was likely due to the lower ionization efficiency of polar/acidic lipids under negative ion mode detection in conjunction with the much smaller sample volumes introduced in-capillary (˜10 nL) in MSI-NACE-MS than LC-MS methods. Although only 8 FA species satisfied the selection criteria in the lipidomics harmonization study, MSI-NACE-MS can quantify more than 20 FAs from blood extracts as described elsewhere.6,53
A major analytical challenge in contemporary lipidomic research remains reliable quantification given the lack and/or high costs of lipid standards and matching stable-isotope internal standards. However, a key advantage of MSI-NACE-MS is that ionic lipids migrate with a steady-state mobility under isocratic BGE conditions while using a continuous sheath liquid solution during ionization unlike LC-MS methods that rely on gradient elution for optimal separation performance. Multiplexed separations in MSI-NACE-MS not only improve sample throughput, but also enable versatile serial sample injection configuration to encode mass spectral information temporally within a separation,38 which reduces mass ambiguities when credentialing ionic lipids in an untargeted manner.55
Table 3 summarizes the performance of MSI-NACE-MS for reliable quantification of four representative plasma PCs when using external calibration curves as compared to a serial dilution of NIST SRM-1950. As expected, good accuracy was achieved when quantifying methylated PC 34:0, PC 38:6, and PC 40:6 in both spike-recovery studies, as well as unspiked reference plasma (mean bias<10%) when using calibration curves by MSI-NACE-MS when compared to untargeted LC-MS methods.15 Slightly higher bias (<25%) was found for PC 38:6 and PC 40:6 concentrations in NIST SRM-1950 when compared to a targeted shotgun (separation-free) lipidomic inter-laboratory comparison study by DI-MS/MS using a commercial lipid kit under standardized operating conditions.17 The latter discrepancy may arise due to isobaric interferences when high efficiency separations are not used in lipidomic analyses. Overall, poor accuracy (mean bias ˜−50%) was noted primarily for PC 30:0 after hexane sample cleanup since this procedure favors a quantitative recovery of more lipophilic PLs having longer total carbon acyl chain lengths. An alternative strategy for semi-quantitative estimation of other plasma PLs lacking chemical standards was also explored via response factors derived from the serial dilution of NIST SRM-1950 when using the median of mean consensus lipid concentrations reported by Bowden et al.15 As expected, this strategy was better suited to more abundant plasma PLs (>10 mM) given the serial dilution process unlike lipid standards that permitted PL quantification over a wider linear dynamic range (
Nevertheless, this approach offers a higher throughput approach for quantitative lipidomic analyses even in cases when standards are not available, which was recently applied to identify two specific circulating PCs as surrogate biomarkers of the omega-3 index following high-dose fish oil, docosahexaenoic acid or eicosapentaenoic acid supplementation (see Example 2).55 In summary, expanded lipidome coverage was achieved in MSI-NACE-MS when using a two-step pre-column chemical derivatization strategy to convert zwitter-ionic PLs into their corresponding cationic methyl phosphate esters. This labeling procedure is quantitative and more convenient to use than diazomethane for PL methylation, which results in improved separation performance and ionization efficiency. Overall, 75 cationic PCs and SMs were characterized from reference human plasma with adequate precision when using MSI-NACE-MS following FMOC/MTT derivatization and hexane back extraction as compared to an international lipidomic harmonization study. Additionally, more than 69 other acidic and polar PLs from NIST SRM-1950 plasma extracts can also be measured by MSI-NACE-MS under negative ion mode without chemical derivatization, not including polar lipid classes poorly retained in reversed-phase LC-MS (e.g., PAs, PSs, FAs). This strategy greatly expands conventional CE-MS metabolomic protocols that rely on aqueous buffer systems and thus have been limited to the analysis of hydrophilic/polar metabolites. Lipid annotation and structural classification was also supported based on predictable trends in the electrophoretic mobility for methylated PCs and SMs that are dependent on polar head group/chemical linkage, total fatty acyl chain length and degrees of unsaturation. Advantages of MSI-NACE-MS include greater throughput and minimal ion suppression effects that allows for unique data workflows for data acquisition and lipid authentication in comparison to other separation methods that utilize single sample injections. MSI-NACE-MS is also more amenable to standardization since it operates using only a bare-fused silica capillary under an isocratic nonaqueous buffer system unlike LC-MS that rely on different column types and gradient elution programs when using reversed-phase and HILIC separations. However, MSI-NACE-MS with a coaxial sheath liquid interface suffers from higher detection limits and lower concentration sensitivity for ionic lipids as compared to LC-MS protocols due to the smaller sample volume introduced on-capillary. Also, electrically neutral lipid classes are not resolved or reliably measured even after methylation, such as diacylglycerides and cholesteryl esters.
In this work, a two-step chemical derivatization strategy was introduced using FMOC/MTT for the methylation of zwitter-ionic PLs to expand lipid profiling coverage by MSI-NACE-MS under positive ion mode conditions. FMOC was used as a compatible protecting agent to prevent generation of PE isobaric species to PCs that also reduced ion suppression effects from excess MTT by-products prior to hexane back extraction. The efficacy of this reaction was optimized to generate quantitative yields of 75 cationic methylated PCs and SMs verified in reference human plasma when using MSI-NACE-MS, which comprised 90% of consensus plasma lipids within these two classes as reported in an international lipidomics harmonization study. Overall, PL methylation resulted in improved separation resolution, faster analysis times, reduced ion suppression while allowing for better lipid structural classification based on changes in their electrophoretic mobility. This method is optimal for lipidomic studies requiring higher sample throughput and lower operating costs with stringent quality control, while consuming minimal volumes of sample and organic solvent. Complementary analysis of other polar or acidic lipid classes can be achieved by their direct analysis using MSI-NACE-MS under negative ion mode without chemical derivatization. Good precision and accuracy was also demonstrated when quantifying methylated PCs and SMs in reference plasma samples, including the potential for use of serial dilution of NIST SRM-1950 to estimate relative response factors for lipids lacking chemical standards provided they are present at concentrations >5 mM. This methylation strategy offers a practical alternative to diazomethane for improved lipid analysis when using other MS instrumental platforms without excessive hazards and safety precautions, including direct infusion-MS, ion mobility-MS and LC-MS/MS methods. Although the applicability of this two-tiered derivatization scheme s demonstrated on phosphatidylcholine (PC) and sphingomyelin (SM) using MSI-NACE-MS, other lipid species containing phosphoric acid moieties that exist in biological samples are subject to separation and ionization enhancement using derivatization. This can be especially useful when trying to profile polar lipids using conventional nontargeted lipidomics protocols using ion mobility and/or chromatographic separations coupled to high resolution MS. For example, methylation using trimethylsilyl-diazomethane has been demonstrated to improve separation efficiency and responsiveness of various polar lipids by supercritical fluid chromatography/tandem mass spectrometry (SFC/MS/MS) (134), and more recently, even enhancing resolution of phosphoinositide regioisomers (135). Additionally, a methylation approach was shown to be effective for profiling fatty acyl-coenzyme As (acyl-CoAs) (137) by improving peak shape and reducing carry over effects. The use of FMOC and MTT presents as an alternative strategy for methylation of polar phosphoric acid containing lipid species to enhance column retention, resolution and ionization response for larger scale, routine analysis with considerably lower hazards than diazomethane.
Evidence-based nutritional policies are urgently needed given an alarming increase in obesity and cardiometabolic disease burden worldwide (56). Public health guidelines have historically focused on lowering dietary fat intake (e.g., cholesterol, saturated fats) as a purported ‘heart healthy’ diet (57) rather than assessing overall diet quality (58). For instance, there is widespread deficiency of omega-3 long-chain polyunsaturated fatty acids (n3-LCPUFAs) as it comprises only a small fraction of total fats consumed in contemporary Western diets (59) since endogenous synthesis of this important class of fatty acid (FA) is low (60). For these reasons, the American Heart Association Nutrition Committee recommends the consumption of oily fish/seafood as a marine source of dietary n3-LCPUFA up to twice a week to reduce cardiovascular disease risk (61). Unlike saturated or monounsaturated FAs, humans are unable to synthesize sufficient amounts of n3-LCPUFAs enriched within the cellular membrane of certain tissues/organs (e.g., retina, brain, heart), including docosahexaenoic acid (DHA, 22:6) and eicosapentaenoic acid (EPA, 20:5) (62). Omega-3 FA nutrition impacts membrane composition and cellular function while also modulating inflammatory processes, such as the formation of resolvins and anti-inflammatory lipid mediators (63). Optimal intake of n3-LCPUFAs may also improve skeletal muscle function in older persons by enhancing amino acid-stimulated muscle protein synthesis rates, and mitochondrial respiration kinetics (64).
Although dietary sources of n3-LCPUFAs are derived primarily from marine sources, the content of DHA and EPA in commonly consumed wild and farmed fish species varies widely (65). Alternatively, commercial fish oil (FO) dietary supplements offer a way to ensure adequate omega-3 FA nutrition together with emerging microalgae sources (66), and prescription EPA and/or DHA products (67). Yet, there have been conflicting results of n3-LCPUFAs in clinical trials in terms of their efficacy for cardiovascular disease protection (68). This outcome likely stems from inadequate dosage (<2 g/day) using impure formulations that do not target high-risk patients with hypertriglyceridemia and other comorbidities having a low baseline O3I status (69). For instance, high-dose prescription (4 g/day) icosapent ethyl treatment has been reported to reduce cardiovascular events in current and former smokers to levels similar to never smokers (70). However, prescription, supplemental and/or dietary intake of n3-LCPUFAs do not address excessive consumption of omega-6 FAs prevalent in processed foods (71), or differences in fatty acid desaturase activity (72) that contribute to variations in treatment response.
Both human n3-LCPUFA supplementation trials in this study obtained signed informed consent from all participants and abided by ethical principles of the Declaration of Helsinki. In the first discovery cohort, fasting serum samples were collected from participants in a randomized, double-blinded, placebo-controlled intervention study that investigated the effects of FO supplementation on attenuating skeletal muscle disuse atrophy following leg immobilization (84). This clinical trial was registered at the US National Library of Medicine (https://clinicaltrials.gov/) as NCT03059836, and approved by the Hamilton Integrated Research Ethics Board. Briefly, this study comprised a cohort of healthy young women with a mean age of 22 years (range: 19-31 years) and BMI of 24 kg/m2 (range: 18-26 kg/m2) recruited locally from the Hamilton area. All participants received either a high-dose FO (3.0 g EPA and 2.0 g DHA daily; n=9) or a placebo control based on an isoenergetic and volume equivalent sunflower oil (SO) daily (n=9). Repeat fasting serum samples were collected from participants at baseline and after 28, 42 and 56 days of the intervention. All serum samples were then stored frozen at −80° C. Further details on blood collection, participant selection and exclusion criteria, and erythrocyte PL omega-3 FA analysis for O3I determination are described elsewhere (84). Briefly, lipids were extracted from red blood cells using the Folch method (90) in chloroform-methanol (2:1 vol.) containing butylated hydroxytoluene (BHT, 0.01% vol.) as an antioxidant and heptadecanoic acid as an internal standard. Thin-layer chromatography silica plates isolated PL fractions (Silica Gel 60, 0.22 mm; Merck, Kenilworth, NJ, USA) using heptane: isopropylether: acetic acid (60:40:3 vol.) as the elution solvent. Gel bands were scraped off the plate and transferred into screw cap tubes for transmethylation with BF3 in methanol. Fatty acid methyl esters (FAMEs) were then dissolved in hexane and analyzed using a Hewlett-Packard 5890 Series II GC with flame-ionization detection while using a Varian CP-SIL capillary column (100 m, internal diameter of 0.25 mm) (Palo Alto, CA, USA). These measurements were then used to calculate the O3I by taking the sum of quantified EPA and DHA relative to the total of 17 saturated, monosaturated and polyunsaturated FAs in fasting serum samples.
In the second validation cohort, fasting plasma samples were collected from participants in a randomized, double-blinded, multi-arm, placebo-controlled parallel group trial comparing the effects of supplementing using either ˜3 g/day EPA, DHA, or olive oil (OO) over a 90-day period (85). This study was approved by the Research Ethics Board at the University of Guelph. Participant characteristics (sex, age, BMI etc.) and blood draws for O3I assessment were obtained for all participants (n=83) on study day visits. Purified EPA (KD-PUR EPA700TG) and DHA (KD-PUR DHA700TG) oils, as well as OO, were obtained from KD Pharma (Bexbach, Germany) with EPA and DHA in their triglyceride forms. The FA content of these supplements was previously reported to be 75.7%±0.01% for oleic acid (18:1) in the OO supplement, 74.7%±0.09% EPA and 0.55%±0.01% DHA in the EPA supplement, and 72.3%±1.3% DHA and 1.05+0.11% EPA in the DHA supplement (91). All capsules contained 0.20% vol. tocopherol to prevent oxidation of polyunsaturated lipids. Exclusion criteria included use of FO supplements within the previous 3 months, >2 servings of fish/seafood or other omega-3 FA-rich products per week, prescribed medication use (except oral contraceptives), current smoking and history of cardiovascular disease. Participants were assigned via block randomization with stratification by sex to one of three treatment arms, namely OO supplement (n=27), EPA supplement (n=28) and DHA supplement (n=28). Participants were instructed to maintain regular exercise and dietary habits throughout the study. After overnight fasts, participants were subject to blood sampling at the Human Nutraceutical Research Unit at the University of Guelph before (baseline) and after (endpoint) of the 90-day intervention period. Blood was collected into EDTA-treated vacutainers was used to isolate plasma and erythrocytes. Samples were separated by centrifugation at 700×g at 4° C. for 15 min. A similar protocol was performed for FAME analysis from erythrocyte PL extracts following fractionation and saponification using GC-FID with normalization to heptadecanoic acid as internal standard (92). In this case, the O3I was calculated by taking the sum of EPA and DHA relative to the sum of 15 saturated, monosaturated and polyunsaturated FAs in fasting plasma samples.
Fasting serum and plasma samples were subject to a two-step chemical derivatization protocol using 9-fluorenylmethyoxycarbonyl chloride (FMOC) and 3-methyl-1-p-tolyltriazene (FMOC/MTT) as described in example 1. This reaction was introduced as a more convenient alternative to diazomethane to improve separation resolution and ionization efficiency by converting zwitter-ionic PL species that co-migrate close to the electroosmotic flow (EOF) into methylated phosphatidylcholines (PCs) and sphingomyelins (SMs) with a permanent positive charge. Briefly, in a glass sample vial, a 50 μL aliquot of serum/plasma sample was subject to a methyl-tert-butyl ether (MTBE) extraction, where 100 μL of methanol with 0.01% vol of BHT as antioxidant, and PC 16:0[D62] as internal standard were first added, and samples then mixed to induce protein precipitation. Next, 250 μL of MTBE was added and mixed prior to adding 100 μL of deionized water to induce phase separation. Samples were then centrifuged at 4000 g at 4° C. where then 200 μL of the organic layer was transferred into a new glass vial and dried down. Next, 100 μL of 0.85 mmol/L FMOC in chloroform containing PC 18:0[D70] as a second internal standard was added to dried serum/plasma extracts and mixed for 5 min at room temperature before drying down again. Next, 50 μL of MTBE containing 450 mmol/L of MTT was added to the glass vial with the lid sealed with Teflon tape. This vessel was then heated to 60° C. for 60 min. Once the reaction was complete, the solution was dried down and then subject to a back extraction, where 100 μL of methanol was added, followed by 250 μL of hexane and then 200 μL of deionized water before centrifuging for 10 min at 4000 g at 4° C. Then, 200 μL of the upper hexane layer was transferred out and dried down. Once completely dried, all samples were subsequently reconstituted in 50 μL containing acetonitrile/isopropanol/water (70:20:10 vol.) with 10 mmol/L ammonium formate and benzyltriethylammonium (BTA) chloride as a third internal standard. All three internal standards had a final concentration of 5.0 μmol/L in the final plasma/serum extract, where PC 16:0[D62] was used for data normalization of methylated PCs to improve method precision based on their relative peak areas (RPA) and relative migration times (RMT). Overall, derivatization yields of about 90% was achieved for quantitative analysis of methylated PCs by MSI-NACE-MS using a reference human plasma sample (87; as described in Example 1).
In order to expand overall lipidome coverage, lipid ether extracts were also analyzed directly without methylation, namely acidic/polar PL classes, including lysophosphatidylcholines (LPCs), phosphatidylethanolamines (PEs), lysophosphatidylethanolamines (LPEs), phosphatidylinositols (PIs) and NEFAs when using MSI-NACE-MS under negative ion mode as described elsewhere (88) and in example 1. Briefly, a 50 μL aliquot was first subjected to MTBE extraction where 100 μL of MeOH containing 0.01% vol. BHT was added to samples containing deuterated myristic acid, FA 14:0[D27] as an internal standard. Following rigorous shaking, phase separation induced by adding water, where samples were centrifuged to sediment protein at 4000 g at 4° C. for 30 min. The formation of a biphasic solution allowed for the top, lipid-rich ether layer to be extracted at a fixed volume (200 μL), where it was then dried under a gentle stream of nitrogen gas at room temperature. The dried extracts were then concentrated 2-fold after reconstitution in 25 μL acetonitrile-isopropanol-water (70:20:10 vol) containing 10 mM ammonium acetate and 50 μmol/L of deuterated stearic acid, FA 18:0[D35] as a second internal standard. However, FA 14:0[D27] was used for data normalization of acidic lipids to improve method precision.
An Agilent 6230 TOF mass spectrometer equipped with a coaxial sheath liquid ESI ionization source was used with an Agilent G7100A capillary electrophoresis (CE) unit for all experiments (Agilent Technologies Inc.). To supply a sheath liquid during electrophoretic separations, an Agilent 1260 Infinity isocratic pump delivered a solution containing 80% vol. methanol with 0.1% vol. formic acid at a flow rate of 10 μL/min into the sprayer. All separations were performed using bare fused-silica capillaries with an internal diameter of 50 μm, outer diameter of 360 μm and total length of 110 cm (Polymicro Technologies Inc.). Electrophoretic separations were performed with an applied voltage of 30 kV with the capillary cartridge set at 25° C. while using an isocratic pressure of 10 mbar (1 kPa). The background electrolyte (BGE) was 35 mmol/L ammonium formate in 70% vol. acetonitrile, 15% vol. methanol, and 5% vol. isopropanol with an apparent pH of 2.3 that was adjusted by the addition of formic acid. Derivatized ether extracts were injected hydrodynamically at 50 mbar (5 kPa) alternating between 5 s for each sample plug and 40 s for the background electrolyte spacer plug to total seven discrete samples that were analyzed within 30 min for a single experimental run. Repeat QC samples were created by pooling samples from each study cohort, which were then introduced in a randomized position for each MSI-NACE-MS run to assess the technical precision of the method in both FO (n=13) and EPA or DHA (n=29) supplementation trials. All methylated lipid extracts were analyzed in positive ion mode acquisition with a Vcap at 3500V with full-scan data acquisition over the range of (m/z 50-1700). Acidic lipids without derivatization were analyzed directly by MSI-NACE-MS under negative ion mode, which was performed only for the pooled sub-group analysis in the discovery FO trial. This instrumental configuration used a sheath liquid of 80% vol. methanol with 0.5% vol. ammonium hydroxide delivered at a flow rate of 10 μL/min using a CE-MS coaxial sheath liquid interface kit. The separations were performed on the same bare fused-silica capillaries with internal diameter of 50 μm, outer diameter of 360 μm and total length of 95 cm. The applied voltage was set to 30 kV at 25° C. for CE separations while applying an isocratic pressure of 20 mbar (2 kPa). The BGE consisted of 35 mM ammonium acetate in 70% vol. acetonitrile, 15% vol. methanol and 5% vol. isopropanol with an apparent pH of 9.5 that was adjusted using the addition of 12% vol ammonium hydroxide. These underivatized serum ether extracts from the FO discovery trial were injected hydrodynamically at 50 mbar (5 kPa) alternating between 5 s for each sample and 40 s for the BGE spacer for a total of seven discrete samples that were analyzed within a 30 min run (87,88,93). The TOF was operated in negative ion mode acquisition with Vcap at 3500 V for full-scan data acquisition over the range of (m/z 50-1700).
Overall, untargeted lipid profiling was performed on pooled serum extracts in a sub-group analysis of participants from the FO intervention trial when using MSI-NACE-MS under positive and negative ion modes. This was followed by a targeted lipidomic analysis and subsequent validation of lead candidate PC biomarkers responsive to n3-LCPUFA supplementation in both FO, and EPA or DHA only placebo-controlled trials when using MSI-NACE-MS under positive ion mode following FMOC/MTT derivatization. Structural elucidation of putative PC biomarkers of the O3I were performed by collision-induced dissociation experiments when using a single injection format in CE coupled to a 6550 quadrupole-time of flight-mass spectrometer system (Agilent Technologies Inc.) at different collision energies under positive and negative ion mode as described elsewhere (87,88,93). Access to a purified reference standard for PC 16:0/22:6 (Toronto Research Chemicals, Toronto, ON) was available to confirm the likely molecular structure of PC 38:6 after spiking in pooled plasma (i.e., co-migration) together with a comparison of the relative intensity of fatty acid product ions using MS/MS under negative ion mode. However, lack of access to other lipid standards, including PC 16:0/20:5 and potential positional isomers (e.g., PC 22:6/16:0) prevented the reporting of definitive lipid molecular structures for these lipids in this study. Further details on the methodology used in this study is summarized in a reporting checklist from the Lipid Standards Initiative (https://doi.org/10.5281/zenodo.8339260).
All MSI-NACE-MS data was analyzed using Agilent MassHunter Workstation Software (Qualitative Analysis Version 10.0, Agilent Technologies, 2012). All molecular features were extracted in profile mode within a 10 ppm mass window where derivatized lipids were annotated based on their characteristic m/z corresponding to their molecular ion and relative migration time (RMT). The manually integrated peak areas obtained from the extracted ion electropherograms were normalized to PC 16:0[D62] (positive ion mode) or FA 14:0[D27] (negative ion mode) to determine relative peak areas (RPAs) and RMT for serum/plasma lipids. Extracted ion electropherograms were integrated after smoothing using a quadratic/cubic Savitzky-Golay filter (7 points). Absolute concentrations reported for select PLs were estimated based on a serial dilution of NIST SRM-1950 human plasma when using MSI-NACE-MS as described in example 1 based on consensus concentrations reported in a multi-center lipidomics harmonization study (94). However, PC 38:6 was quantified directly using an external calibration curve normalized to PC 16:0[D62], whereas the response factor for PC 36:5 was estimated using a higher abundance surrogate lipid, PC 36:4 needed to attain adequate linear dynamic range after serial dilution of NIST-SRM 1950 human plasma as described in example 1. Least-squares linear regression and correlation plots were performed using Excel (Microsoft Office). Visualization of data, heat maps, and unsupervised principal component analysis (PCA) were performed using MetaboAnalyst version 5.0 (95). Normality tests and nonparametric statistical analysis was performed using IBM SPSS version 23 (IBM), whereas MedCalc version 12.5.0 (MedCalc Software) was used to generate boxplots and control charts with exception of trajectory box plots (R Foundation for Statistical Computing). A two-way between and within mixed-model ANOVA (treatment×time) was used for assessing the impact of high-dose FO supplementation at three times points as compared to baseline. For the study involving DHA or EPA supplementation relative to OO as placebo, a Wilcoxon signed ranked test was performed to evaluate treatment effects after confirming non-normally distributed data. A Pearson correlation analysis was used to evaluate the association between lead candidate PCs in serum or plasma extracts as compared to O3I based on erythrocyte membrane PLs.
An untargeted screen for serum PLs associated with n3-LCPUFA supplementation was initially performed based on an analysis of pooled serum extracts from all participants in the placebo/baseline as compared to the FO treatment arm (EPA, 3 g/day+DHA, 2 g/day). These two sub-groups of samples were analyzed in triplicate with a blank extract to rapidly identify differentiating PL species following high-dose FO ingestion using two complementary MSI-NACE-MS configurations as shown in
For example,
However, other ionic PL classes containing likely EPA or DHA (e.g., LPCs, PIs, PEs, LPEs etc.) were not found to be responsive to FO supplementation in this study. Also, certain serum PLs may comprise unresolved mixtures of isomers or isobars that lack specificity (e.g., PC 38:5), whereas other NEFAs derived from less abundant n3-LCPUFA in FO did not respond to supplementation, such as docasapentaenoic acid (DPA, 22:5). Type-2 isotopic effects were also not a significant problem to correct for as most co-migrating lipid isotopomers, notably for PC 35:5 and PC 38:6 lacked homologous PCs having an additional double bond (
Validation of Serum PC Panels Associated with High-Dose FO Supplementation:
Overall, 44 PC species were quantified consistently from all serum ether extracts in a cohort of young women (n=8) at baseline and then at three time points following high-dose FO or sunflower oil (SO) placebo intervention over 56 days (
As the high-dose FO trial relied on an unequal mixture of n3-LCPUFAs in a modest number of women, it was next aimed to further validate lead candidate PC biomarkers of O3I status in an independent trial involving a larger cohort (n=83) using purified EPA or DHA only supplements at the same dosage level (˜3 g/day over a 56-day period) relative to olive oil (OO) as the placebo. In addition, it was sought to confirm whether the same lipids can be related to the O3I in a different blood fraction, namely human plasma (EDTA as anticoagulant) rather than serum. This cohort comprised young, normal weight, non-smoking Canadian adults of both sexes who had a different (p=5.67×10−3) baseline O3I status of (3.77±0.63%) and (3.34±0.76%) for women (n=43) and men (n=40), respectively (Table 8). Also, the mean O3I status at baseline for all participants was (3.50±0.68% ranging from 1.87% to 5.21%) with 75% of participants having an 031<4%. High-dose EPA and DHA intake significantly increased their average O3I status from baseline to (8.30±1.21%) and (6.49±1.17%), respectively as compared to OO placebo (3.61±0.60%) after 90 days. As a result, DHA more effectively increased the O3I than EPA supplementation as reflected by 71% versus 11% of participants achieving a low cardiovascular risk profile of O3I>8%, respectively.
After identifying several n3-LCPUFA containing PC species and panels responsive to FO supplementation in the sub-group screen (Table 6) and full analysis (Table 7), a targeted lipidomic analyses of these same PC biomarker candidates was subsequently performed in a second independent placebo-controlled EPA and DHA only trial. As expected, the same circulating PCs responded to this specific n3-LCPUFA dietary intervention, notably PC 36:5 from a median baseline of 3.4 mmol/L to 23.8 mmol/L (median FC˜7.0) following EPA ingestion as shown in
In contrast, ingestion of a high-dose DHA-specific supplement elicited a more attenuated increase in plasma PC 38:6 (median FC˜2.1) from 20.1 mmol/L to 42.3 mmol/L that was similar in magnitude to the EPA-containing PC 36:5 (˜88% increase from baseline) as highlighted in
It was next determined whether circulating PCs may serve as potential surrogate measures of erythrocyte PL derived O3I while also reflecting intake of high-dose FO intake or purified supplements of either EPA or DHA. While the total sum of all six n3-LCPUFA containing PC species demonstrated a moderate correlation (r=0.636) to the O3I, statistical outcomes were improved when using fewer PCs within the panel (Table 9). Similar to the outcomes reported from the high-dose FO trial, the strongest correlation to the O3I in this cohort was achieved using the sum concentration for plasma PC 36:5 and PC 38:6, representing two of the most abundant circulating EPA and DHA containing PL species in human blood (89).
Epidemiological studies of Greenland Inuit consuming a traditional diet rich in marine organisms first implicated greater n3-LCPUFA intake with a lower incidence of cardiovascular disease than Western dietary patterns (99). However, changes in diet and cultural practices have lowered the omega-3 FA nutritional status of contemporary Inuit coinciding with an epidemiological transition of greater chronic disease burden and psychological distress (100,101). Several prospective studies in other populations have reported that low fish/seafood consumption and poor n3-LCPUFA nutrition is associated with higher all-cause and cardiovascular mortality (102-105), with EPA demonstrating the strongest association independent of other risk factors (106). Indeed, clinical trials involving purified high-dose (˜3-4 g/day) EPA and its analogs provide growing evidence of its utility as an adjunct therapy for the prevention of major coronary events in high-risk patients (107,108) by reducing circulating triglyceride levels, as well as vascular inflammation as compared to DHA alone or DHA+EPA mixtures (109). Thus, EPA and DHA have overlapping and divergent effects on gene expression (110), membrane structure (111), lipogenesis (85), and cellular metabolism in subjects with chronic inflammation (112). As a result, objective biomarkers of n3-LCPUFA intake are urgently needed to measure these conditionally essential FAs during the lifespan as they are not reliably quantified by questionnaires given the variability in their amount, quality and composition in dietary fats (113).
To date, a major challenge in using the O3I as a risk assessment tool in clinical medicine is the variety of analytical methods (e.g., specimen type, extraction procedure, fractionation etc.) used for measuring n3-LCPUFAs from different circulating lipid pools, including erythrocytes, plasma total lipids, plasma PL fraction, and whole blood (114,115). Although the gold standard for O3I determination remains GC analysis of FAMEs from the PL fraction of erythrocytes isolated after thin-layer chromatography, this procedure is both time consuming and less amenable to high throughput screening (75-77). Also, the total number of reported fatty acids (up to 50) can vary widely between methods, which complicates standardization and data comparisons when reporting the sum of EPA and DHA as their wt % (103). Alternatively, 1H-NMR may enable the reliable estimation of O3I status in large-scale prospective studies based on the analysis of DHA % and non-DHA % plasma lipoproteins with a good mutual agreement to GC results (116). However, neither GC or NMR methods directly resolve and quantify specific intact lipid species in small volumes of blood specimens that are best achieved when using chromatographic, ion mobility or electrophoretic separations coupled to high resolution MS (117). Herein, a high throughput lipidomic platform based on MSI-NACE-MS was applied under two configurations that takes advantage of serial injection of seven serum/plasma extracts in a single analytical run as shown in example 1 (88,89). MSI-NACE-MS allows for unique data workflows by encoding mass spectral information temporally within a separation when performing untargeted lipidomics. For instance, this approach was used to reliably authenticate and identify lipid features that increased following high-dose FO intake in a pooled sub-group analysis, which was subsequently validated in two randomized placebo-controlled trials, including EPA or DHA only supplementation. Although a two-stage FMOC/MTT derivatization procedure is required to generate cationic methylated PCs from serum/plasma ether extracts prior to MSI-NACE-MS analyses, this is far less hazardous than using diazomethane previously reported to improve the chromatographic performance, as well as enhance the selectivity and sensitivity for glycerophospholipid and sphingolipid analyses by LC-MS/MS (98,118). In general, MSI-NACE-MS offers better selectivity than HILIC-MS methods since polar/ionic lipids are resolved based on differences not only in their polar head group, but also bond linkage and total acyl chain length that impact their apparent electrophoretic mobility as described in example 1. However, type-II isobaric interferences may occur if not verified or corrected for in complex biological samples due to co-migration of PLs having differences in the number of double bonds (
Recently, Dawzynski et al. (120) reported that dietary polyunsaturated fatty acids predominately increased several DHA-containing plasma phosphatidylethanolamines (PEs) and plasmalogens following consumption of algal oil as a vegetarian marine source of n3-LCPUFAs in a small number of participants. In contrast, it was found that most circulating classes of ionic lipids measured by MSI-NACE-MS, including omega-3 FA containing PEs (e.g., PE 38:5, PE 38:6), LPEs (LPE 20:5, LPE 22:6), PIs (e.g., PI 40:6, PI 40:7) and LPCs (e.g., LPC 20:5, LPC 22:6) did not exhibit increases following high-dose FO supplementation with the exception of EPA and DHA as their NEFAs, but not DPA (
Among young, normal weight and otherwise healthy Canadian adults recruited in the placebo-controlled EPA and DHA-specific supplementation trial, their average O3I at baseline/placebo was (3.50±0.68%) with most participants (74%) classified as having an 031<4% (
Overall, it was demonstrated that serum concentrations for PC 36:5 and PC 38:6 had a better correlation with greater sensitivity to detect changes in O3I than the sum of DHA and EPA as their NEFAs (
In summary, the impact of high-dose n3-LCPUFA supplementation using FO, EPA and DHA specific formulations, was explored on global changes in the blood lipidome profiles of healthy young adults. An accelerated data workflow was first applied when using MSI-NACE-MS to identify putative circulating lipid biomarkers associated with high-dose FO intake in a pooled sub-group analysis subsequently validated in two independent placebo-controlled trials. The sum of only two circulating PCs, namely PC 16:0_20:5 and PC 16:0_22:6 in serum or plasma, provided the strongest correlation to the O3I that reflects local changes in erythrocyte membrane composition and cellular function after a minimum of 28 days of supplementation. However, PC 16:0_20:5 was more sensitive to omega-3 FA supplementation than PC 16:0_22:6 despite DHA intake generating greater changes in the O3I from baseline. Although MSI-NACE-MS was used for the discovery of circulating biomarkers of the O3I, other lipidomic platforms can also be used for their routine screening in small volumes of blood, including ion mobility-MS/MS and LC-MS/MS. The potential for non-invasive assessment of the O3I and its physiological effects following EPA and/or DHA supplementation in urine specimens may allow for more convenient population screening. Future work will further validate these findings in a larger prospective cohort since circulating lipid pools of EPA and DHA are modifiable dietary risk factors correlated with longevity and vascular health. This work is critical to guide evidence-based dietary and lifestyle interventions for optimal health outcomes on an individual level.
While the present disclosure has been described with reference to examples, it is to be understood that the scope of the claims should not be limited by the embodiments set forth in the examples, but should be given the broadest interpretation consistent with the description as a whole.
All publications, patents and patent applications are herein incorporated by reference in their entirety to the same extent as if each individual publication, patent or patent application was specifically and individually indicated to be incorporated by reference in its entirety. Where a term in the present disclosure is found to be defined differently in a document incorporated herein by reference, the definition provided herein is to serve as the definition for the term.
1 Bowden et al. J. Lipid Res. 2017 58: 2275-2288.
1Annotated lipid species/isobars from NIST SRM-1950 consistently measured by various LC-MS methods in an inter-laboratory lipidomics harmonization study by Bowden et al.15
2Reported consensus plasma phospholipid concentrations determined by a median of the means from at least 5 different labs having an overall COV < 40%.
3Relative response factors for each plasma phospholipid species following a serial dilution of NIST SRM-1950 to derive a linear calibration curve by MSI-NACE-MS with a minimum of 4 concentration levels (except for PC 30:0).
aSerum lipid extracts were analyzed by MSI-NACE-MS following methylation under positive ion mode (PCs), or underivatized under negative ion mode conditions (FAs, LPCs, PEs, LPEs, PIs). Top-ranked PCs (*) were also replicated in negative ion mode.
bAverage fold-change in ion response for serum lipid following FO supplementation to baseline in pooled samples.
cStatistical significance of pooled serum lipid increase following FO supplementation using paired student's t-test.
aAll PCs are derivatized as their cationic phosphomethylesters to improve separation resolution and ionization responses in MSI-NACE-MS under positive ion mode detection.
bPC 36:5 = PC (16:0_20:5), PC 38:6 = PC (16:0_22:6).
cPC 38:5 was subsequently determined to be comprised of two unresolved lipid species, namely PC 16:0_22:5 and PC 18:1_20:4.
aReported values are mean ± standard deviation
bp-values calculated with Student's t-test after confirming normality using Shapiro-Wilk test (p > 0.05)
cp-values calculated with Mann-Whitney U test after confirming non-normality using Shapiro-Wilk test (p < 0.05)
This application claims benefit of U.S. Provisional Patent Application Ser. No. 63/604,948 filed Dec. 1, 2023, and U.S. Provisional Patent Application Ser. No. 63/604,953 filed Dec. 1, 2023, both of which are incorporated herein by reference in their entirety.
| Number | Date | Country | |
|---|---|---|---|
| 63604948 | Dec 2023 | US | |
| 63604953 | Dec 2023 | US |
