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Study designs and populations DIVAS trial

Lipidomics analysis was performed in a subset of participants (n=113 of 195) from the DIVAS trial, a 16-week, single-blind randomized controled parallel trial (registered at http://www.clinicaltrials.gov under accession number NCT01478958). The DIVAS trial was conducted according to the guidelines of the Declaration of Helsinki, and favorable ethical opinion for conduct was given by the West Berkshire Local Research Ethics Committee (09/H0505/56) and the University of Reading Research Ethics Committee (09/40). All individuals provided written informed consent before participating. This study recruited men and women aged between 21 and 60 years and with estimated moderate CVD risk who were randomized to one of three isoenergetic diets: rich in SFAs, rich in MUFAs or rich in mixed UFAs including both MUFAs and omega-6 PUFAs. The target compositions (percent total energy of total fat:SFA:MUFA:PUFA) were 36:17:11:4 for the SFA-rich diet (n=38), 36:9:19:4 for the MUFA-rich diet (n=39) and 36:9:13:10 for the mixed UFA-rich diet (n=36). We collapsed the MUFA-rich and mixed UFA-rich diets into one UFA-rich diet arm for the generation of the MLS.

In the DIVAS dietary intervention trial, all participants diets were isoenergetic and provided 36% of total energy (percent total energy) from fats. Nonfat macronutrient intake and sources were consistent between the intervention and control diets. However, different spreads, oils, dairy products and snacks were used to modify the diets SFA:UFA ratio. The control diet was high in saturated fat (SFA-rich diet; 17% of total energy from SFAs and 15% of total energy from UFAs; n=38 with lipidomics data). In the intervention diet, 8% of total energy from SFAs was substituted for 8% of total energy from UFAs (UFA-rich diet; 9% of total energy from SFAs and 23% of total energy from UFAs; n=75 with lipidomics data). The analysis of 4-day weighed diet diaries indicated successful implementation of these dietary targets over the intervention period (Fig. 2a)29,35. The SFA:MUFA:omega-6-PUFA content in percent total energy in the control group was 17:11:4 and was either 9:19:4 or 9:13:10 in the intervention group arms with different MUFA:PUFA ratios. The omega-3-PUFA content was standardized across all diet groups. Extensive sensitivity analyses revealed that our analysis workflow yielded highly consistent results in the two intervention arms. Therefore, we present comparisons between the control group (high SFA intake) and a pooled intervention group (high UFA intake). We collapsed the MUFA-rich and mixed UFA-rich diet into one UFA-rich diet arm to generate the MLS.

All participants were nonsmokers; were not pregnant or lactating; had normal blood biochemistry and liver and kidney function; did not take dietary supplements or medication for hypertension, raised lipids or inflammatory disorders; had no prior diagnosis of MI, stroke or diabetes; did not consume excessive amounts of alcohol (males: less than 21U per week; females: less than 14U per week) and performed fewer than three 30-min sessions of aerobic exercise per week. The trial was single blinded, and randomization was conducted by a study researcher using minimization stratified for sex, age, BMI and estimated CVD risk. The participants were unaware of the assigned intervention diet and were asked to replace habitually consumed sources of exchangeable fats with study foods (spreads, oils, dairy products and commercially available snacks) of specific fatty acid composition provided free of charge.

Dietary guidance was provided at baseline and throughout the study via 1:1 verbal and written instructions. Compliance was monitored through weighed 4-day diet diaries (weeks 0, 8 and 16), records of study food intake and plasma phospholipid fatty acids as short-term biomarkers of intake (weeks 0 and 16). Observed fatty acid intake compositions were largely in line with the defined target fatty acid compositions35. Body weight, which was to remain constant, was monitored every 4 weeks, and changes were addressed with advice to the participants to adapt study food or carbohydrate consumption and/or activity levels. Fasting blood samples were taken at baseline and after 16 weeks at a similar time of day, and blood fractions were immediately separated and stored at 80C.

The EPIC-Potsdam cohort study is a prospective cohort study that recruited 27,548 participants (16,644 women and 10,904 men of primarily Middle European ancestry, age range: 3565 years) from the general population of Potsdam, Germany, and the surrounding geographical area from 1994 to 1998. Follow-up occurred every 23 years by mailed questionnaires and, if necessary, by telephone. Response rates ranged between 90% and 96% per follow-up round. The study protocol was approved by the ethics committee of the Medical Society of the State of Brandenburg, Germany, and all participants provided a statement of written informed consent before enrollment.

Incident CVD was defined as incidence of primary nonfatal and fatal MI and stroke (International Statistical Classification of Diseases and Related Health Problems (ICD)-10 codes: I21 for acute MI, I63.0 to I63.9 for ischemic stroke, I61.0 to I61.9 for intracerebral hemorrhage, I60.0 to I60.9 for subarachnoid hemorrhage and I64.0 to I64.9 for unspecified stroke). Incidence of CVD was captured by participants self-reports or based on information from the death certificates, which were validated by contacting the treating physicians. Inquired information included ICD-10 code, date of occurrence and further information on symptoms and diagnosis criteria. For MI, diagnostic criteria included clinical symptoms, electrocardiograms, cardiac enzymes and known coronary heart disease. For stroke, diagnosis was based on anamnesis, clinical symptoms, computed tomography/magnetic resonance tomography, angiogram, lumbar puncture, echocardiogram, Doppler and electrocardiogram plus imaging techniques if available. Participants with silent cardiovascular events that had not been documented within 28days after occurrence were excluded as nonverifiable cases from all analyses.

Information on incidence of T2D was systematically acquired through self-report of a diagnosis, T2D-relevant medication or dietary treatment due to T2D diagnosis during follow-up. Additionally, death certificates and information from tumor centers, physicians or clinics that provided assessments for other diagnoses were screened for indication of incident T2D. For participants who were classified as potential cases based on that information, a standard inquiry form was sent to the treating physician. Only physician-verified cases with a diagnosis of T2D (ICD-10 code E11) and a diagnosis date after the baseline examination were considered confirmed incident cases of T2D.

Nested casecohorts were constructed for efficient study of molecular phenotypes. From all participants who provided blood at baseline (n=26,437), a random sample (subcohort, n=1,262) was drawn, which served as a common reference population for both endpoints. For each endpoint, all incident cases that occurred in the full cohort until a specified censoring date were included in the analysis. After excluding prevalent cases of the respective outcomes, the analytical sample for T2D comprised 1,886 participants, including 775 incident cases (26 cases in the subcohort), and the analytical sample for CVD comprised 1,671 participants, including 551 incident cases (28 cases in the subcohort). Follow-up was defined as the time between enrollment and study exit determined by diagnosis of the respective disease, death, dropout or final censoring date, whichever came first. Endpoint-specific censoring dates were 30 November 2006 for stroke and MI and 31 August 2005 for T2D.

Anthropometric and blood pressure measurements were conducted according to a standardized protocol65,66. Information on lifestyle and education was obtained using computer-assisted personal interviews. These included information on recreational physical activity, smoking status, average alcohol intake and educational attainment. Participants were categorized as hypertensive at study baseline if they had a systolic blood pressure of 140mmHg, diastolic blood pressure of 90mmHg, reported prior diagnosis of hypertension or current antihypertensive medication use. At baseline, trained study personnel obtained 30ml of peripheral venous blood from each participant. Blood was partitioned into serum, plasma (with 10% of total volume citrate) and blood cells and was subsequently separately stored in tanks of liquid nitrogen at 196C or in deep freezers at 80C until the time of analysis. Plasma samples, from which aliquots were drawn for the lipidomics measurements in 2016, were never or only once thawed and refrozen during storage (93 samples were defrosted and refrozen once for aliquoting for unrelated analysis).

Plasma concentrations of standard blood lipids (total cholesterol, HDL-C, triglycerides, HbA1c, glucose and hsCRP) were measured at the Department of Internal Medicine, University of Tbingen, with an automatic ADVIA 1650 analyzer (Siemens Medical Solutions) in 2007. All biomarker measurements conducted in plasma, including the lipidomics measurements (detailed below), were corrected for the dilution introduced by citrate volume to improve comparability with concentrations measured in EDTA-plasma reported in the literature. Laboratory measurements were conducted by experienced technical personnel following the manufacturers instructions. Single imputation based on linear regression was used to impute missing covariate information (participants with missing data for: waist circumference, n=2; BMI, n=12; standard blood lipids (triglycerides, HDL-C and triglycerides), n=82; and blood pressure, n=148).

The NHS recruited 121,701 female nurses aged 3055 years in 1976 (ref. 67). A subset of 32,826 nurses provided blood samples in 1989 or 1990, of whom 18,743 provided a second blood sample in 2000 or 2001. The NHSII cohort was established in 1989 and recruited 116,429 female nurses aged 2542 years. In NHSII, blood samples from 29,611 participants were collected between 1996 and 1999. The standardized blood collection procedure is described elsewhere37. Participants reported their usual intake of a standard portion of each item in the FFQ (frequency ranging from never to more than six times per day) during the past year every 4 years. The reproducibility and validity of the FFQ has been extensively documented68,69,70. The NHSs were approved by the Human Research Committee at the Brigham and Womens Hospital, Boston, MA, and participants provided written informed consent.

We computed the intake of individual nutrients by multiplying the frequency of consumption of each food by the nutrient content of the specified portion based on food composition data from the US Department of Agriculture and data from manufacturers. Intake of carbohydrate, fat and protein was expressed as nutrient densities (that is, percent energy)71. In a validation study comparing energy-adjusted macronutrient intake assessed by the FFQ with four 1-week diet records, the Pearson correlation coefficients were 0.61 for total carbohydrates, 0.52 for total protein and 0.54 for total fat70.

Participants who reported a stroke were asked for permission to review their medical records. For both nonfatal and fatal strokes, available medical records related to the clinical event, such as imaging and autopsy reports, were reviewed by physicians who were blind to participant risk factor status. Strokes were defined according to the National Survey of Stroke criteria and were classified as ischemic or hemorrhagic72,73. The ischemic stroke lipidomics casecontrol study in the NHS/NHSII cohorts used in our analyses included 968 participants with lipidomics data to construct the rMLS (484 casecontrol pairs). Matching factors included age, fasting, smoking status, race, ethnicity and season of blood collection.

In NHS/NHSII cohorts, T2D incidence was detected based on self-reported diagnosis and was confirmed by a validated supplementary questionnaire74. Before 1998, confirmation of T2D incidence relied on the National Diabetes Data Group criteria and from 1998 onward relied on the American Diabetes Association diagnostic criteria. Validation studies in the NHS have demonstrated the validity of the supplementary questionnaires to adjudicate T2D diagnosis, showing that more than 97% of participants with self-reported T2D detected by questionnaires were reconfirmed through medical record review by endocrinologists blinded to questionnaire information74,75.

We also designed a 1:1-matched nested casecontrol study for lipidomics and T2D. Matching factors were age, race, ethnicity and season of blood collection. The T2D casecontrol study in NHS included 1,456 participants (728 matched casecontrol pairs) with baseline lipidomics data to construct the rMLS. A subset of casecontrol pairs had repeated lipidomics data approximately 10 years apart to construct the rMLS based on fasting (8h) blood samples from both times (1989/1990 and 2000/2001). In the repeated blood sampling study, all participants remained diabetes free until after the second blood collection, and all incident T2D cases occurred between 2002 and 2008.

The study protocols were approved by the Institutional Review Boards of Brigham and Womens Hospital and Harvard T.H. Chan School of Public Health. Participants completion of questionnaires was considered as implied consent.

The PREDIMED study was a multicenter dietary intervention trial with 7,447 participants in three intervention arms and demonstrated cardiometabolic risk reduction by a Mediterranean diet intervention (www.predimed.es; ISRCTN registry: ISRCTN35739639)33,76. The PREDIMED trial received ethical approval from the Institutional Review Board of the Hospital Clinic in Barcelona, Spain, 16 July 2002. The PREDIMED trial inclusion criteria were either prevalence of T2D or prevalence of three or more major cardiovascular risk factors (smoking, dyslipidemia, hypertension and adiposity). Besides the low-fat diet control group, the Mediterranean diet intervention included two arms (one particularly high in extra virgin olive oil and the other particularly high in tree nut intake) that we pooled into one Mediterranean diet group for our primary analyses. Preintervention blood samples were taken after an overnight fast by trained study personnel according to a standard protocol and fractioned, and the EDTA-plasma was stored at 80C in deep freezers.

The PREDIMED T2D casecohort study with available lipidomics data comprised 694 randomly selected participants (approximately 20% of participants) who fulfilled inclusion criteria, that is, no prevalent T2D at recruitment and available plasma samples and all incident T2D cases during a median of 3.8 years of intervention (n=251; per casecohort design 53 incident T2D cases were randomly included in the subcohort). The analytical sample was restricted to participants with complete data on lipid metabolites in the rMLS (n=678, including 211 participants with incident T2D). Of those, 468 participants (including 148 participants with subsequent T2D incidence) had additional plasma samples and lipidomics profiles from 1 year after recruitment.

The PREDIMED CVD casecohort study with lipidomics data comprised 791 randomly selected participants with available plasma samples at recruitment (approximately 10% of the eligible participants) and all incident CVD cases during a median of 3.8 years of intervention (n=231). After excluding participants with missing rMLS lipid metabolite values, the analytical sample comprised 871 participants, including 215 participants with incident CVD. Of those, 736 participants (including 136 participants with subsequent CVD incidence) had additional plasma samples and lipidomics profiles from 1 year after recruitment. The study protocols were approved by the Institutional Review Boards at all study locations (PREDIMED) and the Harvard T.H. Chan School of Public Health (PREDIMED casecontrol subproject). All participants gave written informed consent.

The LIPOGAIN-2 study was a 12-week, double-blind, parallel-group randomized trial focusing on overweight individuals. In this manuscript, only the first phase of the trial, consisting of an 8-week overfeeding period, was used.

Participants aged between 20 and 55 years with a BMI ranging from 25 to 32kgm2 were eligible. Exclusion criteria were diabetes (fasting glucose of >7mM on two occasions) or liver disease, pregnancy, lactation, alcohol abuse, claustrophobia, abnormal clinical chemistry test results, use of drugs influencing energy metabolism, use of omega-3 supplements or extreme diets, regular heavy exercise (>3h per week), intolerance to gluten, egg or milk protein and implanted metals. Participants were required to fast overnight for 10 to 12h and avoid physical exercise and alcohol for 48h before measurements were taken.

The trial took place at Uppsala University Hospital in Uppsala, Sweden, from August 2014 to June 2015. Participants were assigned to groups through a computer-generated list, which was prepared by a statistician not involved in the study, and stratified for sex, age and BMI. This study is registered on http://www.clinicaltrials.gov under the identifier NCT02211612 and was conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent before inclusion, and the study was approved by the Regional Ethical Review Board in Uppsala (Dnr 2014/186).

In total, 61 participants were randomized to receive muffins made with either refined sunflower oil, which is high in PUFAs (specifically linoleate 18:2n-6), or refined palm oil rich in SFAs (mainly palmitate 16:0) for 8 weeks. Participant body weight was monitored weekly when they visited the clinic to receive their muffins, which were prepared in large batches under controlled conditions in a metabolic kitchen at Uppsala University. These muffins, identical in composition except for the type of fat, were added to the participants regular diets to be eaten at any time of the day. Their number was adjusted weekly by plus or minus one muffin per day based on the rate of weight gain, with the goal being an average weight gain of 3% (equivalent to about 2.90.5 muffins or approximately 40g of oil per day). The muffins comprised 51% fat, 44% carbohydrates and 5% protein by energy percentage. One participant was removed due to missing sphingolipid measurements.

Lipidomics analysis was performed with Metabolons Complex Lipid Panel for the EPIC-Potsdam cohort and the DIVAS trial separately. In brief, the platform generates concentrations of molecular species and nearly complete fatty acid composition per lipid class in plasma. The lipid fraction is extracted with methanol:dichloromethane, concentrated under nitrogen and reconstituted in ammonium acetate dichloromethane:methanol (BUME extraction). Extracts are then infused into the ionization source of a Sciex SelexION-5500 QTRAP mass spectrometer operated in multiple reaction monitoring mode with positive/negative switching. Lipid classes are subsequently separated by differential mobility spectrometry. Using 1,100 multiple reaction monitorings, lipid mass and characteristic fragments are determined with the help of more than 50 isotopically labeled internal standards that are simultaneously introduced with the biological sample. Molecular species are quantified by taking the ratio of the signal intensity of each target compound to that of its assigned internal standard and multiplying by the concentration of internal standard added to the sample77.

The Complex Lipid Panel produced measurements for 14 lipid classes (cholesteryl esters, monoglycerides, ceramides, dihydroceramides, lactosylceramides, hexosylceramides, sphingomyelins, lysophosphatidylethanolamines, lysophosphatidylcholines, diglycerides, triglycerides, phosphatidylcholines, phosphatidylethanolamines and phosphatidylinositol). For phosphatidylethanolamines, species from the two subclasses phosphatidylethanolamine ether and phosphatidylethanolamine plasmalogen were detected. Measured concentrations of molecular species were used to calculate within-class fatty acid sums (summing all concentrations of molecular species containing a specific fatty acid within a lipid class). Within-class fatty acid sums are synonymous with molecular species level in lipid classes containing only one reported variable fatty acid per molecule (one-fatty-acid-containing classes: cholesteryl esters, monoglycerides, ceramides, dihydroceramides, lactosylceramides, hexosylceramides, sphingomeylins, lysophosphatidylethanolamines and lysophosphatidylcholines).

For comparability with the species-level lipidomics in the PREDIMED trial and NHS/NHS2 cohorts (see below), we further calculated the species level for those classes with more than one fatty acid per molecule (that is, diglycerides, triglycerides, phosphatidylcholines, phosphatidylethanolamines and phosphatidylinositol) by summing all species with the same total atomic mass and degree of saturation of the contained fatty acids (that is, isobaric species). We used the updated shorthand notations from the LIPIDMAPS initiative where applicable78. We only refer to the shorthand notations of fatty acids for brevity. According to the manufacturer, the median coefficient of variation of species at a 1M concentration in serum or plasma was approximately 5%. Several lipid species had higher percentages of missing values because they were likely below the lower limit of quantification. Lipid species with more than 70% missing values were excluded, while missing values in the remaining lipid species were imputed using the Quantile Regression Imputation of Left-Censored data approach from the R package imputeLCMD (https://CRAN.R-project.org/package=imputeLCMD).

At the Broad Institute, plasma polar and nonpolar lipids were identified using a Shimadzu Scientific Instrument Nexera x2 U-HPLC system, which was linked to a Thermo Fisher Scientific Exactive Plus Orbitrap mass spectrometer. Lipids were extracted from the plasma (10l) using 190l of isopropanol that had 1,2-didodecanoyl-sn-glycero-3-phosphocholine as an internal standard, supplied by Avanti Polar Lipids. After centrifugation (10min, 9,000g, room temperature), the supernatants (2l) were directly injected onto a 1002.1mm ACQUITY BEH C8 column (1.7m) from Waters. The column was flushed isocratically at a flow rate of 450lmin1 for 1min at 80% of mobile phase A (95:5:0.1 (vol/vol/vol) of 10mmoll1 ammonium acetate:methanol:acetic acid), succeeded by a linear gradient to 80% of mobile phase B (99.9:0.1 (vol/vol) methanol:acetic acid) for 2min and a linear gradient to 100% mobile phase B over 7min and finally maintained at 100% mobile phase B for 3min.

Mass spectrometry analyses were performed in positive ion mode using electrospray ionization and full scan analysis over m/z 2001,100 at a resolution of 70,000 and a data acquisition rate of 3Hz. The following other mass spectrometry parameters were used: ion spray voltage at 3.0kV, capillary and probe heater temperature at 300C, sheath gas at 50, auxiliary gas at 15 and S-lens RF level at 60. Progenesis QI software (NonLinear Dynamics) was used to process raw data for feature alignment, nontargeted signal detection and signal integration. Targeted processing of a subset of lipids was conducted using TraceFinder software (version 3.2; Thermo Fisher Scientific). Lipids were characterized by their headgroup, overall acyl carbon content and total acyl double bond content79. The Broad Institute metabolomics data in NHS/NHSII were measured in several casecontrol studies. Within each casecontrol study, lipid species with more than 70% missing values were excluded, whereas missing values in remaining lipid metabolites were imputed with half the minimal measured value. Due to the platform evolution in the NHS/NHSII cohorts, some metabolite levels were not measured in specific casecontrol studies. For calculation of the rMLS, nonmeasured values of specific metabolites in specific casecontrol studies were substituted with the median of all measured values across the whole dataset (only applicable to the rMLS diet substitution models in the NHS/NHSII cohorts).

Sphingolipids from serum were extracted using butanolmethanol methods80,81. Sphingolipids were detected and quantified using ultraperformance liquid chromatography/tandem mass spectrometry, as previously described82.

All lipidomics variables in all study samples were log transformed.

We assessed the difference in postintervention within-class fatty acid sum concentrations between the SFA-rich and UFA-rich diets via linear regression models with trial arm coded as an indicator variable (SFA-rich diet as a reference) and adjusted for respective baseline concentrations in addition to age, BMI and sex. All lipids that were statistically significantly different between the diets after controlling for an FDR83 at 5% were used for calculating the MLS (Supplementary Tables 10 and 11). Using the estimated intervention effects as weights, we calculated the MLS in the DIVAS trial and, again, used linear regression to estimate baseline-adjusted differences in MLS between the diets. For the analyses of sphingolipids, sphingolipid score and apolipoprotein B in the LIPOGAIN-2 trial, we used the same approach as in the DIVAS trial. The models were similarly adjusted for age, sex and BMI.

Using the estimated intervention effects as weights, we calculated the MLS in the EPIC-Potsdam cohort and divided the score by the observed diet effect on the MLS in the DIVAS trial so that one unit increase in the MLS corresponds to the magnitude of the DIVAS diet intervention effect. Like the above approach, we estimated the diet effect on other risk biomarkers (HbA1c, fasting glucose, total triglycerides, HDL-C, non-HDL-C and hsCRP) and applied the respective observed effect as a scale for the hypothetical DIVAS intervention effect in the EPIC-Potsdam cohort.

We assessed the association between MLS and incident CVD and T2D with Cox proportional hazards models. The casecohort design was accounted for by assigning weights as proposed by Prentice. Age was the underlying time variable, with entry time as age at baseline and exit time as age at event or censoring. The fully adjusted model included age (years), sex, waist circumference (cm), height (cm), leisure-time physical activity (average h per week), highest achieved education level (three categories: primary school, secondary school/high school and college/higher education degree), fasting status at blood draw (three categories: overnight fast, only drink and unfasted), total energy intake (gday1), blood pressure (systolic and diastolic; mmHg), smoking status (four categories: never, former, current smoker (<20Uday1) and current smoker (20Uday1)), alcohol intake (six sex-specific categories: none, low, moderately low, moderately high, high and very high), antihypertensive medication (yes/no), lipid-lowering medication (yes/no) and acetylsalicylic acid medication (yes/no) as covariates. Models for CVD were additionally adjusted for prevalent T2D. To check if the presentation of stratified results was warranted, we tested the potential for effect measure modification by sex by including MLSsex interaction terms into the multivariable-adjusted model.

The rMLS was constructed with the same weights as were used in the EPIC-Potsdam cohort; however, those lipids that were not available in the Broad Institute lipidomics data in the NHS/NHSII cohorts and PREDIMED trial were either skipped or, where possible, imputed using regression weights from the EPIC-Potsdam cohort. In detail, the Broad Institute lipidomics datasets available in the NHS/NHSII cohorts and the PREDIMED trial offer species-level lipidomics in those lipid classes that contain more than one fatty acid residue per molecule, whereas the platform used in the EPIC-Potsdam cohort and the DIVAS trial generated resolution down to the molecular species level, indicating all fatty acid residues per molecule (with the exception of triglycerides). We calculated species levels in the EPIC-Potsdam cohort and used these to predict within-class fatty acid sums. These lipid species-specific weights were then applied to generate a predicted value of the missing lipid variable in the PREDIMED trial and the NHS/NHSII cohorts, where possible.

Diet and lipidomics profiles were available from 10,894 women in the NHS (n=7,479) and NHSII (n=3,415) cohorts. For macronutrient substitution modeling, we used the average of the macronutrient intakes derived from the two FFQs closest to the blood collection that was used in the dietary substitution analyses (NHS cohort: 1986 and 1990; NHSII cohort: 1995 and 1999). We then included all dietary macronutrient variables (as percent total energy) except for saturated fat in a linear model with the variance standardized MLS as outcome, adjusting for total energy intake excluding alcohol (kcalday1), alcohol intake (gday1), BMI (kgm2), age (years) and diet quality (AHEI without alcohol points). Macronutrient intake was scaled to 8% of total energy. Therefore, effect estimates from this linear model can be interpreted as the association of substituting 8% of total energy from SFAs with 8% of total energy from other macronutrients. Conditional logistic regression models were used to assess the associations of the rMLS with the risk of developing stroke and T2D.

We further assessed the correlation of the rMLS with established diet quality indices, including LCDs84, the aMed85 and the AHEI86. For the general LCD, participants were divided into 11 strata based on percentage of energy from each total fat, protein and carbohydrates. Points were assigned descending from 10 for the highest stratum in fat and protein to 0 for the lowest. For carbohydrates, scoring was reversed, with the lowest intake receiving 10 points and the highest receiving 0. We applied the same methodology to compute two additional LCD scores: one animal based and one vegetable based. The animal-based LCD score was based on the percentage of energy derived from carbohydrates, animal protein and animal fat. Conversely, the vegetable-based LCD score was calculated from the energy percentages from carbohydrates, vegetable protein and vegetable fat84.

The aMed score, adapted from Trichopoulou et al.87, includes vegetables (excluding potatoes), fruits, nuts, whole grains, legumes, fish and the ratio of monounsaturated to saturated fats along with red and processed meats and alcohol. Participants scoring above the median intake in these categories received 1 point, except for red and processed meats where scoring below the median earned a point; all others received 0. Alcohol intake scoring awarded 1 point for daily consumption between 5 and 15g. The aMed score ranges from 0 to 9, with higher scores indicating greater adherence to the Mediterranean diet85.

The AHEI was developed after a comprehensive literature review and consultations with nutrition researchers to identify dietary factors consistently linked with a reduced risk of chronic diseases in clinical and epidemiological research. Beneficial AHEI components include vegetables, fruits, whole grains, nuts, legumes, long-chain omega-3 PUFAs and total PUFAs, whereas adverse components comprise sugar-sweetened beverages, red and processed meats, trans-fats and sodium. Moderate alcohol consumption scores highest, with high consumption scoring lowest. Each AHEI component is rated from 0 (worst) to 10 (best), resulting in a total score ranging from 0 (no adherence) to 110 (perfect adherence)86.

Risk associations with stroke and T2D in the nested 1:1-matched casecontrol studies were assessed with conditional logistic regressions adjusted for age, BMI, alcohol intake, diet quality and smoking. Analyses on 10-year change in MLS were further adjusted for status after 10 years of these variables (except age).

We used Prentice-weighted Cox proportional hazards regression to assess the association between the rMLS and the risk of incident disease endpoints in PREDIMED. The interaction analyses were performed in the subsamples with two lipidomics profiles (preintervention and 1-year into the intervention). The interaction model contained a three-way interaction term between Mediterranean diet intervention and the repeated rMLS measurements (preintervention rMLSMediterranean diet intervention1-year intervention rMLS) along with the main effect terms and were adjusted for age and sex. The results of the interaction analyses informed the subsequent stratified analyses according to the Mediterranean diet intervention. The Cox models in the intervention strata were adjusted for age, sex and preintervention BMI.

We estimated a network model of conditional dependencies, where edges represent covariance between two lipids that could not be explained by adjustment for any subset of other lipids. To this end, we applied an order-independent implementation of the causal structure learning PC algorithm88. The resulting network graphically encoded the family of causal models that could have generated the observed conditional independence structure, that is, the skeleton of the data-generating directed acyclic graph. Within this network, we identified clusters of lipids using the Louvain modularity detection algorithm. The Louvain method is a fast heuristic algorithm for detecting communities in large networks by optimizing modularity. It iteratively merges nodes into communities to maximize within-community links compared to between-community links38.

We then calculated cluster-specific lipid scores using the same weights as for the full MLS and associated the resulting scores with risk of cardiometabolic diseases in the same way as the full MLS. We furthermore applied the NetCoupler algorithm (netcoupler.github.io/NetCoupler/) to identify those lipiddisease connections that could not be attributed to the influence of related MLS lipids. The algorithm uses the conditional independence network to detect links between individual lipids and disease incidence that could not be explained by confounding influences through other lipids. By definition, at least one subset of direct neighbors is sufficient to block confounding from the whole network. However, sufficient adjustment sets cannot be unambiguously read from the graph because the edges are not directed. Therefore, the NetCoupler algorithm iterates for each lipid through adjustment for all possible combinations of direct network neighbors. A lipid is then only classified as a direct effector if the association with disease incidence is robust across all these submodels39,40.

All analyses were performed using R (version 4.3.0). Further information on used R packages is reported in Supplementary Table 13.

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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Following a Mediterranean diet and taking omega-3 supplements may help reduce acne severity in patients with mild to moderate cases, according to new research published in the Journal of Cosmetic Dermatology.1 The study also showed that increased omega-3 levels led to improved clinical appearance and quality of life.

Diets high in processed foods and dairy products are known to increase the risk for acne, but there has been little research on how dietary interventions could help alleviate the severity of symptoms.

In the pursuit of skin health, and particularly in a juvenile patient cohort, such as acne vulgaris, clinicians and patients are more than ever seeking treatment approaches that go beyond the conventional options of topical and systemic prescription medications, the authors wrote. As the understanding of the interplay between so-called exposome factors and skin health deepens, there is increasing evidence pointing to the pivotal role of nutrition in shaping dermatoses.

Investigators from the University Hospital at Ludwig Maximilian University of Munich conducted a study to assess EPA and DHA levels in patients with acne, as well as to examine the effect of dietary interventions and supplementation on clinical severity. The single-center intervention study occurred over a 16 week period .

The study cohort included 60 patients who were not currently taking a prescription medication, of which 23 had acne comedonica and 37 had acne papulopustulosa. For the study, patients adhered to a Mediterranean diet that focused on plants and unprocessed, seasonal, nutrient-dense ingredients. Patients were encouraged to make homemade meals and limit ultra-processed foods, dairy products, and meat.

Study participants also took 2 different doses of oral algae-derived omega-3 supplements throughout the study period: 600mg of DHA and 300mg of EPA for weeks 1 through 8; and 800mg of DHA and 400mg of EPA for weeks 8 through 16. Patients were evaluated at 4 follow-up visits: baseline, week 6, week 12, and week 16.

At baseline, 98.3% of patients had an EPA/DHA deficit. Investigators found that mean HS-omega 3 index scores rose from 4.9% at the first follow-up visit to 8.3% at the fourth follow-up visit. Patients with acne comedonica had higher indices at the fourth follow-up visit compared to patients with acne papulopustulosa. There were also objective improvements in inflammatory and non-inflammatory lesions.

Additionally, although self-reported appearance in 4 patients worsened, patients overall quality of life improved. This was particularly seen in patients with acne papulopustulosa. No adverse events were reported during the study period.

Study limitations include an inability to provide each patient with meals and supplements due to time constraints, potential recall bias due to self-reported adherence to dietary recommendations, and a predominance of female participants, though the authors noted that this may not have significantly impacted the studys results.

Lifestyle interventions, including dietary recommendations, should not be considered in opposition to prescription medications, but rather as a valuable adjunct to any modern acne treatment plan, Anne Guertler, MD, a corresponding author on the study, said in a release.2 Future studies should build on the foundation laid by our current findings in a randomized, placebo-controlled design to improve dietary recommendations for acne patients.

References

[This article was originally published by our sister publication, Drug Topics.]

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Children can reap the benefits of the Mediterranean diet just as well as adults, according to a new meta-analysis.

Researchers from the University of the Americas, Ecuador, reviewed nine previously published clinical trials which assessed how Mediterranean diets can affect cardiovascular health among children and adolescents.

The authors found that just eight weeks of Mediterranean-style nutrition was associated with a significant reduction in blood pressure and total cholesterol.

The results were published in JAMA Network Open.

Prior to the work of the University of the Americas researchers, there were several hundred published studies on the effects of the Mediterranean diets on the cardiometabolic health of children. There was no known meta-analysis of this literature, however.

To undertake this mammoth review, the researchers sifted through the available studies to find nine randomized controlled clinical trials. These robust studies accounted for 577 participants (59.6% girls, 40.4% boys) with an average age of 11 years. Six of the trials focused on children who were overweight; one trial enrolled children with prediabetes; the other two studies involved apparently healthy children.

After assessing the results of all nine trials, the researchers found that, compared to the control groups which didnt consume a Mediterranean diet, the children who did try the famed European regimen experienced a significant reduction in systolic blood pressure, blood lipids and total cholesterol. The Med-dieting children also experienced an increase in high-density lipoproteins, which are often known as good cholesterol.

The researchers believe these changes may be explained by the low levels of saturated fats and higher levels of mono- and poly-unsaturated fats (from olive oil, nuts, fish, etc.) typically found in Mediterranean meals.

The diets absence of ultra-processed foods the class of artificially altered food thought tocontribute to the rise of obesity, cardiovascular disease and cancers seen in the Western world may also have contributed to the health benefits seen in the children.

While the authors do acknowledge the caveats of their analysis mainly, the small number of trials involved they nonetheless conclude that Mediterranean diet-based interventions could be vital in curbing cases of atherosclerosis and cardiovascular diseases that some children would otherwise have gone on to develop in later life. Mediterranean diet-based interventions in schools and hospitals could, they say, be a valuable tool for preventing these illnesses and optimizing cardiometabolic health in the younger population.

Reference: Lpez-Gil JF,Garca-Hermoso A,Martnez-Gonzlez M,Rodrguez-Artalejo F. Mediterranean Diet and Cardiometabolic Biomarkers in Children and Adolescents:A Systematic Review and Meta-Analysis.JAMA Netw Open.2024. doi:10.1001/jamanetworkopen.2024.21976

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Wanda Hammock experienced high cholesterol and knew she needed to change her eating habits. She switched to a plant-based diet after facing a diabetes diagnosis.

CASWELL COUNTY, N.C. We all know about the importance of maintaining a healthy diet.

It helps boost your energy, supports weight loss, and helps protect you against many diseases.

One type of diet, Cone Health providers say can be beneficial, is a plant-based diet.

A Caswell County woman knows about the diet all too well. Wanda Hammock experienced high cholesterol and knew she needed to change her eating habits.

She switched to a plant-based diet in 2022 after facing a diabetes diagnosis.

She says the switch to eating healthy happened gradually.

"It was difficult at first because it was changing my habit. I am a busy person so I was eating on the run a lot. I was eating a lot of convenience foods, hitting the drive-thru - that sort of thing. I had to change my habits to start doing more meal prep for when I would eat and where I would eat," Hammock said.

Hammock said she began to eat more salads and beans by eliminating fast foods and processed foods.

Because of the diet, her health has improved.

She is much more happy and has lost over 70 pounds in 13 months.

"My lab work is phenomenal at this point - when I started this," Hammock said.

Dr. Gebre Nida, a diabetologist with Cone Health, works with more than 200 patients benefiting from the diet.

He says 93% of people in the world are medically unhealthy and that the top five medical conditions including diabetes benefit from a whole food plant-based diet.

"Keep foods simple from the ground or from the farmer as much as possible, instead of from the factories," Nida said.

He said the diet can help your body fight inflammation, giving you a good medical advantage.

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Hello, health enthusiasts! My name is Kaitlin, and Im here to provide you with some wellness tips to help you live your best life. The holiday week may have come and gone, but summer is still in high gear and so is extreme heat. Before you pick out your outfit, check out our guide on how to dress on hot days. Plus, read up on how to have the best July, from celebrating the Summer Olympics to getting your eyes checked. (It is Healthy Vision Month, after all.)

As always, check the weather in your area and your horoscope, if youre so inclined. Then read up on the below health and wellness tips to keep your summer the best one yet.

A new study found that older women who experienced more gratitude had a 9% lower risk of death from any cause over three years. Fortunately, gratitude is an easy skill to practice for anyone. Try writing down what you're thankful for in a gratitude journal each day it will also help you become more mindful overall.

July 11 was National Polyphenol Day but you should be including polyphenols in your diet year-round. Polyphenols are natural compounds found in plants, which have the power to potentially lower cancer risk, boost brain health and reduce inflammation. Berries, dark chocolate, green tea, red wine, apples and nuts like almonds and walnuts all have polyphenols in them, so you have plenty of opportunities to enjoy these good-for-you compounds.

We know that sitting all day is bad for your health and sitting on the wrong chair all day, or in the wrong position, can cause major pain. Aim for a chair that has good lumbar support, which can help distribute your body weight more evenly and dont stress about maintaining a straight, perfect-posture position all day, which can actually lead to more pain. Instead, incorporate many micro-movements throughout your day (like crossing and uncrossing your legs, or shifting your weight) in order to stay comfortable.

Gut health is a major topic on social media but in general, experts say we may be overly concerned with the so-called healing of our digestive systems. According to experts who spoke to Womens Health, though, there are certain signs that you should get a literal gut check, like frequent bouts of diarrhea, constipation or bloating. Just make sure to consult your doctor not your FYP.

The Mediterranean diet gets plenty of praise, but you may also want to try the Atlantic diet, which is inspired by the diets of the people living in northwest Spain and Portugal. While theres plenty of overlap between the Mediterranean diet and the Atlantic diet (both love olive oil, for example!), the Atlantic diet proposes eating more seafood, dairy, lean meat and nuts, as well as carbs like potatoes and bread. (The Mediterranean diets carb of choice is pasta.)

Got acne? The Mediterranean diet might be your better bet, according to a new study, which found that the diet led to significant reductions in skin lesions for participants. Researchers think that the anti-inflammatory effects of the low-sugar, high-omega-3 diet could be the reason why.

This newly trendy food (which includes sardines, anchovies and mackerel) is shelf-stable, and comes with good-for-you nutrients like B12 and vitamin D, as well as minerals like calcium and selenium. Toss some tiny fish in your salad, or blend them into a pasta sauce for a rich umami flavor.

Theres a lot of buzz (pun intended) around vibration plates, with some people claiming that exercising on these platforms can improve bone density and increase muscle strength. Experts say theyre onto something: These plates make your muscles contract in an attempt to maintain balance, which can make your body work harder overall. Next time you see one of these shake machines at the gym, hop on and try some squats or arm circles.

Going to a party where you wont know anyone? Saba Harouni Lurie, a licensed marriage and family therapist, gives helpful tips on how to feel more comfortable striking up conversations like offering to assist the host.

A new study published in Nature Medicine found that swapping out saturated animal fats (like butter) for plant-based unsaturated fats (like olive oil, a major component of the Mediterranean diet) may lower your risk of developing conditions like cardiovascular disease and type 2 diabetes. So, next time youre looking for a simple pasta dish, go for a drizzle of EVOO instead of butter and noodles.

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Try the Atlantic diet, snack on berries and skip the butter. 9 health and wellness tips to help you have a healthy week. - Yahoo Life

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Sleep may be one of the most underrated health habits. When we dont get enough of it, it can affect everything from mood and anxiety levels to immunity and heart health. But quality sleep can feel elusive to many of us. Whether you have a sleep disorder, like sleep apnea or insomnia, or find it difficult to unplug earlier in the evening so you get enough sleep, youre not alone. Around 40% of American adults are not getting sufficient sleep, according to the Centers for Disease Control and Prevention.

Sometimes the reason for insufficient sleep is difficult to figure out. If you feel like youre doing everything rightyouve got a bedtime routine that prepares your body for sleep and you sleep in darkness, allowing your body to produce melatoninand yet, you still dont sleep well, you might have a microbiome problem. A new literature review published on July 13, 2024, in Nutrients sheds some light on this very topic. Lets see what these researchers found when they dug into 203 studies on the sleep-gut connection.

Your gut contains millions of different microorganismsboth beneficial and potentially damagingthat influence gut and overall health. These microorganisms produce metabolitessubstances that are necessary for or a result of chemical reactions in the cells. All these microorganisms and their metabolites make up your microbiomeand this includes disease-causing bacteria, as well as health-inducing types of bacteria.

According to these researchers, our microbiomes begin to form at birth when the baby picks up bacteriaincluding healthy, beneficial bacteriafrom the mothers skin and vagina, depending on whether its a vaginal or cesarean birth. By the age of 5, the foundation of gut bacteria has been laid. And while its established early on in life, the microbiome will fluctuate throughout our lives, depending on many factors including diet, sleep, stress, exercise, medications, infections and environment.

Besides building a healthy gut, these microorganisms also produce chemicals (metabolites) necessary for overall good health. One of these is serotonin, which acts as both a hormone and a neurotransmitter (neurotransmitters carry messages between nerve cells) and plays a pivotal role in your bodys circadian rhythms, cognitive function, pain perception and emotional control. Circadian rhythms are a type of biological clock and are related to sleep-wake cycles. When youre regularly operating outside of your bodys natural circadian rhythms, youre more likely to get less quality sleep. It also affects your microbiomes health.

Serotonin is a precursor of melatonin, the chemical that is necessary for sleep. In other words, you must have enough serotonin to produce melatonin. And you must have enough melatonin to get good sleep. And to have enough serotonin, you need a healthy gut.

Are you starting to see a connection here?

Gamma-aminobutyric acid, GABA for short, is another chemical that is produced in the gut. GABA plays a role in stress relief and sleep regulation. Like serotonin, you must have a healthy gut to produce enough GABA.

Then there are short-chain fatty acids (SCFAs). These are formed in the gut from fiber, polyphenols (antioxidants) and omega-3 fatty acids. According to these researchers, certain types of SCFAs can signal the brain when its time to sleep. There is evidence that people with insomnia have been shown to have a decrease in the number of these SCFAs in their gut.

SCFAs also influence the production of serotonin and GABA. You must have enough SCFAs in your gut to produce enough serotonin (which, remember, is a precursor of melatonin) and GABA, which in turn will influence your sleep.

Its important to note that all of these connections are bidirectional. For example, while these metabolitesSCFAs, serotonin, melatonin and GABAcan affect sleep, sleep also influences the production of these metabolites. And so the cycle goes.

This literature review also revealed what foods contribute to a healthy gut and which ones negatively affect the microbiome. Regular, excessive intake of saturated fats, sugar, red and processed meats, and alcohol changes the microbiome in unhealthy ways.

Foods that are high in fiber, polyphenols and unsaturated fatty acids, on the other hand, can stimulate the growth of beneficial bacteria and inhibit the growth of unhealthy bacteria, supporting a lush microbiome thats loaded with beneficial bacteria and metabolites.

These researchers also point out that the timing of eating matters, too. They found that studies suggest that eating later at night can negatively affect circadian rhythms and the microbiome. There is also evidence to suggest that eating at regular intervals helps with circadian rhythms, whereas irregular eating patterns and skipping meals can mess with the rhythmsand consequently, the microbiome.

At EatingWell we believe that all foods can fit into a healthy, balanced diet and that health is about overall patterns. This means that occasionally eating something sweet or having an old-fashioned bologna-and-cheese sandwich on white bread is probably OK in moderationprobably because it depends on each individuals health status and lifestyle. But it's important to consider your eating pattern as a whole.

Are you regularly noshing on a variety of foods that are high in fiber, antioxidants and healthy fats? This includes fruits, vegetables, nuts, seeds, whole grains and seafood. Many plant-based foods act as prebiotics, providing food for your beneficial bacteria so they can multiply and thrive.

While this study doesnt specifically mention fermented foods, we know that they also contribute to a healthy gut by adding probioticsthe beneficial bacteria in our microbiome. This includes foods like yogurt, kefir, sauerkraut and miso.

This also applies to other health habits. For example, we all go through stressful times in our lives. Its when that stress becomes chronic and habitual that it negatively influences our health. Same with sleep.

To start, examine your current patterns in the areas of eating, exercise, stress and sleep. Are your patterns contributing to health or deterring from it?

This literature review includes hundreds of studies that help connect the dots between sleep and gut health. Hormones that contribute to quality sleep are produced in the gut, so it makes sense that you need to have a healthy, thriving microbiome to produce these hormones at optimal levels. Including a variety of foods that support gut health and limiting those that dont will go a long way toward cultivating a healthy microbiome. Its important to remember that this is a bidirectional relationship. While your microbiome will influence your sleep, how much quality sleep youre getting will influence your microbiome. Other health habits also influence gut health, including diet, exercise and stress.

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According to a new study from the University of Georgia, genetics play an important role when it comes to determining if a vegetarian diet is right for you. Published by PLOS Genetics, the study was written by lead author Michael Franics, a graduate of UGAs Institute of Bioinformatics and co-authored by Kaixiong Ye of UGAs Department of Genetics and both Kenneth Westerman and Alisa Manning, of Harvard University.

For many, vegetarianism leads to health benefits like lowered cholesterol and decreased risk of heart disease and Type 2 diabetes. But for some, this specialized diet may come with a cost, the researchers said. The study examined how differences in genes influence how a person responds to nutrients and potential diet-related disease.

Fracis said it provides a strong knowledge base for improving overall health outcomes through nutrition. Francis was a vegetarian for seven years throughout his teens and 20s and, though he eats meat now, he said that it was one of the main reasons he chose to study nutrigenetics.

We are building a scientific foundation for personalized nutrition, which optimizes human health at the level of the individual, instead of one-size-fits-all dietary recommendations, Francis said in a press release.

The researchers analyzed data from over 150,000 participants, and identified 2,300 who followed strict parameters for a vegetarian diet to determine how genetics affect health benefits. They found that most vegetarians had lower cholesterol across all measures, including total cholesterol, low-density lipoprotein and high-density lipoprotein levels, which can be beneficial for heart health.

Vegetarians also had lower Vitamin D levels and higher levels of triglycerides than non-vegetarians. Vitamin D is important for bone health and immune function, and a deficiency can lead to negative health effects. Higher levels of triglycerides, which are a type of fat in the blood, can also increase risk of cardiovascular disease.

By including a genetic component to their analysis, the study found that when specific gene variants, also known as minor alleles, were present, participants saw different health outcomes. This included a variant of the gene MMAA, which relates to calcium metabolism. While most vegetarians see decreased calcium levels, which can have noteworthy negative effects, individuals with this minor allele saw increased calcium levels. This could lead to improvements in bone health and dental health, but high levels of calcium can also have negative health effects including kidney stone development or cardiovascular issues.

Others might see an impact on their hormone levels. While the majority of vegetarians see a decrease in testosterone, a smaller group with another gene variant saw increased testosterone levels. The third significant interaction, according to the study, was a gene variant related to kidney function and kidney filtration rates. The presence of this minor allele modified the effect of vegetarianism, taking it from increasing the eGFR, or estimated glomerular filtration rate, to decreasing that filtration rate.

Highlighting these differences can help individuals find the best diet for the individual needs according to Francis.

People with specific and immediate nutritional requirements related to these three traits should consider being tested for the variants we describe in this manuscript and making changes accordingly, Francis said in a press release.

Moving forward, this study can support future nutrigenetics studies and clinical trials, helping researchers better understand the impact of diet on different groups.

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UGA study reveals vegetarian diet benefits arent one-size-fits-all - Red and Black

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When artificial sweeteners entered the U.S. market in the 1950s, food manufacturers made a big claim: That they could satisfy the American sweet tooth without the negative health effects and calories of sugar.

Today, artificial sweeteners and other sugar substitutes have become ubiquitous in the food supply, showing up in a slew of products including diet sodas, sliced bread and low-sugar yogurts not to mention your morning coffee.

But questions about sugar substitutes have been swirling for decades, with scientists and public health officials suggesting they might come with certain health risks of their own.

The research on how sugar substitutes affect our bodies is preliminary, complex and sometimes contradictory.

They havent been studied as much as they should be in humans, said Dr. Dariush Mozaffarian, a cardiologist and director of the Food is Medicine Institute at Tufts University.

That leaves us with many questions about how to weigh their potential benefits and risks. Heres what we know.

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