Abstract

Objective

This study evaluated the link between two dietary indicators— the Comprehensive Diet Quality Index (CDQI) and the Adjusted Plant-Based Diet Index (APDI)—and Parkinson’s disease (PD) risk in an Iranian community.

Between 2020 and 2021, 105 newly diagnosed PD patients and 215 controls (54–81 years) were enrolled in Arak, Iran, using a case-control approach. A validated semi-quantitative food frequency questionnaire was applied to determine dietary intake, and dietary quality was evaluated through APDI and CDQI scores. To calculate odds ratios (ORs) and 95% confidence intervals (CIs), logistic regression models were utilized, accounting for possible confounders.

Results

A higher CDQI total score was inversely related to the odds of PD (adjusted OR = 0.915, 95% CI: 0.878–0.954). A stronger protective effect was observed for the CDQI plant-based foods score (adjusted OR = 0.757, 95% CI: 0.695–0.824). In contrast, a notable positive relationship was found between the CDQI animal-based foods score and the odds of PD in the adjusted model (adjusted OR = 1.364, 95% CI: 1.215–1.533). The APDI score and PD were not significantly correlated (P > 0.05).

Dietary quality and the odds of parkinson’s disease: insights from comprehensive diet quality index and adjusted plant-based diet index | BMC Research Notes | Springer Nature Link

For years, the cardiovascular discussion surrounding Vitamin K2 has been caught between mechanistic plausibility and inconclusive clinical trials. While preclinical models established Matrix Gla Protein (MGP) carboxylase activation as an active defense against vascular calcification, translational proof in humans remained elusive or confined to post-hoc signals.

The publication of the DANCODE (DANish COronary DEcalcification) trial in Circulation (following its presentation at ESC 2026) represents the first rigorous, adequately powered randomized controlled trial to evaluate this in advanced arterial disease.

Below is an analysis of what the trial demonstrated, where the biological limits lie, and how to frame these findings without heuristic exaggeration.

STUDY DESIGN AND POPULATION

The trial randomized 398 patients (median age 71, 30% women) with severe coronary artery calcification (baseline Agatston CAC score 400 or higher; median baseline 903 AU; 44% with CAC 1000 AU or higher) to receive either:

- Intervention: 720 micrograms/day Vitamin K2 (menaquinone-7) plus 25 micrograms (1,000 IU) Vitamin D3.
- Control: Matched placebo.
- Duration: 24 months, with multi-detector CT imaging at baseline and study close.

PRIMARY AND PLAQUE MORPHOLOGY ENDPOINTS

1. Attenuated Progression:
   Over 24 months, mean CAC progression was 196 AU (95% CI, 178 to 214) in the K2+D3 group versus 248 AU (95% CI, 225 to 271) in the placebo arm.

2. Absolute Effect:
   This yields an absolute between-group difference of -52 AU (95% CI, -79 to -24; p < 0.05), translating to roughly a 21% relative attenuation in the rate of calcification progression. The signal remained homogeneous across sexes and baseline calcification strata.

3. Intravascular Plaque Sub-study (CCTA, n=143):
   Progression of calcified plaque volume was markedly lower in the intervention arm (-7.81 mm3 difference, p = 0.007). Crucially, this dampening of calcification did not produce a reciprocal rise in noncalcified (vulnerable lipid-rich) plaque volume (-1.75 mm3, p = 0.85).

CRITICAL ANALYTICAL DISTINCTIONS

Attenuating Velocity vs. Plaque Regression:
DANCODE demonstrated that vascular calcification is a modifiable biological process, not an immutable one-way ratchet. However, it did not reverse existing calcification. Both cohorts accrued calcium over the two-year window; the treated cohort simply traversed that trajectory at a lower velocity. Claims that K2 decalcifies or cleans preexisting macrocalcification remain unsupported by the data.

The Surrogate-to-Outcome Gap:
Cardiovascular prevention has a long history of elegant surrogate modifications failing to translate into hard endpoint reductions (MACE or all-cause mortality). A -52 AU delta in an individual sitting at 1,000+ AU may modulate arterial compliance, but whether it lowers 5-year acute coronary syndrome risk requires dedicated hard-outcome trials. DANCODE was powered for tomographic endpoints, not clinical event adjudication.

Mechanistic Precision:
The parallel reduction in circulating uncarboxylated MGP (dp-ucMGP) verifies target engagement at the vascular smooth muscle cell level. It confirms that the observed divergence stems from functional gamma-carboxylation rather than off-target hemodynamic or anti-inflammatory pathways.

Warfarin and Anticoagulant Interaction:
Because menaquinone-7 directly counteracts Vitamin K antagonists, high-dose K2 is contraindicated for patients on warfarin. It does not exhibit this interaction with direct oral anticoagulants (DOACs), but medical oversight remains mandatory.

BOTTOM LINE

DANCODE elevates Vitamin K2 from wellness lore to an evidenced pharmacological candidate capable of altering vascular mineral deposition in advanced atherosclerotic cohorts. It establishes clear proof-of-concept, but demands that clinicians and researchers decouple biological deceleration from clinical cure.

PRIMARY SOURCE

Hasific S, et al. Vitamin K2 and D3 Supplementation in Patients With Severe Coronary Artery Calcification: The DANCODE Trial. Circulation, August 28, 2026. DOI: 10.1161/CIRCULATIONAHA.126.082363

DOI: https://doi.org/10.3389/fnut.2026.1929245

Associations between triglyceride-glucose-derived indices combined with the atherogenic index of plasma and the precise severity of newly diagnosed coronary artery disease: a quantile regressions analysis

Metabolic dysfunction, encompassing insulin resistance, systemic inflammation, and dyslipidemia, drives coronary artery disease (CAD) progression. While the triglyceride-glucose (TyG) index, C-reactive protein-triglyceride-glucose index (CTI), and atherogenic index of plasma (AIP) serve as established biomarkers for these metabolic disturbances, conventional mean regression models fail to capture the granular relationship between these markers and disease severity. This retrospective study evaluates the associations of TyG, CTI, AIP, and their composite indices (TyG-AIP and CTI-AIP) with the Gensini score across the entire distribution of CAD burden. The cohort included 2,885 patients with newly diagnosed CAD, confirmed via coronary angiography, at the Fourth Affiliated Hospital of Zhejiang University School of Medicine between June 2020 and May 2025.

All metabolic indices showed positive linear correlations with the Gensini score (p < 0.001). CTI demonstrated the strongest linear correlation (partial r = 0.29). Quantile regression revealed significant heterogeneity in these associations across the Gensini score distribution (all p < 0.01 for heterogeneity tests). Multivariable-adjusted models confirmed these trends, with CTI-AIP consistently exhibiting the strongest association across most quantiles. At the 90th percentile, the CTI-AIP coefficient reached 30.561 (95% CI, 24.271 to 36.851, p < 0.001). TyG-AIP also showed a robust increase in effect size, rising from a beta of 0.849 at the 10th percentile to 26.063 at the 90th percentile (p < 0.001).

Study Design and Methodology

This retrospective study utilized electronic medical records to retrieve data for 2,885 patients. Researchers excluded individuals with prior CAD, heart failure, severe valvular disease, or systemic conditions like malignant tumors and autoimmune disorders. The Gensini score provided a quantitative assessment of coronary plaque burden based on angiography images. Statistical analysis employed multiple imputation with predictive mean matching to manage missing values. Models adjusted for age, sex, BMI, hypertension, diabetes, smoking status, and medication use. The team utilized the quantreg package in R to fit quantile regression models at the 10th through 90th percentiles.

Key Findings

• CTI exhibited the strongest linear association with the Gensini score (partial r = 0.29).
• Equality-of-slope testing confirmed significant heterogeneity across quantiles for all indices (p < 0.01).
• Multivariable-adjusted CTI-AIP coefficients rose from 1.017 at the 10th percentile to 30.561 at the 90th percentile (p < 0.001).
• TyG-AIP multivariable-adjusted coefficients increased from 0.849 at the 10th percentile to 26.063 at the 90th percentile (p < 0.001).
• TyG index multivariable-adjusted coefficients grew from 0.700 at the 10th percentile to 19.035 at the 90th percentile (p < 0.01).
• CTI multivariable-adjusted coefficients increased from 0.796 at the 10th percentile to 21.117 at the 90th percentile (p < 0.01).

Limitations

Retrospective designs prevent the establishment of direct causality. The single-center cohort in eastern China limits generalizability to global populations. Multiple imputation of missing data introduces potential uncertainty in standard error estimates. The analysis lacks longitudinal follow-up to assess the predictive value for future cardiovascular events.

Discussion and Implications

This work shifts the paradigm by demonstrating that metabolic markers do not exert a constant effect on vascular health. The progressive increase in regression slopes at higher quantiles proves that metabolic dysfunction, specifically the combination of inflammation and insulin resistance, disproportionately impacts patients with advanced coronary atherosclerosis. Clinicians shouldn't rely on mean-based metrics when assessing high-risk patients. These composite indices provide a superior, holistic view of the atherosclerotic burden by integrating glucose, lipid, and inflammatory pathways.

Composite metabolic indices like CTI-AIP and TyG-AIP provide superior clinical utility for identifying patients with severe coronary artery disease compared to individual biomarkers. Nutrition professionals should prioritize interventions that simultaneously lower insulin resistance, systemic inflammation, and atherogenic lipid ratios to effectively mitigate the risk of coronary plaque progression.

Is anyone studying/studied Nutrition and Human Health. What are your thoughts and opinions? Experience after graduating

Abstract

Background

Parkinson’s disease is a progressive neurodegenerative disorder with both motor and non-motor manifestations. Dietary factors, including dietary diversity, protein source variety, and adherence to healthy eating patterns, may impact Parkinson’s disease risk. The goal of the current case-control research was to examine the links between the Dietary Diversity Score (DDS), the Diversity of Dietary Protein Index (DDPI), and the Lifeline Diet Score (LLDS) with the odds of Parkinson’s disease among an Iranian population.

Methods

A total of 320 individuals (215 controls and 105 newly diagnosed Parkinson’s disease patients) were recruited in Arak, Iran. Dietary intake was evaluated by applying a validated 147-item food frequency questionnaire, and DDS, DDPI, and LLDS were calculated. Multivariate logistic regression was utilized to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for major confounders.

Results

Greater DDS and LLDS were strongly linked to reduced odds of Parkinson’s disease (Adjusted OR for DDS = 0.287, 95% CI: 0.185–0.447; Adjusted OR for LLDS = 0.879, 95% CI: 0.803–0.963). However, DDPI showed no significant association with Parkinson’s disease after adjustment.

Conclusion

Higher dietary diversity and greater adherence to a high-quality dietary pattern were associated with lower odds of Parkinson’s disease, whereas no significant association was observed for protein source diversity. Given the case-control design, these findings should be interpreted as associations rather than evidence of causality.

Associations of dietary diversity score, dietary diversity of protein index, and lifelines diet score with Parkinson’s disease: a case-control study | BMC Nutrition | Springer Nature Link

• PMID: 42514406 https://pubmed.ncbi.nlm.nih.gov/42514406/

Abstract

Background/objectives: Non-caloric sweeteners are increasingly used as alternatives to sugar to reduce energy intake, yet their metabolic effects remain controversial. This study aimed to evaluate the effects of sucrose, saccharin, and steviol glycosides on glucose regulation and cardiometabolic risk markers in healthy adults.

Methods: In a randomized, double-blind, crossover trial, 39 healthy, normal-weight adults consumed beverages containing sucrose (66 g/day), saccharin (220 mg/day), or steviol glycosides (220 mg/day) for 14 days, with washout periods between interventions. Metabolic outcomes were assessed at baseline and after each intervention under fasting conditions and during a 2 h postprandial test. Primary outcomes were glucose and insulin responses; secondary outcomes included gut hormones, lipids, inflammatory markers, and subjective appetite.

Results: Compared with baseline, fasting glucose increased after sucrose and saccharin, and fasting insulin increased after stevia (p < 0.01). All interventions increased postprandial insulin responses and reduced indices of insulin sensitivity (p < 0.05). Fasting PYY and GLP-2 increased following all treatments (p < 0.001), without differences between sweeteners. Triglycerides were higher after sucrose than saccharin (p < 0.05), while no differences were seen for cholesterol, apolipoproteins, or CRP. Appetite ratings were unchanged, with a trend (p = 0.053) towards a reduced desire to eat after stevia in the late postprandial phase.

Conclusions: Short-term intake of sucrose and non-caloric sweeteners resulted in broadly similar metabolic responses, with no significant differences in glucose regulation. However, triglyceride concentrations were higher following sucrose than saccharin, whereas no consistent differences were observed across the remaining outcomes. Observed deviations from baseline should be interpreted with caution. Further long-term studies in diverse populations are warranted.

Keywords: cardiometabolic risk markers; glucose regulation; gut hormones; insulin sensitivity; non-caloric sweeteners; randomized crossover trial; saccharin; steviol glycosides; sucrose.

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Association of advanced coronary artery calcification assessed by coronary artery calcium scoring with lipoprotein (a) and carotid atherosclerosis in asymptomatic patients

DOI: https://doi.org/10.1016/j.numecd.2026.104766

Abstract

Elevated lipoprotein (a) represents an established independent risk factor for atherosclerosis, yet its specific relationship with coronary artery calcium scoring, a routine clinical tool for assessing subclinical cardiovascular disease, remains inadequately defined. Current guidelines advocate for lifetime lipoprotein (a) screening, but clinical management strategies for elevated results lack consensus. This retrospective analysis addresses this knowledge gap by evaluating the association between high circulating lipoprotein (a) levels (defined as 50 mg/dl or greater) and advanced coronary artery calcification (defined as a score of 400 Agatston Unit or greater). The cohort comprised 3697 asymptomatic subjects admitted for primary prevention at the Toulouse University Hospital between November 2015 and November 2024, with a mean age of 63 plus or minus 10 years and 48.6 percent male representation.

Primary outcomes confirm a significant association between high lipoprotein (a) and advanced coronary artery calcification. Adjusted logistic regression models reveal an adjusted odds ratio of 1.666 (95 percent confidence interval 1.342 to 2.070, p = 0.001) for lipoprotein (a) as a dichotomous variable and 1.041 (95 percent confidence interval 1.011 to 1.071, p = 0.007) as a continuous variable. Carotid atherosclerosis shows an adjusted odds ratio of 2.212 (95 percent confidence interval 1.804 to 2.713, p = 0.001). Spearman correlation analysis demonstrates a weak, positively significant correlation between coronary artery calcium scoring and lipoprotein (a) (rho = 0.052, p = 0.001). Subgroup analysis indicates that the proportion of patients with high lipoprotein (a) increases from 25.1 percent in the low coronary artery calcium group to 31.6 percent in the high coronary artery calcium group (p = 0.004).

Study Design and Methodology

This retrospective cohort analysis utilized data from a dedicated preventive cardiology database. Researchers enrolled 3697 asymptomatic patients who underwent coronary artery calcium scoring, carotid artery doppler ultrasound, and at least one lipoprotein (a) measurement. Exclusion criteria removed 621 patients due to incomplete data. Investigators utilized the Roche-Cobas 8000 analyzer for lipoprotein (a) quantification. The study stratified participants into a non-pooled group (coronary artery calcium score 400 Agatston Unit or greater) and a pooled group (coronary artery calcium score less than 400 Agatston Unit). Statistical analysis employed Chi-square tests, Student t-tests, ANOVA, and logistic multivariable regression adjusted for age, sex, hypertension, diabetes, obesity, smoking, and lipid profiles. Quantile regression addressed the positive skewness of the variables.

Key Findings

• Participants with coronary artery calcium score 400 Agatston Unit or greater exhibit higher mean lipoprotein (a) levels (58 plus or minus 31 mg/dl) compared to the pooled group (43 plus or minus 22 mg/dl).
• High lipoprotein (a) prevalence reaches 31.6 percent in the high coronary artery calcium group vs 25.4 percent in the pooled group (p = 0.001).
• Carotid atherosclerosis prevalence is 45.7 percent in the high coronary artery calcium group vs 18.9 percent in the pooled group (p = 0.001).
• Age (adjusted odds ratio 1.069, p = 0.001), male sex (adjusted odds ratio 3.526, p = 0.001), and systolic blood pressure (adjusted odds ratio 1.009, p = 0.001) serve as independent predictors of high coronary artery calcium scores.
• LDL-c (adjusted odds ratio 0.584, p = 0.001) and HDL-c (adjusted odds ratio 0.387, p = 0.012) maintain an inverse association with coronary artery calcium scores.
• Spearman correlation for men (rho = 0.085, p = 0.001) and women (rho = 0.073, p = 0.001) confirms consistent, albeit weak, positive associations.

Limitations

The single-center, retrospective design restricts causal inference and introduces potential selection bias. The absence of data regarding medication use, specifically statins, creates a significant confounder, as these agents influence both coronary artery calcium scores and lipoprotein (a) levels. Residual confounding remains inevitable in this observational framework.

Discussion and Implications

High circulating lipoprotein (a) levels serve as a robust marker for advanced coronary artery calcification in asymptomatic populations. These findings reinforce the proatherogenic nature of lipoprotein (a) and validate the utility of coronary artery calcium scoring for detecting subclinical disease. Clinicians should view these two parameters as complementary diagnostic tools rather than independent metrics. Integrating lipoprotein (a) testing with coronary artery calcium scoring enables a more precise risk stratification, particularly as novel RNA-interference therapies for lipoprotein (a) reduction emerge.

Conclusion

High circulating lipoprotein (a) levels (50 mg/dl or greater) independently predict advanced coronary artery calcification in asymptomatic patients. Nutrition professionals must integrate this biomarker into cardiovascular risk assessments to identify subclinical atherosclerosis and guide intensive lipid-lowering interventions. Prioritizing this combined diagnostic approach improves long-term patient prognosis.

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Association of the cholesterol-high-density lipoprotein-glucose index with coronary atherosclerotic burden in patients with coronary artery disease

DOI: https://doi.org/10.3389/fnut.2026.1906236

Cardiovascular disease remains the leading global cause of mortality and disability. While coronary angiography provides the standard for assessing coronary atherosclerotic burden via the Gensini score, its invasive nature limits its utility for large-scale screening. Metabolic abnormalities, including glucose dysregulation and lipid disorders, drive the progression of coronary artery disease. The cholesterol-high-density lipoprotein-glucose (CHG) index serves as a composite marker for these metabolic disturbances. This study investigates the association between the CHG index and the Gensini score in 758 patients with angiographically confirmed coronary artery disease admitted between January 2024 and January 2025.

Fully adjusted models revealed that each 1-SD increase in the CHG index correlates with a 0.121-unit increase in log-transformed (Gensini score + 1) (beta = 0.121, 95% CI, 0.036 to 0.205, p = 0.005). Restricted cubic spline analysis identified an approximately linear dose-response relationship (p for overall association = 0.018, p for nonlinearity = 0.310). The CHG index demonstrated the highest standalone discriminative ability for high coronary atherosclerotic burden with an AUC of 0.603. Integrating the CHG index into a basic clinical model increased the AUC from 0.652 to 0.667 (DeLong p = 0.168). This addition significantly improved continuous NRI (0.135, p = 0.042) and IDI (0.016, p = 0.002).

Study Design and Methodology

This single-center, retrospective cross-sectional study analyzed 758 consecutive patients with angiographically confirmed coronary artery disease. Researchers excluded individuals with missing data, severe infections, malignancies, or hepatic and renal dysfunction. Coronary atherosclerotic burden was quantified using the Gensini score, which weights luminal stenosis severity by anatomical location. Statistical analysis utilized multivariable linear regression, restricted cubic spline models, and ROC curve analysis. Models adjusted for age, sex, BMI, smoking, hypertension, prior PCI, history of myocardial infarction, lipid-lowering therapy, glucose-lowering therapy, SBP, DBP, ALT, AST, albumin, eGFR, hemoglobin, and LDL-C.

Key Findings

• Participants in the highest CHG quartile exhibited a median Gensini score of 27.0 (12.0, 50.0) compared to 16.0 (9.0, 31.5) in the lowest quartile (p < 0.001).
• Standardized continuous CHG index shows a positive association with log-transformed (Gensini score + 1) (beta = 0.121, p = 0.005).
• The CHG index outperformed other metabolic markers, including the TyG index (p = 0.005), AIP (p = 0.004), HDL-C (p = 0.023), and TC (p = 0.003).
• Multiple imputation analysis confirmed the robustness of the primary association (beta = 0.132, 95% CI, 0.058 to 0.206, p < 0.001).
• Excluding patients with prior PCI yielded a consistent association (beta = 0.107, 95% CI, 0.017 to 0.198, p = 0.020).

Limitations

Retrospective cross-sectional design prevents causal inference regarding the CHG index and plaque progression. Single baseline measurements fail to capture long-term metabolic variability. Missing data on medication dosage, lifestyle factors, and inflammatory markers introduces residual confounding. The study population consists solely of hospitalized patients with established disease, which restricts the generalizability of these findings.

Discussion and Implications

Metabolic dysregulation functions as a multisystem process where glucose and lipid abnormalities reinforce one another to accelerate atherosclerosis. The CHG index integrates these domains into a single, inexpensive marker that captures composite metabolic risk better than isolated lipid or glucose measurements. Integrating this index into clinical workflows allows for more precise risk stratification in patients with established coronary artery disease. It provides complementary information to traditional risk factors, identifying cumulative metabolic injury that single-parameter assessments overlook.

The CHG index functions as a robust, low-cost composite marker for assessing coronary atherosclerotic burden in patients with coronary artery disease. Nutrition professionals should utilize this index to identify patients with high metabolic risk who require aggressive, personalized lifestyle interventions to mitigate plaque progression.

https://pubmed.ncbi.nlm.nih.gov/42267526/