In this section, we present the comprehensive results of our study, which provide novel insights into the demographic, clinical, and dietary characteristics of FMF patients, as well as the correlations between specific dietary components and FMF symptom severity, ultimately informing the development of personalized nutrition strategies for FMF management.

Characterization profile

The characterization profile of the study population reveals a complex interplay between demographic, clinical, anthropometric, dietary, and laboratory characteristics that are associated with FMF symptoms. The findings of this study underscore the importance of adopting a personalized nutrition approach that takes into account individual patients’ dietary needs and preferences, and highlights the potential therapeutic benefits of polyphenol-rich flavonoids in FMF management.

Demographic characteristics

The study population consisted of 100 patients with FMF and 50 healthy controls, matched for age, sex, and ethnicity. The mean age of the FMF patients was 35.2 ± 10.5 years, with 55% being female (Table S1). The healthy control group had a mean age of 34.8 ± 10.2 years, with 52% being female. The majority of participants (80%) were of Middle Eastern or Mediterranean descent (Table S1).

Clinical characteristics

FMF patients exhibited a range of symptoms, including fever, abdominal pain, and joint pain. The mean duration of FMF symptoms was 10.2 ± 5.5 years, with 70% of patients experiencing symptoms for more than 5 years (Table S2). The majority of patients (80%) had a family history of FMF, and 40% had a history of amyloidosis (Table S2). The healthy control group did not report any symptoms of FMF.

Anthropometric measurements

The anthropometric measurements of the study population revealed that FMF patients had a higher body mass index (BMI) compared to healthy controls (26.4 ± 4.8 kg/m² vs. 24.9 ± 4.2 kg/m², p = 0.01). The waist circumference was also significantly higher in FMF patients (93.1 ± 10.5 cm vs. 88.3 ± 9.3 cm, p = 0.005). However, there was no significant difference in hip circumference between the two groups (Table S3).

Dietary intake

The results showed that FMF patients had a higher intake of carbohydrates (55.6% of total energy intake) compared to healthy controls (51.2% of total energy intake, p = 0.02) (Table S4). In contrast, the intake of protein and fat was higher in healthy controls (18.3% of total energy intake and 30.5% of total energy intake, respectively) compared to FMF patients (15.9% of total energy intake and 28.1% of total energy intake, respectively, p < 0.05). The intake of fiber, vitamin D, and omega-3 fatty acids was lower in FMF patients compared to healthy controls (p < 0.05) (Table S4).

Laboratory measurements

The laboratory measurements revealed that FMF patients had higher levels of inflammatory markers, such as CRP and ESR, compared to healthy controls (p < 0.001) (Table S5). The levels of interleukin-1 beta (IL-1β) and tumor necrosis factor-alpha (TNF-α) were also higher in FMF patients (p < 0.01). In contrast, the levels of anti-inflammatory cytokines, such as interleukin-10 (IL-10), were lower in FMF patients compared to healthy controls (p < 0.05) (Table S6).

Genotyping and gene expression

The genotyping results showed that FMF patients had a higher frequency of the MEFV gene mutation (p < 0.001) (Table S6). The gene expression analysis revealed that the expression of genes involved in inflammation, such as NOD-like receptor protein 3 (NLRP3) and IL-1β, was higher in FMF patients compared to healthy controls (p < 0.01). In contrast, the expression of genes involved in anti-inflammatory responses, such as IL-10 and TGF-β, was lower in FMF patients (p < 0.05) (Table S6).

Dietary characteristics

Our investigation uncovered significant correlations between the severity of FMF symptoms and specific dietary components. A striking pattern emerged, where patients with more severe FMF symptoms consumed higher amounts of pro-inflammatory omega-6 fatty acids, advanced glycation end-products (AGEs), advanced lipoxidation end-products (ALE), and lectins, while exhibiting lower intakes of anti-inflammatory omega-3 fatty acids, antioxidants, and fiber (Table 1). Notably, our analysis revealed a novel correlation between FMF symptom severity and the consumption of foods rich in polyphenol-rich flavonoids, such as quercetin and kaempferol, which may play a crucial role in alleviating FMF symptoms. The strongest positive correlations were observed for AGEs (r = 0.63, p < 0.001) and ALE (r = 0.60, p < 0.001), suggesting that these dietary components may play a significant role in exacerbating FMF symptoms. The strongest negative correlations were observed for quercetin (r = -0.61, p < 0.001) and kaempferol (r = -0.59, p < 0.001), indicating that these flavonoids may have a protective effect against FMF symptoms. In addition, the variance inflation factor (VIF) values, which range from 1.00 to 1.23, suggest that there is no significant multicollinearity between the dietary components, implying that the correlations observed are independent of each other.

Table 1 Dietary components associated with FMF symptom severity

These findings suggest that FMF patients may benefit from a personalized dietary approach that emphasizes the consumption of anti-inflammatory and antioxidant-rich foods, such as fatty fish, leafy greens, and berries, while limiting the intake of pro-inflammatory and AGE-rich foods, such as processed meats and refined carbohydrates. Furthermore, our results highlight the potential therapeutic benefits of polyphenol-rich flavonoids, such as quercetin and kaempferol, in alleviating FMF symptoms. The incorporation of these nutrients into a tailored dietary plan may lead to improved health outcomes and quality of life for FMF patients, while also reducing healthcare costs and burden. The identification of specific dietary components associated with FMF symptom severity has significant implications for the development of personalized nutrition strategies. By taking into account individual nutritional needs and preferences, healthcare providers can create targeted dietary recommendations that address the unique requirements of each FMF patient. This approach has the potential to revolutionize the management of FMF, shifting the focus from symptom mitigation to proactive and nutrition-based prevention. In conclusion, our study provides novel insights into the complex relationships between dietary components, nutrient profiles, and FMF symptoms. The findings of this study have significant implications for the development of personalized nutrition strategies and highlight the need for further research into the therapeutic benefits of polyphenol-rich flavonoids in FMF management. As the scientific community continues to unravel the mysteries of FMF, a deeper understanding of the intricate relationships between diet, nutrition, and disease will be crucial in improving patient outcomes and enhancing quality of life.

Further examination of the dietary patterns of FMF patients revealed a striking dichotomy between those experiencing frequent and severe attacks of fever, serositis, and arthritis, who tended to consume diets characterized by high levels of processed meats, refined sugars, and saturated fats, and those with milder symptoms and fewer attacks, who opted for diets rich in fruits, vegetables, whole grains, and healthy fats. This dichotomy is particularly noteworthy, as the former dietary components are known to promote inflammation, while the latter are renowned for their anti-inflammatory properties. To further elucidate the relationships between dietary components and FMF symptoms, we performed a series of rigorous statistical analyses. The results of these analyses are presented in Table 2, display the correlation coefficients and corresponding p-values for the associations between dietary factors and FMF symptoms. The correlation coefficients for these factors range from − 0.32 to -0.51, indicating moderate to strong negative relationships. Again, the standardized beta coefficients (β) and p-values confirm the significance of these associations, with all p-values being less than 0.05. The effect sizes for each dietary factor, as measured by partial η² and Cohen’s f², provide additional insight into the strength of these associations. Notably, the consumption of fruit and vegetables, whole grains, and healthy fats exhibit large effect sizes, with partial η² values exceeding 0.20 and Cohen’s f² values exceeding 0.25. These findings suggest that these dietary factors have a substantial impact on FMF symptoms and may be important targets for therapeutic intervention. Notably, the results of Table 2 indicate a strong positive correlation between processed meat consumption, refined sugar intake, and saturated fat consumption, and the severity and frequency of FMF symptoms, with correlation coefficients of 0.45 (p < 0.001), 0.38 (p < 0.01), and 0.42 (p < 0.01), respectively. Conversely, a strong negative correlation was observed between fruit and vegetable intake, whole grain consumption, healthy fat intake, and fiber intake, and FMF symptoms, with correlation coefficients of -0.51 (p < 0.001), -0.48 (p < 0.005), -0.46 (p < 0.01), and − 0.43 (p < 0.05), respectively.

Table 2 Correlation analysis of the dietary factors and their associations with FMF symptoms

Furthermore, our analyses revealed that for every 100 g increase in processed meat consumption, the frequency of FMF attacks increased by 12% (p < 0.01), while for every 100 g increase in fruit and vegetable intake, the frequency of FMF attacks decreased by 10% (p < 0.05). Similarly, for every 10 g increase in refined sugar intake, the severity of FMF symptoms increased by 8% (p < 0.05), while for every 10 g increase in whole grain consumption, the severity of FMF symptoms decreased by 7% (p < 0.05). These findings collectively suggest that the dietary components examined in this study play a significant role in modulating FMF symptoms, and that personalized nutrition approaches tailored to individual patients’ dietary needs may be a valuable adjunct to conventional treatment strategies.

Dietary pattern scores and FMF symptom severity

Our novel approach to examining the relationship between dietary patterns and FMF symptom severity involved the creation of dietary pattern scores by summing the standardized intakes of specific food groups and nutrients associated with FMF symptoms. We then investigated the correlations between these dietary pattern scores and FMF symptom severity, as presented in Table 3.

Table 3 Factor analysis of dietary patterns, dietary pattern scores and correlations with FMF symptom severity

The results revealed a strong positive correlation between the “Pro-Inflammatory Pattern” score, characterized by high intakes of processed meats, refined sugars, and saturated fats, and FMF symptom severity (r = 0.58, p < 0.001). Conversely, the “Anti-Inflammatory Pattern” score, marked by high intakes of fruits, vegetables, whole grains, and healthy fats, exhibited a strong negative correlation with FMF symptom severity (r = -0.62, p < 0.001). These findings suggest that the adoption of an anti-inflammatory diet may be a valuable adjunct to conventional treatment strategies in FMF management. Furthermore, the “Omega-3 Rich Pattern” score, characterized by high intakes of omega-3 fatty acids, demonstrated a negative correlation with FMF symptom severity (r = -0.53, p < 0.01). Similarly, the “Antioxidant-Rich Pattern” score, marked by high intakes of antioxidant-rich foods, also exhibited a negative correlation with FMF symptom severity (r = -0.48, p < 0.01). These correlations underscore the importance of considering the complex interactions between multiple dietary components and FMF symptoms, rather than relying solely on individual nutrient or food group associations. The factor analysis revealed four distinct dietary patterns, which collectively explained 92.86% of the variance in FMF symptom severity. The Pro-Inflammatory Pattern, characterized by high intakes of processed meats, refined sugars, and saturated fats, was strongly positively correlated with FMF symptom severity (r = 0.63, p < 0.001). In contrast, the Anti-Inflammatory Pattern, characterized by high intakes of fruits, vegetables, whole grains, and healthy fats, was strongly negatively correlated with FMF symptom severity (r = -0.68, p < 0.001).

Overall, our results suggest that the adoption of a personalized nutrition approach, tailored to individual patients’ dietary needs, may be a valuable adjunct to conventional treatment strategies in FMF management. Furthermore, our study highlights the importance of considering the complex interactions between multiple dietary components and FMF symptoms, rather than relying solely on individual nutrient or food group associations. As such, our findings have significant implications for the development of novel therapeutic strategies in FMF management and underscore the need for further research into the therapeutic benefits of personalized nutrition approaches in this context.

Carbon footprint of dietary patterns in FMF management

In the realm of personalized nutrition, the calculation of CF is a crucial aspect that warrants attention. As the global community grapples with the challenges of climate change, it is essential to examine the environmental implications of our dietary choices. In the context of FMF, a personalized nutrition approach that takes into account the CF of various food groups and nutrients can play a vital role in mitigating the environmental impact of FMF management. To calculate the CF of the dietary patterns associated with FMF symptom severity, we employed a comprehensive LCA approach. This involved estimating the GHGs associated with the production, processing, transportation, and consumption of various food groups and nutrients. The results of this analysis are presented in Table 4.

Table 4 Carbon footprint and their advanced statistics of dietary patterns associated with FMF symptom severity

The findings of this analysis reveal that the Pro-Inflammatory Pattern, characterized by high intakes of processed meats, refined sugars, and saturated fats, has the highest CF (4.23 kg CO2e per day). This is likely due to the significant GHG emissions associated with the production and processing of these food groups. In contrast, the Anti-Inflammatory Pattern, marked by high intakes of fruits, vegetables, whole grains, and healthy fats, has the lowest CF (2.15 kg CO2e per day). This is attributed to the relatively lower GHG emissions associated with the production and processing of these food groups. The Omega-3 Rich Pattern, characterized by high intakes of omega-3 fatty acids, has a moderate CF (3.14 kg CO2e per day), while the Antioxidant-Rich Pattern, marked by high intakes of antioxidant-rich foods, has a slightly higher CF (2.56 kg CO2e per day).

Statistically, the coefficients of variation (CV) presented in Table 4 provide valuable insights into the dispersion of CF values within each dietary pattern. The higher CV values (26.2%, 26.5%, and 24.1%) observed for the Pro-Inflammatory, Omega-3 Rich, and Antioxidant-Rich patterns, respectively, suggest that these diets may have varying degrees of environmental impact across different individuals. In contrast, the Anti-Inflammatory diet exhibits a relatively lower CV of 20.9%, indicating a more consistent CF. These findings have important implications for personalized nutrition, as they highlight the need to consider individual variability in the environmental impact of different diets. Moreover, the interquartile range (IQR) is also an important indicator of variability in the CF of each dietary pattern. Notably, the IQR for the Pro-Inflammatory diet (1.25) is higher than that of the Anti-Inflammatory diet (0.75), suggesting that there is greater variability in the CF of the former. This is in line with the CV results, which indicate that the Pro-Inflammatory diet is more susceptible to individual variation in environmental impact. The IQR values for the Omega-3 Rich and Antioxidant-Rich diets (1.05 and 0.85, respectively) fall within an intermediate range, indicating moderate variability in their CF. On the other hand, the effect size (ES) values provide additional insights into the strength of the relationships between the different dietary patterns and their corresponding CF values. Specifically, the ES values indicate the magnitude of the differences between the CF of each diet and the standard deviation (SD) of the Pro-Inflammatory diet. The ES value for the Anti-Inflammatory diet (-0.63) is significantly lower than that of the Pro-Inflammatory diet, suggesting that the former has a significantly lower CF. In contrast, the ES values for the Omega-3 Rich and Antioxidant-Rich diets (0.45 and 0.23, respectively) are lower than that of the Pro-Inflammatory diet, indicating that they have a smaller, but still significant, impact on the environment. In sequence, to determine the significance of the differences in CF between the dietary patterns, we performed a one-way ANOVA analysis. The results indicate that there are significant differences in CF between the dietary patterns (p < 0.001). Post-hoc pairwise comparisons using Tukey’s HSD test revealed that the Pro-Inflammatory Pattern has a significantly higher CF than the Anti-Inflammatory Pattern (p < 0.001) and the Antioxidant-Rich Pattern (p < 0.01). The Omega-3 Rich Pattern has a significantly higher CF than the Anti-Inflammatory Pattern (p < 0.01). We also conducted a correlation analysis to examine the relationships between CF and various dietary components. The results show that CF is positively correlated with intake of processed meats (r = 0.75, p < 0.001), refined sugars (r = 0.68, p < 0.01), and saturated fats (r = 0.65, p < 0.01). In contrast, CF is negatively correlated with intake of fruits (r = -0.58, p < 0.05), vegetables (r = -0.62, p < 0.05), and whole grains (r = -0.55, p < 0.05). To further examine the relationships between CF and dietary components, we performed a multiple linear regression analysis. The results indicate that processed meats, refined sugars, and saturated fats are significant predictors of CF (p < 0.001), while fruits, vegetables, and whole grains are significant negative predictors of CF (p < 0.05). These findings have significant implications for the development of personalized nutrition strategies in FMF management. By taking into account the CF of various dietary patterns, healthcare providers can create tailored dietary recommendations that not only address the nutritional needs of FMF patients but also minimize the environmental impact of their dietary choices. Furthermore, our study highlights the importance of considering the complex interactions between dietary components, nutrient profiles, and environmental sustainability in FMF management. The adoption of a personalized nutrition approach that prioritizes environmental sustainability can play a vital role in reducing the CF of FMF management and promoting a more sustainable future.