Anatolian genetic ancestry in North Lebanese populations.

Lebanon's rich history as a cultural crossroad spanning millennia has significantly impacted the genetic composition of its population through successive waves of migration and conquests from surrounding regions. Within modern-day Lebanon, the Koura district stands out with its unique cultural foundations, primarily characterized by a notably high concentration of Greek Orthodox Christians compared to the rest of the country. This study investigates whether the prevalence of Greek Orthodoxy in Koura can be attributed to modern Greek heritage or continuous blending resulting from the ongoing influx of refugees and trade interactions with Greece and Anatolia. We analyzed both ancient and modern DNA data from various populations in the region which could have played a role in shaping the current population of Koura using our own and published data. Our findings indicate that the genetic influence stemming directly from modern Greek immigration into the area appears to be limited. While the historical presence of Greek colonies has left its mark on the region's past, the distinctive character of Koura seems to have been primarily shaped by cultural and political factors, displaying a stronger genetic connection mostly with Anatolia, with affinity to ancient but not modern Greeks.

Epidemiological topology data analysis links severe COVID-19 to RAAS and hyperlipidemia associated metabolic syndrome conditions.

MOTIVATION: The emergence of COVID-19 (C19) created incredible worldwide challenges but offers unique opportunities to understand the physiology of its risk factors and their interactions with complex disease conditions, such as metabolic syndrome. To address the challenges of discovering clinically relevant interactions, we employed a unique approach for epidemiological analysis powered by redescription-based topological data analysis (RTDA). RESULTS: Here, RTDA was applied to Explorys data to discover associations among severe C19 and metabolic syndrome. This approach was able to further explore the probative value of drug prescriptions to capture the involvement of RAAS and hypertension with C19, as well as modification of risk factor impact by hyperlipidemia (HL) on severe C19. RTDA found higher-order relationships between RAAS pathway and severe C19 along with demographic variables of age, gender, and comorbidities such as obesity, statin prescriptions, HL, chronic kidney failure, and disproportionately affecting Black individuals. RTDA combined with CuNA (cumulant-based network analysis) yielded a higher-order interaction network derived from cumulants that furthered supported the central role that RAAS plays. TDA techniques can provide a novel outlook beyond typical logistic regressions in epidemiology. From an observational cohort of electronic medical records, it can find out how RAAS drugs interact with comorbidities, such as hypertension and HL, of patients with severe bouts of C19. Where single variable association tests with outcome can struggle, TDA's higher-order interaction network between different variables enables the discovery of the comorbidities of a disease such as C19 work in concert. AVAILABILITY AND IMPLEMENTATION: Code for performing TDA/RTDA is available in https://github.com/IBM/Matilda and code for CuNA can be found in https://github.com/BiomedSciAI/Geno4SD/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

AI-enabled evaluation of genome-wide association relevance and polygenic risk score prediction in Alzheimer's disease.

GWAS focuses on significance loosing false positives; machine learning probes sub-significant features relying on predictivity. Yet, these are far from orthogonal. We sought to explore how these inform each other in sub-genome-wide significant situations to define relevance for predictive features. We introduce the SVM-based RubricOE that selects heavily cross-validated feature sets, and LDpred2 PRS as a strong contrast to SVM, to explore significance and predictivity. Our Alzheimer's test case notoriously lacks strong genetic signals except for few very strong phenotype-SNP associations, which suits the problem we are exploring. We found that the most significant SNPs among ML and PRS-selected SNPs captured most of the predictivity, while weaker associations tend also to contribute weakly to predictivity. SNPs with weak associations tend not to contribute to predictivity, but deletion of these features does not injure it. Significance provides a ranking that helps identify weakly predictive features.

Coronary artery disease patients with rs7904519 (TCF7L2) are at a persistent risk of type 2 diabetes.

AIMS: Type 2 diabetes (T2D) and coronary artery disease (CAD) often coexist and share genetic factors.This study aimed to investigate the common genetic factors underlying T2D and CAD in patients with CAD. METHODS: A three-step association approach was conducted: a) a discovery step involving 943 CAD patients with T2D and 1,149 CAD patients without T2D; b) an eliminating step to exclude CAD or T2D specific variants; and c) a replication step using the UK Biobank data. RESULTS: Ten genetic loci were associated with T2D in CAD patients. Three variants were specific to either CAD or T2D. Five variants lost significance after adjusting for covariates, while two SNPs remained associated with T2D in CAD patients (rs7904519*G: TCF7L2 and rs17608766*C: GOSR2). The T2D susceptibility rs7904519*G was associated with increased T2D risk, while the CAD susceptibility rs17608766*C was negatively associated with T2D in CAD patients. These associations were replicated in a UK Biobank data, confirming the results. CONCLUSIONS: No significant common T2D and CAD susceptibility genetic association was demonstrated indicating distinct disease pathways. However, CAD patients carrying the T2D susceptibility gene TCF7L2 remain at higher risk for developing T2D emphasizing the need for frequent monitoring in this subgroup.

Homocysteine levels, H-Hypertension, and the MTHFR C677T genotypes: A complex interaction.

Background and objectives: High homocysteine levels are associated with increased risk of hypertension and stroke. Homocysteine is metabolized by the methylenetetrahydrofolate reductase (MTHFR). We aimed to investigate the levels of homocysteine and their association with hypertension, stroke, and antihypertensive medication usage in patients with different MTHFR C677T genotypes. Methods and results: Genotype frequency of MTHFR polymorphism was performed, and plasma homocysteine levels were measured in 2,640 adult Lebanese patients. Hypertension, history of stroke, and list of medications were documented, among other clinical and demographic parameters. The TT mutant genotype and the T mutant allele of MTHFR were more prevalent in hyperhomocysteinemia (HHcy) and H-hypertensive (H-HTN, defined as hypertension with hyperhomocysteinemia) patients when compared to non-HHcy subjects and non H-HTN patients respectively. Homocysteine levels were significantly higher in hypertensive patients specifically among those on diuretics. A higher level of homocysteine was found in hypertensive patients with the MTHFR T allele compared to patients carrying the C allele. Among the T allele carriers, the average plasma homocysteine level was 13.3 ± 0.193 µmol/L for hypertensive subjects compared to 11.9 ± 0.173 µmol/L (non-hypertensives). Furthermore, homocysteine levels significantly correlated with stroke risk in patients with the T alleles. Conclusions: We found an association of homocysteine with hypertension, hypertensive medication, and stroke risk among patients with the MTHFR T allele and the TT genotype. The association of diuretics therapy with higher homocysteine levels calls for routine measurements and therapeutic control of homocysteine in patients on diuretic, to improve health-related outcomes.

The impact of forced displacement: trauma, increased levels of inflammation and early presentation of diabetes in women Syrian refugees.

BACKGROUND: Forced displacement and war trauma cause high rates of post-traumatic stress, anxiety disorders and depression in refugee populations. We investigated the impact of forced displacement on mental health status, gender, presentation of type 2 diabetes (T2D) and associated inflammatory markers among Syrian refugees in Lebanon. METHODS: Mental health status was assessed using the Harvard Trauma Questionnaire (HTQ) and the Hopkins Symptom Checklist-25 (HSCL-25). Additional metabolic and inflammatory markers were analyzed. RESULTS: Although symptomatic stress scores were observed in both men and women, women consistently displayed higher symptomatic anxiety/depression scores with the HSCL-25 (2.13 ± 0.58 versus 1.95 ± 0.63). With the HTQ, however, only women aged 35-55 years displayed symptomatic post-traumatic stress disorder (PTSD) scores (2.18 ± 0.43). Furthermore, a significantly higher prevalence of obesity, prediabetes and undiagnosed T2D were observed in women participants (23.43, 14.91 and 15.18%, respectively). Significantly high levels of the inflammatory marker serum amyloid A were observed in women (11.90 ± 11.27 versus 9.28 ± 6.93, P = 0.036). CONCLUSIONS: Symptomatic PTSD, anxiety/depression coupled with higher levels of inflammatory marker and T2D were found in refugee women aged between 35 and 55 years favoring the strong need for psychosocial therapeutic interventions in moderating stress-related immune dysfunction and development of diabetes in this subset of female Syrian refugees.

Elevated Lp(a) Levels Correlate with Severe and Multiple Coronary Artery Stenotic Lesions.

Backgrounds and Aims: The role of Lipoprotein(a) (Lp(a)) in increasing the risk of cardiovascular diseases is reported in several populations. The aim of this study is to investigate the correlation of high Lp(a) levels with the degree of coronary artery stenosis. Methods: Two hundred and sixty-eight patients were enrolled for this study. Patients who underwent coronary artery angiography and who had Lp(a) measurements available were included in this study. Binomial logistic regressions were applied to investigate the association between Lp(a) and stenosis in the four major coronary arteries. The effect of LDL and HDL Cholesterol on modulating the association of Lp(a) with coronary artery disease (CAD) was also evaluated. Multinomial regression analysis was applied to assess the association of Lp(a) with the different degrees of stenosis in the four major coronary arteries. Results: Our analyses showed that Lp(a) is a risk factor for CAD and this risk is significantly apparent in patients with HDL-cholesterol ≥35 mg/dL and in non-obese patients. A large proportion of the study patients with elevated Lp(a) levels had CAD even when exhibiting high HDL serum levels. Increased HDL with low Lp(a) serum levels were the least correlated with stenosis. A significantly higher levels of Lp(a) were found in patients with >50% stenosis in at least two major coronary vessels arguing for pronounced and multiple stenotic lesions. Finally, the derived variant (rs1084651) of the LPA gene was significantly associated with CAD. Conclusion: Our study highlights the importance of Lp(a) levels as an independent biological marker of severe and multiple coronary artery stenosis.

Topology and redescriptions detect multiple alternative biological pathways from clinical phenotypes.

Biological pathways play a crucial role in the properties of diseases and are important in drug discovery. Identifying the logical relationships among distinctive phenotypic clusters could reveal possible connections to the underlying pathways. However, this process is challenging since clinical phenotypes are often available through unstructured electronic health records. Moreover, in the absence of a standardized questionnaire, there could be bias among physicians toward selecting certain medical terms. In this article, we develop an efficient pipeline to address these challenges and help practitioners to reveal the pathways associated with the disease. We use topological data analysis and redescriptions and propose a pipeline of four phases: (1) pre-processing the clinical notes to extract the salient concepts, (2) constructing a feature space of the patients to characterize the extracted concepts, (3) leveraging the topological properties to distill the available knowledge and visualize the extracted features, and finally, (4) investigating the bias in the clinical notes of the selected features and identify possible pathways. Our experiments on a publicly available dataset of COVID-19 clinical notes testify that our pipeline can indeed extract meaningful pathways.

Observational study of factors associated with morbidity and mortality from COVID-19 in Lebanon, 2020-2021.

BACKGROUND: The COVID-19 pandemic claimed millions of lives worldwide without clear signs of abating despite several mitigation efforts and vaccination campaigns. There have been tremendous interests in understanding the etiology of the disease particularly in what makes it severe and fatal in certain patients. Studies have shown that COVID-19 patients with kidney injury on admission were more likely to develop severe disease, and acute kidney disease was associated with high mortality in COVID-19 hospitalized patients. METHODS: This study investigated 819 COVID-19 patients admitted between January 2020-April 2021 to the COVID-19 ward at a tertiary care center in Lebanon and evaluated their vital signs and biomarkers while probing for two main outcomes: intubation and fatality. Logistic and Cox regressions were performed to investigate the association between clinical and metabolic variables and disease outcomes, mainly intubation and mortality. Times were defined in terms of admission and discharge/fatality for COVID-19, with no other exclusions. RESULTS: Regression analysis revealed that the following are independent risk factors for both intubation and fatality respectively: diabetes (p = 0.021 and p = 0.04), being overweight (p = 0.021 and p = 0.072), chronic kidney disease (p = 0.045 and p = 0.001), and gender (p = 0.016 and p = 0.114). Further, shortness of breath (p<0.001), age (p<0.001) and being overweight (p = 0.014) associated with intubation, while fatality with shortness of breath (p<0.001) in our group of patients. Elevated level of serum creatinine was the highest factor associated with fatality (p = 0.002), while both white blood count (p<0.001) and serum glutamic-oxaloacetic transaminase levels (p<0.001) emerged as independent risk factors for intubation. CONCLUSIONS: Collectively our data show that high creatinine levels were significantly associated with fatality in our COVID-19 study patients, underscoring the importance of kidney function as a main modulator of SARS-CoV-2 morbidity and favor a careful and proactive management of patients with elevated creatinine levels on admission.

K-Mer Analyses Reveal Different Evolutionary Histories of Alpha, Beta, and Gamma Papillomaviruses.

Papillomaviruses (PVs) are a heterogeneous group of DNA viruses that can infect fish, birds, reptiles, and mammals. PVs infecting humans (HPVs) phylogenetically cluster into five genera (Alpha-, Beta-, Gamma-, Mu- and Nu-PV), with differences in tissue tropism and carcinogenicity. The evolutionary features associated with the divergence of Papillomaviridae are not well understood. Using a combination of k-mer distributions, genetic metrics, and phylogenetic algorithms, we sought to evaluate the characteristics and differences of Alpha-, Beta- and Gamma-PVs constituting the majority of HPV genomes. A total of 640 PVs including 442 HPV types, 27 non-human primate PV types, and 171 non-primate animal PV types were evaluated. Our analyses revealed the highest genetic diversity amongst Gamma-PVs compared to the Alpha and Beta PVs, suggesting reduced selective pressures on Gamma-PVs. Using a sequence alignment-free trimer (k = 3) phylogeny algorithm, we reconstructed a phylogeny that grouped most HPV types into a monophyletic clade that was further split into three branches similar to alignment-based classifications. Interestingly, a subset of low-risk Alpha HPVs (the species Alpha-2, 3, 4, and 14) split from other HPVs and were clustered with non-human primate PVs. Surprisingly, the trimer-constructed phylogeny grouped the Gamma-6 species types originally isolated from the cervicovaginal region with the main Alpha-HPV clade. These data indicate that characterization of papillomavirus heterogeneity via orthogonal approaches reveals novel insights into the biological understanding of HPV genomes.

Integrating Linguistics, Social Structure, and Geography to Model Genetic Diversity within India.

India represents an intricate tapestry of population substructure shaped by geography, language, culture, and social stratification. Although geography closely correlates with genetic structure in other parts of the world, the strict endogamy imposed by the Indian caste system and the large number of spoken languages add further levels of complexity to understand Indian population structure. To date, no study has attempted to model and evaluate how these factors have interacted to shape the patterns of genetic diversity within India. We merged all publicly available data from the Indian subcontinent into a data set of 891 individuals from 90 well-defined groups. Bringing together geography, genetics, and demographic factors, we developed Correlation Optimization of Genetics and Geodemographics to build a model that explains the observed population genetic substructure. We show that shared language along with social structure have been the most powerful forces in creating paths of gene flow in the subcontinent. Furthermore, we discover the ethnic groups that best capture the diverse genetic substructure using a ridge leverage score statistic. Integrating data from India with a data set of additional 1,323 individuals from 50 Eurasian populations, we find that Indo-European and Dravidian speakers of India show shared genetic drift with Europeans, whereas the Tibeto-Burman speaking tribal groups have maximum shared genetic drift with East Asians.

Lies, Gosh Darn Lies, and not enough good statistics: why epidemic model parameter estimation fails.

We sought to investigate whether epidemiological parameters that define epidemic models could be determined from the epidemic trajectory of infections, recovery, and hospitalizations prior to peak, and also to evaluate the comparability of data between jurisdictions reporting their statistics. We found that, analytically, the pre-peak growth of an epidemic underdetermines the model variates, and that the rate limiting variables are dominated by the exponentially expanding eigenmode of their equations. The variates quickly converge to the ratio of eigenvector components of the positive growth mode, which determines the doubling time. Without a sound epidemiological study framework, measurements of infection rates and other parameters are highly corrupted by uneven testing rates, uneven counting, and under reporting of relevant values. We argue that structured experiments must be performed to estimate these parameters in order to perform genetic association studies, or to construct viable models accurately predicting critical quantities such as hospitalization loads.

Autosomal genetics and Y-chromosome haplogroup L1b-M317 reveal Mount Lebanon Maronites as a persistently non-emigrating population.

Currently, there are 18 different religious communities living in Lebanon. While evolving primarily within Lebanon, these communities show a level of local isolation as demonstrated previously from their Y-haplogroup distributions. In order to trace the origins and migratory patterns that may have led to the genetic isolation and autosomal clustering in some of these communities we analyzed Y-chromosome STR and SNP sample data from 6327 individuals, in addition to whole genome autosomal sample data from 609 individuals, from Mount Lebanon and other surrounding communities. We observed Y chromosome L1b Levantine STR branching that occurred around 5000 years ago. Autosomal DNA analyses suggest that the North Lebanese Mountain Maronite community possesses an ancestral Fertile Crescent genetic component distinct from other populations in the region. We suggest that the Levantine L1b group split from the Caucasus ancestral group around 7300 years ago and migrated to the Levant. This event was distinct from the earlier expansions from the Caucasus region that contributed to the wider Levantine populations. Differential cultural adaption by populations from the North Lebanese Mountains are clearly aligned with the L1b haplotype STR haplogroup clusters, indicating pre-existing and persistent cultural barriers marked by the transmission of L1b lineages. Our findings highlight the value of uniparental haplogroups and STR haplotype data for elucidating biosocial events among these populations.

Variant analysis of SARS-CoV-2 genomes.

OBJECTIVE: To analyse genome variants of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). METHODS: Between 1 February and 1 May 2020, we downloaded 10 022 SARS CoV-2 genomes from four databases. The genomes were from infected patients in 68 countries. We identified variants by extracting pairwise alignment to the reference genome NC_045512, using the EMBOSS needle. Nucleotide variants in the coding regions were converted to corresponding encoded amino acid residues. For clade analysis, we used the open source software Bayesian evolutionary analysis by sampling trees, version 2.5. FINDINGS: We identified 5775 distinct genome variants, including 2969 missense mutations, 1965 synonymous mutations, 484 mutations in the non-coding regions, 142 non-coding deletions, 100 in-frame deletions, 66 non-coding insertions, 36 stop-gained variants, 11 frameshift deletions and two in-frame insertions. The most common variants were the synonymous 3037C > T (6334 samples), P4715L in the open reading frame 1ab (6319 samples) and D614G in the spike protein (6294 samples). We identified six major clades, (that is, basal, D614G, L84S, L3606F, D448del and G392D) and 14 subclades. Regarding the base changes, the C > T mutation was the most common with 1670 distinct variants. CONCLUSION: We found that several variants of the SARS-CoV-2 genome exist and that the D614G clade has become the most common variant since December 2019. The evolutionary analysis indicated structured transmission, with the possibility of multiple introductions into the population.

Association of waterpipe smoking with myocardial infarction and determinants of metabolic syndrome among catheterized patients.

BACKGROUND: Waterpipe smoking is a rising global public health epidemic perceived by many users to be less harmful, though its toxicity overlaps or even exceeds that of cigarette smoking. Short-term cardiovascular changes due to waterpipe smoking are well established, but longer-term health impacts are still not fully elucidated. OBJECTIVE: We aim to investigate the association of waterpipe smoking with myocardial infarction among patients undergoing cardiac catheterization. METHODS: The study was performed on Lebanese patients referred for cardiac catheterization. Patient's blood was collected for metabolic measures and questionnaires were filled out to include socio-demographic, behavioral and pertinent medical characteristics of the study subjects. RESULTS: Myocardial infarction is significantly and independently associated with waterpipe smoking, with odds ratio (OR) of 1.329 (95% CI: [1.04-1.68]; p = .021), which is lower than that for cigarette smoking (OR = 1.87, 95% CI: [1.63-2.15]; p < .001). Only diabetes showed significant association with waterpipe smoking among MI enrollees (OR = 1.66, 95%CI: [1.04-2.63]; p = .032). CONCLUSION: The study provides yet another evidence for the adverse cardiovascular effects of waterpipe smoking on a clinical level. The harmful effects of waterpipe smoking should be underscored by health care professionals.

Type II diabetes mellitus and hyperhomocysteinemia: a complex interaction.

BACKGROUND: Elevated homocysteine (Hc) levels have a well-established and clear causal relationship to epithelial damage leading to coronary artery disease. Furthermore, it is strongly associated with other metabolic syndrome variables, such as hypertension, which is correlated with type II diabetes mellitus (T2DM). Studies on T2DM in relation to Hc levels have shown both positive and negative associations. The aim of the present study is to examine the relationship between Hc levels and risk of T2DM in the Lebanese population. METHODS: We sought to identify whether Hc associates positively or negatively with diabetes in a case-control study, where 2755 subjects enrolled from patients who had been catheterized for coronary artery diagnosis and treatment. We further sought to identify whether the gene variant MTHFR 667C>T is associated with T2DM, and how Hc and MTHFR 667C>T also impact other correlates of T2DM, including the widely used diuretics in this study population. RESULTS: We found that Hc levels were significantly reduced among subjects with diabetes compared to those without diabetes when adjusted for all potential confounders (OR 0.640; 95% CI [0.44-0.92]; p = 0.0200). The associations between Hc levels and other variates contradicted the result: hypertension associates positively with high Hc levels, and with T2DM. The MTHFR 667C>T only associated significantly with high Hc levels. CONCLUSION: These results suggest population-specific variations among a range of mechanisms that modulate the association of Hc and T2DM, providing a probe for future studies.

Mapping Post-Glacial expansions: The Peopling of Southwest Asia.

Archaeological, palaeontological and geological evidence shows that post-glacial warming released human populations from their various climate-bound refugia. Yet specific connections between these refugia and the timing and routes of post-glacial migrations that ultimately established modern patterns of genetic variation remain elusive. Here, we use Y-chromosome markers combined with autosomal data to reconstruct population expansions from regional refugia in Southwest Asia. Populations from three regions in particular possess distinctive autosomal genetic signatures indicative of likely refugia: one, in the north, centered around the eastern coast of the Black Sea, the second, with a more Levantine focus, and the third in the southern Arabian Peninsula. Modern populations from these three regions carry the widest diversity and may indeed represent the most likely descendants of the populations responsible for the Neolithic cultures of Southwest Asia. We reveal the distinct and datable expansion routes of populations from these three refugia throughout Southwest Asia and into Europe and North Africa and discuss the possible correlations of these migrations to various cultural and climatic events evident in the archaeological record of the past 15,000 years.

Characterizing redescriptions using persistent homology to isolate genetic pathways contributing to pathogenesis.

BACKGROUND: Complex diseases may have multiple pathways leading to disease. E.g. coronary artery disease evolves from arterial damage to their epithelial layers, but has multiple causal pathways. More challenging, those pathways are highly correlated within metabolic syndrome. The challenge is to identify specific clusters of phenotype characteristics (composite phenotypes) that may reflect these different etiologies. Further, GWAS seeking to identify SNPs satisfying multiple composite phenotype descriptions allows for lower false positive rates at lower α thresholds, allowing for the possibility of reducing false negatives. This may provide a window into the missing heritability problem. METHODS: We identify significant phenotype patterns, and identify fuzzy redescriptions among those patterns using Jaccard distances. Further, we construct Vietoris-Rips complexes from the Jaccard distances and compute the persistent homology associated with those. The patterns comprising these topological features are identified as composite phenotpyes, whose genetic associations are explored with logistic regression applied to pathways and to GWAS. RESULTS: We identified several phenotypes that tended to be dominated by metabolic syndrome descriptions, and which were distinct among the combinations of metabolic syndrome conditions. Among SNPs marking the RAAS complex, various SNPs associated specifically with different groups of composite phenotypes, as well as distinguishing between the composite phenotypes and simple phenotypes. Each of these showed different genetic associations, namely rs6693954, rs762551, rs1378942, and rs1133323. GWAS identified SNPs that associated with composite phenotypes included rs12365545, rs6847235, and rs701319. Eighteen GWAS identified SNPs appeared in combinations supported in composite combinations with greater power than for any individual phenotype. CONCLUSIONS: We do find systematic associations among metabolic syndrome variates that show distinctive genetic association profiles. Further, the systematic characterization involves composite phenotype descriptions that allow for combined power of individual phenotype GWAS tests, yielding more significance for lower individual thresholds, permitting the exploration of SNPs that would otherwise show as false negatives.

Caffeine Impact on Metabolic Syndrome Components Is Modulated by a CYP1A2 Variant.

Cultural, dietary, and lifestyle factors are the main modulators of type 2 diabetes mellitus (T2DM) disease risk. Coffee is one of the most popular worldwide beverages, and recent epidemiological studies have showed that coffee consumption is associated with a lower risk of T2DM. This study investigates the impact of coffee intake on T2DM risk and assesses the effect of CYP variants with caffeine exposures on T2DM. Data from 7,607 study subjects were analyzed by logistic regression models, among whom 3,290 GWAS data were available for CYP variants association studies using Plink analysis. These data suggest a protective relationship for women, but not for men; however, the results were not statistically significant in this dataset and there is a significant interaction in favor of women regarding heavy coffee consumption. The interaction between male gender and heavy coffee consumption becomes significant, thereby tending to cancel the protective effect of coffee for males. CYP rs2470890 allele 'C' increases the odds of T2DM by a factor of around 1.2 but decreases the odds of caffeine boosting T2DM of 1.7 by a factor of 0.77. rs2470890 showed an association with T2DM only when the interaction with coffee was considered, thereby setting an example of genetic activation by dietary changes associating with metabolic syndrome.

Association of coronary artery disease and chronic kidney disease in Lebanese population.

BACKGROUND: More evidence is emerging on the strong association between chronic kidney disease (CKD) and cardiovascular disease. We assessed the relationship between coronary artery disease (CAD) and renal dysfunction level (RDL) in a group of Lebanese patients. METHODS: A total of 1268 patients undergoing cardiac catheterization were sequentially enrolled in a multicenter cross sectional study. Angiograms were reviewed and CAD severity scores (CADSS) were determined. Estimated glomerular filtration rate (eGFR) was calculated and clinical and laboratory data were obtained. CKD was defined as eGFR < 60 ml/min. Logistic regression model was performed using multivariate analysis including all traditional risk factors associated with both diseases. ANOVA and the Tukeytestswere used to compare subgroups of patients and to assess the impact of each disease on the severity of the other. RESULTS: Among the 82% patients who exhibited variable degrees of CAD, 20.6% had an eGFR < 60 ml/min. Logistic regression analysis revealed a bidirectional independent association between CAD and CKD with an OR = 2.01 (P < 0.01) and an OR = 1.99 (P < 0.01) for CAD and CKD frequencies, respectively. We observed a steady increase in the CADSS mean as eGFR declined and a progressive reduction in renal function with the worsening of CAD (P < 0.05). This correlation remained highly significant despite considerable inter-patient variability and was at its highest at the most advanced stages of both diseases. CONCLUSIONS: Our results show a strong, independent and graded bidirectional relationship between CAD severity and RDL. We propose to add CAD to the list of risk factors for the development and progression of CKD.