Associations Between Dietary Patterns and Kidney Health Assessed in the Population-Based CHRIS Study Using Reduced Rank Regression.

OBJECTIVE: While diet plays a key role in chronic kidney disease (CKD) management, the potential for diet to impact CKD prevention in the general population is less clear. Using a priori knowledge, we derived disease-related dietary patterns (DPs) through reduced rank regression (RRR) and investigated associations with kidney function, separately focusing on generally healthy individuals and those with self-reported kidney diseases, hypertension, or diabetes mellitus. METHODS: Eight thousand six hundred eighty-six participants from the population-based Cooperative Health Research in South Tyrol study were split into a group free of kidney disease, hypertension and diabetes (n = 6,133) and a group with any of the 3 conditions (n = 2,553). Diet was assessed through the self-administered Global Allergy and Asthma Network of Excellence food frequency questionnaire and DPs were derived through RRR selecting food frequency questionnaire-derived sodium, potassium, phosphorus, and protein intake as mediators. Outcomes were creatinine-based estimated glomerular filtration rate, urinary albumin-to-creatinine ratio, CKD and microalbuminuria. Multiple linear and logistic models were used to assess associations between RRR-based DPs and kidney outcomes separately in the 2 analytic groups. RESULTS: We identified 3 DPs, where high adherence reflected high levels of all nutrients (DP1), high potassium-phosphorus and low protein-sodium levels (DP2), and low potassium-sodium and high protein-phosphorus levels (DP3), respectively. We observed heterogeneous associations with kidney outcomes, varying by analytic group and sex. Kidney outcomes were much more strongly associated with DPs than with single nutrients. CONCLUSION: RRR is a feasible approach to estimate disease-related DPs and explore the combined effects of nutrients on kidney health. Heterogeneous associations across kidney outcomes suggest possible specificity to kidney function or damage. In individuals reporting kidney disease, hypertension or diabetes, specific dietary habits were associated with better kidney health, indicating that disease-specific dietary interventions can be effective for disease control.

Integrating multiple kidney function markers to predict all-cause and cardiovascular disease mortality: prospective analysis of 366 758 UK Biobank participants.

Background: Reduced kidney function is a risk factor of cardiovascular and all-cause mortality. This association was demonstrated for several kidney function markers, but it is unclear whether integrating multiple measured markers may improve mortality risk prediction. Methods: We conducted an exploratory factor analysis (EFA) of serum creatinine- and cystatin C-based estimated glomerular filtration rate [eGFRcre and eGFRcys; derived by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and European Kidney Function Consortium (EKFC) equations], blood urea nitrogen (BUN), uric acid and serum albumin among 366 758 participants in the UK Biobank without a history of kidney failure. Fitting Cox proportional hazards models, we compared the ability of the identified latent factors to predict overall mortality and mortality by cardiovascular disease (CVD), also considering CVD-specific causes like coronary heart disease (CHD) and cerebrovascular disease. Results: During 12.5 years of follow-up, 26 327 participants died from any cause, 5376 died from CVD, 2908 died from CHD and 1116 died from cerebrovascular disease. We identified two latent factors, EFA1 and EFA2, both representing kidney function variations. When using the CKD-EPI equation, EFA1 performed like eGFRcys, with EFA1 showing slightly larger hazard ratios for overall and CVD-related mortality. At 10 years of follow-up, EFA1 and eGFRcys showed moderate discrimination performance for CVD-related mortality, outperforming all other kidney indices. eGFRcre was the least predictive marker across all outcomes. When using the EKFC equation, eGFRcys performed better than EFA1 while all other results remaining similar. Conclusions: While EFA is an attractive approach to capture the complex effects of kidney function, eGFRcys remains the most practical and effective measurement for all-cause and CVD mortality risk prediction.

Genetic determinants of complement activation in the general population.

Complement is a fundamental innate immune response component. Its alterations are associated with severe systemic diseases. To illuminate the complement's genetic underpinnings, we conduct genome-wide association studies of the functional activity of the classical (CP), lectin (LP), and alternative (AP) complement pathways in the Cooperative Health Research in South Tyrol study (n = 4,990). We identify seven loci, encompassing 13 independent, pathway-specific variants located in or near complement genes (CFHR4, C7, C2, MBL2) and non-complement genes (PDE3A, TNXB, ABO), explaining up to 74% of complement pathways' genetic heritability and implicating long-range haplotypes associated with LP at MBL2. Two-sample Mendelian randomization analyses, supported by transcriptome- and proteome-wide colocalization, confirm known causal pathways, establish within-complement feedback loops, and implicate causality of ABO on LP and of CFHR2 and C7 on AP. LP causally influences collectin-11 and KAAG1 levels and the risk of mouth ulcers. These results build a comprehensive resource to investigate the role of complement in human health.

Genome-Wide Association Study Meta-Analysis Uncovers Novel Genetic Variants Associated with Olfactory Dysfunction.

IMPORTANCE: Olfactory dysfunction is among the earliest signs of many age-related neurodegenerative diseases and has been associated with increased mortality in older adults; however, its genetic basis remains largely unknown. OBJECTIVE: To identify the genetic loci associated with olfactory dysfunction in the general population. DESIGN SETTING AND PARTIICIPANTS: This genome-wide association study meta-analysis (GWMA) included participants of European ancestry (N = 22,730) enrolled in four different large population-based studies, followed by a multi-ancestry GWMA including participants of African ancestry (N = 1,030). The data analysis was performed from March 2023 through June 2024. EXPOSURES: Genome-wide single nucleotide polymorphisms. MAIN OUTCOMES AND MEASURES: Olfactory dysfunction was the outcome and assessed using a 12-item smell identification test. RESULTS: GWMA revealed a novel genome-wide significant locus (tagged by rs11228623 at 11q12) associated with olfactory dysfunction. Gene-based analysis revealed a high enrichment for olfactory receptor genes in this region. Phenome-wide association studies demonstrated associations between genetic variants related to olfactory dysfunction and blood cell counts, kidney function, skeletal muscle mass, cholesterol levels and cardiovascular disease. Using individual-level data, we also confirmed and quantified the strength of these associations on a phenotypic level. Moreover, employing two-sample Mendelian Randomization analyses, we found evidence for causal associations between olfactory dysfunction and these phenotypes. CONCLUSIONS: These findings provide novel insights into the genetic architecture of the sense of smell and highlight its importance for many aspects of human health.

Nuclear and mitochondrial genetic variants associated with mitochondrial DNA copy number.

Mitochondrial DNA copy number (mtDNA-CN) is a biomarker for mitochondrial dysfunction associated with several diseases. Previous genome-wide association studies (GWAS) have been performed to unravel underlying mechanisms of mtDNA-CN regulation. However, the identified gene regions explain only a small fraction of mtDNA-CN variability. Most of this data has been estimated from microarrays based on various pipelines. In the present study we aimed to (1) identify genetic loci for qPCR-measured mtDNA-CN from three studies (16,130 participants) using GWAS, (2) identify potential systematic differences between our qPCR derived mtDNA-CN measurements compared to the published microarray intensity-based estimates, and (3) disentangle the nuclear from mitochondrial regulation of the mtDNA-CN phenotype. We identified two genome-wide significant autosomal loci associated with qPCR-measured mtDNA-CN: at HBS1L (rs4895440, p = 3.39 × 10-13) and GSDMA (rs56030650, p = 4.85 × 10-08) genes. Moreover, 113/115 of the previously published SNPs identified by microarray-based analyses were significantly equivalent with our findings. In our study, the mitochondrial genome itself contributed only marginally to mtDNA-CN regulation as we only detected a single rare mitochondrial variant associated with mtDNA-CN. Furthermore, we incorporated mitochondrial haplogroups into our analyses to explore their potential impact on mtDNA-CN. However, our findings indicate that they do not exert any significant influence on our results.