Genome-Wide Association Study of Susceptibility to Pseudomonas aeruginosa Infection in Cystic Fibrosis.

QUESTION: Pseudomonas aeruginosa (Pa) is a common pathogen that contributes to progressive lung disease in Cystic Fibrosis (CF). Genetic factors other than CF-causing CFTR variations contribute approximately 85% of the variation in chronic Pa infection age in CF according to twin studies, but the susceptibility loci remain unknown. Our objective is to advance understanding of the genetic basis of host susceptibility to Pa infection. MATERIALS AND METHODS: We conducted a genome-wide association study (GWAS) of chronic Pa infection age in 1037 Canadians with CF. We subsequently assessed the genetic correlation between chronic Pa infection age and lung function through polygenic risk score (PRS) analysis and inferred their causal relationship through bi-directional Mendelian Randomization analysis. RESULTS: Two novel genome-wide significant loci with lead SNPs rs62369766 (chr5p12; p-value= 1.98 ×10-8) and rs927553 (chr13q12.12; p-value= 1.91 × 10-8) were associated with chronic Pa infection age. The rs62369766 locus was validated using an independent French cohort (N=501). Furthermore, PRS constructed from CF lung function-associated SNPs was significantly associated with chronic Pa infection age (p-value=0.002). Finally, our analysis presented evidence for a causal effect of lung function on the chronic Pa infection age (Beta=0.782 years, p-value= 4.24 × 10-4). In the reverse direction, we observed a moderate effect (Beta=0.002, p-value=0.012). CONCLUSIONS: We identified two novel loci that are associated with chronic Pa infection age in individuals with CF. Additionally, we provided evidence of common genetic contributors and a potential causal relationship between Pa infection susceptibility and lung function in CF. Therapeutics targeting these genetic factors may delay the onset of chronic infections which accounts for significant remaining morbidity in CF.

The prevalence and genotype distribution of human papillomavirus in central Fujian Province during the COVID-19 pandemic.

BACKGROUND: Global human activities were significantly impacted by the emergence of the coronavirus disease 2019 (COVID-19) pandemic caused by the 2019 novel coronavirus. This study aimed to investigate the prevalence and genotype distribution of HPV infection in Central Fujian Province during the pandemic. METHODS: Cervical samples were collected from 21,612 outpatients and 12,664 females who underwent physical examinations and HPV screening at the People's Hospital of Fujian Province in Fuzhou from April 2020 to April 2023. HPV detection and genotyping were conducted using PCR hybridization. RESULTS: The overall HPV infection rate was 16.1% during the COVID-19 pandemic, with the outpatient group exhibiting a greater infection rate (19.0%) than did the healthy group (12.3%). The top five high-risk HPV (HR-HPV) genotypes in both groups were HPV52, HPV53, HPV58, HPV16, and HPV51. Additionally, HPV81 and HPV43 were the two most common low-risk HPV (LR-HPV) genotypes in the patient group, while HPV81 and HPV42 were the two most common LR-HPV genotypes in the healthy group. The highest prevalence of HPV infection was observed in individuals aged ≤ 24 years (28.4%, 95% CI 25.9-30.9), followed by those aged ≥ 55 years (23.6%, 95% CI 21.6-24.7) and other age groups. The prevalence decreased from 23.0% (95% CI 22.4-23.7) in 2018-2019 to 13.8% (95% CI 12.0-15.5) in 2023. CONCLUSION: This study provides valuable insights into the prevalence and genotypes of HPV infection in the female population of Central Fujian Province from 2020 to 2023. The findings indicate that the prevalence of HPV infection in Central Fujian Province remains relatively low compared to the national average. Furthermore, the prevalence of HPV decreased during the COVID-19 pandemic; however, as the pandemic waned, there was potential for an increase in HPV infection rates. Therefore, it is crucial to strengthen HPV screening and vaccination strategies to prevent the potential spread of HPV.

Better together against genetic heterogeneity: A sex-combined joint main and interaction analysis of 290 quantitative traits in the UK Biobank.

Genetic effects can be sex-specific, particularly for traits such as testosterone, a sex hormone. While sex-stratified analysis provides easily interpretable sex-specific effect size estimates, the presence of sex-differences in SNP effect implies a SNP×sex interaction. This suggests the usage of the often overlooked joint test, testing for an SNP's main and SNP×sex interaction effects simultaneously. Notably, even without individual-level data, the joint test statistic can be derived from sex-stratified summary statistics through an omnibus meta-analysis. Utilizing the available sex-stratified summary statistics of the UK Biobank, we performed such omnibus meta-analyses for 290 quantitative traits. Results revealed that this approach is robust to genetic effect heterogeneity and can outperform the traditional sex-stratified or sex-combined main effect-only tests. Therefore, we advocate using the omnibus meta-analysis that captures both the main and interaction effects. Subsequent sex-stratified analysis should be conducted for sex-specific effect size estimation and interpretation.

Association Between Obesity and Chronic Kidney Disease: Multivariable Mendelian Randomization Analysis and Observational Data From a Bariatric Surgery Cohort.

Obesity is postulated to independently increase chronic kidney disease (CKD), even after adjusting for type 2 diabetes (T2D) and hypertension. Dysglycemia below T2D thresholds, frequently seen with obesity, also increases CKD risk. Whether obesity increases CKD independent of dysglycemia and hypertension is unknown and likely influences the optimal weight loss (WL) needed to reduce CKD. T2D remission rates plateau with 20-25% WL after bariatric surgery (BS), but further WL increases normoglycemia and normotension. We undertook bidirectional inverse variance weighted Mendelian randomization (IVWMR) to investigate potential independent causal associations between increased BMI and estimated glomerular filtration rate (eGFR) in CKD (CKDeGFR) (<60 mL/min/1.73 m2) and microalbuminuria (MA). In 5,337 BS patients, we assessed whether WL influences >50% decline in eGFR (primary outcome) or CKD hospitalization (secondary outcome), using <20% WL as a comparator. IVWMR results suggest that increased BMI increases CKDeGFR (b = 0.13, P = 1.64 × 10-4; odds ratio [OR] 1.14 [95% CI 1.07, 1.23]) and MA (b = 0.25; P = 2.14 × 10-4; OR 1.29 [1.13, 1.48]). After adjusting for hypertension and fasting glucose, increased BMI did not significantly increase CKDeGFR (b = -0.02; P = 0.72; OR 0.98 [0.87, 1.1]) or MA (b = 0.19; P = 0.08; OR 1.21 [0.98, 1.51]). Post-BS WL significantly reduced the primary outcome with 30 to <40% WL (hazard ratio [HR] 0.53 [95% CI 0.32, 0.87]) but not 20 to <30% WL (HR 0.72 [0.44, 1.2]) and ≥40% WL (HR 0.73 [0.41, 1.30]). For CKD hospitalization, progressive reduction was seen with increased WL, which was significant for 30 to <40% WL (HR 0.37 [0.17, 0.82]) and ≥40% WL (HR 0.24 [0.07, 0.89]) but not 20 to <30% WL (HR 0.60 [0.29, 1.23]). The data suggest that obesity is likely not an independent cause of CKD. WL thresholds previously associated with normotension and normoglycemia, likely causal mediators, may reduce CKD after BS.

Analysis of gut microbiota diversity in Hashimoto's thyroiditis patients.

BACKGROUND: Hashimoto's thyroiditis (HT) is an autoimmune disease. Recent studies have found that the gut microbiota may play an important role in inducing HT, but there are no systematic studies on the changes in the gut microbiota during the development of HT. METHODS: In this study, 16S rDNA high-throughput sequencing technology in combination with the Kruskal-Wallis test, CCA/RDA analysis, Spearman correlation analysis, and other statistical methods were used to analyze the effects of age, gender, hormones, and other environmental factors on gut microbiota by comparing the differences in the microbiota at different stages of HT development. RESULTS: The results showed that there were differences in the gut microbiota composition between healthy people (HCA) and in patients with HT. Lachnoclostridium, Bilophila, and Klebsiella were enriched in the HCA group, while Akkermansia, Lachnospiraceae, Bifidobacterium, Shuttleia, and Clostriworthdia were enriched in the HT group. Environmental factors analysis revealed that the Bifidobacterium and Klebsiella were two groups of bacteria that have undergone dramatic changes in HCA and HT, and mainly affected by gender. Romboutsia and Haemophilus regulated by the hormone of free triiodothyronine (FT3) may promote the development of HT, while Faecalibacterium and Lachnospiraceae regulated by free thyroxine (FT4) may protect the host. CONCLUSIONS: Comprehensive studies have shown that gender is an important factor affecting gut microbial composition, but with the development of HT, hormones, age, and TSH begin to become dominant factors.

Interacting evolutionary pressures drive mutation dynamics and health outcomes in aging blood.

Age-related clonal hematopoiesis (ARCH) is characterized by age-associated accumulation of somatic mutations in hematopoietic stem cells (HSCs) or their pluripotent descendants. HSCs harboring driver mutations will be positively selected and cells carrying these mutations will rise in frequency. While ARCH is a known risk factor for blood malignancies, such as Acute Myeloid Leukemia (AML), why some people who harbor ARCH driver mutations do not progress to AML remains unclear. Here, we model the interaction of positive and negative selection in deeply sequenced blood samples from individuals who subsequently progressed to AML, compared to healthy controls, using deep learning and population genetics. Our modeling allows us to discriminate amongst evolutionary classes with high accuracy and captures signatures of purifying selection in most individuals. Purifying selection, acting on benign or mildly damaging passenger mutations, appears to play a critical role in preventing disease-predisposing clones from rising to dominance and is associated with longer disease-free survival. Through exploring a range of evolutionary models, we show how different classes of selection shape clonal dynamics and health outcomes thus enabling us to better identify individuals at a high risk of malignancy.