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Biomedical subjects

Xavier Farré

Publications and source records attributed to Xavier Farré.

2 recordsLinked to original sources

Genetic trade-offs in fertility and longevity explain the maintenance of disease-associated alleles in humans.

Genetic variants that increase the risk for complex diseases persist in human populations, despite adverse effects on health and longevity. Life-history theory predicts that such alleles can be maintained by trade-offs arising from pleiotropy, yet direct genomic evidence has been limited. We asked whether disease-associated variants persist because they enhance reproduction, despite costs to health and lifespan. By analysing genome-wide data across 62 diseases, longevity and fertility, we show that disease-risk alleles are, on average, associated with reduced longevity and increased fertility. Moreover, the subset of alleles that increase both fertility and disease risk appear to have been favoured by natural selection over the past 50,000 years. Using Mendelian randomization, we detect a causal effect of genetic liability to disease on longevity, but no robust evidence for a causal effect on fertility; importantly, these estimates remain stable after adjusting for socioeconomic factors. At the individual level, we compared offspring numbers between affected and unaffected individuals with high polygenic disease risk. For most diseases, affected individuals had more children than unaffected ones. But for early-onset diseases, the pattern reverses, indicating reproductive costs of early morbidity. Together, these results support antagonistic pleiotropy and help explain the persistence of disease-risk alleles in human populations.

Humans

VEGFA sex-specific signature is associated to long COVID symptom persistence.

BACKGROUND: Long COVID involves persistent symptoms after COVID-19 recovery, affecting multiple organ systems for months or years. Risk factors include female sex, prior chronic conditions, severe SARS-CoV-2 infection, reinfections, and lack of vaccination. As a major public health concern, ongoing research continues to investigate its causes, mechanisms, and long-term effects. METHODS: Proteomic expression analysis of 171 individuals, in two time points, with confirmed SARS-CoV-2 infection, including 133 long COVID patients from the deeply characterized COVICAT cohort, assessed 1395 protein biomarkers using Olink® technology. Statistical analyses with linear mixed models examined protein expression changes, long COVID status, and sex-specific differences. Functional analysis included gene set enrichment analysis and protein-protein interaction networks. RESULTS: Findings revealed VEGFA overexpression in long COVID patients (effect size 0.322, SE = 0.098, p = 0.0013), along with sex-specific expression patterns and the influence of sex-hormonal status in females, with significant overexpression of circulating VEGFA levels specifically in postmenopausal women (Mann-Whitney U test p value = 8.55 × 10-3). Network analysis identified 109 nodes and 274 edges, with VEGFA ranking highest in centrality. Dysregulated chemokine signaling, complement activation, and viral reactivation were also confirmed, consistent with prior studies. CONCLUSIONS: Using high-throughput proteomic profiling in a population-based cohort, we observed that vascular dysfunction, particularly involving VEGFA, is a key feature of long COVID, especially in milder cases, with significant overexpression of VEGFA in postmenopausal women. Sex-specific proteomic patterns suggest distinct recovery mechanisms, highlighting the need to consider sex, vascular health, and disease severity in the pathogenesis and management of long COVID.

Humans