Publications by authors named "A Lionikas"
Article Synopsis
- Age-related macular degeneration (AMD) is a leading cause of central vision loss, with age, genetics, and smoking as key risk factors.
- Machine learning was used to predict biological age across different organ systems and assess their association with AMD, revealing that most organ systems in AMD patients showed accelerated ageing, particularly the immune system in younger males.
- Interestingly, AMD patients had slower ageing in their liver compared to controls, especially in females, and genetic risk scores for AMD correlated with faster ageing in most organs, highlighting the complex relationship between AMD and biological ageing.
Article Synopsis
- Genetic variability plays a crucial role in differences in skeletal muscle mass, but the specific genes responsible are not well understood; this study focuses on Rps6ka6 and Pou3f4 genes located on chromosome X in mice.
- The study involved analyzing muscle samples from male CFW mice with different alleles linked to muscle mass, revealing that the "increasing" allele led to larger muscle size and more muscle fibers, particularly in the fast-twitch extensor digitorum longus muscle.
- Findings suggest that Rps6ka6 influences muscle fiber count in fast-twitch muscles, whereas the Pou3f4 gene impacts fiber numbers in slow-twitch muscles, indicating distinct genetic roles in muscle development.
Aims: Stanniocalcin-2 (STC2) has recently been implicated in human muscle mass variability by genetic analysis. Biochemically, STC2 inhibits the proteolytic activity of the metalloproteinase PAPP-A, which promotes muscle growth by upregulating the insulin-like growth factor (IGF) axis. The aim was to examine if STC2 affects skeletal muscle mass and to assess how the IGF axis mediates muscle hypertrophy induced by functional overload.
View Article and Find Full Text PDFCombining samples for genetic association is standard practice in human genetic analysis of complex traits, but is rarely undertaken in rodent genetics. Here, using 23 phenotypes and genotypes from two independent laboratories, we obtained a sample size of 3076 commercially available outbred mice and identified 70 loci, more than double the number of loci identified in the component studies. Fine-mapping in the combined sample reduced the number of likely causal variants, with a median reduction in set size of 51%, and indicated novel gene associations, including Pnpo, Ttll6, and GM11545 with bone mineral density, and Psmb9 with weight.
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