The 3p21.31 genetic locus promotes progression to type 1 diabetes through the CCR2/CCL2 pathway

The association of rs17713054 with Neanderthal origin at 3p21.31 locus with the severity of COVID-19 in Iranian patients

Since the COVID-19 pandemic, the diversity of clinical manifestations in patients has been a tremendous challenge. It seems that genetic variations, as one of the players, contribute to the variety of symptoms. Genome-wide association studies have demonstrated the influence of certain genomic regions on the disease prognosis. Particularly, a haplotype at 3p21.31 locus, inherited from Neanderthals, showed an association with COVID-19 severity. Despite several studies regarding this haplotype, some key variants are not sufficiently addressed. In the present study, we investigated the association of rs17713054 at 3p21.31 with COVID-19 severity. We analyzed the genotype of 251 Iranian COVID-19 patients (151 patients with asymptomatic to mild form as control and 100 patients with severe to critical symptoms without any comorbidities as case group) using the ARMS-PCR method. Results demonstrated that the A allele confers an almost twofold increased risk for COVID-19 severity (P value = 0.008). The AA genotype also raises the risk by more than 11 times following the recessive model (P value = 0.013). In conclusion, the A allele in rs17713054 was a risk allele in Iranian patients and was independently associated with COVID-19 severity. More studies are beneficial to confirm these findings in other populations and to develop strategies for risk assessment, prevention, and personalized medicine.

Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics

Multimorbidity is characterized by multidimensional complexity emerging from interactions between multiple diseases across levels of biological (including genetic) and environmental determinants and the complex array of interactions between and within cells, tissues and organ systems. Advances in spatial genomic research have led to an unprecedented expansion in our ability to link alterations in genome folding with changes that are associated with human disease. Studying disease-associated genetic variants in the context of the spatial genome has enabled the discovery of transcriptional regulatory programmes that potentially link dysregulated genes to disease development. However, the approaches that have been used have typically been applied to uncover pathological molecular mechanisms occurring in a specific disease-relevant tissue. These forms of reductionist, targeted investigations are not appropriate for the molecular dissection of multimorbidity that typically involves contributions from multiple tissues. In this perspective, we emphasize the importance of a whole-body understanding of multimorbidity and discuss how spatial genomics, when integrated with additional omic datasets, could provide novel insights into the molecular underpinnings of multimorbidity.