BACKGROUND: The use of molecular biomarkers for COVID-19 remains unconclusive. The application of a molecular biomarker in combination with clinical ones that could help classifying aggressive patients in first steps of the disease could help clinician and sanitary system a better management of the disease. Here we characterize the role of ACE2, AR, MX1, ERG, ETV5 and TMPRSS2 for trying a better classification of COVID-19 through knowledge of the disease mechanisms. METHODS: A total of 329 blood samples were genotyped in ACE2, MX1 and TMPRSS2. RNA analyses were also performed from 258 available samples using quantitative polymerase chain reaction for genes: ERG, ETV5, AR, MX1, ACE2, and TMPRSS2. Moreover, in silico analysis variant effect predictor, ClinVar, IPA, DAVID, GTEx, STRING and miRDB database was also performed. Clinical and demographic data were recruited from all participants following WHO classification criteria. RESULTS: We confirm the use of ferritin (p < 0.001), D-dimer (p < 0.010), CRP (p < 0.001) and LDH (p < 0.001) as markers for distinguishing mild and severe cohorts. Expression studies showed that MX1 and AR are significantly higher expressed in mild vs severe patients (p < 0.05). ACE2 and TMPRSS2 are involved in the same molecular process of membrane fusion (p = 4.4 × 10-3), acting as proteases (p = 0.047). CONCLUSIONS: In addition to the key role of TMPSRSS2, we reported for the first time that higher expression levels of AR are related with a decreased risk of severe COVID-19 disease in females. Moreover, functional analysis demonstrates that ACE2, MX1 and TMPRSS2 are relevant markers in this disease.

BACKGROUND: Cardiovascular diseases and especially Acute Coronary Syndrome (ACS) constitute a major health issue impacting millions of patients worldwide. Being a leading cause of death and hospital admissions in many European countries including Spain, it accounts for enormous amounts of healthcare expenditures for its management. Clopidogrel is one of the oldest antiplatelet medications used as standard of care in ACS. METHODS: In this study, we performed an economic evaluation study to estimate whether a genome-guided clopidogrel treatment is cost-effective compared to conventional one in a large cohort of 243 individuals of Spanish origin suffering from ACS and treated with clopidogrel. Data were derived from the U-PGx PREPARE clinical trial. Effectiveness was measured as survival of individuals while study data on safety and efficacy, as well as on resource utilization associated with each adverse drug reaction were used to measure costs to treat these adverse drug reactions. A generalized linear regression model was used to estimate cost differences for both study groups. RESULTS: Based on our findings, PGx-guided treatment group is cost-effective. PGx-guided treatment demonstrated to have 50% less hospital admissions, reduced emergency visits and almost 13% less ADRs compared to the non-PGx approach with mean QALY 1.07 (95% CI, 1.04-1.10) versus 1.06 (95% CI, 1.03-1.09) for the control group, while life years for both groups were 1.24 (95% CI, 1.20-1.26) and 1.23 (95% CI, 1.19-1.26), respectively. The mean total cost of PGx-guided treatment was 50% less expensive than conventional therapy with clopidogrel [€883 (95% UI, €316-€1582), compared to €1,755 (95% UI, €765-€2949)]. CONCLUSION: These findings suggest that PGx-guided clopidogrel treatment represents a cost-effective option for patients suffering from ACS in the Spanish healthcare setting.

BACKGROUND: Knowledge of the frequency of rare SERPINA1 mutations could help in the management of alpha1 antitrypsin deficiency (AATD). The present study aims to assess the frequencies of rare and null alleles and their respiratory and hepatic pathogenicity. METHODS: This is a secondary analysis of a study that evaluated the viability of the Progenika diagnostic genotyping system in six different countries by analyzing 30,827 samples from cases of suspected AATD. Allele-specific genotyping was carried out with the Progenika A1AT Genotyping Test which analyses 14 mutations in buccal swabs or dried blood spots samples. SERPINA1 gene sequencing was performed for serum AAT-genotype discrepancies or by request of the clinician. Only cases with rare mutations were included in this analysis. RESULTS: There were 818 cases (2.6%) carrying a rare allele, excluding newly identified mutations. All were heterozygous except for 20 that were homozygous. The most frequent alleles were the M-like alleles, PI*Mmalton and PI*Mheerlen. Of the 14 mutations included in the Progenika panel, there were no cases detected of PI*Siiyama, PI*Q0granite falls and PI*Q0west. Other alleles not included in the 14-mutation panel and identified by gene sequencing included PI*Mwürzburg, PI*Zbristol, and PI*Zwrexham, and the null alleles PI*Q0porto, PI*Q0madrid, PI*Q0brescia, and PI*Q0kayseri. CONCLUSIONS: The Progenika diagnostic network has allowed the identification of several rare alleles, some unexpected and not included in the initial diagnostic panel. This establishes a new perspective on the distribution of these alleles in different countries. These findings may help prioritize allele selection for routine testing and highlights the need for further research into their pathogenetic role.

Atrial fibrillation (AF) and heart failure (HF) contribute to about 45% of all cardiovascular disease (CVD) deaths in the USA and around the globe. Due to the complex nature, progression, inherent genetic makeup, and heterogeneity of CVDs, personalized treatments are believed to be critical. To improve the deciphering of CVD mechanisms, we need to deeply investigate well-known and identify novel genes that are responsible for CVD development. With the advancements in sequencing technologies, genomic data have been generated at an unprecedented pace to foster translational research. Correct application of bioinformatics using genomic data holds the potential to reveal the genetic underpinnings of various health conditions. It can help in the identification of causal variants for AF, HF, and other CVDs by moving beyond the one-gene one-disease model through the integration of common and rare variant association, the expressed genome, and characterization of comorbidities and phenotypic traits derived from the clinical information. In this study, we examined and discussed variable genomic approaches investigating genes associated with AF, HF, and other CVDs. We collected, reviewed, and compared high-quality scientific literature published between 2009 and 2022 and accessible through PubMed/NCBI. While selecting relevant literature, we mainly focused on identifying genomic approaches involving the integration of genomic data; analysis of common and rare genetic variants; metadata and phenotypic details; and multi-ethnic studies including individuals from ethnic minorities, and European, Asian, and American ancestries. We found 190 genes associated with AF and 26 genes linked to HF. Seven genes had implications in both AF and HF, which are SYNPO2L, TTN, MTSS1, SCN5A, PITX2, KLHL3, and AGAP5. We listed our conclusion, which include detailed information about genes and SNPs associated with AF and HF.

BACKGROUND: Haploinsufficiency of the transcription factor PAX6 is the main cause of congenital aniridia, a genetic disorder characterized by iris and foveal hypoplasia. 11p13 microdeletions altering PAX6 or its downstream regulatory region (DRR) are present in about 25% of patients; however, only a few complex rearrangements have been described to date. Here, we performed nanopore-based whole-genome sequencing to assess the presence of cryptic structural variants (SVs) on the only two unsolved "PAX6-negative" cases from a cohort of 110 patients with congenital aniridia after unsuccessfully short-read sequencing approaches. RESULTS: Long-read sequencing (LRS) unveiled balanced chromosomal rearrangements affecting the PAX6 locus at 11p13 in these two patients and allowed nucleotide-level breakpoint analysis. First, we identified a cryptic 4.9 Mb de novo inversion disrupting intron 7 of PAX6, further verified by targeted polymerase chain reaction amplification and sequencing and FISH-based cytogenetic analysis. Furthermore, LRS was decisive in correctly mapping a t(6;11) balanced translocation cytogenetically detected in a second proband with congenital aniridia and considered non-causal 15 years ago. LRS resolved that the breakpoint on chromosome 11 was indeed located at 11p13, disrupting the DNase I hypersensitive site 2 enhancer within the DRR of PAX6, 161 Kb from the causal gene. Patient-derived RNA expression analysis demonstrated PAX6 haploinsufficiency, thus supporting that the 11p13 breakpoint led to a positional effect by cleaving crucial enhancers for PAX6 transactivation. LRS analysis was also critical for mapping the exact breakpoint on chromosome 6 to the highly repetitive centromeric region at 6p11.1. CONCLUSIONS: In both cases, the LRS-based identified SVs have been deemed the hidden pathogenic cause of congenital aniridia. Our study underscores the limitations of traditional short-read sequencing in uncovering pathogenic SVs affecting low-complexity regions of the genome and the value of LRS in providing insight into hidden sources of variation in rare genetic diseases.

BACKGROUND: The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic changes over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in genome-wide association studies (GWAS). To investigate these aspects, we divided MVP participants into five birth cohorts (N-range = 123,888 [born from 1943 to 1947] to 136,699 [born from 1948 to 1953]). RESULTS: Ancestry groups were defined by (i) HARE (harmonized ancestry and race/ethnicity) and (ii) a random-forest clustering approach using the 1000 Genomes Project and the Human Genome Diversity Project (1kGP + HGDP) reference panels (77 world populations representing six continental groups). In these groups, we performed GWASs of height, a trait potentially affected by population stratification. Birth cohorts demonstrate important trends in ancestry diversity over time. More recent HARE-assigned Europeans, Africans, and Hispanics had lower European ancestry proportions than older birth cohorts (0.010 < Cohen's d < 0.259, p < 7.80 × 10-4). Conversely, HARE-assigned East Asians showed an increase in European ancestry proportion over time. In GWAS of height using HARE assignments, genomic inflation due to population stratification was prevalent across all birth cohorts (linkage disequilibrium score regression intercept = 1.08 ± 0.042). The 1kGP + HGDP-based ancestry assignment significantly reduced the population stratification (mean intercept reduction = 0.045 ± 0.007, p < 0.05) confounding in the GWAS statistics. CONCLUSIONS: This study provides a characterization of ancestry diversity of the MVP cohort over time and compares two strategies to infer genetically defined ancestry groups by assessing differences in controlling population stratification in genome-wide association studies.

INTRODUCTION: The ability to accurately predict whether a woman will develop breast cancer later in her life, should reduce the number of breast cancer deaths. Different predictive models exist for breast cancer based on family history, BRCA status, and SNP analysis. The best of these models has an accuracy (area under the receiver operating characteristic curve, AUC) of about 0.65. We have developed computational methods to characterize a genome by a small set of numbers that represent the length of segments of the chromosomes, called chromosomal-scale length variation (CSLV). METHODS: We built machine learning models to differentiate between women who had breast cancer and women who did not based on their CSLV characterization. We applied this procedure to two different datasets: the UK Biobank (1534 women with breast cancer and 4391 women who did not) and the Cancer Genome Atlas (TCGA) 874 with breast cancer and 3381 without. RESULTS: We found a machine learning model that could predict breast cancer with an AUC of 0.836 95% CI (0.830.0.843) in the UK Biobank data. Using a similar approach with the TCGA data, we obtained a model with an AUC of 0.704 95% CI (0.702, 0.706). Variable importance analysis indicated that no single chromosomal region was responsible for significant fraction of the model results. CONCLUSION: In this retrospective study, chromosomal-scale length variation could effectively predict whether or not a woman enrolled in the UK Biobank study developed breast cancer.

BACKGROUND: Clinical severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outcomes could be influenced by genetic polymorphisms in angiotensin I-converting enzyme (ACE1) and ACE2. This study aims to examine three polymorphisms (rs1978124, rs2285666, and rs2074192) on the ACE2 gene and ACE1 rs1799752 (I/D) in patients who have coronavirus disease 2019 (COVID-19) with various SARS-CoV-2 variants. METHODS: Based on polymerase chain reaction-based genotyping, four polymorphisms in the ACE1 and ACE2 genes have been identified in 2023 deceased patients and 2307 recovered patients. RESULTS: The ACE2 rs2074192 TT genotype was associated with the COVID-19 mortality in all three variants, whereas the CT genotype was associated with the Omicron BA.5 and Delta variants. ACE2 rs1978124 TC genotypes were related to COVID-19 mortality in the Omicron BA.5 and Alpha variants, but TT genotypes were related to COVID-19 mortality in the Delta variant. It was found that ACE2 rs2285666 CC genotypes were associated with COVID-19 mortality in Delta and Alpha variants, and CT genotypes in Delta variants. There was an association between ACE1 rs1799752 DD and ID genotypes in the Delta variant and COVID-19 mortality, whereas there was no association in the Alpha or Omicron BA.5 variants. In all variants of SARS-CoV-2, CDCT and TDCT haplotypes were more common. In Omicron BA.5 and Delta, CDCC and TDCC haplotypes were linked with COVID-19 mortality. In addition to COVID-19 mortality, the CICT, TICT, and TICC were significantly correlated. CONCLUSION: The ACE1/ACE2 polymorphisms had an impact on COVID-19 infection, and these polymorphisms had different effects in various SARS-CoV-2 variants. To confirm these results, however, more research needs to be conducted.

BACKGROUND: Inattention has been given to the pathogenesis of adolescent and young adult (AYA) hepatocellular carcinoma (HCC). Due to the more advanced tumor progression and poorer prognosis of AYA-HCC, together with a better tolerance ability, noncirrhotic background, and a stronger willingness to treat AYA-HCC, clinical and molecular biology studies are urgent and necessary, especially for those with hepatitis B infection. METHODS: For clinical aspects, the overall survival, the recurrence-free survival, and the Cox analyses were performed. Then, functional analysis, gene clustering, metabolic-related analysis, immune infiltration and competing endogenous RNA (ceRNA) construction were carried out using whole transcriptome sequencing technique. RESULTS: Based on the clinical information of our HCC cohort, the overall survival and recurrence-free survival rates were worse in the AYA group than in the elderly group as previously described. According to our whole transcriptome sequencing results, functional analysis revealed that metabolism-related pathways as well as protein translation and endoplasmic reticulum processing were enriched. Then the hub metabolism-related genes were screened by metabolite-protein interactions (MPIs) and protein-protein interactions (PPIs). Fatty acid metabolism is a crucial component of metabolic pathways, abnormalities of which may be the reason for the worse prognosis of HBV-AYA HCC. Finally, the relationship of disrupted expression of metabolism-related genes with immune infiltration was also analyzed, and the lncRNA‒miRNA‒mRNA-related ceRNA network for HBV-AYA HCC was constructed, which may provide new cues for HBV-AHA HCC prevention. CONCLUSION: The worse prognosis and recurrence rate of HBV-AYA HCC may be related to abnormalities in metabolism-related pathways, especially disorders of fatty acid metabolism.

BACKGROUND: Individuals infected with SARS-CoV-2 vary greatly in their disease severity, ranging from asymptomatic infection to severe disease. The regulation of gene expression is an important mechanism in the host immune response and can modulate the outcome of the disease. miRNAs play important roles in post-transcriptional regulation with consequences on downstream molecular and cellular host immune response processes. The nature and magnitude of miRNA perturbations associated with blood phenotypes and intensive care unit (ICU) admission in COVID-19 are poorly understood. RESULTS: We combined multi-omics profiling-genotyping, miRNA and RNA expression, measured at the time of hospital admission soon after the onset of COVID-19 symptoms-with phenotypes from electronic health records to understand how miRNA expression contributes to variation in disease severity in a diverse cohort of 259 unvaccinated patients in Abu Dhabi, United Arab Emirates. We analyzed 62 clinical variables and expression levels of 632 miRNAs measured at admission and identified 97 miRNAs associated with 8 blood phenotypes significantly associated with later ICU admission. Integrative miRNA-mRNA cross-correlation analysis identified multiple miRNA-mRNA-blood endophenotype associations and revealed the effect of miR-143-3p on neutrophil count mediated by the expression of its target gene BCL2. We report 168 significant cis-miRNA expression quantitative trait loci, 57 of which implicate miRNAs associated with either ICU admission or a blood endophenotype. CONCLUSIONS: This systems genetics study has given rise to a genomic picture of the architecture of whole blood miRNAs in unvaccinated COVID-19 patients and pinpoints post-transcriptional regulation as a potential mechanism that impacts blood traits underlying COVID-19 severity. The results also highlight the impact of host genetic regulatory control of miRNA expression in early stages of COVID-19 disease.