While populations at risk for severe SARS-CoV-2 infections have been clearly identified, susceptibility to the infection and its clinical course remain unpredictable. As the nasopharyngeal microbiota may promote the acquisition of several respiratory infections and have an impact on the evolution of their outcome, we studied the nasopharyngeal microbiota of COVID-19 patients in association with baseline disease-related clinical features compared to that of patients tested negative. We retrospectively analyzed 120 nasopharyngeal pseudonymized samples, obtained for diagnosis, divided into groups (infected patients with a favorable outcome, asymptomatic, and deceased patients) and patients tested negative for SARS-CoV-2, by using Illumina-16S ribosomal ribonucleic acid (rRNA) sequencing and specific polymerase chain reaction (PCR) targeting pathogens. We first found a depletion of anaerobes among COVID-19 patients, irrespective of the clinical presentation of the infection (p < 0.029). We detected 9 taxa discriminating patients tested positive for SARS-CoV-2 from those that were negative including Corynebacterium propinquum/pseudodiphtericum (p ≤ 0.05), Moraxella catarrhalis (p ≤ 0.05), Bacillus massiliamazoniensis (p ≤ 0.01), Anaerobacillus alkalidiazotrophicus (p ≤ 0.05), Staphylococcus capitis subsp. capitis (p ≤ 0.001), and Afipia birgiae (p ≤ 0.001) with 16S rRNA sequencing, and Streptococcus pneumoniae (p ≤ 0.01), Klebsiella pneumoniae (p ≤ 0.01), and Enterococcus faecalis (p ≤ 0.05) using real-time PCR. By designing a specific real-time PCR, we also demonstrated that C. propinquum is decreased in asymptomatic individuals compared to other SARS-CoV 2 positive patients. These findings indicate that the nasopharyngeal microbiota as in any respiratory infection plays a role in the clinical course of the disease. Further studies are needed to elucidate the potential role in the clinical course of the disease of M. catarrhalis, Corynebacterium accolens, and more specifically Corynebacterium propinquum/diphteriticum in order to include them as predictors of the severity of COVID-19.