Deficient Generation of Spike-Specific Long-Lived Plasma Cells in the Bone Marrow After Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

Generation of a stable long-lived plasma cell (LLPC) population is the sine qua non of durable antibody responses after vaccination or infection. We studied 20 individuals with a prior coronavirus disease 2019 infection and characterized the antibody response using bone marrow aspiration and plasma samples. We noted deficient generation of spike-specific LLPCs in the bone marrow after severe acute respiratory syndrome coronavirus 2 infection. Furthermore, while the regression model explained 98% of the observed variance in anti-tetanus immunoglobulin G levels based on LLPC enzyme-linked immunospot assay, we were unable to fit the same model with anti-spike antibodies, again pointing to the lack of LLPC contribution to circulating anti-spike antibodies.

On Measuring Vaccine Effectiveness with Observational Study Designs.

Herein, we present a bird's eye view of common observational study designs utilized for measurement of vaccine effectiveness. Assessing vaccines effectiveness is an integral part of vaccine research, particularly for the newly developed vaccines. A cohort study is prospective, directing from an exposure to one or more outcomes. The design is the best method to ascertain the attack rate of an infectious disease. A traditional case-control study is retrospective, directing from a given outcome to one or more exposures. The design cannot provide the relative risk, but it can provide the odds ratio, which is a good estimation of the relative risk when the attack rate is low. Critically depending on laboratory test results and performance, the test-negative case-control study design is another type of observational study commonly used nowadays for the evaluation of the vaccine effectiveness. Comparing to cohort and traditional case-control designs, conducting a test-negative case-control study is relatively cheaper and faster. Herein, we describe each of the above-mentioned study designs through examples generated by a Monte-Carlo simulation program assuming real-world conditions. CONCLUSION: The simulation shows that regardless of the study design employed, the diagnostic test specificity is of utmost importance in providing a valid estimate of the vaccine effectiveness.

Determining the SARS-CoV-2 serological immunoassay test performance indices based on the test results frequency distribution.

Introduction: Coronavirus disease 2019 (COVID-19) is known to induce robust antibody response in most of the affected individuals. The objective of the study was to determine if we can harvest the test sensitivity and specificity of a commercial serologic immunoassay merely based on the frequency distribution of the SARS-CoV-2 immunoglobulin (Ig) G concentrations measured in a population-based seroprevalence study. Materials and methods: The current study was conducted on a subset of a previously published dataset from the canton of Geneva. Data were taken from two non-consecutive weeks (774 samples from May 4-9, and 658 from June 1-6, 2020). Assuming that the frequency distribution of the measured SARS-CoV-2 IgG is binormal (an educated guess), using a non-linear regression, we decomposed the distribution into its two Gaussian components. Based on the obtained regression coefficients, we calculated the prevalence of SARS-CoV-2 infection, the sensitivity and specificity, and the most appropriate cut-off value for the test. The obtained results were compared with those obtained from a validity study and a seroprevalence population-based study. Results: The model could predict more than 90% of the variance observed in the SARS-CoV-2 IgG distribution. The results derived from our model were in good agreement with the results obtained from the seroprevalence and validity studies. Altogether 138 of 1432 people had SARS-CoV-2 IgG ≥ 0.90, the cut-off value which maximized the Youden's index. This translates into a true prevalence of 7.0% (95% confidence interval 5.4% to 8.6%), which is in keeping with the estimated prevalence of 7.7% derived from our model. Our model can provide the true prevalence. Conclusions: Having an educated guess about the distribution of test results, the test performance indices can be derived with acceptable accuracy merely based on the test results frequency distribution without the need for conducting a validity study and comparing the test results against a gold-standard test.

The apparent prevalence, the true prevalence.

Serologic tests are important for conducting seroepidemiologic and prevalence studies. However, the tests used are typically imperfect and produce false-positive and false-negative results. This is why the seropositive rate (apparent prevalence) does not typically reflect the true prevalence of the disease or condition of interest. Herein, we discuss the way the true prevalence could be derived from the apparent prevalence and test sensitivity and specificity. A computer simulation based on the Monte-Carlo algorithm was also used to further examine a situation where the measured test sensitivity and specificity are also uncertain. We then complete our review with a real example. The apparent prevalence observed in many prevalence studies published in medical literature is a biased estimation and cannot be interpreted correctly unless we correct the value.

Pre-Implantation Genetic Testing for Monogenic Disorders (PGT-M) in A Family with A Novel Mutation in DPAGT1 Gene.

Congenital disorders of glycosylation (CDG) are a heterogeneous group of systemic disorders characterized by defects in glycosylation of lipids and proteins. One of the rare subtypes of CDG is CDG-Ij (MIM # 608093), which is caused by pathogenic mutations in DPAGT1, a gene encoding UDP-N-acetylglucosaminedolichyl-phosphate N-acetylglucosaminephosphotransferase enzyme. This enzyme catalyzes the first step of oligosaccharide synthesis in glycoprotein biosynthesis pathway. Preimplantation genetic testing for monogenic disorders (PGT-M) is a diagnostic technique that can reveal the genetic profile of embryos before implantation phase of in vitro fertilization (IVF). Currently, this approach is performed using next generation sequencing (NGS) technology. Herein, with the help of whole-exome and Sanger sequencing, we detected a novel missense mutation (NM_001382, c.1217 A>G) in DPAGT1 gene in two families with consanguineous marriage. Using different online bioinformatics tools including MutationTaster, I-Mutant v2.0, T- Coffee, and CADD v1.0, this mutation was predicted pathogen. Finally, after performing PGT-M followed by successful pregnancy, a normal child was born in one of these families. In conclusion, we identified a novel pathogenic mutation in DPAGT1 in a family with multiple members affected by CDG, which extends the range of pathogenic variants associated with CDG and therefore facilitates early detection of the disease.

Autophagy: The Potential Link between SARS-CoV-2 and Cancer.

COVID-19 infection survivors suffer from a constellation of symptoms referred to as post-acute COVID-19 syndrome. However, in the wake of recent evidence highlighting the long-term persistence of SARS-CoV-2 antigens in tissues and emerging information regarding the interaction between SARS-CoV-2 proteins and various components of the host cell macroautophagy/autophagy machinery, the unforeseen long-term consequences of this infection, such as increased risk of malignancies, should be explored. Although SARS-CoV-2 is not considered an oncogenic virus, the possibility of increased risk of cancer among COVID-19 survivors cannot be ruled out. Herein, we provide an overview of the possible mechanisms leading to cancer development, particularly obesity-related cancers (e.g., colorectal cancer), resulting from defects in autophagy and the blockade of the autophagic flux, and also immune escape in COVID-19 survivors. We also highlight the potential long-term implications of COVID-19 infection in the prognosis of patients with cancer and their response to different cancer treatments. Finally, we consider future directions for further investigations on this matter.

High-throughput imaging of ATG9A distribution as a diagnostic functional assay for adaptor protein complex 4-associated hereditary spastic paraplegia.

Adaptor protein complex 4-associated hereditary spastic paraplegia is caused by biallelic loss-of-function variants in AP4B1, AP4M1, AP4E1 or AP4S1, which constitute the four subunits of this obligate complex. While the diagnosis of adaptor protein complex 4-associated hereditary spastic paraplegia relies on molecular testing, the interpretation of novel missense variants remains challenging. Here, we address this diagnostic gap by using patient-derived fibroblasts to establish a functional assay that measures the subcellular localization of ATG9A, a transmembrane protein that is sorted by adaptor protein complex 4. Using automated high-throughput microscopy, we determine the ratio of the ATG9A fluorescence in the trans-Golgi-network versus cytoplasm and ascertain that this metric meets standards for screening assays (Z'-factor robust >0.3, strictly standardized mean difference >3). The 'ATG9A ratio' is increased in fibroblasts of 18 well-characterized adaptor protein complex 4-associated hereditary spastic paraplegia patients [mean: 1.54 ± 0.13 versus 1.21 ± 0.05 (standard deviation) in controls] and receiver-operating characteristic analysis demonstrates robust diagnostic power (area under the curve: 0.85, 95% confidence interval: 0.849-0.852). Using fibroblasts from two individuals with atypical clinical features and novel biallelic missense variants of unknown significance in AP4B1, we show that our assay can reliably detect adaptor protein complex 4 function. Our findings establish the 'ATG9A ratio' as a diagnostic marker of adaptor protein complex 4-associated hereditary spastic paraplegia.

Investigating the association between common DRD2/ANKK1 genetic polymorphisms and schizophrenia: a meta-analysis.

Genetic factors play an important role in the pathogenesis of schizophrenia. Dysregulations in the dopaminergic system have long been known to play an influential role in the development of this disorder. Although a large number of studies have investigated the association between genetic polymorphisms in the genes involved in this system and the risk of schizophrenia, the results have been inconsistent. In this meta-analysis, we searched for publications in Ovid Medline, Embase, Web of Science (science citation index expanded), and PsycNET for articles published until January 2020. We identified case-control studies investigating the association between four common genetic polymorphisms (rs6277, rs1799732, rs1800497, and rs1801028) and the risk of schizophrenia. The studies were subsequently selected according to the predefined inclusion and exclusion criteria. The data extraction was conducted according to the PRISMA guidelines.We also assessed the quality of the studies and investigated publication bias using funnel plot and Egger's regression test. The association analysis was conducted in allelic, dominant, and recessive genetic models. Subsequently, bioinformatics analysis of the effect of the polymorphisms found to be significantly associated with schizophrenia on protein stability, posttranslational modifications, and 3D protein structure was conducted. This meta-analysis showed that Taq1A (allelic model: OR, 0.856, 95% CI, 0.734-0.998) has a protective effect against the development of schizophrenia. Further, it was found that this variant may decreaseANKK1protein stability. Further, this polymorphism was found to lead to the gain of modifications sites for ubiquitination (Ubi. score =-1.894) and methylation (Meth. score =-0.834). Several genetic factors contribute to the susceptibility of schizophrenia. The updated knowledge emerging from this meta-analysis showing the protective effect of rs1800497 polymorphism (Taq1A) can shed light on the role of Taq1A polymorphism in the susceptibility to schizophrenia and also pave way for further functional studies investigating the role of ANKK1 protein in the pathogenesis of schizophrenia.

Clinicopathological study of hepatic mesenchymal hamartoma and undifferentiated embryonal sarcoma of the liver: a single center study from Iran.

BACKGROUND: Undifferentiated embryonal sarcoma of liver (UESL) and hepatic mesenchymal hamartoma (HMH) are two rare entities which mainly affect the pediatric population. The aim of this investigation was to provide a comprehensive overview of the clinicopathologic characteristics of the patients diagnosed with these two conditions in a tertiary referral center in Iran. METHODS: In this retrospective study patients diagnosed with UESL or HMH between 2012 and 2020 were studied. A comprehensive histopathologic evaluation of the cases along with immunohistochemistry evaluation using a panel of antibodies was conducted. Furthermore, clinical, paraclinical, and treatment data and follow up information was collected. RESULTS: A total of 16 patients (8 UESL, 8 HMH) were studied in this investigation. Patients with UESL had a significantly (p = 0.002) higher age at diagnosis compared with those with HMH. Histologically, UESL cases were characterized by anaplastic cells with eosinophilic cytoplasm and bizarre nuclei and frequent atypical mitosis and spindling in a myxoid stroma while disordered arrangement of hepatic parenchyma, bile ducts, and primitive mesenchyme was seen in HMH. Furthermore, small round cells and extramedullary hematopoiesis were seen in 2 UESL and 3 HMH cases, respectively. Concurrent HMH was also seen in two UESL cases. Immunohistochemistry panel showed positive staining for Vimentin, Glypican-3, Desmin, CD56, CD10, and BCL2 in UESL cases and immunoreactivity for Vimentin, HepPar 1, Glypican-3, SMA, CD56, BCL2, and CD34 in various components of HMH. CONCLUSIONS: In this study, the clinicopathologic features of UESL and HMH cases are presented. We also evaluated the utility of an immunohistochemistry panel in the diagnosis of these two rare entities and suggested novel markers. Our study corroborated the findings of previous investigations and expanded the clinicopathologic features of these two rare entities with diagnostic and potential therapeutic implications.

Biallelic variants in TMEM222 cause a new autosomal recessive neurodevelopmental disorder.

PURPOSE: To elucidate the novel molecular cause in families with a new autosomal recessive neurodevelopmental disorder. METHODS: A combination of exome sequencing and gene matching tools was used to identify pathogenic variants in 17 individuals. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) and subcellular localization studies were used to characterize gene expression profile and localization. RESULTS: Biallelic variants in the TMEM222 gene were identified in 17 individuals from nine unrelated families, presenting with intellectual disability and variable other features, such as aggressive behavior, shy character, body tremors, decreased muscle mass in the lower extremities, and mild hypotonia. We found relatively high TMEM222 expression levels in the human brain, especially in the parietal and occipital cortex. Additionally, subcellular localization analysis in human neurons derived from induced pluripotent stem cells (iPSCs) revealed that TMEM222 localizes to early endosomes in the synapses of mature iPSC-derived neurons. CONCLUSION: Our findings support a role for TMEM222 in brain development and function and adds variants in the gene TMEM222 as a novel underlying cause of an autosomal recessive neurodevelopmental disorder.

Molecular diagnostic assays for COVID-19: an overview.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the cardinal importance of rapid and accurate diagnostic assays. Since the early days of the outbreak, researchers with different scientific backgrounds across the globe have tried to fulfill the urgent need for such assays, with many assays having been approved and with others still undergoing clinical validation. Molecular diagnostic assays are a major group of tests used to diagnose COVID-19. Currently, the detection of SARS-CoV-2 RNA by reverse transcription polymerase chain reaction (RT-PCR) is the most widely used method. Other diagnostic molecular methods, including CRISPR-based assays, isothermal nucleic acid amplification methods, digital PCR, microarray assays, and next generation sequencing (NGS), are promising alternatives. In this review, we summarize the technical and clinical applications of the different COVID-19 molecular diagnostic assays and suggest directions for the implementation of such technologies in future infectious disease outbreaks.

On the information hidden in a classifier distribution.

Classification tasks are a common challenge to every field of science. To correctly interpret the results provided by a classifier, we need to know the performance indices of the classifier including its sensitivity, specificity, the most appropriate cut-off value (for continuous classifiers), etc. Typically, several studies should be conducted to find all these indices. Herein, we show that they already exist, hidden in the distribution of the variable used to classify, and can readily be harvested. An educated guess about the distribution of the variable used to classify in each class would help us to decompose the frequency distribution of the variable in population into its components-the probability density function of the variable in each class. Based on the harvested parameters, we can then calculate the performance indices of the classifier. As a case study, we applied the technique to the relative frequency distribution of prostate-specific antigen, a biomarker commonly used in medicine for the diagnosis of prostate cancer. We used nonlinear curve fitting to decompose the variable relative frequency distribution into the probability density functions of the non-diseased and diseased people. The functions were then used to determine the performance indices of the classifier. Sensitivity, specificity, the most appropriate cut-off value, and likelihood ratios were calculated. The reference range of the biomarker and the prevalence of prostate cancer for various age groups were also calculated. The indices obtained were in good agreement with the values reported in previous studies. All these were done without being aware of the real health status of the individuals studied. The method is even applicable for conditions with no definite definitions (e.g., hypertension). We believe the method has a wide range of applications in many scientific fields.

Predicting the outcome of asymptomatic univesicular liver hydatids: diagnostic accuracy of unenhanced CT.

OBJECTIVES: To establish the role of unenhanced CT in predicting the outcome of liver hydatid cysts. We sought to determine whether the presence of laminated membrane detachment (LMD) or pericyst degenerative changes (PDCs) detected on CT were reliable signs for predicting a favorable outcome of liver hydatids. METHODS: In a 20-year-long study, we prospectively followed changes occurred in CT of 106 cysts of 98 patients with incidentally discovered asymptomatic univesicular liver hydatids who accepted to enter a watch-and-wait program. An "unfavorable" outcome was defined as the occurrence of a complication (most commonly, cyst fistula or infection) or increase in the cyst size during the follow-up; otherwise, the outcome was considered "favorable." The parameters derived from a binary logistic regression analysis (with the outcome taken as the dependent variable), after appropriate transformation of the independent variables (presence of LMD or PDCs on CT), were used to calculate the sensitivity, specificity, positive and negative likelihood ratios, and positive and negative predictive values of the presence of either the abovementioned CT findings for the prediction of a favorable outcome. RESULTS: The presence of LMD or PDCs had a high specificity (88%) and positive predictive value (96%) for a favorable outcome; they had high false-negative rates. CONCLUSIONS: The presence of either LMD or PDCs on unenhanced CT, in incidentally discovered asymptomatic univesicular liver hydatids, was associated with a high probability of a favorable outcome. Their absence does not rule out a favorable outcome. KEY POINTS: • Computed tomography can be used for predicting the outcome of those with incidentally discovered univesicular liver hydatids. • The presence of laminated membrane detachment and/or pericyst degenerative changes is associated with a favorable outcome. • Their absence does not necessarily indicate an unfavorable outcome.

LncRNA-miRNA-mRNA Networks of Gastrointestinal Cancers Representing Common and Specific LncRNAs and mRNAs.

Gastrointestinal (GI) cancers are responsible for approximately half of cancer-related deaths, highlighting the need for the identification of distinct and common features in their clinicopathological characteristics. Long ncRNA (lncRNAs), which are involved in competitive endogenous RNA (ceRNA) networks with critical roles in biological processes, constitute a substantial number of non-coding RNAs. Therefore, our study aimed to investigate the similarities and differences in the ceRNA networks of The Cancer Genome Atlas (TCGA)-GI cancers. We performed a comprehensive bioinformatics analysis of ceRNA networks for TCGA-GI cancers in terms of the deferential mRNA, lncRNA, and miRNA expression levels, ceRNA networks, overall survival analysis, correlation analysis, pathological cancer stages, and gene set enrichment analysis. Our study revealed several common and distinct mRNAs and lncRNAs with prognostic values in these networks. It was specifically noteworthy that MAGI2-AS3 lncRNA was found to be shared in almost all GI cancers. Moreover, the most common shared mRNAs between GI cancers were MEIS1, PPP1R3C, ADAMTSL3, RIPOR2, and MYLK. For each cancer ceRNA network, we found that the expression level of a number of lncRNAs and mRNAs was specific. Furthermore, our study provided compelling evidence that several genes, most notably KDELC1, can act as novel proto-oncogenes in cancers. This, in turn, can highlight their role as new prognostic and therapeutic targets. Moreover, we found cell cycle and extracellular matrix structural constituent as the top shared KEGG and molecular function, respectively, among GI cancers. Our study revealed several known lncRNAs and known and unknown mRNAs in GI cancers with diagnostic and prognostic values.

The Immunomodulatory Effect of Radiofrequency Electromagnetic Field on Serum Cytokine Levels in A Mouse Model of Hindlimb Unloading.

OBJECTIVE: Astronauts are exposed to a wide range of environmental stresses during spaceflights that reduce their immune responses and make them more susceptible to infections and malignancies. Exposure to a low dose of a certain stress induces an adaptive response, which leads to resistance to higher doses of the same or other types of stress. We designed this study to investigate the effect of radiofrequency electromagnetic field (RF-EMF)-induced adaptive response on immune system modulation in a mouse model of hindlimb unloading (HU) as a ground-based animal model of spaceflight conditions. MATERIALS AND METHODS: In this experimental study, serum levels of T helper (Th)-mediated cytokines were determined by the multiplex cytometric bead assay in four groups of mice (n=10 per group): HU mice, RF-EMF-treated mice, HU mice pre-exposed to RF-EMF; and untreated controls. Mice were exposed to 2450 MHz RF-EMF with SAR 0.478 W/ kg for 12 hours/day for three successive days. RESULTS: Tumor necrosis factor-alpha (TNF-α), interleukin-9 (IL-9) and IL-22 were significantly decreased in HU mice. Comparison between HU mice and RF-EMF-treated mice showed an opposite change in IL-6, while IL-9, IL-22, IFN-γ and TNF-α decreased in both groups. However, just interferon gamma (IFN-γ) was significantly decreased in HU mice that were pre-exposed to RF-EMF compared to the control group. CONCLUSION: The effect of RF-EMF in elevating IL-6 and reducing IL-9 in opposite directions in HU mice suggest a modulating effect of RF-EMF on HU-induced changes in these cytokines, as Th2 and Th9 eventually returned to normal levels and balances in cytokine ratios were also restored in HU mice pre-exposed to RF-EMF.

The potential effectiveness of acetazolamide in the prevention of acute kidney injury in COVID-19: A hypothesis.

Acute kidney injury (AKI) is an important complication of COVID-19 encompassing a wide range of presentations. SARS-CoV-2 is proposed to cause AKI in the patients through various mechanisms. We are, nevertheless, far from a comprehensive understanding of the underlying pathophysiological mechanisms of the kidney injury in this infection. AKI has been shown to be a marker of disease severity and also a negative prognostic factor for survival. Unfortunately, no effective preventive strategy to decrease the risk of kidney damage in these patients has yet been identified. In this hypothesis, we highlight the potential protective effects of acetazolamide, a carbonic anhydrase inhibitor, in preventing the proximal tubular damage caused by the virus through disrupting the virus-endosome fusion and also interfering with the lysosomal proteases. Our proposed mechanisms could pave the way for further in vitro studies and subsequent clinical trials.

A novel stop-gain mutation in DPYS gene causing Dihidropyrimidinase deficiency, a case report.

BACKGROUND: Dihidropyrimidinase (DHP) deficiency is an inherited inborn error of pyrimidine metabolism with a variable clinical presentation and even asymptomatic subjects. Dihydropyrimidinase is encoded by the DPYS gene, thus pathogenic mutations in this gene can cause DHP deficiency. To date, several variations in the DPYS gene have been reported but only 23 of them have been confirmed to be pathogenic. Therefore, the biochemical, clinical and genetic aspects of this disease are still unclear. CASE PRESENTATION: Here, we report a 22-year-old woman with DHP deficiency. To identify the genetic cause of DHP deficiency in this patient, Whole Exome Sequencing (WES) was performed, which revealed a novel homozygote stop gain mutation (NM_001385: Exon 9, c.1501 A > T, p.K501X) in the DPYS gene. Sanger sequencing was carried out on proband and other family members in order to confirm the identified mutation. According to the homozygote genotype of the patient and heterozygote genotype of her parents, the autosomal recessive pattern of inheritance was confirmed. In addition, bioinformatics analysis of the identified variant using Mutation Taster and T-Coffee Multiple Sequence Alignment showed the pathogenicity of mutation. Moreover, mRNA expression level of DPYS gene in the proband's liver biopsy showed about 6-fold reduction compared to control, which strongly suggested the pathogenicity of the identified mutation. CONCLUSIONS: This study identified a novel pathogenic stop gain mutation in DPYS gene in a DHP deficient patient. Our findings can improve the knowledge about the genetic basis of the disease and also provide information for accurate genetic counseling for the families at risk of these types of disorders.

Temperature, humidity, and latitude analysis to predict potential spread and seasonality for COVID-19.

Background: A significant number of infectious diseases display seasonal patterns in their incidence, including human coronaviruses. Betacoronaviruses such as MERS-CoV and SARS-CoV are not thought to be seasonal. Methods: We examined climate data from cities with significant community spread of COVID-19 using ERA-5 reanalysis, and compared to areas that are either not affected, or do not have significant community spread. Results: To date, Coronavirus Disease 2019 (COVID-19), caused by SARS-CoV-2, has established significant community spread in cities and regions along a narrow east west distribution roughly along the 30-50° N' corridor at consistently similar weather patterns consisting of average temperatures of 5-11°C, combined with low specific (3-6 g/kg) and absolute humidity (4-7 g/m3). There has been a lack of significant community establishment in expected locations that are based only on population proximity and extensive population interaction through travel. Conclusions and Relevance: The distribution of significant community outbreaks along restricted latitude, temperature, and humidity are consistent with the behavior of a seasonal respiratory virus. Additionally, we have proposed a simplified model that shows a zone at increased risk for COVID-19 spread. Using weather modeling, it may be possible to predict the regions most likely to be at higher risk of significant community spread of COVID-19 in the upcoming weeks, allowing for concentration of public health efforts on surveillance and containment.

Temperature, Humidity, and Latitude Analysis to Estimate Potential Spread and Seasonality of Coronavirus Disease 2019 (COVID-19).

Importance: Coronavirus disease 2019 (COVID-19) infection has resulted in a global crisis. Investigating the potential association of climate and seasonality with the spread of this infection could aid in preventive and surveillance strategies. Objective: To examine the association of climate with the spread of COVID-19 infection. Design, Setting, and Participants: This cohort study examined climate data from 50 cities worldwide with and without substantial community spread of COVID-19. Eight cities with substantial spread of COVID-19 (Wuhan, China; Tokyo, Japan; Daegu, South Korea; Qom, Iran; Milan, Italy; Paris, France; Seattle, US; and Madrid, Spain) were compared with 42 cities that have not been affected or did not have substantial community spread. Data were collected from January to March 10, 2020. Main Outcomes and Measures: Substantial community transmission was defined as at least 10 reported deaths in a country as of March 10, 2020. Climate data (latitude, mean 2-m temperature, mean specific humidity, and mean relative humidity) were obtained from ERA-5 reanalysis. Results: The 8 cities with substantial community spread as of March 10, 2020, were located on a narrow band, roughly on the 30° N to 50° N corridor. They had consistently similar weather patterns, consisting of mean temperatures of between 5 and 11 °C, combined with low specific humidity (3-6 g/kg) and low absolute humidity (4-7 g/m3). There was a lack of substantial community establishment in expected locations based on proximity. For example, while Wuhan, China (30.8° N) had 3136 deaths and 80 757 cases, Moscow, Russia (56.0° N), had 0 deaths and 10 cases and Hanoi, Vietnam (21.2° N), had 0 deaths and 31 cases. Conclusions and Relevance: In this study, the distribution of substantial community outbreaks of COVID-19 along restricted latitude, temperature, and humidity measurements was consistent with the behavior of a seasonal respiratory virus. Using weather modeling, it may be possible to estimate the regions most likely to be at a higher risk of substantial community spread of COVID-19 in the upcoming weeks, allowing for concentration of public health efforts on surveillance and containment.