KS-WNK1 is required for the renal response to extreme changes in potassium intake.

Kidney-specific with-no-lysine kinase 1 (KS-WNK1) is an isoform of WNK1 kinase that is predominantly found in the distal convoluted tubule of the kidney. The precise physiological function of KS-WNK1 remains unclear. Some studies have suggested that it could play a role in regulating potassium renal excretion by modulating the activity of the Na+-Cl- cotransporter (NCC). However, changes in the potassium diet from normal to high failed to reveal a role for KS-WNK1, but under a normal-potassium diet, the expression of KS-WNK1 is negligible. It is only detectable when mice are exposed to a low-potassium diet. In this study, we investigated the role of KS-WNK1 in regulating potassium excretion under extreme changes in potassium intake. After following a zero-potassium diet (0KD) for 10 days, KS-WNK1-/- mice had lower plasma levels of K+ and Cl- while exhibiting higher urinary excretion of Na+, Cl-, and K+ compared with KS-WNK1+/+ mice. After 10 days of 0KD or normal-potassium diet (NKD), all mice were challenged with a high-potassium diet (HKD). Plasma K+ levels markedly increased after the HKD challenge only in mice previously fed with 0KD, regardless of genotype. KSWNK1+/+ mice adapt better to HKD challenge than KS-WNK1-/- mice after a potassium-retaining state. The difference in the phosphorylated NCC-to-NCC ratio between KS-WNK1+/+ and KS-WNK1-/- mice after 0KD and HKD indicates a role for KS-WNK1 in both NCC phosphorylation and dephosphorylation. These observations show that KS-WNK1 helps the distal convoluted tubule to respond to extreme changes in potassium intake, such as those occurring in wildlife.NEW & NOTEWORTHY The findings of this study demonstrate that kidney-specific with-no-lysine kinase 1 plays a role in regulating urinary electrolyte excretion during extreme changes in potassium intake, such as those occurring in wildlife. .

Glucose/Fructose Delivery to the Distal Nephron Activates the Sodium-Chloride Cotransporter via the Calcium-Sensing Receptor.

BACKGROUND: The calcium-sensing receptor (CaSR) in the distal convoluted tubule (DCT) activates the NaCl cotransporter (NCC). Glucose acts as a positive allosteric modulator of the CaSR. Under physiologic conditions, no glucose is delivered to the DCT, and fructose delivery depends on consumption. We hypothesized that glucose/fructose delivery to the DCT modulates the CaSR in a positive allosteric way, activating the WNK4-SPAK-NCC pathway and thus increasing salt retention. METHODS: We evaluated the effect of glucose/fructose arrival to the distal nephron on the CaSR-WNK4-SPAK-NCC pathway using HEK-293 cells, C57BL/6 and WNK4-knockout mice, ex vivo perfused kidneys, and healthy humans. RESULTS: HEK-293 cells exposed to glucose/fructose increased SPAK phosphorylation in a WNK4- and CaSR-dependent manner. C57BL/6 mice exposed to fructose or a single dose of dapagliflozin to induce transient glycosuria showed increased activity of the WNK4-SPAK-NCC pathway. The calcilytic NPS2143 ameliorated this effect, which was not observed in WNK4-KO mice. C57BL/6 mice treated with fructose or dapagliflozin showed markedly increased natriuresis after thiazide challenge. Ex vivo rat kidney perfused with glucose above the physiologic threshold levels for proximal reabsorption showed increased NCC and SPAK phosphorylation. NPS2143 prevented this effect. In healthy volunteers, cinacalcet administration, fructose intake, or a single dose of dapagliflozin increased SPAK and NCC phosphorylation in urinary extracellular vesicles. CONCLUSIONS: Glycosuria or fructosuria was associated with increased NCC, SPAK, and WNK4 phosphorylation in a CaSR-dependent manner.

Comprehensive Evaluation of the Impact of Sociodemographic Inequalities on Adverse Outcomes and Excess Mortality During the Coronavirus Disease 2019 (COVID-19) Pandemic in Mexico City.

BACKGROUND: The impact of the coronavirus disease 2019 (COVID-19) pandemic in Mexico City has been sharp, as several social inequalities at all levels coexist. Here we conducted an in-depth evaluation of the impact of individual and municipal-level social inequalities on the COVID-19 pandemic in Mexico City. METHODS: We analyzed suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases, from the Mexico City Epidemiological Surveillance System from 24 February 2020 to 31 March 2021. COVID-19 outcomes included rates of hospitalization, severe COVID-19, invasive mechanical ventilation, and mortality. We evaluated socioeconomic occupation as an individual risk, and social lag, which captures municipal-level social vulnerability, and urban population density as proxies of structural risk factors. Impact of reductions in vehicular mobility on COVID-19 rates and the influence of risk factors were also assessed. Finally, we assessed discrepancies in COVID-19 and non-COVID-19 excess mortality using death certificates from the general civil registry. RESULTS: We detected vulnerable groups who belonged to economically unfavored sectors and experienced increased risk of COVID-19 outcomes. Cases living in marginalized municipalities with high population density experienced greater risk for COVID-19 outcomes. Additionally, policies to reduce vehicular mobility had differential impacts modified by social lag and urban population density. Finally, we report an under-registry of COVID-19 deaths along with an excess mortality closely related to marginalized and densely populated communities in an ambulatory setting. This could be attributable to a negative impact of modified hospital admission criteria during the pandemic. CONCLUSIONS: Socioeconomic occupation and municipality-wide factors played a significant role in shaping the course of the COVID-19 pandemic in Mexico City.

WNK1 in the kidney.

PURPOSE OF REVIEW: The aim of this manuscript was to review recent evidence uncovering the roles of the With No lysine (K) kinase 1 (WNK1) in the kidney. RECENT FINDINGS: Analyses of microdissected mouse nephron segments have revealed the abundance of long-WNK1 and kidney-specific-WNK1 transcripts in different segments. The low levels of L-WNK1 transcripts in the distal convoluted tubule (DCT) stand out and support functional evidence on the lack of L-WNK1 activity in this segment. The recent description of familial hyperkalaemic hypertension (FHHt)-causative mutations affecting the acidic domain of WNK1 supports the notion that KS-WNK1 activates the Na+:Cl- cotransporter NCC. The high sensitivity of KS-WNK1 to KLHL3-targeted degradation and the low levels of L-WNK1 in the DCT, led to propose that this type of FHHt is mainly due to increased KS-WNK1 protein in the DCT. The observation that KS-WNK1 renal protein expression is induced by low K+ diet and recent reassessment of the phenotype of KS-WNK1-/- mice suggested that KS-WNK1 may be necessary to achieve maximal NCC activation under this condition. Evidences on the regulation of other renal transport proteins by WNK1 are also summarized. SUMMARY: The diversity of WNK1 transcripts in the kidney has complicated the interpretation of experimental data. Integration of experimental data with the knowledge of isoform abundance in renal cell types is necessary in future studies about WNK1 function in the kidney.

Profiling Cases With Nonrespiratory Symptoms and Asymptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infections in Mexico City.

We profiled cases with nonrespiratory symptoms (NRS) and asymptomatic severe acute respiratory syndrome coronavirus 2 infections assessed within Mexico City's Epidemiological Surveillance System. Initially asymptomatic or NRS cases have decreased risk of adverse outcomes compared with cases with respiratory symptoms. Comorbidity and age influence symptom development in initially asymptomatic cases.

Assessing the Burden of Coronavirus Disease 2019 (COVID-19) Among Healthcare Workers in Mexico City: A Data-Driven Call to Action.

BACKGROUND: Healthcare workers (HCWs) could be at increased occupational risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections due to increased exposure. Information regarding the burden of coronavirus disease 2019 (COVID-19) epidemic in HCWs living in Mexico is scarce. Here, we aimed to explore the epidemiology, symptoms, and risk factors associated with adverse outcomes in HCWs in Mexico City. METHODS: We explored data collected by the National Epidemiological Surveillance System in Mexico City, in HCWs who underwent real-time reverse transcription polymerase chain reaction (RT-PCR) test. We explored COVID-19 outcomes in HCWs and the performance of symptoms to detect SARS-CoV-2 infection. RESULTS: As of 20 September 2020, 57 758 HCWs were tested for SARS-CoV-2 and 17 531 were confirmed (30.35%); 6610 were nurses (37.70%), 4910 physicians (28.0%), 267 dentists (1.52%), and 5744 laboratory personnel and other HCWs (32.76%). Overall, 2378 HCWs required hospitalization (4.12%), 2648 developed severe COVID-19 (4.58%), and 336 required mechanical-ventilatory support (.58%). Lethality was recorded in 472 (.82%) cases. We identified 635 asymptomatic SARS-CoV-2 infections (3.62%). Compared with general population, HCWs had higher incidence, testing, asymptomatic cases, and mortality rates. No individual symptom offers adequate performance to detect SARS-CoV2. Older HCWs with chronic noncommunicable diseases and severe respiratory symptoms were associated with higher risk for adverse outcome; physicians were at higher risk compared with nurses and other HCWs. CONCLUSIONS: We report a high prevalence of SARS-CoV-2 infection in HCWs in Mexico City. Symptoms as a screening method are not efficient to discern those HCWs with a positive PCR-RT test. Particular attention should focus on HCWs with risk factors to prevent adverse outcomes.

Bloodstream infection caused by S. aureus in patients with cancer: a 10-year longitudinal single-center study.

BACKGROUND: Staphylococcus aureus bloodstream infections (SABIs) represent a significant cause of morbidity and mortality in cancer patients. In this study, we compared infection characteristics and evaluated epidemiology and risk factors associated to SABIs and 30-day attributable mortality in cancer patients. METHODS: Clinical and microbiological data from patients with cancer and positive blood cultures for S. aureus were retrieved during a 10-year period at an oncology reference center. Analyses were performed according to type of malignancy and infection with methicillin-resistant S. aureus (MRSA). Data was evaluated using competing risk analyses to identify risk factors associated to 30-day mortality and used to create a point system for mortality risk stratification. RESULTS: We included 450 patients and MRSA was documented in 21.1%. Hospital-acquired infection, healthcare-associated pneumonia, and type-2 diabetes were associated to MRSA. In patients with hematologic malignancies, MRSA was more frequent if hospital-acquired, but less likely in primary bacteremia. Variables associated to mortality included abdominal source of infection, hematologic malignancy, MRSA, glucose levels > 140 mg/dL, and infectious endocarditis; catheter removal and initiation of adequate treatment within 48 h of positive blood culture were protective factors. From our designed mortality prediction scale, patients with a score > 3 had a 70.23% (95%CI 47.2-85.3%) probability of infection-related death at 30 days. CONCLUSION: SABIs are a significant health burden for cancer patients. Risk factors for SABI-related mortality in this population are varied and impose a challenge for management to improve patient's outcomes. Risk stratification might be useful to evaluate 30-day mortality risk.

Diagnostic performance and clinical implications of rapid SARS-CoV-2 antigen testing in Mexico using real-world nationwide COVID-19 registry data.

BACKGROUND: SARS-CoV-2 testing capacity is important to monitor epidemic dynamics and as a mitigation strategy. Given difficulties of large-scale quantitative reverse transcription polymerase chain reaction (qRT-PCR) implementation, rapid antigen tests (Rapid Ag-T) have been proposed as alternatives in settings like Mexico. Here, we evaluated diagnostic performance of Rapid Ag-T for SARS-CoV-2 infection and its associated clinical implications compared to qRT-PCR testing in Mexico. METHODS: We analyzed data from the COVID-19 registry of the Mexican General Directorate of Epidemiology up to April 30th, 2021 (n = 6,632,938) and cases with both qRT-PCR and Rapid Ag-T (n = 216,388). We evaluated diagnostic performance using accuracy measures and assessed time-dependent changes in the Area Under the Receiver Operating Characteristic curve (AUROC). We also explored test discordances as predictors of hospitalization, intubation, severe COVID-19 and mortality. RESULTS: Rapid Ag-T is primarily used in Mexico City. Rapid Ag-T have low sensitivity 37.6% (95%CI 36.6-38.7), high specificity 95.5% (95%CI 95.1-95.8) and acceptable positive 86.1% (95%CI 85.0-86.6) and negative predictive values 67.2% (95%CI 66.2-69.2). Rapid Ag-T has optimal diagnostic performance up to days 3 after symptom onset, and its performance is modified by testing location, comorbidity, and age. qRT-PCR (-) / Rapid Ag-T (+) cases had higher risk of adverse COVID-19 outcomes (HR 1.54 95% CI 1.41-1.68) and were older, qRT-PCR (+)/ Rapid Ag-T(-) cases had slightly higher risk or adverse outcomes and ≥7 days from symptom onset (HR 1.53 95% CI 1.48-1.59). Cases detected with rapid Ag-T were younger, without comorbidities, and milder COVID-19 course. CONCLUSIONS: Rapid Ag-T could be used as an alternative to qRT-PCR for large scale SARS-CoV-2 testing in Mexico. Interpretation of Rapid Ag-T results should be done with caution to minimize the risk associated with false negative results.

Unequal Impact of Structural Health Determinants and Comorbidity on COVID-19 Severity and Lethality in Older Mexican Adults: Considerations Beyond Chronological Aging.

BACKGROUND: COVID-19 has had a disproportionate impact on older adults. Mexico's population is younger, yet COVID-19's impact on older adults is comparable to countries with older population structures. Here, we aim to identify health and structural determinants that increase susceptibility to COVID-19 in older Mexican adults beyond chronological aging. METHODS: We analyzed confirmed COVID-19 cases in older adults using data from the General Directorate of Epidemiology of Mexican Ministry of Health. We modeled risk factors for increased COVID-19 severity and mortality, using mixed models to incorporate multilevel data concerning healthcare access and marginalization. We also evaluated structural factors and comorbidity profiles compared to chronological age for COVID-19 mortality risk prediction. RESULTS: We analyzed 20 804 confirmed SARS-CoV-2 cases in adults aged 60 and older. Male sex, smoking, diabetes, and obesity were associated with pneumonia, hospitalization, and intensive care unit (ICU) admission in older adults, CKD and COPD were associated with hospitalization. High social lag indexes and access to private care were predictors of COVID-19 severity and mortality. Age was not a predictor of COVID-19 severity in individuals without comorbidities and combination of structural factors and comorbidities were better predictors of COVID-19 lethality and severity compared to chronological age alone. COVID-19 baseline lethality hazards were heterogeneously distributed across Mexican municipalities, particularly when comparing urban and rural areas. CONCLUSIONS: Structural factors and comorbidity explain excess risk for COVID-19 severity and mortality over chronological age in older Mexican adults. Clinical decision-making related to COVID-19 should focus away from chronological aging onto more a comprehensive geriatric care approach.

Impact of undiagnosed type 2 diabetes and pre-diabetes on severity and mortality for SARS-CoV-2 infection.

INTRODUCTION: Diabetes and hyperglycemia are risk factors for critical COVID-19 outcomes; however, the impact of pre-diabetes and previously unidentified cases of diabetes remains undefined. Here, we profiled hospitalized patients with undiagnosed type 2 diabetes and pre-diabetes to evaluate its impact on adverse COVID-19 outcomes. We also explored the role of de novo and intrahospital hyperglycemia in mediating critical COVID-19 outcomes. RESEARCH DESIGN AND METHODS: Prospective cohort of 317 hospitalized COVID-19 cases from a Mexico City reference center. Type 2 diabetes was defined as previous diagnosis or treatment with diabetes medication, undiagnosed diabetes and pre-diabetes using glycosylated hemoglobin (HbA1c) American Diabetes Association (ADA) criteria and de novo or intrahospital hyperglycemia as fasting plasma glucose (FPG) ≥140 mg/dL. Logistic and Cox proportional regression models were used to model risk for COVID-19 outcomes. RESULTS: Overall, 159 cases (50.2%) had type 2 diabetes and 125 had pre-diabetes (39.4%), while 31.4% of patients with type 2 diabetes were previously undiagnosed. Among 20.0% of pre-diabetes cases and 6.1% of normal-range HbA1c had de novo hyperglycemia. FPG was the better predictor for critical COVID-19 compared with HbA1c. Undiagnosed type 2 diabetes (OR: 5.76, 95% CI 1.46 to 27.11) and pre-diabetes (OR: 4.15, 95% CI 1.29 to 16.75) conferred increased risk of severe COVID-19. De novo/intrahospital hyperglycemia predicted critical COVID-19 outcomes independent of diabetes status. CONCLUSIONS: Undiagnosed type 2 diabetes, pre-diabetes and de novo hyperglycemia are risk factors for critical COVID-19. HbA1c must be measured early to adequately assess individual risk considering the large rates of undiagnosed type 2 diabetes in Mexico.

Adaptive Metabolic and Inflammatory Responses Identified Using Accelerated Aging Metrics Are Linked to Adverse Outcomes in Severe SARS-CoV-2 Infection.

BACKGROUND: Chronological age (CA) is a predictor of adverse coronavirus disease 2019 (COVID-19) outcomes; however, CA alone does not capture individual responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Here, we evaluated the influence of aging metrics PhenoAge and PhenoAgeAccel to predict adverse COVID-19 outcomes. Furthermore, we sought to model adaptive metabolic and inflammatory responses to severe SARS-CoV-2 infection using individual PhenoAge components. METHOD: In this retrospective cohort study, we assessed cases admitted to a COVID-19 reference center in Mexico City. PhenoAge and PhenoAgeAccel were estimated using laboratory values at admission. Cox proportional hazards models were fitted to estimate risk for COVID-19 lethality and adverse outcomes (intensive care unit admission, intubation, or death). To explore reproducible patterns which model adaptive responses to SARS-CoV-2 infection, we used k-means clustering using PhenoAge components. RESULTS: We included 1068 subjects of whom 222 presented critical illness and 218 died. PhenoAge was a better predictor of adverse outcomes and lethality compared to CA and SpO2 and its predictive capacity was sustained for all age groups. Patients with responses associated to PhenoAgeAccel >0 had higher risk of death and critical illness compared to those with lower values (log-rank p < .001). Using unsupervised clustering, we identified 4 adaptive responses to SARS-CoV-2 infection: (i) inflammaging associated with CA, (ii) metabolic dysfunction associated with cardiometabolic comorbidities, (iii) unfavorable hematological response, and (iv) response associated with favorable outcomes. CONCLUSIONS: Adaptive responses related to accelerated aging metrics are linked to adverse COVID-19 outcomes and have unique and distinguishable features. PhenoAge is a better predictor of adverse outcomes compared to CA.

Predicting Mortality Due to SARS-CoV-2: A Mechanistic Score Relating Obesity and Diabetes to COVID-19 Outcomes in Mexico.

BACKGROUND: The SARS-CoV-2 outbreak poses a challenge to health care systems due to its high complication rates in patients with cardiometabolic diseases. Here, we identify risk factors and propose a clinical score to predict COVID-19 lethality, including specific factors for diabetes and obesity, and its role in improving risk prediction. METHODS: We obtained data of confirmed and negative COVID-19 cases and their demographic and health characteristics from the General Directorate of Epidemiology of the Mexican Ministry of Health. We investigated specific risk factors associated to COVID-19 positivity and mortality and explored the impact of diabetes and obesity on modifying COVID-19-related lethality. Finally, we built a clinical score to predict COVID-19 lethality. RESULTS: Among the 177 133 subjects at the time of writing this report (May 18, 2020), we observed 51 633 subjects with SARS-CoV-2 and 5,332 deaths. Risk factors for lethality in COVID-19 include early-onset diabetes, obesity, chronic obstructive pulmonary disease, advanced age, hypertension, immunosuppression, and chronic kidney disease (CKD); we observed that obesity mediates 49.5% of the effect of diabetes on COVID-19 lethality. Early-onset diabetes conferred an increased risk of hospitalization and obesity conferred an increased risk for intensive care unit admission and intubation. Our predictive score for COVID-19 lethality included age ≥ 65 years, diabetes, early-onset diabetes, obesity, age < 40 years, CKD, hypertension, and immunosuppression and significantly discriminates lethal from non-lethal COVID-19 cases (C-statistic = 0.823). CONCLUSIONS: Here, we propose a mechanistic approach to evaluate the risk for complications and lethality attributable to COVID-19, considering the effect of obesity and diabetes in Mexico. Our score offers a clinical tool for quick determination of high-risk susceptibility patients in a first-contact scenario.

Clinical characterization of data-driven diabetes subgroups in Mexicans using a reproducible machine learning approach.

INTRODUCTION: Previous reports in European populations demonstrated the existence of five data-driven adult-onset diabetes subgroups. Here, we use self-normalizing neural networks (SNNN) to improve reproducibility of these data-driven diabetes subgroups in Mexican cohorts to extend its application to more diverse settings. RESEARCH DESIGN AND METHODS: We trained SNNN and compared it with k-means clustering to classify diabetes subgroups in a multiethnic and representative population-based National Health and Nutrition Examination Survey (NHANES) datasets with all available measures (training sample: NHANES-III, n=1132; validation sample: NHANES 1999-2006, n=626). SNNN models were then applied to four Mexican cohorts (SIGMA-UIEM, n=1521; Metabolic Syndrome cohort, n=6144; ENSANUT 2016, n=614 and CAIPaDi, n=1608) to characterize diabetes subgroups in Mexicans according to treatment response, risk for chronic complications and risk factors for the incidence of each subgroup. RESULTS: SNNN yielded four reproducible clinical profiles (obesity related, insulin deficient, insulin resistant, age related) in NHANES and Mexican cohorts even without C-peptide measurements. We observed in a population-based survey a high prevalence of the insulin-deficient form (41.25%, 95% CI 41.02% to 41.48%), followed by obesity-related (33.60%, 95% CI 33.40% to 33.79%), age-related (14.72%, 95% CI 14.63% to 14.82%) and severe insulin-resistant groups. A significant association was found between the SLC16A11 diabetes risk variant and the obesity-related subgroup (OR 1.42, 95% CI 1.10 to 1.83, p=0.008). Among incident cases, we observed a greater incidence of mild obesity-related diabetes (n=149, 45.0%). In a diabetes outpatient clinic cohort, we observed increased 1-year risk (HR 1.59, 95% CI 1.01 to 2.51) and 2-year risk (HR 1.94, 95% CI 1.13 to 3.31) for incident retinopathy in the insulin-deficient group and decreased 2-year diabetic retinopathy risk for the obesity-related subgroup (HR 0.49, 95% CI 0.27 to 0.89). CONCLUSIONS: Diabetes subgroup phenotypes are reproducible using SNNN; our algorithm is available as web-based tool. Application of these models allowed for better characterization of diabetes subgroups and risk factors in Mexicans that could have clinical applications.