Understanding COVID-19: A hypothesis regarding digit ratio (2D:4D), ACE I/D polymorphism, oxygen metabolism and national case fatality rates

Digit ratios and hospitalization for COVID-19: A test of the low-androgen-driven and high-androgen-driven theories of COVID-19 severity

BACKGROUND

Sex hormones are likely to be important determinants of COVID-19 severity, and two opposing explanations regarding severity, the low-androgen-driven and high-androgen-driven theories, seek to explain this pattern. Digit ratios are sex dependent (males < females) and are claimed to be markers for both prenatal and postnatal testosterone.

OBJECTIVES

Here, we use a measure of COVID-19severity (hospitalization), compare digit ratios in patients and controls and consider whether vaccination status changed these associations.

MATERIAL AND METHODS

Four digits were measured (2D, 3D, 4D, 5D). There were 194 participants (94 hospitalized patients [45 men] and 100 controls [53 men]) in Sample I and 162 participants (100 hospitalized [42 men], including 40 vaccinated and 62 controls [32 men]) in Sample II. Six ratios were calculated (2D:3D; 2D:4D; 2D:5D; 3D:4D; 3D:5D, 4D:5D) and compared between COVID-19 hospitalized and non-hospitalized patients and vaccinated and non-vaccinated.

RESULTS

In comparison to controls, we found higher ("feminized") means in patient ratios that included 5D (2D:5D; 3D:5D; 4D:5D) in both samples. The differences were independent of sex and age. Hospitalized patients with COVID-19 have higher (feminized) means and higher standard deviations (SDs) for 5D digit ratios.

DISCUSSION

Digit ratios are sex dependent (males < females) and are considered as markers for both prenatal and postnatal testosterone. If verified in future studies, the results will be helpful in regard to targeting mortality-reducing therapies for COVID-19 in certain groups of patients.

CONCLUSION

We conclude that the association between high (feminized) 5D ratios and hospitalization supports the low-androgen-driven theory of COVID-19 severity.

Understanding Covid-19: Digit ratios and duration of oxygen therapy in hospitalized Covid-19 patients

BACKGROUND

Covid-19 severity shows a sex difference (males>females) and progressive hypoxia among the most seriously affected. Digit ratios are sexually dimorphic and may be negatively-related to prenatal (2nd-to-4th digits' ratio; 2D:4D) and pubertal (3rd-to-5th digits' ratio; 3D:5D) testosterone. Oxygen therapy is important in Covid-19 treatment and low 2D:4D is linked to efficient oxygen metabolism. We consider relationships between digit ratios and duration of oxygen treatment in hospitalized Covid-19 patients.

METHODS

Digit lengths were measured from photographs of the patient's hands. Age, Sex, BMI, vaccination status and number of days of O2 treatment, were recorded.

RESULTS

There were 100 (58 women) patients. Sex differences (males

CONCLUSION

We have found that high (feminized) 2D:4D of males and females is positively related to duration of oxygen therapy. This adds to the evidence for links between severity of Covid-19 and national and individual level variation in foetal androgen (as measured by 2D:4D). We discuss our finding in the light of the "low-androgen-driven COVID-19 pandemic theory".

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Key Words

• COVID-19
• Digit ratio
• Oxygen therapy

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MESH Headings

• Humans
• Male
• Female
• Androgens
• Fingers/anatomy & histology
• Digit Ratios
• COVID-19/therapy
• Pandemics
• COVID-19 Drug Treatment
• Sex Characteristics
• Oxygen/therapeutic use

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Affiliation(s)

Anna Kasielska-Trojan Plastic, Reconstructive and Aesthetic Surgery Clinic, Institute of Surgery, Medical University of Lodz, Lodz, Poland.
Maciej Jabłkowski Department of Infectious and Liver Diseases, Medical University of Lodz, Lodz, Poland
Jolanta Białkowska-Warzecha Department of Infectious and Liver Diseases, Medical University of Lodz, Lodz, Poland
Oliwia Kwaśniewska Medical University of Lodz, Lodz, Poland
Bogusław Antoszewski Plastic, Reconstructive and Aesthetic Surgery Clinic, Institute of Surgery, Medical University of Lodz, Lodz, Poland

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Combinatorial analysis of ACE and ACE2 polymorphisms reveals protection against COVID-19 worsening: A genetic association study in Brazilian patients

Since angiotensin-converting enzyme 2, ACE2, was identified as the receptor for SARS-CoV-2 and considering the intense physiological interplay between the two angitensinases isoforms, ACE and ACE2, as counter-regulatory axis of the renin-angiotensin system, we proposed the evaluation of polymorphisms in these two key regulators in relation to COVID-19 severity. A genetic association study involving 621 COVID-19 hospitalized patients from Brazil was performed. All subjects had a confirmed diagnosis of COVID-19 via RT-PCR. Patients were categorized into two groups: the "mild" group (N = 296), composed of individuals hospitalized in ward beds who progressed to cure, and the "severe" group (N = 325), composed of individuals who required hospitalization in an intensive care unit (ICU), or who died. Blood samples were genotyped for ACE I/D polymorphism and ACE2 G8790A polymorphism by real-time PCR via TaqMan assay. The analysis of combined polymorphisms revealed a protective role for genotypic profile II/A_ (ORA = 0,26; p = 0,037) against the worsening of COVID-19 in women. The results indicate a protection profile to COVID-19 progression, in which the II/A_ carriers have almost four times less chance of a severe outcome. It is proposed that a decreased activity of ACE (deleterious effects) in conjunction with an increased ACE2 activity (protective effects), should be the underlying mechanism. The findings are unprecedented once other studies have not explored the genotypic combination analysis for ACE and ACE2 polymorphisms and bring perspectives and expectations for dealing with the COVID-19 pandemic based on definitions of genetically-based risk groups within the context of personalized medicine.

Understanding the Geography of COVID-19 Case Fatality Rates in China: A Spatial Autoregressive Probit-Log Linear Hurdle Analysis

This study employs a spatial autoregressive probit-log linear (SAP-Log) hurdle model to investigate the influencing factors on the probability of death and case fatality rate (CFR) of coronavirus disease 2019 (COVID-19) at the city level in China. The results demonstrate that the probability of death from COVID-19 and the CFR level are 2 different processes with different determinants. The number of confirmed cases and the number of doctors are closely associated with the death probability and CFR, and there exist differences in the CFR and its determinants between cities within Hubei Province and outside Hubei Province. The spatial probit model also presents positive spatial autocorrelation in death probabilities. It is worth noting that the medical resource sharing among cities and enjoyment of free medical treatment services of citizens makes China different from other countries. This study contributes to the growing literature on determinants of CFR with COVID-19 and has significant practical implications.

COVID-19 and syndemic challenges in 'Battling the Big Three': HIV, TB and malaria

Indirect effects of the COVID-19 pandemic have the potential to seriously undermine the health system in sub-Saharan Africa with an increase in the incidences of malaria, tuberculosis (TB) and HIV infections. Based on current evidence in the African region the collateral impact of COVID-19 on the "big three diseases" shall be addressed in the following.

No credible evidence for links between 2D:4D and COVID-19 outcomes: A probabilistic perspective on digit ratio, ACE variants, and national case fatalities

Research into COVID-19 susceptibility and outcomes are critical, but claims must be carefully evaluated to inform policy decisions. In a recent series of articles, Manning and Fink [1-3] use national-level data to describe associations between case-fatality ratios and male and female finger ratios (2D:4D), a suggested measure of prenatal androgen exposure, as well as angiotensin-converting enzyme (ACE) allele and genotype frequencies. The authors suggest that 2D:4D is linked with ACE variant prevalence, and that higher male 2D:4D is associated with higher case fatality ratios, and point to 2D:4D as a useful prognostic measure for COVID-19 susceptibility. A critical review and robust Bayesian analysis of the hypothesis is described here, finding no conclusive evidence of COVID-19 mortality and 2D:4D, nor associations between 2D:4D and ACE1 allele or ACE2 genotype frequency. This absence of evidence is present for data taken from the second wave of COVID-19 in October 2020. Problematic theoretical grounding, individual-level conclusions drawn from national-level data, and issues with statistical inference in the original articles are discussed. Taken together, the current data offer no clear utility of 2D:4D in determining COVID-19 outcomes.