Does Genetic Predisposition Contribute to the Exacerbation of COVID-19 Symptoms in Individuals with Comorbidities and Explain the Huge Mortality Disparity between the East and the West?

The elderly and patients with several comorbidities experience more severe cases of coronavirus disease 2019 (COVID-19) than healthy patients without underlying medical conditions. However, it is unclear why these people are prone to developing alveolar pneumonia, rapid exacerbations, and death. Therefore, we hypothesized that people with comorbidities may have a genetic predisposition that makes them more vulnerable to various factors; for example, they are likely to become more severely ill when infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To test this hypothesis, we searched the literature extensively. Polymorphisms of genes, such as those that encode angiotensin-converting enzyme 1 (ACE1), have been associated with numerous comorbidities, such as cardiovascular disease, hypertension, diabetes, chronic kidney disease, and obesity, and there are potential mechanisms to explain these associations (e.g., DD-type carriers have greater ACE1 activity, and patients with a genetic alpha-1 anti-trypsin (AAT) deficiency lack control over inflammatory mediators). Since comorbidities are associated with chronic inflammation and are closely related to the renin-angiotensin-aldosterone system (RAAS), these individuals may already have a mild ACE1/ACE2 imbalance before viral infection, which increases their risk for developing severe cases of COVID-19. However, there is still much debate about the association between ACE1 D/I polymorphism and comorbidities. The best explanation for this discrepancy could be that the D allele and DD subtypes are associated with comorbidities, but the DD genotype alone does not have an exceptionally large effect. This is also expected since the ACE1 D/I polymorphism is only an intron marker. We also discuss how polymorphisms of AAT and other genes are involved in comorbidities and the severity of SARS-CoV-2 infection. Presumably, a combination of multiple genes and non-genetic factors is involved in the establishment of comorbidities and aggravation of COVID-19.

Epidemiological correlation between COVID-19 epidemic and prevalence of α-1 antitrypsin deficiency in the world.

Among 68 countries in the world, severity of the COVID-19 epidemic was correlated with the prevalence of α-1 antitrypsin (AAT) deficiency. For the severe variant, PI*Z, the correlation coefficient (CC) was 0.8584 for the number of patients and 0.8713 for the number of deaths. For the milder variant, PI*S, it was 0.5818 and 0.6326, respectively. In Japan, the number of patients and deaths correlated with the population size with a CC of 0.6667 and 0.7074 respectively, and was proportional to the population size to the power of 1.65 and 1.54. The prevalence of AAT deficiency also correlated with the epidemiological pattern of COVID-19. In countries with high prevalence of AAT deficiency, after the initial rise, the daily number of patients and that of deaths ran parallel at a high level for more than 6 months without sign of abatement. In countries with a low prevalence of AAT deficiency, after the first wave of the epidemic, the number of the deaths decreased continuously while the number of patients remained the same or even increased resulting in a decreasing case-fatality rate. When the cumulative number of deaths was plotted on the y-axis against the cumulative number of patients on the x-axis, plots fell on a straight line in countries with a high prevalence of AAT deficiency; while in countries with a low prevalence of AAT deficiency, a break appeared, after which the plots fell on flatter slope indicating decreasing case-fatality rate. The observation suggests emergence of an attenuated variant in countries with a low prevalence of AAT deficiency.

Changing Demography of Genital Chlamydia, Gonorrhea, Genital Herpes, Condyloma, and Syphilis Infections in Japan.

There was an epidemiological correlation in time and space between gonorrhea and genital chlamydia as well as between condyloma and genital herpes. There was, however, no correlation in other combinations, such as, gonorrhea and condyloma, genital herpes and chlamydia, etc. The annual incidence of gonorrhea and that of genital chlamydia were mono-phasic with a peak in 2005-2006. The annual incidence of condyloma and that of genital herpes were biphasic with the first distinct peak in 2004-2006 borne by the younger generation and the second broad peak by the older generation that experienced the first wave. The epidemiology of syphilis was entirely different from the above infections: the incidences of early, late, and asymptomatic syphilis started increasing around 2010, which was associated with a shift of patients' peak age towards the younger generation.

Declining Vibrio parahaemolyticus and Salmonella, Increasing Campylobacter and Persisting Norovirus Food Poisonings: Inference Derived from Food Poisoning Statistics of Japan.

The annual number of outbreaks of Vibrio parahaemolyticus and Salmonella food poisoning and that of patients in Japan, from 2000 to 2018, decreased exponentially even though the size of the individual outbreaks (the number of patients per outbreak) tended to become larger. For food poisonings caused by Campylobacter, the annual number of outbreaks increased exponentially while outbreak size became smaller and the annual number of patients remained almost unchanged. For food poisoning caused by norovirus, both the number of outbreaks and that of patients remained high throughout. Over time, the geographical and seasonal distribution of food poisonings became narrower for Vibrio parahaemolyticus and Salmonella, while they became wider for Campylobacter and norovirus. Further analyses using the attack rate-patient number plots suggested that the number of the outbreaks was determined mainly by the levels of microbial contamination of foods before they were brought into the facilities for consumption.

Attack Rate-Patient Number Plot for Analysis of Food Poisoning Caused by Microbes and Plant or Animal Toxins.

The number of food consumers (eaters) and patients per outbreak followed a log-normal distribution in food poisoning caused by microbes. In contrast, it followed a scale-free distribution in food poisoning caused by plant or animal toxins. Attack rates of the individual outbreaks were distributed continuously and almost linearly from ＞ 0 to 1 for all the food poisoning cases, i.e., they could not be represented by median and standard deviation. For simultaneous monitoring of the number of patients and the attack rate in individual outbreaks, the number of patients was plotted on the x-axis in the logarithmic scale against the attack rate on the y-axis in the normal scale. This led to the formation of plots characterized by repeating arcs, assuming the shape of a butterfly with extended wings when viewed from above, which was called "backbone configuration." The butterfly-shaped plot patterns were generally stable over time, although it varied depending on the pathogens, implicated facilities and their combinations. The backbone configuration was reproduced assuming that the number of patients per outbreak was distributed continuously from 1 to the number of eaters per outbreak.

Shift of HIV/AIDS Deaths to an Older Age and Gender Difference: Inferences Derived from the Vital Statistics of Japan.

From 1995 to 2000, the mortality rates of human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) patients < 54 years of age have declined; however, since 2000, deaths of HIV/AIDS patients aged > 55 have started to increase. Although deaths directly linked to infections have declined since 2005, those related to malignancy, encephalopathy, interstitial pneumonia, wasting syndrome, etc. persisted. In 10 years from 1999-2004 to 2010-2017, the age at death shifted by 5 years towards an older age in the general population and in patients with HIV/AIDS (mainly males), adult T-cell leukemia, or Creutzfeldt-Jakob disease. Among these, HIV/AIDS patients and the general population exhibited an unequivocal gender difference. As of 2011-2016, the median of the deaths of the HIV/AIDS patients was 52.5 years for males and 70 years for females, while the median of the deaths of the general population was 75 years for males and 85 years for females. Hence, male HIV/AIDS patients died 22.5 years earlier and female HIV/AIDS patients 15 years earlier than did the general population. A common denominator of HIV/AIDS-related deaths and deaths among the general population could be CD4+T cells as these cells are primary targets of HIV, and a decline in naïve CD4+T cell count is a hallmark of aging.

HIV/AIDS in Japan: Route and Age of Infection that Shaped the Epidemics in 1987-2016.

In Japan, HIV infection is classified as "HIV" or "AIDS" depending upon whether the infection was detected before or after the development of AIDS. In male homosexuals, in the plot of the number of "AIDS" notified annually versus the that of "HIV" notified annually, the plot fell on a straight line with a slope close to 1. When the number of "HIV" no longer increased, that of "AIDS" also stopped increasing. The number of "HIV" notified in one region or age group was correlated with that of other regions or age groups, respectively. However, no such correlation was observed among male heterosexuals. "HIV" was detected more frequently among male homosexuals and females than among male heterosexuals. The rate of "AIDS" detection increased with age in all infection categories. Our analysis, supported by findings of other studies, suggested that the higher rate of "HIV" detection among male homosexuals and females was attributed to the increased risk of receptive sexual intercourse, while the higher rate of "AIDS" detection among the elderly people was attributed to immunological senescence.

Age Distribution of People Dying of HIV/AIDS that Shifted toward Older Ages by 10 Years in the Past 20 Odd Years.

The frequency of the ages at which HIV/AIDS-related deaths occurred and that of patients detected before or after development of AIDS followed a normal distribution. The median age of HIV/AIDS-related deaths was 40-44 years in 1995-1998 and 50-54 years in 2014-2016, whereas the median age at detection of "HIV" or "AIDS" infection was constantly 25-29 years, implying that the survival time of the HIV/AIDS patients became longer by 10 years in the past 20 odd years. The increased survival time could possibly be attributable to the introduction of HIV/AIDS therapies such as HAART. Importantly, however, during the same period, the life span of the Japanese population was lengthened by nearly 10 years. Under the assumption that HIV/AIDS patients died 20 years after the detection of the infection, the total number of deaths was 1,446 in 1990-2016, which was close to 1,532, the total number of deaths in Vital Statistics during the same period.

Population Size Dependency of Measles Epidemic That Was Scalable from Japanese Prefectures to European Countries.

The relationship between the number of measles patients (y) and the population size (x) was expressed by the equation y=axs, where a is a constant and s the slope of the plot; s was 2.04-2.17 for prefectures in Japan, i.e., the number of patients was proportional to the square of the population size of the prefecture. For European countries that joined the European Union (EU) no later than 2009, the slope was 1.43-1.87. The population dependency of measles found among prefectures in Japan was thus scalable to European countries. This was surprising because, unlike Japan, the population densities of EU countries were not uniform and not proportional to the population size. The population size dependency was not observed among Western Pacific and South-East Asian countries probably due to confounding from interacting socioeconomic factors. The correlation between measles incidence and birth rate, infant mortality or gross domestic product per capita was almost insignificant. The size distribution of local infection clusters (LICs) of measles and rubella in Japan followed a power law. For measles, although the population dependency remained unchanged after "elimination," there were changes in the Zipf-type plots of LIC sizes. After "elimination," LICs linked to importation-related outbreaks in less populated prefectures emerged as the top-ranked LICs.

Geographic Spread of Influenza under the Influence of Community Population Size, Which Differed from That of Measles and Rubella.

The influenza season is defined as the period from week 36 of the year to week 20 of the subsequent year in this report. The population size of prefectures (x) and number of patients per prefecture (y) were initially uncorrelated, but a correlation developed as the season advanced. The correlation with correlation coefficient >0.7 emerged increasingly earlier over time; it developed in week 5 of the subsequent year in 2001/2002, but in week 47 of the same year in 2014/2015. Once x and y were correlated, plots of y on the vertical axis against x on the horizontal axis resulted in a straight line, y = Cxs, where s was the slope of the plot and C was a constant. The slope was high (s>1) initially, but decreased (s<1) later, indicating that influenza first spread to populated prefectures and then nationwide, involving less populated prefectures. This spread pattern was the same for the seasonal influenza and AH1pdm2009, although the progression of the latter was much faster. For measles and rubella epidemics, the number of patients per prefecture was proportional to the square of the population size from the start to the end of the season.

Seasonality and Geographical Distribution of Tsutsugamushi Diseases in Japan: Analysis of the Trends since 1955 till 2014.

Data concerning the seasonality and geographical location of tsutsugamushi disease (TD) in Japan from 1955 to 2014 were compiled. After disappearance of "classical" TD in the mid-1960s, there was a long near-vacuum. Then, in 1975, a TD epidemic with October-December seasonality emerged in southern prefectures, and in 1979, that with May-June seasonality in northern prefectures. The current TD epidemic could be classified according to seasonality and geography into three types: a large October-December epidemic with a negligibly small May-June epidemic in the southern part of Japan, a large May-June epidemic with a mid-sized October-December epidemic on the Pacific coast of northern Japan, and a large epidemic in May-June with a negligibly small October-December epidemic on the Japan Sea coast of northern Japan. In addition, there were a few patients that were scattered throughout the year in various places in Japan. How these different epidemic patterns emerged is discussed.

Attack Rates of Norovirus and Campylobacter Food Poisonings that Cannot Be Represented by Numeric Constant but by Plotting the Attack Rate against the Number of Patients per Incident in Cartesian Coordinates.

In norovirus and Campylobacter food poisonings, the frequencies of the number of patients per incident and that of the number of eaters per incident followed a lognormal distribution, with medians of 12-27 and 23-48 for norovirus and 5-8 and 9-21 for Campylobacter food poisonings, respectively. The lognormal frequency distribution of eaters could be simulated by assuming that people find a dish more appealing if that dish has already been found to be appealing to others. The numbers of patients and eaters per incident were not necessarily inter-correlated; the frequencies of the attack rates (number of patients/number of eaters) were distributed evenly from 0.01 to 1; that is, the attack rates of these food poisonings could not be represented by means and standard deviations. The frequency distributions of the attack rates were nevertheless not entirely disordered; plotting the attack rate against the number of patients in individual incidents produced fingerprint-like patterns that were repeatedly produced at the prefectural and national levels.

Population Dependency of Measles, Syphilis, and Amebiasis in Japan and Community Evolution.

The population dependency of measles, syphilis, and amebiasis was expressed as P = kNm, where P, N, and m were number of patients, population size, and a constant (～2 for measles, and 1.3～1.4 for syphilis and amebiasis), respectively. The population size dependency emerged only when conditions other than population size, such as infant mortality, hygienic condition, vaccination practices, and others, improved to the same level in all the prefectures in Japan. The formation of prefectures and municipalities was well simulated by the random coin toss assuming that people are attracted to a community with a probability proportional to the number of the residents to the 1.3rd power. When the number of inflow population was plotted against the number of the resident population in a prefecture, or when the number of coins that were added in a round was plotted against the number of coins that were present before the coin toss, the plots fell on a straight line with the slope ～1.3, which was almost the same as the slope obtained when the number of cases of syphilis or amebiasis was plotted against the population size.

Scale-Free Distribution of Local Infection Clusters of Measles, Rubella, Syphilis, and HIV/AIDS: Correlation with Scale-Free Distribution of Municipality Population by Size.

The size distribution of a local infection cluster (LIC), a group of infections reported from the same prefecture without interruption in successive weeks, was scale-free for infections that are transmitted from person-to-person (e.g., measles, rubella, syphilis, and HIV/AIDS). For infections that do not spread from person-to-person, the distribution was entirely random. The size distribution for measles, rubella, syphilis, and HIV/AIDS could be simulated successfully by random coin tossing with probabilities that were higher for highly populated prefectures. The size distribution of the population in large municipalities (>120,000), as well as that of LICs, was found to be scale free. As the number of patients per prefecture was correlated with the equation P = kNm, where m was 1.38 for syphilis, 1.63 for HIV/AIDS, and 2 for measles or rubella, the frequency distribution of N1.38, N1.63, and N2, where N was population of municipalities, was compared with the frequency distributions of LIC sizes of syphilis, HIV/AIDS, measles, and rubella. The frequency distribution of LICs, particularly those of measles and rubella during the years when the epidemic was more severe, was close to the frequency distribution of Nm. The analysis suggested that LICs were products of stochastic events under the influence of municipality population size.

Erratum: Geo-Demography of HIV/AIDS in Japan from 1985 to 2011: Incidence and Transmission Mode under Influence of Population Size/Density.

Volume 69, no. 2, p. 97-108, 2016. Page 107, Figure 11 should appear as shown below.

Measles and Rubella: Scale Free Distribution of Local Infection Clusters.

This study examined the size distribution of local infection clusters (referred to as clusters hereafter) of measles and rubella from 2008-2013 in Japan. When the logarithm of the cluster sizes were plotted on the x-axis and the logarithm of their frequencies were plotted on the y-axis, the plots fell on a rightward descending straight line. The size distribution was observed to follow a power law. As the size distribution of the clusters could be equated with that of local secondary infections initiated by 1 patient, the size distribution of the clusters, in fact, represented the effective reproduction numbers at the local level. As the power law distribution has no typical sizes, it was suggested that measles or rubella epidemics in Japan had no typical reproduction number. Higher the population size and higher the total number of patients, flatter was the slope of the plots, thus larger was the proportion of larger clusters. An epidemic of measles or rubella in Japan could be represented more appropriately by the cluster size frequency distribution rather than by the reproduction number.

Geo-Demography of HIV/AIDS in Japan from 1985 to 2011: Incidence and Transmission Mode under Influence of Population Size/Density.

A stable relation was found between number of HIV/AIDS patients (P) and population size (N) and between HIV/AIDS incidence (I) and population density (D). The relation could be expressed as P = kN(m) or I = hD(n), where k, h, m, and n are constants. For "AIDS"/"AIDS diagnosis", the constant m was 1.5 for Japan and 1.3 for the United States of America (USA); n was 0.38 for both Japan and the USA. These observations indicated that larger population sizes related to disproportionately larger numbers of HIV/AIDS patients, and denser populations had disproportionately higher incidences of HIV/AIDS. Considering the wide geo-demographic difference between the two countries, it was striking that the same equations with constants within a narrow range were applicable to both Japan and the USA. Modes of HIV transmission appeared to be variable among prefectures in Japan. Homosexual transmission was suggested as being more predominant in more populated prefectures.