Zika might not be acting alone: Using an ecological study approach to investigate potential co-acting risk factors for an unusual pattern of microcephaly in Brazil

<div><p>Zika virus infections can cause a range of neurologic disorders including congenital microcephaly. However, while Zika infections have been notified across all regions in Brazil, there has been an unusual number of congenital microcephaly case notifications concentrated in the Northeast of the country. To address this observation, we investigated epidemiological data (2014–2016) on arbovirus co-distribution, environmental and socio-economic factors for each region in Brazil. Data on arbovirus reported cases and microcephaly were collected from several Brazilian Ministry of Health databases for each Federal unit. These were complemented by environmental management, social economic and <i>Aedes aegypti</i> infestation index data, extracted from multiple databases. Spatial time “ecological” analysis on the number of arboviruses transmitted by <i>Aedes</i> mosquitoes in Brazil show that the distribution of dengue and Zika was widespread in the whole country, with higher incidence in the West-Central region. However, reported chikungunya cases were higher in the Northeast, the region also with the highest number of microcephaly cases registered. Social economic factors (human development index and poverty index) and environmental management (water supply/storage and solid waste management) pointed the Northeast as the less wealthy region. The Northeast is also the region with the highest risk of <i>Aedes aegypti</i> house infestation due to the man-made larval habitats. In summary, the results of our ecological analysis support the hypothesis that the unusual distribution of microcephaly might not be due to Zika infection alone and could be accentuated by poverty and previous or co-infection with other pathogens. Our study reinforces the link between poverty and the risk of disease and the need to understand the effect on pathogenesis of sequential exposure to arboviruses and co-viral infections. Comprehensive large-scale cohort studies are required to corroborate our findings. We recommend that the list of infectious diseases screened, particularly during pregnancy, be regularly updated to include and effectively differentiate all viruses from ongoing outbreaks.</p></div

The placental parameters evaluated by <i>Plasmodium</i> species during infection.

<p>For all placentas, areas of necrosis (B) and intervillous space (C) were measured by overlaying a square grid (A) and counting the number of intersecting points that touched necrotic areas (yellow dots; the white circle indicates an example) or intervillous space areas (blue dots; the black circle indicates an example). The ratios of intervillous space area per necrosis (D) and intervillous space area per placental barrier thickness (E) were calculated. The placentas in the “no plasmodium” group (n = 41; white boxes) appear to have similar necrotic areas and more intervillous space than the placentas in the “P. vivax” group (n = 59; red boxes). The placentas in the “P. falciparum” group (n = 19; grey boxes) exhibited more necrotic areas and less intervillous space. Graphs (B, C, D and E) represent the transformed data. The boxes represent the mean and standard deviation values. The whiskers represent the 5^th and 95^th percentiles. The photograph was taken using a Zeiss Axio Imager M2 light microscope equipped with a Zeiss Axio Cam HRc. Grid overlays and counts were performed using Image J.</p

Results and univariate analysis of the placental parameters, evaluated by histology, according to the species of <i>Plasmodium</i> infection during pregnancy^†.

†<p>Women were grouped according to their malaria diagnoses during pregnancy, based on microscopy data. (IQ) 25^th and 75^th percentile. (n) number of women. (%) percentage (N/A) not applicable. For differences between groups all continuous variables were Ln-transformed and one-way ANOVA tests with Bonferroni post-tests were performed. Chi² tests were used to evaluate differences in categorical variables between groups. Refer to the “methods section” for a full description of how each parameter was measured.</p>*<p><i>P. falciparum</i> vs. No Malaria, P = 0.004.</p>§<p><i>P. falciparum</i> vs. <i>P. vivax</i>, P = 0.005.</p>°<p><i>P. falciparum</i> vs. No Malaria, P = 0.048.</p>#<p>χ² test: <i>P.</i> vivax or <i>P.</i> falciparum, P<0.001.</p

The immune-cell parameters evaluated by <i>Plasmodium</i> species during infection.

<p>The percentage of immune cells present in the intervillous space of the placentas evaluated (A) was calculated after counting a total of 500 intervillous space cells. Total leucocytes percentage (B), mononuclear cells percentage (C) and polymorphonuclear cells percentage (D) were plotted against <i>Plasmodium</i> exposure during pregnancy, assessed by microscopy. The placentas from the “no plasmodium” group (n = 41; white boxes) appear to have less immune cells present in the intervillous space than the placentas from the “P. vivax” group (n = 59; red boxes) and the placentas from the “P. falciparum” group (n = 19; grey boxes). * ANOVA test, P-value = 0,039. Graphs (B, C, and D) represent the transformed data. The boxes represent the mean and standard deviation values. The whiskers represent the 5^th and 95^th percentiles. The photograph was taken using a Zeiss Axio Imager M2 light microscope equipped with a Zeiss Axio Cam HRc. Grid overlays and counts were performed using Image J.</p

Stains and scoring system used to quantify malaria-associated placental parameter.

<p>Stains and scoring system used to quantify malaria-associated placental parameter.</p

The placental score differentiates the women who were exposed to <i>P. vivax</i> during pregnancy.

<p>A score (termed the ‘vivax-score’) was developed and applied to all of the placental samples in this study (see main text for details). (A) The placental samples from the “no Plasmodium” group (n = 41, white box) revealed a significantly lower score than the placentas from the “P. vivax” group (n = 59, red box) (* Mann-Whitney, P = 0.027). (B) The vivax-score increased significantly (** Cuzick's trend test: z = 2.76, P = 0.006) with increased exposure to <i>P. vivax</i> during pregnancy. “No infection”, n = 41; “1 infection”, n = 39; “2+ infections”, n = 20).</p

The syncytial parameters evaluated by <i>Plasmodium</i> species during infection.

<p>Syncytial knotting (A and B) and syncytial rupture (C and D) were evaluated on H&E-stained slides at 100× magnification. Placental barrier thickness (E and F) was evaluated on Masson's trichrome-stained slides at 1000× magnification after overlaying horizontal lines with 5 µm of interspace (see Methods and <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002071#pntd-0002071-t001" target="_blank">Table 1</a>). For all parameters, placentas from the “no plasmodium” group (n = 41; white boxes) had the lowest values, followed by placentas from the “P. vivax” (n = 59; red boxes) and “P. falciparum” (n = 19; grey boxes) groups. Graphs (B, D and F) represent the transformed data. * ANOVA test, P-value≤0,006. The boxes represent the mean and standard deviation values. The whiskers represent the 5^th and 95^th percentiles. Photographs were taken using a Zeiss Axio Imager M2 light microscope equipped with a Zeiss Axio Cam HRc. The grid overlays and counts were conducted using Image J. Arrow heads on A, C and D point to syncytial knots, syncytial rupture and an example of a thickness measurement, respectively.</p

Characteristics of the women who participated in the study according to infection status^†.

†<p>Women were grouped according to their malaria diagnoses during pregnancy, based on microscopy data. (SD) standard deviation. (IQ) 25^th and 75^th percentile. (n) number of women with data recorded. (%) percentage of total women in each group. (Hb) hemoglobin. (Ep.) number of episodes. (N/A) not applicable. Anemia: Hb<11 g/dL. Low birth weight: birth weight<2,500 g. 2+ infections during pregnancy: women with two or more infections detected over the duration of the pregnancy. Month of infection: Gestation month of first diagnosed infection. Trimester of infection: percentage of infections that were detected per trimester of gestation.</p>◊<p>Student's t-test: <i>P. falciparum</i> vs. no malaria, P = 0.015.</p>•<p>Student's t-test: <i>P. falciparum</i> vs. <i>P. vivax</i>, P = 0.029.</p>§<p>χ² test: no malaria vs. <i>P.</i> vivax or <i>P.</i> falciparum, P<<0.001.</p

Cuzick's trend test analysis of placental changes across ordered groups by number of <i>P. vivax</i> infections during pregnancy^†.

†<p>Women were divided according to the number of <i>P. vivax</i> infections that were diagnosed microscopically during pregnancy.</p>a<p>Cuzick's trend test was performed across the ordered groups: no <i>P. vivax</i> infection (0), one <i>P. vivax</i> infection (1) and two or more <i>P. vivax</i> infections (2+). (z) Measure and direction of tendency.</p

Malaria in Pregnancy Interacts with and Alters the Angiogenic Profiles of the Placenta

<div><p>Malaria in pregnancy remains a substantial public health problem in malaria-endemic areas with detrimental outcomes for both the mother and the foetus. The placental changes that lead to some of these detrimental outcomes have been studied, but the mechanisms that lead to these changes are still not fully elucidated. There is some indication that imbalances in cytokine cascades, complement activation and angiogenic dysregulation might be involved in the placental changes observed. Nevertheless, the majority of studies on malaria in pregnancy (MiP) have come from areas where malaria transmission is high and usually restricted to <i>Plasmodium falciparum</i>, the most pathogenic of the malaria parasite species. We conducted a cross-sectional study in Cruzeiro do Sul, Acre state, Brazil, an area of low transmission and where both <i>P</i>. <i>vivax</i> and <i>P</i>. <i>falciparum</i> circulate. We collected peripheral and placental blood and placental biopsies, at delivery from 137 primigravid women and measured levels of the angiogenic factors angiopoietin (Ang)-1, Ang-2, their receptor Tie-2, and several cytokines and chemokines. We measured 4 placental parameters (placental weight, syncytial knots, placental barrier thickness and mononuclear cells) and associated these with the levels of angiogenic factors and cytokines. In this study, MiP was not associated with severe outcomes. An increased ratio of peripheral Tie-2:Ang-1 was associated with the occurrence of MiP. Both Ang-1 and Ang-2 had similar magnitudes but inverse associations with placental barrier thickness. Malaria in pregnancy is an effect modifier of the association between Ang-1 and placental barrier thickness.</p></div