Multiplex serologic testing within a cross-sectional lymphatic filariasis sentinel site survey in coastal Kenya reveals community-level differences in IgG antibody responses to parasitic diseases and vaccines

Accurate, cost-effective measurement of the burden of co-endemic infections would enable public health managers to identify opportunities for implementation of integrated control programs. Dried blood spots (DBS) collected during a cross-sectional lymphatic filariasis sentinel site survey in the Kenyan coastal counties of Lamu, Tana River, Kilifi, Kwale, and Taita-Taveta were used for the integrated detection of serologic IgG antibodies against antigens from several parasitic infections (Wuchereria bancrofti, Schistosoma mansoni, Plasmodium spp, Ascaris lumbricoides, and Strongyloides stercoralis) as well as markers for immunity to vaccine-preventable diseases (measles, diphtheria, and tetanus) on a multiplex bead assay (MBA) platform. High heterogeneity was observed in antibody responses by pathogen and antigen across the sentinel sites. Antibody seroprevalence against Wb123, Bm14, and Bm33 recombinant filarial antigens were generally higher in Ndau Island (p<0.0001), which also had the highest prevalence of filarial antigenemia compared to other communities. Antibody responses to the Plasmodium species antigens CSP and MSP-119 were higher in Kilifi and Kwale counties, with Jaribuni community showing higher overall mean seroprevalence (p<0.0001). Kimorigo community in Taita-Taveta County was the only area where antibody responses against Schistosoma mansoni Sm25 recombinant antigen were detected. Seroprevalence rates to Strongyloides antigen NIE ranged between 3% and 26%, and there was high heterogeneity in immune responses against an Ascaris antigen among the study communities. Differences were observed between communities in terms of seroprevalence to vaccine-preventable diseases. Seroprotection to tetanus was lower in all 3 communities in Kwale County compared to the rest of the communities. This study has demonstrated that the MBA platform holds promise for rapid integrated monitoring of trends of infections of public health importance in endemic areas, and assessing the effectiveness of control and elimination programs. Author Summary Establishment of successful private-public partnerships in the recent past has led to an increase in resources available for control and elimination of malaria and Neglected Tropical Diseases (NTDs). Implementation of control and elimination programs and their subsequent monitoring and evaluation would be greatly facilitated by development of new tools and strategies for rapid identification of areas of transmission so that interventions could be prioritized to regions where they were most needed. Since development of antibody responses in a host depend on exposure to an infectious agent, assessment of such serologic markers provides a sensitive way to measure differences between populations in pathogen exposure. Our study applied a state-of-the-art multiplex bead assay platform to perform integrated measurement of antibody responses to multiple parasitic diseases and immunizing antigens for vaccine-preventable diseases (VPDs) in ten lymphatic filariasis sentinel sites across the Kenyan coastal region. A community-level analysis of age-specific and overall mean seroprevalence fit using a flexible model ensemble provided an improved understanding about the distributions of the various parasitic infections and seroprotection to VPDs. This study provides an important proof of concept for how we could dramatically increase the value of existing surveillance activities using small volumes of blood collected on filter paper and analyzed using a single multiplex laboratory assay and novel data analysis techniques.


Introduction
Persons living in tropical and subtropical areas are often faced with enormous health challenges resulting from the co-endemicity of HIV/AIDS, tuberculosis, and malaria. In addition, several other infectious diseases found in sub-Saharan Africa including some Neglected Tropical Diseases (NTDs) are common, particularly among the poor [1][2][3]. Past studies in the region have In the past, lack of resources and competing health priorities in sub-Saharan Africa have led to insufficient commitments to control NTDs. More recently, implementation of successful publicprivate partnerships (PPPs) for health have availed resources for control and/or elimination of NTDs as public health problems. In 2000 the World Health Organization (WHO) Global Programme to Eliminate Lymphatic Filariasis (GPELF), launched in response to World Health Assembly resolution WHA50.29, urged Member States to initiate activities to eliminate LF as a public health problem, a goal subsequently targeted for 2020 [11]. Community-wide mass drug administration (MDA) of antifilarial drugs for 4-6 years is recommended for LF elimination, and modeling studies have estimated adequate treatment coverage to be at least 65% of total population in endemic areas [12,13]. Substantial progress has been made towards elimination of LF, with Togo being the first country in sub-Saharan Africa to be recognized by WHO for eliminating the disease as a public health problem [14,15]. The Kenyan Ministry of Health launched an LF elimination program in 2002, but the program did not sustain MDA campaigns annually as per GPELF recommendations [16,17]. In 2015, the Ministry of Health successfully appealed to World Health Organization Regional Office for Africa (WHO-AFRO) and other partners for support to re-establish annual MDA campaigns. Subsequently, the WHO Country Office selected the Eastern and Southern Africa Centre of International Parasitic Control (ESACIPAC), which is part of the Kenya Medical Research Institute (KEMRI), to conduct a comprehensive epidemiological assessment of LF infection before re-starting MDA.
Antibody levels can provide valuable information about exposure to infections and can be helpful for characterizing pathogen transmission dynamics to help identify where interventions are needed the most. As some parasite antigens are known to elicit an immunoglobulin G (IgG) response that can be detected for a long period of time, serological analysis of young children provide an estimate of more recent exposure [18,19]. A state-of-art multiplex bead assay (MBA) serological platform that enables simultaneous detection of antibodies against multiple antigens using a small volume of blood sample dried on filter paper [10 µL dried blood spots (DBS)] has been developed as a tool for integrated biomarker surveys [20][21][22]. The MBA has successfully been used to simultaneously measure antibody responses to multiple parasitic diseases of public health importance as part of a vaccine-preventable disease serological survey in Cambodia [23]. The platform has also been used to simultaneously assess IgG responses to a panel of malaria antigens [24,25]. In the current study, the MBA platform was used for multiplex serosurveillance of diseases of public health importance by testing for antibodies against LF and several other parasitic diseases (malaria, schistosomiasis, ascariasis, strongyloidiasis) as well as seroprevalence to selected vaccinepreventable diseases (measles, diphtheria, and tetanus).

Study design and samples
The DBS samples used in this study were collected during a cross-sectional LF survey conducted in October 2015 in ten sentinel sites located across the coastal region in Taita-Taveta, Kwale, Kilifi, Tana River and Lamu counties as previously described [17]. Briefly, 300 persons aged 2 years or more in each sentinel site were targeted for the LF survey as recommended in the WHO guidelines [11]. The characteristics of the study participants are described in Njenga et al. [17]. The middle finger of consenting individuals was cleaned using a cotton ball soaked in 70% isopropyl alcohol. After drying, the tip of the finger was pricked using a sterile lancet and blood was collected into capillary tubes for detection of circulating filarial antigen (CFA) by immunochromatographic card test (ICT) and onto filter paper for preparation of dried blood spots (6 spots of 10 µl each; Tropbio Pty Ltd, Queensland, Australia) which were used for the MBA.

Ethical considerations
The study received ethical approval from Kenya Medical Research Institute (KEMRI) Scientific and Ethics Review Unit (SSC No. 3018). In the study villages, chiefs and assistant chiefs arranged for community mobilization meetings during which the purpose of the survey and procedures to be followed were explained. Written informed consent was obtained from every individual who agreed to participate in this study; parents or legal guardians provided signed informed consent forms on behalf of children under 18 years of age. All of the community acquired samples were assayed in the KEMRI-ESACIPAC laboratory in Nairobi, Kenya.

Recombinant antigens and coupling to microsphere beads
Recombinant Schistosoma mansoni glutathione-S-transferase (GST) protein was expressed from pGEX 4T-2 plasmid (GE Healthcare, Piscataway, NJ) and purified as previously described [ with 0.85% NaCl at a concentration of 60 µg of protein per 1.25 x 10 7 beads in 1 ml final volume. In order to decrease background reactivity, measles MV-N was purified by chromatography on a MonoQ HR 5/5 strong anion exchange column (GE Healthcare, Piscataway, NJ) prior to use. Protein (0.75 mg) was loaded onto the column at a flow rate of 1 ml/ min and washed with 4 ml of 25 mM Tris buffer at pH 8.0. This was followed by a 10 ml linear gradient to 0.25 M NaCl in Tris buffer, then by a 5 ml linear gradient to 1 M NaCl in Tris buffer. The majority of antibody-reactive MV-N eluted in the high salt fractions between 0.4 and 0.7 M NaCl. These fractions were pooled, concentrated using a Centricon-30 centifugal filter device (Millipore Corporation, Bedford, MA), and exchanged into buffer containing 10 mM sodium phosphate with 0.85% NaCl at pH 7.2 (PBS). Approximately 115 µg of protein was recovered (BCA micro assay, Pierce, Rockford, IL). MonoQ purified MV-N was coupled in buffer containing 50 mM MES at pH 5.0 with 0.85% NaCl at a concentration of 6 µg of protein per 1.25 x 10 7 beads in 1 ml final volume.

Multiplex bead assay
One bloodspot from each person, corresponding to about 10 µl of whole blood, was eluted overnight at 4⁰C with 200 microliters of PBS containing 0.05% Tween-20 and 0.05% sodium azide (1:40 serum dilution assuming a 50% hematocrit). A further dilution of 50 microliters of eluate into 450 µl of PBS containing 0.5% casein, 0.3% Tween 20, 0.02% sodium azide, 0.5% polyvinyl alcohol (PVA), and 0.8% polyvinylpyrrolidone (PVP) (designated as PBN1) with 3 micrograms/ml Escherichia coli extract was made for a final serum dilution of 1:400. Serum dilutions were centrifuged at maximum speed to pellet the E. coli extract particulates immediately before use. Bloodspot dilutions were assayed in duplicate with antigen-coupled microsphere beads using a BioPlex 200 system platform (Bio-Rad, Hercules, CA) as previously described [21,23,25]. The average of the median fluorescent intensity values from the duplicate wells minus the background fluorescence from the buffer-only blank was reported as the "median fluorescence intensity minus background" (MFI-bg).
Samples having a coefficient of variation of >15% for ≥2 positive responses between the duplicate wells were repeated. anonymous US children was used to identify the cutoff for the Ascaris Hb MBA. All of the parasitic disease cutoff values were adjusted to account for differences between the instrument used for cutoff determination at the CDC in Atlanta, GA, and the instrument used to assay the Kenyan sample set at KEMRI in Nairobi, Kenya. Two-fold serial dilutions of the same strong positive sera were assayed on both instruments to generate standard curves for cutoff value adjustment.

Cutoff determinations
S. mansoni SEA and Sm25 coupled beads were used in an earlier study, and the adjusted, ROC- We also estimated seropositivity cutoff points for malaria, LF, and helminth antibody responses using the mean plus three standard deviations of a seronegative distribution estimated from the study measurements using finite Gaussian mixture models with two components [42].

Statistical analysis
Mean antibody levels (MFI-bg) were analyzed on the log10 scale due to skewness in their distribution. We estimated age-dependent mean antibody levels and seroprevalence for each study community using cross-validated, ensemble machine learning, with a library that included the simple mean, linear models, locally weighted regression (loess), and smoothing splines with 2 to 10 degrees of freedom, selected using 10-fold cross-validation [43]. We estimated age-adjusted geometric mean antibody levels and seroprevalence for each community using targeted maximum likelihood estimation with influence curve-based standard errors [43]. In cases where seroprevalence approached zero, we estimated exact binomial confidence intervals. Analyses were conducted using R version 3.3.1, and full replication files (data, scripts) are available through the Open Science Framework (https://osf.io/taknp).

Results
Antibody measurements were obtained from 2,837 individuals (range 271 -297 per community) (S1 Fig). Antibody distributions varied by pathogen and antigen, and overall there was good concordance between seropositivity cutoff values for malaria, LF and helminth antibody responses derived through ROC curve analysis or mean plus 3 standard deviation calculations and those derived by Gaussian mixture model analysis ( Figure 1). We therefore relied on cutoff values derived from the Gaussian mixture model antibody responses for comparability to future studies that may not have access to positive and negative control specimens. Age-dependent patterns and community-level estimates of mean antibody levels and seroprevalence were highly consistent (S2 Fig, S3 Fig, S4 Fig, S5 Fig, S6 Fig), so we report results based on mean antibody levels in supporting information.

Antibody responses to other parasite antigens
Antibody responses to the P. falciparum CSP and MSP-119 antigens and to the P. malariae MSP-119 antigen increased with age in communities in Kilifi and Kwale counties, with higher seroprevalence in Jaribuni community compared to other communities in Kilifi (p<0.0001, Figure 3).
Mean antibody responses against P. malariae MSP-119 antigen also increased with age and were highest in Jaribuni (p<0.0001), but very low in Ndau Island and Kipini communities (p<0.0001 for difference with other communities).
Antibody responses against Schistosoma mansoni Sm25 recombinant antigen were primarily detected in Kimorigo community, and the seroprevalence increased gradually with age, reaching a peak at around 25 years of age ( Figure 4). However, although antibody responses to S. mansoni SEA antigen also increased with age in Kimorigo community and mean seroprevalance was higher, there were some responses against this antigen in many other communities.
Steady increases in S. stercoralis NIE seroprevalence with age were observed and community level mean seroprevalence ranged between 3% and 26% ( Figure 5). There was heterogeneity in agedependent Ascaris Hb seroprevalence patterns across communities, with seroprevalence increasing with age in some communities and decreasing with age in others ( Figure 5).

Immune responses to vaccine preventable diseases
Immune response against measles MV-N antigen increased with age, but two communities in Kwale County (Mirihini and Mwadimu) had <90% seroprotection ( Figure 6). Immune responses to diphtheria toxoid were relatively higher among children, but waned slightly around the ages of 30-40 years before increasing slightly. Generally, diphtheria seroprotection ranged between 22-44% across communities, and partial protection (defined as responses of 0.01-0.099 IU/ml) ranged between 70-88% across communities. Immune responses against tetanus toxoid decreased by age in all communities until around 15 years when the levels increased again. Tetanus seroprotection was lower in all 3 communities in Kwale County. arabiensis, and An. merus [51]. The study also showed that relatively high malaria parasite prevalence can occur at low and even non-detectable levels of entomological inoculation rates (EIR), suggesting that measurement of EIR may be a relatively insensitive indicator of malaria transmission in some settings. Although malaria parasite prevalence and/or EIR have traditionally been used for reporting malaria transmission intensity [52], serological markers have increasingly been recognized as useful indicators for estimating malaria transmission intensity, which is key for assessing the impact of control interventions [53][54][55][56]. Because of the longevity of the specific antibody response, seroprevalence reflects cumulative exposure and thus is less affected by seasonality or unstable transmission [57].

Discussion
In Kenya, Schistosoma haematobium is highly endemic along the coast where human exposure occurs primarily at pond and stream snail habitats [9, 58,59]. The absence of S. mansoni from most of the Kenyan coastal region is attributable to the absence of the Biomphalaria spp.
intermediate-host snails [60]. In Mikinduni Community, along the lower Tana River, crude antigen SEA antibody responses were observed, but S. mansoni-specific Sm25 responses were lacking. In contrast, Taveta area in Taita-Taveta County is known to be endemic for both S. haematobium and S. mansoni infections [61,62], and this is reflected in the high SEA and Sm25 antibody responses we observed in Kimorigo, a community located on the banks of the shallow freshwater Lake Jipe. The absence of S. mansoni species-specific antibody responses to Sm25 recombinant antigen in all of the communities except Kimorigo confirms that S. mansoni infection is likely absent from the lower coastal areas. Thus, S. mansoni Sm25 recombinant antigen seems to be an excellent antigen for measuring antibody responses to S. mansoni infection [63], and SEA antigen likely detects antibody responses caused by both Schistosoma species by virtue of cross-reactivity.
Presence of responses to S. stercoralis NIE antigen is noteworthy because there has been little information on the geographic distribution of this helminth in Kenya due to diagnostic limitations. Copromicroscopic diagnostic methods commonly used in soil-transmitted helminthiasis prevalence studies are inadequate for S. stercoralis detection [64], and thus its distribution in many areas is unknown. Concentration methods, namely the Baermann technique and Koga agar plate culture, have better but still unsatisfactory sensitivity [65]. A study employing NIE serology in Argentina found no cross-reactivity between S. stercoralis and infections with A. lumbricoides, hookworms, or H. nana, and the presence of other helminths in the stool did not affect the S. stercoralis-specific antibody responses [66]. A study comparing five serologic tests identified NIE-Luciferase Immunoprecipitation System to be the most accurate assay for the diagnosis of S. stercoralis infection [67]. Previous studies using the recombinant NIE have documented high seroprevalence of S. stercoralis infection in remote Australian Indigenous communities and suggest that collection of dried blood spots may be a useful approach for field diagnosis of S. stercoralis seroprevalence [68,69]. This study, therefore, provides evidence for possible low-level transmission of S. stercoralis in coastal Kenya as the seroprevalence varies from community to community.
Community mean antibody responses to the Ascaris Hb native antigen and seroprevalence exhibited high heterogeneity among the study communities. A population-based study in Indonesia has shown that an assay for antibodies to Ascaris Hb is useful for assessing transmission of Ascaris infections, and community antibody rates decreased rapidly following MDA of anthelmintic drugs. The decrease was also found to reflect reduced egg excretion at the community level [33].
Vaccination is one of the most one of the most cost-effective public health interventions available, and the epidemiology and burden of vaccine-preventable diseases vary by country and by region partly because of differences in vaccine uptake [70]. This multiplex integrated serosurveillance study identified heterogeneity in serologic antibody levels against measles, diphtheria, and tetanus antigens. Our study demonstrates a need for regularly monitoring serological responses to vaccination programs in resource-poor settings where coverage may be low.
Some of the limitations of this study are somewhat similar to those highlighted previously [23]. Serological studies are traditionally faced with the challenge of establishing diagnostic cutoff points especially when well-characterized positive and negative serum samples are not available.
Finite Gaussian mixture models applied in this study led to cutoff values that were very similar to those derived through ROC curves or from mean plus 3 standard deviation calculations for malaria, LF and helminth antibody responses (Fig 1). This result is consistent with a recent, multi-country comparison of cutoff methodology for trachoma antibodies [71], and supports the use of finite mixture models to identify seropositivity cutoffs in studies without access to panels of known positive and negative specimens. For pathogens where cutoff values fall in the centre of a unimodal distribution and it is more difficult to distinguish seropositive and seronegative groups (e.g., A. suum Hb in Fig 1), the use of community mean antibody levels avoids the requirement of choosing a cutoff, and observed antibody response patterns were very consistent with seroprevalence estimates across all of the antibodies tested in this study (S2-S6 Figs). Another limitation of this study is potential for antibody cross-reactivity. Since the coastal area has a typical tropical climate, it is likely that a plethora of pathogens are coincident, some with potentially cross-reactive antigens. A previous study reported that cross-reactivity of the Ascaris Hb native antigen with hookworm and possibly S. stercoralis and Toxocara spp. limited its value in serology if one is interested in ascariasis alone [33]. Thus, further studies are required to identify sensitive and specific recombinant antigens that could be used with more confidence in serological assays.
In spite of these limitations this study employed a single multiplex integrated serological assay and analysis methodology to measure antibody levels against several pathogens. There was no need to run separate assays for each pathogen, and we did not need to develop different mathematical models for each pathogen in order to compare exposure across communities and counties. The study highlighted overlap in pathogen burden that would not necessarily have been detected through single-disease surveillance. For example, Ndau Island was found to have the highest LF seroprevalence, but it also had highest Ascaris seroprevalence, thus supporting integrated control of these two helminths. Interestingly, Ndau had almost no evidence for P. falciparum malaria transmission. On the other hand Jaribuni community was found to stand out in terms of malaria, LF, and Strongyloides. Multiplex, integrated surveillance has the potential to enable us to look across diseases for opportunities for integrated control, thus providing synergy to global public health initiatives.

Conclusion
This study highlighted the utility of the MBA platform for integrated serosurveillance of biomarkers of diseases of public health importance. The multiplex integrated serologic assay has the potential to become an invaluable tool for integrated monitoring of trends in endemicity of diseases of public health importance and the effectiveness of public health control programs. . Antibody response measured in multiplex using median fluorescence units minus background (MFI-bg) on a BioRad Bio-Plex platform. Seroprotection cutoff points for measles, diphtheria, and tetanus estimated using a standard curve from WHO reference standards. Seropositive cut points for other antigens estimated using negative control serum samples (solid) and finite Gaussian mixture models (dashed). There was no negative control cutoff point determined for the P. falciparum CSP antigen. Table S1 includes cutoff values. The script that created this figure is here: https://osf.io/d9jr.

Figure 2:
Lymphatic filariasis antibody age-dependent seroprevalence and overall means, stratified by community in Kenya's coastal region, 2015. Community-level mean seroprevalence is ageadjusted and error bars represent 95% confidence intervals. Figure S2 is an extended version of this figure that also includes quantitative antibody levels. The script that created this figure is here: https://osf.io/5zkxw. Community-level mean seroprevalence is age-adjusted and error bars represent 95% confidence intervals. Figure S3 is an extended version of this figure that also includes quantitative antibody levels. The script that created this figure is here: https://osf.io/kzfd3. Community-level mean seroprevalence is age-adjusted and error bars represent 95% confidence intervals. Figure S4 is an extended version of this figure that also includes quantitative antibody levels. The script that created this figure is here: https://osf.io/tpcg7.

Figure 5:
Age-dependent seroprevalence and overall mean for antibodies to S. stercoralis and A. lumbricoides, stratified by community in Kenya's coastal region, 2015. Community-level mean seroprevalence is age-adjusted and error bars represent 95% confidence intervals. Figure S5 is an extended version of this figure that also includes quantitative antibody levels. The script that created this figure is here: https://osf.io/j7ux3. Figure 6: Age-dependent seroprotection and overall seroprotection for measles, diphtheria, and tetanus stratified by community in Kenya's coastal region, 2015. Community-level seroprotection is age-adjusted and error bars represent 95% confidence intervals. For diphtheria, we included separate community level estimates of seroprotection (MFI > 4393 corresponding to 0.1 IU/ml) and partial protection (MFI > 183 corresponding to 0.01 IU/ml). Figure S6 is an extended version of this figure that also includes quantitative antibody levels. The script that created this figure is here: https://osf.io/qrkhm. Supporting Information S1 Checklist: STROBE checklist. S1 Figure. Community level sample size and age distribution. The script that created this figure is here: https://osf.io/7jxmn.

S2 Figure:
Lymphatic filariasis antibody age-dependent mean response and seroprevalence, stratified by community in Kenya's coastal region, 2015. Community-level mean antibody response and seroprevalence are age-adjusted and error bars represent 95% confidence intervals. Antibody response measured in median fluorescence units minus background (MFI-bg) on a BioRad Bio-Plex platform. The script that created this figure is here: https://osf.io/c79rw.   for measles, diphtheria, and tetanus estimated using a standard curve from WHO reference standards. Seropositive cut points for other antigens estimated using negative control serum samples (solid) and finite Gaussian mixture models (dashed). There was no negative control cutoff point determined for the P. falciparum CSP antigen. Table S1 includes cutoff values.  Community-level mean seroprevalence is age-adjusted and error bars represent 95% confidence intervals. Figure S2 is an extended version of this figure that also includes quantitative antibody levels. Figure created with computational notebook: https://osf.io/5zkxw . Community-level mean seroprevalence is ageadjusted and error bars represent 95% confidence intervals. Figure S3 is an extended version of this figure that also includes quantitative antibody levels. Figure  Community-level mean seroprevalence is ageadjusted and error bars represent 95% confidence intervals. Figure S4 is an extended version of this figure that also includes quantitative antibody levels. Community-level mean seroprevalence is age-adjusted and error bars represent 95% confidence intervals. Figure S5 is an extended version of this figure that also includes quantitative antibody levels.   Figure S6 is an extended version of this figure that also includes quantitative antibody levels. Figure created with