Social Marketing: Planning Before Conceiving Preconception Care

Social marketing approaches can help to shape the formation of and to create demand for preconception care services. This article describes four components of social marketing, often referred to as the 4 P’s, that should be carefully researched and set in place before a national effort to launch and sustain preconception care services is pursued. First, the product or package of services must be defined and adapted using the latest in scientific and health care standards and must be based on consumer needs and desires. Second, the pricing of the services in financial or opportunity costs must be acceptable to the consumer, insurers, and health care service providers. Third, the promotion of benefits must be carefully crafted to reach and appeal to both consumers and providers. Fourth, the placement and availability of services in the marketplace must be researched and planned. With the application of market research practices that incorporate health behavior theories in their exploration of each component, consumer demand for preconception care can be generated, and providers can take preconception care to the market with confidence.
Introduction
Preconception care (PCC) is a critical component of maternal and child health that does not currently have a strong foothold in our health care delivery system [1–3]. A more detailed discussion of how preconception care supports preconception health (PCH) and ultimately healthy pregnancies and babies is found in the introduction of this volume. In order to market a health product or service, it is important to understand what people want or need before it is developed, and then to provide them with the opportunity to meet those needs in a way that is compelling to them and also improves a mutually beneficial outcome for patients and their providers: a healthy baby. Of course, unlike commercial products, the outcome of preconception care services (a healthy pregnancy and a healthy baby), cannot be guaranteed; there are many factors that influence pregnancy and birth outcomes that are outside a mother or healthcare provider’s realm of control. Despite the risk of adverse outcomes, there is much a woman, her partner, and her health care provider can do together preconceptionally to optimize pregnancy and birth outcomes. Social marketing is defined as “the application of commercial marketing technologies to the analysis, planning, execution, and evaluation of programs designed to influence voluntary behavior of target audiences in order to improve their personal welfare and that of society” (4). The social marketing process involves identifying an effective “marketing mix” of product, price, promotion, and place with the goal of offering an exchange that has clear and compelling benefits, minimal barriers, and an advantage over the competition. In plain language, that means setting up a situation so that future parents, health care professionals, and health insurers can all benefit and support a common goal of healthy women, healthy pregnancies, and healthy babies. To accomplish this, resources first need to be dedicated to conducting audience and market research using a systematic approach at all levels. Often, health behavior theories can be used to shape the development of new products or services as well as to evaluate their effectiveness in achieving intended outcomes. Table 1 lists some of the theories and frameworks that can be applied to addressing the 4 P’s of preconception care services (5).
Table 1Theories and frameworks applicable to guiding research on the 4 P’s of social marketing preconception care servicesMarketing componentTheory or frameworkFocus of the theory or frameworkRelevant constructs or conceptsProductSocial marketingThe application of marketing techniques to the design, implementation, and evaluation of programs designed to facilitate voluntary exchanges of mutual benefit and improved personal well-being and societal welfareFormative research; Market segmentation; Competitive analysisDiffusion of InnovationThe spread of new ideas, products, or services within a society or from one society to another; focus on innovationRelative advantage; Compatibility; Complexity; Trialability; ObservabilityPriceSocial cognitive theoryThe interaction between personal factors, environmental factors, and human behaviorReciprocal determinism; Behavioral capability; Expectations; Self-efficacy; Observational learning; ReinforcementsHealth belief modelThe perceptions of threat posed by a health problem, the benefits of avoiding the threat, and factors influencing the decision to actPerceived benefits; Perceived barriers; Cues to action; Self-efficacyPromotionDiffusion of innovationThe spread of new ideas, products, or services within a society or from one society to another; focus on diffusionCommunication channels; Social systems/networksPrecaution adoption process modelThe journey from lack of awareness to action and maintenance in dealing with hazards; acknowledge inherent riskUnawareness; Unengaged; Decision-making; ActingPlaceCommunication theoryThe different types of communication that affect health behaviorMedia Exposure; Media effects; Agenda setting; FramingNote. For easy-to-understand information about the theories, frameworks, constructs, and concepts listed in this table, go to http://www.nci.nih.gov/theory/pdf for a downloadable copy of NCI’s “Theory at a Glance—A guide for health promotion practice”
Viewing health care services as a business, and using language such as “marketing” and “sales,” may be uncomfortable to some who prefer to view the process of having a baby as a natural, emotional and deeply personal part of the human experience. However, the notion of providing preconception care as a service could very well benefit from a well-conceived and constructed social marketing research plan and execution that acknowledges and embraces the emotions of the patient and her partner. Thus, thinking about developing a social marketing plan to support preconceptional health care could help to ensure that babies are born with the best start in life.
One example of how the business market has taken advantage of this type of opportunity is the development of a bank that preserves umbilical cord blood (UCB). The original idea in 1988 was a not-for-profit resource bank of donated cord blood for those who might need it for transplantation purposes (6). However, since that time, enterprising companies have created a market and generated the “need” for cord blood storage for a couple’s own child—even though the chances they will personally need it are roughly 1 in 10,000. Companies who forecast a profit in this service use direct marketing strategies to expectant couples through diaper companies and magazine subscriptions. Attempts to patent the cryopreservation processes and limit competition have raised legal, ethical and clinical questions—but the market to sell the idea of cord blood collection and preservation is lucrative and the demand is increasing (7). Advocates of preconception care can learn important lessons from the UBC preservation business marketing executives who market, sell and provide services to a similar audience.
Product
Preconception care (PCC) is the product or concept we are trying to “sell” as a precursor for assuring PCH: The need for PCC is well-supported by research in the health field (1, 8, 9). The product has been described in a number of publications as including a “bundle” of services most often including screening of the following elements: reproductive history; medications and potential teratogens; environmental exposures; age, family medical and genetic history; infections and immunizations; social habits and risk behaviors; diet and exercise; and any chronic medical conditions (10, 11). Preconception care is supported by a number of practitioner specialties (1, 12, 13) and was related to a Healthy People 2000 goal (14). Whereas some aspects of PCC have more evidence linking them to improved outcomes (e.g., folic acid for NTDs and glycemic control for diabetes) and others have less evidence (e.g., genetic counseling and smoking cessation), the need for a more integrated approach to health prior to conception enjoys a broad range of support (15–18). Nevertheless, there has been little support of PCC in a systematic manner in the US or other countries as a standard of care (2, 19–21). A social marketing approach can provide an important support for that uptake by beginning with a critical first step–defining the attributes of the “product” we are selling from a potential consumer’s point of view—which involves formative research with consumers. Key questions for the research may include: what do women and their partners want, when are PCC services optimally delivered, and what needs would have to be met in order for women or couples to value PCC services? This approach dictates that it is important to understand the perspective of the patient (and her partner) as more than just as consumers of health care services, but also by understanding their other perceived needs and desires in order to provide a satisfactory exchange. Couples may not view the decision to start a family as a medical decision, so this may be one reason the health care delivery system is more likely to be engaged some time after conception. In fact, couples may assess their financial readiness to start a family before their physical, emotional, or relationship readiness for this life-altering decision. The research that is an integral part of the social marketing process can help us to understand the decision-making dynamic (or lack thereof) that couples may engage in prior to conception. While only 50% of pregnancies are planned in the U.S., understanding how couples think about pregnancy may be a good place to start. Frishman suggests other “windows of opportunity” that could be explored among women including when women inquire about birth control, obtain negative pregnancy tests, or have recently delivered a baby (22). Wallerstedt et al. suggest that preconceptional health promotion and interconceptional counseling may be even more beneficial for parents who have had previous perinatal or infant loss (23). Social marketing research can help provide an understanding of the motivations and barriers for and against preconception care. A social ecological perspective (24) encourages program planners to look at multiple levels of influence: 1) intrapersonal or individual level; 2) interpersonal or social level; 2) institutional or organizational level; 4) community level; 5) and public policy or societal level. A major corporation preparing to launch a new product for women who might become pregnant (e.g., a new home pregnancy test) would never begin without spending substantial time and resources on understanding the target market and identifying the product attributes that will appeal to that market, while also knowing what the competitive environment is before they make investments in product development that might not have a profitable return. Product attributes can have a major impact on both the speed and extent of a product’s uptake by a target population. Rogers’ diffusion of innovation theory (25) identified a number of product attributes including relative advantage (is the product better than what it will replace?), compatibility (does the product fit with the intended audience?), complexity (is the product easy to use?), trialability (can the product be “tried out” before making a decision to purchase it?), and observability (are the results of the product visible and measurable?). Program planners can position their products effectively in the marketplace if they maximize their product’s appeal by addressing these important product attributes.
Price
The next aspect of social marketing research to increase the supply of and demand for preconception care is price—defining the costs to patients, providers and insurers, measured in time and/or money, in order to have quality and timely preconception care. Once the product attributes have been defined and developed to address PCC services in a mutually satisfactory way for women, health care professionals and insurers, then appropriate pricing is vital to allow for uptake. Lowering the intangible (non-financial) costs to patients can be facilitated by using some common standards of social marketing: the most effective health messages often incorporate emotional connections and values to make behavior change more appealing. Also, the best social marketing approaches make it easy for people to make changes that the service providers want them to—in this case in order to be healthy, and have a healthy pregnancy and baby. In addition to appeal and ease, some marketers would say that a new product would have to have relative advantage over products currently in the marketplace. “New and improved” labeling does matter when a product is introduced. A product’s relative advantage can often be framed as more appealing and/or easier, but at its core it must meet a customer need or desire. Appealing and easy actions to improve health are perceived as less costly by the patient or customer. Social cognitive theory (26) which addresses the interaction between personal, environmental, and behavioral factors is commonly used to understand many facets of a person’s expectations of outcomes from performing a behavior, environmental contexts (helps and hindrances) related to the behavior, experiences in performing the behavior (positive or negative), and efficacy (ability/confidence) in performing the behavior. These are just a few of the ways in which the pricing can build on the positive product attributes developed in the first step. It also helps that the outcome—a healthy pregnancy and baby—is a highly valued and very tangible benefit for those who want it.
The pricing for a health care organization is more complicated. Cost-effectiveness studies and business case studies need to document how the organization’s PCC service costs compare with treatment of preventable health conditions. Balancing financial overhead and time pressures in these times of managed care may be a real challenge—and particularly so for reaching women who may have unplanned pregnancies. The greatest challenge may be weighing the intangible costs and benefits against the financial costs: How much preconceptional folic acid counseling is worth a child being born without a lifelong disability like spina bifida? How many smoking cessation sessions balance out the costs of a premature/low birth weight baby who might spend his first months of life in the NICU? How many fewer patients might a health care professional have time to see and bill for when pregnancy counseling they do for people with genetic conditions takes up more time? And what additional patient education messages, addressing chronic or acute health issues, are not being delivered during a regular well visit because the health care professional’s time is being used discussing preconception health issues? The health care provider medical office may well not be the best and/or most efficient way to market preconception care services to consumers in many cases. The practicing physician may also not be the first or best person to deliver the preconception care message. The goal of a good pricing strategy is to find an effective and innovative way to reach the target market while reducing the costs to both the health care delivery system and the consumer.
Promotion
After the product has been defined as a generally acceptable package of PCC services, and the price to individual and organization is determined to be mutually beneficial, how can a social marketing approach diffuse it into common practice and social norms? This is where the promotion comes into play among two key audiences: 1) people who would like to be providers (or sellers) of the product and 2) people who would be consumers (or buyers) of the product. Often, promotion is thought to focus solely on creating demand among consumers for a particular product, and the promotion process is what most people typically think of as marketing or advertising. However, whereas most businesses prefer to have products “on the shelf” to meet the needs of consumers proactively, consumers are more influential than ever before in demanding that a product appears on their vendor’s shelves. PCC could very well become a product that consumers themselves create demand for—especially since the health care industry already sees the value of preconception care services but has not built a product offering that delivers what they believe to be important. Once the product and pricing attributes are developed, then promoting the product among potential buyers and sellers could be done using a number of communication theories that provide guidance on what types of communication messages and media vehicles (e.g. communication channels) can achieve in terms of exposure and effects. In fact, trade shows and product expositions are a major venue for new products to be introduced to businesses who sell products. Health care provider/insurer conferences, continuing medical education efforts, and medical school training could be venues for promoting PCC services among potential providers (27). Because the product attributes have already been defined as a benefit, and pricing has been addressed in the previous step, promotion should be a matter of convincing both buyers and sellers that they are acting in their own best interests. After promotion has helped to generate consumer demand for the product, PCC is an opportunity for current health care professionals, insurers and those in the business of health to expand their services—as in a classic new product offering. An important way for organizations to justify offering these services is to demonstrate an immediate benefit (perhaps in sales of other products and services) in addition to longer term benefits (perhaps fewer complicated pregnancies, lower malpractice premiums, fewer patients who need life-long care). And of course, the actual benefits would be determined through a process of market research with stakeholders—such as patients, health professionals and insurers (Table 2). Addressing current barriers and how to overcome them is a major contribution of the promotion activities. Using innovative ways to promote preconception care services not only can be modified from general market promotions but also by taking advantage of existing opportunities to deliver tailored “gateways/pathways” to PCC services. These could vary from fertility treatment centers to other family planning arenas. Whether a woman is seeking to become pregnant or trying to avoid becoming pregnant (but preserving her options for the future), she is a consumer who may be fertile ground, so to speak, for preconception care services. A challenging part of promoting PCC services will be figuring out how to move the thinking of a “now-oriented” consumer towards more “future-oriented” events; especially because future outcomes could happen earlier than planned/anticipated. This promotion could take advantage of additional opportunities such as involving male partners and other influential people in women’s lives—and also taking a lifelong approach to health (13, 28). Another challenge to promoting PCC services will be addressing the ethical aspects of promoting a product that cannot guarantee outcomes: Not every woman who chooses and uses preconception care services will be able to have a healthy pregnancy or a healthy baby. In fact, it might even be the case that unhealthy women (e.g. those with chronic diseases or other medical conditions) are the first to want and use preconception care services because they know that their poor health status makes pregnancy a hazardous situation for themselves and their baby. The importance of recognizing hazards and taking precautionary actions to protect health, which are addressed in the precaution adoption process model (29), may be relevant in promoting PCC services in a manner that acknowledges pregnancy as having inherent risk for both the mother and the unborn baby.
Table 2Sample social marketing questions for selected stakeholders of preconceptional care servicesConsumersHealth care providersInsurersProduct – What action must be taken by each audience (e.g., product, behavior, or policy)What does PCC services need to look and feel like for consumers to want/use/demand them?What does PCC services need to look and feel like for busy health care providers to want to offer them?What does PCC services need to look and feel like for health insurers to want to cover this service?Pricing –Why would they want to do it?What is the value of PCC services and what would they be willing to pay for them?What is the value for offering PCC services to patients and what would it cost to offer them?What is the return on investment for including PCC services as a covered service?Promotion –How will each audience be told about the what, why, where, and how?How will PCC services be publicized and made available to consumers in a way that they are attractive, affordable, and accessible?How will PCC services be presented to health care providers so that they are willing and able to offer them?How will PCC services be presented to insurers so that they are willing and able to reimburse for them?Place –Where can they do the action needed?What settings/locations are most acceptable, appropriate, and accessible for providing PCC services?What settings/locations are most acceptable, appropriate, and accessible for offering PCC services?What forums or conferences can instigate productive discussions about including PCC services as a covered expense?
Place
It is useful to ask how PCC services could be placed, or distributed, to women across their reproductive lifespan in a manner that addresses social marketing’s call toward mutually satisfactory exchanges, and how the placement of PCC services could affect their delivery. What components of PCC might change across the life span (e.g. early health promotion/contraception/STD infection/vaccinations/others)? The high level of unintended pregnancies in the US—40–60% for adults, 95% for teens (30)—is also a concern, because any approach that requires a self-selection into the audience will miss about half of the pregnancies. Some authorities have suggested a lifelong approach to preconceptional health—throughout the lifespan of a women’s potential fertility (say, 10–50 years of age) and an approach that may move women from one set of services and questions into another (2, 31). Social marketing can help by determining in the early phases what women and health care professionals want, and thus ensuring that supply can be ready when the demand is articulated. Health care professionals need to be involved in the design of those PCC services that they would deliver, and must do so in the context of what they would want to deliver—and those they would benefit from. Women report that one of their most influential sources of health information is their own health care professional, who knows them, their medical history and their concerns (32). Health care professionals and their medical staff may be the front line “sales people” for preconceptional care; if doctors never offer their patients the opportunity to “buy” this product, it will go nowhere. Medical professionals who are trained on the benefits of the product (e.g., by inclusion in medical school training and on medical board exams) and rewarded for using it (by reducing malpractice premiums for example) will find it more acceptable and worthwhile to integrate the practice into the time pressures of the busy medical office. Once a physician selection is made, patients visit for an acute problem, management of a chronic condition, and for routine checkups. Placement market research will help to define how PCC services may fit into each of these areas. This integrated vision of PCC could become part of the core training curricula for various medical professionals—more than an option during continuing education. This strategic preparation for placement also ensures that when the increased demand from the consumer begins to be evident at the health care provider office, the medical professionals in that office will know how to respond to that demand, and have the knowledge and systems in place to do so. Existing “bundles” of services that can be prepackaged to respond to this demand have in some cases been developed (33, 34). If the research in the first phase shows that the busy medical office is not the best location for providing PCC services, then alternate placement sites must be identified.
Conclusion
The best marketing and sales happen when the product has the qualities that a consumer wants and that a seller wants to provide. PCC must meet the needs and desires of patients, health professionals and insurers in order to be successfully adopted in the United States. For women and their families, that may mean believing that a healthy, wanted baby is in their future. For doctors, that may mean finding a way to give healthy women the preventive services they want and need while still dealing with the urgent care of their sick patients. For insurers it may mean a balance in service provision to meet both short and long term financial goals. But market research is needed to actually define exactly what the benefits are to each of those groups. And it is likely to be that the satisfactory exchange is more than just a purely medical application of clinical services. Consumers across the US are willing to spend $3.00 to drink what is essentially a 50 cent cup of coffee, but they are experiencing something more than the product’s primary attributes (e.g., flavor, caffeine) but also the positive associations with the product (e.g., funky, cool). In the same way, consumers can tell us how they would like to experience preconception health care services (35). All of us need to understand that if we market and sell it as the best experience possible, PCC could contribute to healthier babies, fewer medical treatment costs, and a healthy next generation that thinks about pregnancy in a whole different way.

social marketing
preconception care
behavior theories
preconception health
health communication


Deposition of fluoride on enamel surfaces released from varnishes is limited to vicinity of fluoridation site

The aim of the in-situ study was to determine fluoride uptake in non-fluoridated, demineralized enamel after application of fluoride varnishes on enamel samples located at various distances from the non-fluoridated samples. All enamel samples used were demineralized with acidic hydroxyethylcellulose before the experiment. Intra-oral appliances were worn by ten volunteers in three series: (1, Mirafluorid, 0.15% F; 2, Duraphat, 2.3% F and 3, unfluoridated controls) of 6 days each. Each two enamel samples were prepared from 30 bovine incisors. One sample was used for the determination of baseline fluoride content (BFC); the other was treated according to the respective series and fixed in the intra-oral appliance for 6 days. Additionally, from 120 incisors, each four enamel samples were prepared (one for BFC). Three samples (a–c) were placed into each appliance at different sites: (a) directly neighboured to the fluoridated specimen (=next), (b) at 1-cm distance (=1 cm) and (c) in the opposite buccal aspect of the appliance (=opposite). At these sites, new unfluoridated samples were placed at days 1, 3 and 5, which were left in place for 1 day. The volunteers brushed their teeth and the samples with fluoridated toothpaste twice per day. Both the KOH-soluble and structurally bound fluoride were determined in all samples to determine fluoride uptake and were statistically analyzed. One day, after fluoridation with Duraphat, KOH-soluble fluoride uptake in specimen a (=next) was significantly higher compared to the corresponding samples of both the control and Mirafluorid series, which in turn were not significantly different from each other. At all other sites and time points, fluoride uptake in the enamel samples were not different from controls for both fluoride varnishes. Within the first day after application, intra-oral-fluoride release from the tested fluoride varnish Duraphat leads to KOH-soluble fluoride uptake only in enamel samples located in close vicinity to the fluoridation site.
Introduction
It is well established that fluoride products play an important role in the prevention and remineralization of carious lesions. Topical fluoride applications in the form of varnishes and varnishes may lead to appreciable acquisition of fluoride on and in both enamel and dentin samples, which were directly treated with the agent [4, 6, 14, 21, 25]. Especially, the KOH-soluble fluoride deposit on the surfaces of dental hard tissue might be elevated depending on the fluoride concentration and composition of the fluoride varnish applied. However, the KOH-soluble fluoride deposit is continuously dissolved in the oral cavity due to the influence of saliva. This leads to a drastic reduction of the deposit within a period of about 1 week after application of the fluoride agent [2, 5, 14].
After the use of fluoride-containing products, also, salivary fluoride levels are increased for a certain period of time depending on the concentration and application form used. This effect is important because fluoride levels above 0.04 ppm in the surrounding solution of the dental hard tissue have been shown to be related to lower risk of caries progression in clinical studies [16, 17]. The fluoride distribution in the oral cavity showed site-specific variations, which was exemplarily demonstrated by Weatherell at al. [24] after dissolving a fluoride tablet in the oral vestibulum. With oral fluoride-containing mouthrinses, salivary fluoride levels remain elevated for up to 12 h after application [8, 13, 23, 26]. The use of fluoride mouthwashes twice daily leads to a sustained elevated fluoride level even between the daily applications [12]. Fluoride dentifrices can cause increase in salivary fluoride content for a period of about 60–90 min [3, 11, 26]. Also, after application of fluoride varnishes onto tooth surfaces, salivary fluoride levels remain increased for up to 32 h [13, 18, 22].
The above-mentioned studies had made clear that fluoride-treated tooth surfaces and salivary fluoride levels are increased after administering local fluoride regimes. Besides these effects, it may be speculated that fluoride applications also lead to fluoride uptake at tooth surfaces that were not directly treated or covered with fluoridation agents such as varnishes. This fact could especially be important for demineralized surfaces, which were inaccessible to direct fluoride application such as inter-proximal areas. Due to toxicological and practical reasons, application of fluoride varnishes is mostly limited to some sites of the dentition. Therefore, the aim of the present study was to determine fluoride transfer from fluoride-varnished enamel surfaces to demineralized enamel surfaces located at various distances from the fluoridation site.
Materials and methods
Enamel samples
Enamel cylinders (4 mm in diameter) were prepared from the buccal surface of bovine incisors. The cylinders were ground flat and polished, thereby removing about 200-μm depth of the enamel as controlled with a micrometer. Afterwards, all specimens were sterilized with gamma irradiation (25 kGy). For rehydration, the sterilized samples were stored in synthetic saliva [1] for a minimum of 2 weeks. Then, all samples were demineralized with acidic hydroxyethylcellulose (pH 4.8, 3 days).
According to this procedure, each two enamel samples were prepared from 30 bovine incisors and each four samples were gained from additional 120 incisors. One sample from each tooth was used for the determination of baseline fluoride content of the respective tooth. The remaining samples of the 30 bovine incisors were later treated according to series 1–3. The remaining samples of the 120 bovine incisors were used for the determination of intra-oral fluoride transfer and acquisition.
Set-up of the study
The study was designed and conducted according to the guidelines of Good Clinical Practice. Ethical approval of the study was granted by the Ethics Committee of the University of Göttingen (2/9/01). Ten panellists (aged 21 to 29 years) participated in the study. They were all residents of Göttingen (fluoride content in domestic water: <0.2 ppm F). The subjects had been instructed to avoid fluoride uptake. The participants had a stimulated salivary fluoride rate within the normal range of 1.0–5.0 ml/min. Further inclusion criteria were that they had at least 20 teeth, no faulty dental restorations, no glass ionomer fillings and no current dental caries activity.
Intra-oral, lower jaw appliances with two buccal aspects were worn by ten volunteers in three series of 6 days each. In each series, one enamel sample was placed for 6 days in one buccal aspect of the appliance after treatment according to the respective series (=central, fluoridated sample). With each five of the participants, the fluoridated samples were placed in the right buccal aspect; with the remaining subjects, the fluoridated samples were fixed in the left aspect of the appliance. A washout phase of 1 week elapsed between the three series.
In series 1 and 2, 0.1 g of the fluoride varnish Mirafluorid® (1) or Duraphat® (2) was either applied on the central enamel sample (Table 1). Care was taken to avoid contamination of the remaining enamel samples of the intra-oral appliances with the varnish applied. After application of the varnish, the intra-oral appliances were immediately inserted into the oral cavities. In series 3, the respective samples were not fluoridated with varnish and served as controls.
Table 1Ingredients and composition of the fluoride varnishes Mirafluorid® and Duraphat® according to manufacturers Mirafluorid®Duraphat®Fluoride content0.12%2.26%Fluoride formSodium fluorideSodium fluorideCetylaminehydrofluorideBis(hydroxyethyl)-aminpropyl-N-hydroxyethyl-octadecyl-amindihydrofluoridepH4.6NeutralSolventSolvent-freealcohol (33.14%)BaseWater-soluble polymerNatural resins (colophonium, mastix, shellac)Other ingredients–Wax, saccharine, flavourManufacturerHager & Werken, Duisburg, Germany Colgate-Palmolive, Hamburg, Germany
Each three unfluoridated samples were placed into each appliance at different sites (a–c): (a) directly neighboured to the central, fluoridated specimen (=next), (b) at 1-cm distance (=1 cm) and (c) in the opposite buccal aspect of the appliance (=opposite). These three samples were replaced after 1, 3 and 5 days by new unfluoridated samples, which were removed after 1 day intra-oral exposition. Thus, each one sample was worn at the respective site for the following periods: days 0–1, days 1–2, days 3–4 and days 5–6. The central samples, which were fluoridated on day 0, were not removed from the appliances before completion of the experiment.
The volunteers brushed their teeth and the samples with a pea-size amount of fluoridated toothpaste (0.125% fluoride as amine fluoride) twice per day (elmex®, GABA, Lörrach, Germany) during the experiment to simulate the common practice of using a fluoridated dentifrice and to follow the recommendations of the Ethical Committee, which did not allow detaining a fluoride dentifrice to the participants. They began to use the dentifrice 3 days before the start of the trial. After toothbrushing, the enamel samples in the appliances were carefully cleaned with ten brushing strokes using the toothbrush (impregnated with the remaining dentifrice slurry) that had been used for brushing of the teeth before. A minimum of 8 h elapsed between application of the respective varnish onto the central specimen and first brushing of the samples. During the experiment, the appliances were worn night and day except during meals, during which, they were stored in 0.9% saline.
Fluoride analysis
Immediately after removal from the intra-oral appliances, the enamel samples were cleaned with a soft toothbrush under running tap water and analyzed for KOH-soluble and structurally bound fluoride. The fluoride was assayed by a specific fluoride electrode (Orion Research, Cambridge, USA). The structurally bound fluoride was determined in two successive layers of 30 μm each. The layers were removed by means of a special grinding technique described in detail previously [15]. The amount of KOH-soluble fluoride was determined by the method of Caslavska et al. [9]. The assays were prepared as described in those studies, resulting in a 0.9-ml sample solution for KOH-soluble fluoride and 3-ml solution for structurally bound fluoride determination, respectively. Also, fluoride content of the fluoridated samples was assessed after the experimental period.
Statistics
According to the manufacturer, sensitivity of the fluoride electrode is given as 1 μmol/l in a solution. Bioanalytical guidelines recommend disregarding the measurements that are close to the sensitivity of an assessment method [20]. An international cooperation study [7] determining the lowest level of sensitivity for measurements with a fluoride electrode showed that measurements below 4 μmol/l (equivalent to 0.544 μg/cm2 KOH-soluble fluoride and 604.8 μg/cm3 structurally bound fluoride) were unstable, not reproducible and showed high standard deviations and coefficients of variation (>20%). Therefore, these readings were regarded as to be “below detection limit”. Thus, fluoride uptake was not calculated by subtracting the baseline fluoride content of the respective tooth, which was below detection limit, from the measured value recorded for the specimen.
All groups were compared regarding their number of readings above detection limit using chi-square tests. For those groups, in which more than 50% of the readings were above the detection limit, discriminations were conducted using the rank-sum test according to Wilcoxon and Mann–Whitney. The level of significance was set at P < 0.05.
Results
In Table 2, the percentages of fluoride measurements in the respective groups, which were above the detection limits, are given. It is obvious that most of the groups had more than 50% of their readings below the detection limit. Chi-square tests proved that the sample groups with more than 50% readings above detection limit were statistically significantly different from the remaining groups, which in turn did not differ significantly from each other.
Table 2Percentages of measurements above detection limitsa for KOH-soluble and structurally bound fluoride in two successive layers in enamel specimens worn in intra-oral appliances at different sites and for different periods (days 0–6, days 0–1, days 1–2, days 3–4 or days 5–6) after the application of either Duraphat, Mirafluorid or no fluoride varnish (control) on the central specimen on day 0  KOH-soluble F−1st Layer (0–30 μm)2nd Layer (31–60 μm)PeriodSiteMirafluorid (%)Duraphat (%)Control (%)Mirafluorid (%)Duraphat (%)Control (%)Mirafluorid (%)Duraphat (%)Control (%)0–6Central90100010100101010000–1Next10600030003000–11 cm10300050001000–1Opposite00001000001–2Next20100101000001–21 cm20000000001–2Opposite10000000003–4Next100001000003–41 cm10000000003–4Opposite10000000005–6Next0000000005–61 cm10000000005–6Opposite000000000aDetection limits (KOH-soluble F = 0.544 μg/cm2, structurally bound fluoride = 604.8 μg/cm3)
In Table 3, KOH-soluble fluoride and structurally bound fluoride data of the experimental groups are given, for which more than 50% of the readings were above detection limit. As mentioned above, chi-square tests had proven that these values were statistically significantly different from baseline content and from the remaining groups. For the remaining groups, fluoride contents are not given because statistical data such as mean value or median are not reasonable to calculate for values, which are not reliably measurable by definition. Acquisition of KOH-soluble fluoride was detectable in the central, fluoridated samples of both groups, Mirafluorid and Duraphat, with the latter once accumulating statistically significantly more KOH-soluble fluoride (P = 0.00015). The central, fluoridated Duraphat samples also showed significant uptake of structurally bound fluoride in both enamel layers with significantly higher uptake in the first layer compared to the second one (P = 0.02836). One day after fluoridation, the samples located next to the Duraphat-varnished central specimens also accumulated measurable amounts of KOH-soluble fluoride. The KOH-soluble precipitate on these samples was statistically significantly less pronounced compared to the central specimens (P = 0.00015). The samples located next to the Duraphat-treated showed measurable KOH-soluble fluoride acquisition at days 0–1. They, therefore, differed significantly from both the control and Mirafluorid series, which did not show measurable fluoride acquisition at this time point and were, in turn, not significantly different from each other. At all other sites and time points, fluoride uptake in the enamel samples was not different from controls for both fluoride varnishes.
Table 3Mean ± standard deviation (median; minimum–maximum) of KOH-soluble fluoride and structurally bound fluoride (in 1st and 2nd layer) given for the experimental groups with more than 50% of the respective measurements above detection limit  KOH-soluble F− (μg/cm2)1st Layer (μg/cm3)2nd Layer (μg/cm3)PeriodSiteMirafluoridDuraphatDuraphatDuraphat0–6Central0.67 ± 0.19a (0.62; 0.54–1.1)8.38 ± 3.18a,c (8.82; 3.65–14.5)2237 ± 576b (2,282; 1,233–3,315)1636 ± 487b (1,503; 1,110–2,646)0–1Next–*0.83 ± 0.56c (0.76; 0.16–2.12)–*–**Less than 50% readings above detection limitSignificantly different values in the same line (aKOH-soluble F−, bstructurally bound F−) or ccolumn are marked.
Discussion
As stated in “Introduction”, several investigations had demonstrated that intra-orally applied fluoride regimes may cause fluoride release into saliva. In a previous study, Dijkman et al. [10] had demonstrated that no measurable fluoride enrichment could be detected in untreated sound enamel controls located in a distance of 3 mm from fluoride varnish-treated samples after a period of 1 week. The present study made clear that within the first day after application the highly concentrated fluoride varnish Duraphat KOH-soluble fluoride deposition in close vicinity to the fluoridation occurs. However, in consistence with the investigation by Dijkman et al. [10], no measurable fluoride transfer could be revealed after the first day. Although, when interpreting the results of the present study, it should be noted that a more sensitive method for fluoride determination might have shown slightly different results.
In the present study, no fluoride acquisition could be detected in samples located at a distance of 1 cm from the fluoridated site or fixed in the opposite vestibulum of the participants. This means that fluoride transfer via saliva was strictly limited to the close neighbourhood of the fluoridation site. This finding corresponds to a previous study, which demonstrated that significant elevation of salivary fluoride concentrations is more or less restricted to the fluoridation site [24].
With exception for the samples directly treated with Duraphat, no measurable acquisition of structurally bound fluoride was observed in any other sample group. In a previous study, application of Mirafluorid did not also result in uptake of structurally bound fluoride [2]. However, also the samples which were located next to the specimens treated with Duraphat for 1 day and which showed a KOH-soluble fluoride deposit did not show increase of structurally bound fluoride. This finding could be explained by the fact that formation of structurally bound fluoride is a time-dependent process during which some of the KOH-soluble deposit is dissolved, allowing fluoride to diffuse into the underlying enamel and to be structurally incorporated into the enamel crystallites [19]. However, in these samples, structurally bound fluoride was assessed already 1 day after insertion into the appliance. It might be speculated that with longer exposition in the oral cavity, structurally bound fluoride might have been formed by dissolution from the KOH-soluble fluoride deposit.
In the present study, demineralized enamel specimens were used for assessing fluoride acquisition. Recent studies had proven that fluoridation measures lead to significantly higher uptake of fluoride in demineralized samples as compared to sound enamel [1]. It could, therefore, be assumed that fluoride acquisition of sound enamel surfaces due to fluoride transfer in the oral cavity might be actually more limited as compared to the present results.
Under clinical conditions, a varnish is often applied onto more sites, which might elevate salivary fluoride to a presumably higher extent as in the present study, where the varnishes were applied to a single site only.
Due to the results of the present study, it could be concluded that within the first day after application, intra-oral fluoride release from the tested fluoride varnish Duraphat leads to KOH-soluble fluoride uptake only in demineralized enamel samples, which are located in close vicinity to the fluoridation site. Owing to the negligible transfer of fluoride from the varnish to more remote sites, this finding means, for the clinical situation, that all sites in the oral cavity requiring fluoridation have to be directly treated with the varnish.

fluoride enamel koh-soluble saliva transfer


MLC1 is associated with the Dystrophin-Glycoprotein Complex at astrocytic endfeet

Megalencephalic leukoencephalopathy with subcortical cysts (MLC) is a progressive cerebral white matter disease with onset in childhood, caused by mutations in the MLC1 gene. MLC1 is a protein with unknown function that is mainly expressed in the brain in astrocytic endfeet at the blood–brain and cerebrospinal fluid–brain barriers. It shares its localization at astrocytic endfeet with the dystrophin-associated glycoprotein complex (DGC). The objective of the present study was to investigate the possible association of MLC1 with the DGC. To test this hypothesis, (co)-localization of DGC-proteins and MLC1 was analyzed by immunohistochemical stainings in gliotic brain tissue from a patient with multiple sclerosis, in glioblastoma tissue and in brain tissue from an MLC patient. In control tissue, a direct protein interaction was tested by immunoprecipitation. Results revealed that MLC1 is co-localized with DGC-proteins in gliotic brain tissue. We demonstrated that both MLC1 and aquaporin-4, a member of the DGC, were redistributed in glioblastoma cells. In MLC brain tissue, we showed absence of MLC1 and altered expression of several DGC-proteins. We demonstrated a direct protein interaction between MLC1 and Kir4.1. From these results we conclude that MLC1 is associated with the DGC at astrocytic endfeet.
Introduction
Megalencephalic leukoencephalopathy with subcortical cysts (MLC, MIM 604004) is a childhood leukoencephalopathy with autosomal recessive inheritance [21]. Patients develop macrocephaly during the first year of life, followed by slow motor deterioration with cerebellar ataxia and spasticity [21]. Magnetic resonance imaging (MRI) shows diffusely abnormal, mildly swollen cerebral white matter and subcortical cysts in anterior temporal and frontoparietal areas [21]. Histopathologic and electron microscopic examination of brain tissue reveals countless intramyelinic vacuoles [22].
From early on, the striking similarity in MRI features of MLC and congenital muscular dystrophy (CMD) with merosin deficiency (CMD type 1A, MDC1A) was noted [21]. Patients with MDC1A also have diffusely abnormal, mildly swollen cerebral white matter and sometimes anterior temporal cysts (Fig. 1) [23]. Microscopic examination of the brain of a patient, who was later genetically confirmed to have MDC1A (B. Echenne, personal communication) also revealed myelin vacuolation [8]. MDC1A is caused by mutations in the LAMA2 gene, encoding the laminin-α2 chain of merosin [9]. In contrast to MDC1A, MLC is not associated with muscle disease [21]. We hypothesized that MLC could be the “brain-only” variant of MDC1A. We could, however, not confirm linkage of MLC to the LAMA2 locus and instead demonstrated that mutations in another gene, MLC1, cause MLC [10]. MLC1 encodes a plasma-membrane protein of unknown function. Recently, the MLC1-protein was found to be located in astrocytic endfeet at the blood–brain and cerebrospinal fluid–brain barriers [3, 19].
Fig. 1MRI of the brain of a patient with MLC (a–c) and MDC1A (d–f). The axial T2-weighted images (a, b, d, e) reveal extensive signal abnormalities and mild swelling of the cerebral white matter in both MLC (a, b) and MDC1A (d, e). The corpus callosum and internal capsule are relatively preserved in both cases (a, d). The sagittal T1-weighted images reveal a large cyst in the anterior temporal white matter and smaller cysts in the frontal subcortical white matter in the MLC patient (c). There are small cysts in the same regions in the MDC1A patient (f). Both MLC and MDC1A patients had a genetically confirmed diagnosis
Other proteins localized at astrocytic endfeet are those of a multi-subunit complex called dystrophin-associated glycoprotein complex (DGC) [12, 20]. The DGC is expressed in various tissues and has been characterized best in skeletal muscle where it connects the cytoskeleton of muscle fibers to the extracellular matrix [14]. Mutations in different DGC components lead to various muscular dystrophies. In a subset of muscular dystrophies, the congenital muscular dystrophies (CMDs), the muscular phenotype is often combined with brain involvement, including white matter abnormalities, most notably in MDC1A [23].
The brain DGC is involved in the adhesion of perivascular glia to the extracellular matrix [20]. At the astrocytic endfeet, the DGC consists of four main components [6, 16, 29]: (1) α- and β-dystroglycan, which form the backbone of the DGC by forming a transmembrane link between the actin cytoskeleton and the extracellular matrix. α-Dystroglycan is a heavily glycosylated peripheral membrane protein that binds to extracellular ligands such as merosin and agrin. β-Dystroglycan is a transmembrane protein that anchors the extracellular α-dystroglycan to the plasma membrane and interacts intracellularly with dystrophin (and/or utrophin, which can replace dystrophin) and syntrophin. (2) Dystrophin and/or utrophin, are linker molecules that can form a bridge between actin and β-dystroglycan. (3) α-Dystrobrevin, which is linked to dystrophin and/or utrophin binds to syntrophin. (4) Syntrophin, which binds to the water channel aquaporin-4 and the potassium channel Kir4.1 is responsible for the polarized expression of these proteins in astrocytic endfeet.
The striking similarities in brain MRI features and pathology between MLC and MDC1A, together with the specific localization of both MLC1 and merosin at astrocytic endfeet, brought us to the hypothesis that there may be an association between MLC1 and DGC in the brain. In the present paper we report on our studies to test this hypothesis. We investigated the co-localization of MLC1 and DGC-proteins in gliotic white matter, because MLC1 staining is more intense in gliotic brain tissue than in normal tissue [3]. Previous studies in humans and mice have shown that if members of the DGC are mutated or missing, the complex may be disrupted, which affects the localization of other protein members [1, 13, 16, 27]. We therefore also tested our hypothesis by studying the localization of MLC1 and several DGC-proteins in glioblastoma and MLC brain tissue. Besides, we assessed a direct association between MLC1 and DGC-members by co-immunoprecipitation experiments.
Materials and methods
Immunohistochemical staining of human brain tissue
Human control brain tissue specimens, both frozen and paraffin-embedded, consisting of neocortex and white matter, were obtained at autopsy from patients without neurological disease and neuropathologic abnormalities. Additionally, frozen brain tissue was obtained from a multiple sclerosis patient to study gliotic white matter in which MLC1 has a normal localization but MLC1 expression is increased [3]. During life, all patients or their next of kin had given consent for autopsy and the use of brain tissue for research purposes.
Human glioblastoma multiforme tissue (frozen) and brain biopsy tissue from MLC patients (both frozen and paraffin-embedded) were obtained for diagnostic purposes and used for research purposes with informed consent of patients and families. Light-microscopy of glioblastoma tissue was used to select areas that display characteristic glioblastoma features, including necrosis, giant cells and endothelial proliferation, for further studies. Brain biopsies were obtained in the following MLC patients: EL18 (decreased MLC1 expression [2], frozen tissue), EL649 (homozygous for the c.733G > C (p.Ala245Pro) mutation; paraffin-embedded tissue), and EL746 [compound-heterozygous for the c.268-1G > A and c.597 + 1G > A mutations, leading to splice-defects and truncation of the protein (p.Cys90-Val107del and p.Val200-Ala238del); paraffin-embedded tissue].
Immunohistochemistry was performed as described previously [7] with antibodies against the following proteins: MLC1 (polyclonal; 1:200 [3]); merosin (monoclonal; 1:500 [11]); aquaporin-4 (polyclonal; 1:200, Chemicon, Huissen, The Netherlands); Kir4.1 (polyclonal; 1:200, USBiological, Swampscott, Massachusetts), β-dystroglycan (monoclonal; 1:100, Santa Cruz, Heidelberg, Germany), α-dystroglycan (monoclonal; 1:100, UpstateCellSignaling solutions), agrin (monoclonal; 1:2500 [26]); glial fibrillary acidic protein (GFAP, polyclonal; 1:500, DAKO, Heverlee, Belgium) and NeuN (monoclonal; 1:1600, MAB377, Chemicon). In all slides, except the slides used for double stainings, the nuclei are counterstained with Haematoxylin. Double immunofluorescence staining was performed as described [3] with agrin, β-dystroglycan (monoclonal; 1:100) or syntrophin (monoclonal; 1:100, Affinity BioReagents, Raamdonksveer, The Netherlands) versus MLC1. In negative controls the primary antibodies were omitted. Double-stainings were performed as described previously [25]. In frozen tissue double-stainings were done with agrin (red) antibodies versus AB4 (blue, polyclonal; 1:200, Lab Vision–NeoMarkers, Fremont, CA, USA) antibodies and in paraffin tissue with agrin or α-dystroglycan antibodies versus NeuN or GFAP. For the agrin (brown)/NeuN (blue) double-stainings, agrin was visualized with biotinylated secondary antibodies (DAKO) and NeuN with poly-HRP (Immunologic, Duiven, The Netherlands). For the agrin (red)/GFAP (blue) double-stainings, agrin was detected with poly-HRP (Immunologic) and GFAP with biotinylated secondary antibodies (DAKO). In negative controls the primary antibodies were omitted.
Immuno-precipitation and western blotting
Preparation of brain tissue and immunoprecipitation experiments were performed as previously described [5] without antibodies as a negative control, with 1–15 μg mMLC1-C (home made), with the nonspecific CHOP (Santa Cruz, Heidelberg, Germany) as an extra negative control, and with Kir4.1 (USBiological, Swampscott, Massachusetts) antibodies. Western blots were incubated with the Kir4.1 antibodies overnight at 4°C and complexes were visualized using ECL Western Blot detection reagents (Amersham, Buckinghamshire, United Kingdom).
Results
Co-localization of MLC1 and DGC-members
To test whether MLC1 co-localizes with DGC-proteins at astrocytic endfeet, we performed double-immunofluorescent staining experiments in gliotic brain tissue with the transmembrane protein MLC1 (Fig. 2a, d, g; green) versus the extracellular matrix protein agrin (Fig. 2b; red), the intracellular protein syntrophin (Fig. 2e; red), and the transmembrane protein β-dystroglycan (Fig. 2h; red). There was partial overlap (yellow) between all three DGC-proteins (red) and MLC1 (green). The co-localization (Fig. 2i; yellow) of MLC1 (Fig. 2g; green) and β-dystroglycan (Fig. 2h; red) was most striking. If MLC1, agrin, β-dystroglycan or syntrophin was omitted, fluorescent labeling was only visible for the appropriate isotype, thereby excluding cross-reactivity (not shown). On omission of the primary antibody no staining was observed (not shown).
Fig. 2Co-localization of MLC1 and DGC-proteins. a–i Double immuno-fluorescence labelling of MLC1 (a, d, g, green), agrin (b, red), syntrophin (e, red), and β-dystroglycan (h, red) in gliotic human brain tissue. There is partial overlap (c, f, i, yellow) between MLC1 and these DGC-proteins. The overlap (i, yellow) between the transmembrane proteins MLC1 (green) and β-dystroglycan (red) is most striking. In all panels the ocular magnification and 10 μm scale bars are indicated in the lower right hand corner
MLC1 and aquaporin-4 are redistributed in glioblastoma cells
Staining normal human brain tissue with anti-MLC1 and anti-aquaporin-4 antibodies confirmed their specific expression around blood vessels, consistent with the previously described perivascular localization (Fig. 3a, c) [3, 15]. In glioblastoma tissue, both MLC1 and aquaporin-4 had altered expression patterns. The proteins were no longer confined to astrocytic endfeet, but were redistributed over the entire glioblastoma cell (Fig. 3b, d). Anti-agrin staining showed expression of the protein in the extracellular matrix around blood vessels of all sizes in normal brain tissue (Fig. 3e), whereas it was exclusively expressed around larger blood vessels in glioblastoma tissue (Fig. 3f). Double staining of agrin (red) with AB4 (blue), an endothelial marker, in glioblastoma tissue confirmed agrin and AB4 staining around larger blood vessels (Fig. 3g) and absence of agrin around small vessels (Fig. 3g, boxed area). This is in line with previously published results [27]. On omission of the primary antibody no staining was observed (not shown).
Fig. 3Localization of MLC1 in glioblastoma tissue. Immunohistochemical staining of MLC1, aquaporin-4 (AQP4) and agrin in control brain (a, c, e) and tumor tissue (b, d, f, g). a MLC1 has a perivascular localization in normal tissue. b In glioblastoma tissue, the restriction of MLC1 to perivascular areas is lost and the protein has an intracellular location in glioblastoma cells. cAQP4 is expressed in perivascular astroglial endfeet in control brain. dAQP4 is localized in glioblastoma cells. e, f Agrin is expressed in the extracellular matrix around blood vessels of all sizes in normal tissue (e) and only around large vessels in glioblastoma tissue (f). g Double-staining of agrin (red)/AB4 (blue) in glioblastoma tissue shows agrin and AB4 (endothelial marker) staining around larger blood vessels. The boxed area in panel g shows that agrin staining is absent around small vessels. In all panels the ocular magnification and 10 μm scale bars are indicated in the lower right corner
Absence of MLC1 and altered expression of DGC-proteins in MLC brain tissue
Anti-MLC1 staining revealed perivascular expression of the protein in control brain tissue (Fig. 4a) [3] and absence of staining in MLC tissue (Fig. 4b). The distribution of merosin, β-dystroglycan and aquaporin-4 was similar in control (Fig. 4c, e, g) and MLC tissue (Fig. 4d, f, h). In control tissue, Kir4.1 showed a perivascular localization in configuration suggesting presence in distal atroglial processes (Fig. 4i), while in MLC patient tissue Kir4.1 additionally showed a diffuse cytoplasmic staining of astrocytes (Fig. 4j). In control tissue, agrin (Fig. 4k) and α–dystroglycan (Fig. 4m) were seen in the perivascular extracellular matrix, whereas these proteins were observed both in the perivascular extracellular matrix and within cells in MLC tissue (Fig. 4l, n).
Fig. 4Localization of proteins associated with the DGC in MLC patients. In control tissue the perivascular staining of MLC1 is visible (a), but no staining is observed in MLC brain tissue (b). Normal perivascular basal lamina staining with merosin is seen in control (c) and MLC (d) brain tissue. β-dystroglycan has a normal perivascular distribution in both control (e) and MLC (f) brain tissue. Aquaporin-4 (AQP4) has a normal perivascular distribution in both control (g) and MLC (h) brain tissue. Kir4.1 is present in distal astrocytic processes around blood vessels in control tissue (i). In MLC tissue (j) Kir4.1 is expressed both in distal astrocytic processes around blood vessels and in cell bodies of astrocytes (boxed area). Agrin is expressed in the extracellular matrix around blood vessels in control tissue (k). In MLC tissue (l) agrin is expressed in both the extracellular matrix around blood vessels (boxed area) and in cells, as indicated by arrows. Immunostaining for α–dystroglycan shows a normal perivascular distribution in control tissue (m) and expression of α–dystroglycan around blood vessels (boxed area) and in cells in MLC tissue (arrows in n). o Double-staining of NeuN (blue)/agrin (brown) in MLC tissue shows cytoplasmic agrin staining in NeuN positive cells (arrows). p Double-staining of Agrin (red)/GFAP (blue) in MLC brain tissue. The picture on the left shows an astrocyte that is only GFAP positive (arrow), while the picture on the right shows an astrocyte that is both GFAP and agrin positive (arrow, brown staining in cell body). In all panels the ocular magnification, 10 μm scale bars and patient numbers are indicated in the lower right corner
The cells expressing these latter two DGC-proteins had the morphological characteristics of neurons. Double stainings of agrin and α-dystroglycan with NeuN, a neuronal marker, in MLC brain tissue confirmed that both agrin (brown) (Fig. 4o) and α-dystroglycan (not shown) co-localized with NeuN (blue). Although, most redistribution appeared to be in neurons, double stainings of agrin (red) and GFAP (blue) showed that also some astrocytes displayed positive cell body staining for agrin (Fig. 4p). On omission of the primary antibody no staining was observed (not shown).
Direct protein interaction between MLC1 and Kir4.1
To verify interaction of DGC-proteins with MLC1, immunoprecipitation experiments were performed using human control brain lysates. Figure 5 shows that after immunoprecipitation with both anti-MLC1 and anti-Kir4.1 antibodies and probing the precipitate for the presence of Kir4.1, a band at 200 kDA was detected, the size expected for Kir4.1. This band was not present in a pull-down without antibodies or with an unrelated antibody (anti-CHOP). Of concern in this experiment was the use of cross-linking reagents, since this might cause nonspecific interactions. When cross-linking reagents were left out, we failed to detect interactions, which is in agreement with previous studies on interaction between DGC-members [5].
Fig. 5Co-immunoprecipitation (IP) of human brain lysates. Antibodies used for IP are indicated above the figure. The dash indicates pull-down without antibodies; anti-CHOP was used as a nonspecific antibody. The resulting Western blot was probed with antibodies against Kir4.1. The arrowhead shows the position of Kir4.1 at 200 kDa and the asterisk indicates a nonspecific band that is pulled down with all the antibodies used
Discussion
The DGC is important in linking cytoskeletal proteins to the extracellular basal lamina. It is present in several tissues including muscle, heart, nerve and brain. The composition of this complex shows some differences for different tissues. Structural defects in a number of DGC-members cause muscular dystrophies. Best known is Duchenne muscular dystrophy, related to mutations in dystrophin. Another muscular dystrophy is the CMD MDC1A, in which the MRI features are strikingly similar to those of MLC. MDC1A is caused by mutations in the laminin-α2 chain of merosin [9]. A specific group of CMD variants is known as “dystroglycanopathies” and includes Walker–Warburg syndrome, Fukuyama type of CMD, muscle–eye–brain disease, CMD type 1C and type 1D. They are characterized by hypoglycosylation of α-dystroglycan [14]. MDC1A and most of the dystroglycanopathies lead to both muscle disease and brain involvement, including cerebral white matter abnormalities.
We hypothesized that MLC1 could be associated with the DGC in the brain. To strengthen our hypothesis, we showed co-localization between MLC1 and DGC-proteins around blood vessels by immunofluorescent stainings. A common feature of the DGC is that mutations affecting one of its components often lead to destabilization of the complex with reduced or altered expression of other DGC-members. For instance, in muscle and brain tissue of patients with a dystroglycanopathy, immunostaining is reduced for α-dystroglycan as well as merosin and agrin [13]. In patients with Duchenne muscular dystrophy and Fukuyama type of CMD, decreased expression of multiple DGC-proteins has been found in muscle and brain [4, 17, 18]. In brain tissue of syntrophin, knock out mice altered expression of aquaporin-4 has been reported [16]. In glioblastoma tissue, abnormal expression of aquaporin-4 and syntrophin over the entire surface of glioblastoma cells and absence of α-dystroglycan from glial structures have been reported [27, 28]. Agrin was only present around larger vessels but absent around small vessels in glioblastoma tissue [27, 28]. We decided to use these DGC destabilization phenomena to test our hypothesis. Because of the co-localization of MLC1 and DGC-members at perivascular regions and the disassembly of the DGC in glioblastoma tissue we were interested in whether MLC1 is redistributed in this type of brain tumor. We, therefore, tested the expression pattern of MLC1 by immunohistochemical staining in glioblastoma tissue. We confirmed previous findings for agrin and aquaporin-4 [27, 28] and demonstrated that MLC1, like aquaporin-4, is redistributed in glioblastoma cells. We were also interested whether MLC1 mutations would lead to destabilization of the complex with reduced or altered expression of DGC-members in MLC brain. We demonstrated the absence of MLC1 and altered expression of Kir4.1, agrin and α-dystroglycan in brain tissue of MLC patients, whereas merosin, β-dystroglycan and aquaporin-4 retained their normal perivascular localization. Agrin and α-dystroglycan were redistributed in both neurons and astrocytes, although most positive staining cells appeared to be neurons. All the above results provide circumstantial evidence for an association between MLC1 and the DGC. To show a direct protein–protein interaction we performed co-immunoprecipitation experiments that revealed an association between MLC1 and Kir4.1. All together, the above findings provide strong evidence for an association between MLC1 and the DGC.
So far almost all defects in DGC-proteins have been associated with a muscular dystrophy, which is absent in MLC. This difference can be ascribed to a difference in DGC composition for muscle as compared to brain. Whereas merosin is expressed both in muscle and brain, MLC1 is not expressed in muscle (http://biomed.ngic.re.kr/cgi-bin/cards/carddisp?MLC1&search = KIAA0027) Both in MLC and MDC1A, the water content of the affected white matter is abnormally high due to intramyelinic vacuole formation [8, 22, 24]. The DGC is crucial for anchoring of water and potassium channels at the perivascular endfeet [15]. Destabilization of the DGC may lead to changes in glial polarity, disturbances of the blood–brain barrier and alterations in ion and water homeostasis of the brain [27, 28], and result in an increased myelin water content. Our findings may, therefore, have implications for the pathophysiology of white matter abnormalities observed in MLC, MDC1A and the dystroglycanopathies.


Clinical predictors of neurocognitive deficits in children with chronic kidney disease

The purpose of the study was to explore associations between neurocognitive function and chronic kidney disease (CKD)-related clinical characteristics. Twenty-nine children, ages 7 to 19 years, with an estimated creatinine clearance (eCrCl) of 4–89 ml/min per 1.73 m2 body surface area were enrolled. Intellectual function (IQ), memory, and attention were measured and expressed as age-based standard scores. Clinical data were obtained by physical examination, laboratory testing, parental questionnaires and medical chart review. Pearson correlations and standard Student’s t-tests were used to identify significant (P < 0.05) relationships between targeted clinical variables and neurocognitive scores. Increased CKD severity correlated with lower IQ (P = 0.001) and memory function (P = 0.02). Memory function was lower in children with longer duration of disease (P = 0.03). Similarly, IQ scores were lowest when kidney disease had started at a younger age (P = 0.03) and with a greater percent of life with CKD (P = 0.04). Our findings provide preliminary evidence that increased disease severity, longer duration of disease, and younger age of onset of kidney disease potentially place children with CKD at increased risk of neurocognitive deficits. Additional investigation is required to better quantify these risk factors, particularly regarding how much variability is accounted for by these specific risk factors.
Introduction
Neurocognitive difficulties have long been observed in the chronic kidney disease (CKD) population [1]. While identification and treatment of specific comorbidities of CKD (e.g., anemia) have yielded improvement in the overall functioning of this population, reports of neurocognitive deficits in children with CKD continue to appear. These neurocognitive deficits undoubtedly will have significant lifelong implications for the CKD population as they move into adulthood. A recent review by Groothoff [2] examined the long-term outcomes of children diagnosed with CKD and identified persistent difficulties with a limited knowledge base, memory, and concentration into adulthood, as well as lower educational attainment. A better understanding of potential risk factors for cognitive impairment and decline in the pediatric CKD population could allow for earlier intervention and, possibly, less morbidity, particularly for certain cognitive deficiencies.
Studies aimed at investigating neurocognitive impairment in children with CKD have identified a wide range of delays in motor and cognitive development. Measures of general intelligence, memory and attention have been used most frequently to look at cognitive function in the pediatric CKD population. Most studies have demonstrated lower IQ scores among children with end stage renal disease (ESRD) than in unaffected siblings [3] or the general population [4, 5] and also when pre- and post-transplantation performances are compared [6]. Memory deficits also have been identified in children with mild CKD as well as ESRD [7]. Fennell et al. [7] also reported in this same study that there was no significant decline in measures of attention among these children; however, improved attention performance has been demonstrated in children with ESRD after transplantation [6]. Observations of hyperactivity at school also have been noted in 50% of a study population assessing cognitive outcomes following dialysis during infancy [4]. The measures of cognitive performance in each of these studies varied widely but, when viewed collectively, suggest that children with CKD are vulnerable to cognitive deficiencies in IQ, memory and attention.
One thing to note, however, is that most studies to date have focused primarily on children with ESRD, leaving unanswered whether children with mild to moderate CKD also suffer this same vulnerability. Cognitive deficiencies in children with CKD could arise through a gradual process, proportional to the level of kidney dysfunction, or may develop once a filtration threshold has been passed. It seems logical that the severity of CKD might be proportional to the degree of cognitive impairment, but the data are not yet available to support this. The stage of neurologic development at the time of disease onset or the cumulative time children spend with CKD may also impact on the degree or type of cognitive impairment experienced. To our knowledge, no published study has yet focused specifically on isolating risk factors to identify which children with CKD are most at risk for cognitive decline. The primary goal of this study was to explore associations between clinical aspects describing CKD and selected neurocognitive test scores in a sample of children and adolescents with CKD. In addition, this study should provide the foundation for identifying specific clinical risk factors for subsequent neurodevelopmental dysfunction.
Methods
Participants
Study participants were recruited from a university-based pediatric nephrology practice. The participants included children between 7 and 19 years of age, with an estimated creatinine clearance (eCrCl) by Schwartz formula [8] of less than 90 ml/min per 1.73 m2 body surface area for at least 3 months duration. Renal transplant recipients and children with profound developmental delays were excluded. Following parental consent and patient assent, 29 children meeting these criteria underwent neurocognitive testing at a single point in time. A standardized physical examination and laboratory sample collection were also performed within 2 weeks of cognitive testing. A questionnaire providing demographic and historic information was completed by a parent or legal guardian. The study was reviewed and approved by the University of North Carolina Institutional Review Board.
Included among the study sample were 17 children with obstructive uropathy or structural congenital renal anomalies, seven with glomerulonephritis, one with calcineurin inhibitor toxicity, one who had sustained ischemic injury, one with renal insufficiency of undetermined etiology, one child with Alport’s syndrome, and one with cystinosis. Participants were evenly divided with respect to gender and disease severity. Approximately half the study sample had mild to moderate CKD with eCrCl ranging from 31–89 ml/min per 1.73 m2 body surface area. Kidney disease onset was documented from birth in 59%. The majority (59%) were hypertensive, and, among these children, 70% were on antihypertensive therapy, and 65% had measured blood pressure above the 95th percentile at the time of examination. The mean hemoglobin level was 12.7 mg/dl, with only three (10%) below 11 mg/dl, with values of 10.8 mg/dl, 10.7 mg/dl and 10.1 mg/dl. The general characteristics of our study sample are described in Table 1. All the participants attended school in a regular classroom setting, and two reported having an individualized education plan (IEP) at the time of participation.
Table 1Demographic characteristics and medical variables of the study sample (PD peritoneal dialysis, HD hemodialysis)Study sample characteristicsNumber (n = 29)aRangeAge (years)12.5 (3.2)7–19Male (%)52Caucasian (%)52eCrCl (ml/min per 1.73 m2 body surface area)32 (29)4–89ESRD (13 PD, 1 HD) (%)48Age at disease onset (years)4.4 (5.9)0–16Duration of CKD (years)6.7 (4.7)0.2–15Percent of life with CKD69 (39)1–100Hypertensive (%)59Hemoglobin (mg/dl)12.7 (1.5)10–17aMean (standard deviation) or percent
Neurocognitive instruments
All participants completed a battery of intellectual, attention, and memory tasks as part of a larger neuropsychological evaluation. To gain an estimate of overall intellectual functioning, we administered the Wechsler Abbreviated Scale of Intelligence [9]. The Gordon Diagnostic System [10], a computerized continuous performance test, was also administered to gain an estimate of attention functioning. Within the memory domain, the Wide Range Assessment of Memory and Learning [11] was employed to assess short-term memory across verbal and visual domains. Age-based standard scores (mean = 100, standard deviation = 15) were generated for variables from each of these tasks. In all instances, higher scores represented higher function for each cognitive test result. All tasks were administered by trained examiners who were supervised by a child neuropsychologist.
The Wechsler Abbreviated Scales of Intelligence (WASI) is built on the well-known Wechsler measures of global intellectual functioning [9]. It was designed for ages 6 years through adulthood, and employs a fluid-crystal model of intelligence. Four subtests comprise the WASI and include vocabulary, block design, similarities, and matrix reasoning. All four subtests were administered to gain a brief full scale IQ score.
The Gordon Diagnostic System (GDS) is a computerized continuous performance test that measures various aspects of visual attention [10]. For this study, the vigilance task was administered, which requires the individual to respond to specific visual stimuli (e.g., the number 1 followed by the number 9) from a series of numbers presented at a rate of approximately one per second. This task yields standard scores for the number correct, correct variability, commissions, and commission variability. For this study, the total correct standard score was employed.
The Wide Range Assessment of Memory and Learning (WRAML) is a comprehensive memory battery of tests [11]. It includes nine different subtests that measure short-term verbal memory (story memory, sentence memory, number/letter), short-term visual memory (picture memory, design memory, finger windows), and new learning capabilities (sound symbol, visual learning, verbal learning). A general memory index is also computed from the nine subtests. Normative data are available for ages 6 through 18 years. The WRAML was administered and scored according to standardized procedures, with the general memory index being employed for this study.
Clinical measures
Disease severity, age of onset, and duration of renal disease, coded as time in years and as percent of life with CKD, as well as the presence of anemia or hypertension were explored as potential risk factors of interest, given their association with detrimental cognitive outcomes in the CKD literature. Clinical data were collected through physical examinations and laboratory tests performed within 2 weeks of cognitive testing. Age of disease onset, as well as duration and percent of life with CKD, were determined through record reviews and were based on the date of primary disease diagnosis.
The Schwartz formula [8], using creatinine and height measurements, was used to estimate the eCrCl for non-dialysis patients. Creatinine clearance and urea kinetics were calculated for peritoneal dialysis patients from a 24 h fluid collection. All but three of the peritoneal dialysis patients exceeded Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines for maintaining a Kt/V of at least 2.0, and those not achieving this level ranged from 1.8 to 1.9 [12]. For our continuous analysis, we represented the eCrCl from the 24 h fluid collection from dialysis patients (incorporating residual renal function for the six dialysis patients who still produced urine) on a continuum with the eCrCl from the Schwartz formula that had been calculated for CKD patients. The one hemodialysis participant had a Kt/V of 1.34 and received dialysis four times a week. For analysis, we imputed this participant’s eCrCl, designating the mean creatinine clearance value from anuric peritoneal dialysis participants. For the dichotomous analysis, “mild to moderate” disease was categorized as an eCrCl of 30 to 89 ml/min per 1.73 m2 body surface area, representing those patients with stage 2 or 3 CKD as defined by K/DOQI guidelines [12]. Those with an eCrCl of less than 30 ml/min per 1.73 m2 or those on dialysis, consistent with stage 4 or 5 CKD, were categorized as “severe CKD/ESRD”.
Anemia was defined as a hemoglobin level of less than 11 mg/dl, reflecting the normative ranges of hemoglobin for children aged 9 years and above and the K/DOQI guidelines that specify a target hemoglobin level of 11–12 mg/dl in CKD [13]. Hypertension was defined as either the regular use of antihypertensive medications or the presence of a blood pressure greater than the 95th percentile for age, height, and gender [14].
Data analysis
Initial summary statistical analysis was used to describe the total study sample. This included both descriptive analysis and graphical examination of all relevant variables. To address the primary research question for this study, we used bivariate analysis comparing neurocognitive scores and the clinical characteristics of the study sample, using Pearson’s correlations for all continuous variables. Trend analysis based on linear regression was also used when continuous variables were compared graphically. For those variables that, by definition, were dichotomous (e.g., hypertension), Student’s t-tests were used to compare the mean neurocognitive scores between categories. For those clinical variables for which an argument could be made either to express continuously or to dichotomize on the basis of a normal range (e.g., hemoglobin), both correlations and t-tests were used.
Results
An initial inspection of the neurocognitive test scores showed that the sample of children and adolescents with CKD was mildly variable, with most of the participants falling within the low average to average range on most tasks. For the full study sample, the mean IQ score was 91 (range 61 to 117, SD 16), and the mean memory score was 88 (range 65 to 128, SD 16), both falling within the low average to average range when compared with normative expectations. The mean attention score of 96 fell well within the average range but did show much more variability (range 37 to 120, SD 23).
Disease severity
Disease severity, represented by the eCrCl, yielded the strongest relationship with both IQ (r = 0.57, P = 0.001) and memory (r = 0.45, P = 0.02), demonstrating that higher eCrCl correlated with higher scores in these cognitive domains. Figures 1 and 2 illustrate the linear trend in the relationship between the continuous representation of disease severity and both IQ and memory scores. The correlation between attention and eCrCl was not significant. Additionally, lower IQ measures among severe CKD/ESRD participants in our study were evident when compared dichotomously with those with mild to moderate CKD (P = 0.0008), and the same relationships held for memory scores (P = 0.009) and attention scores (P = 0.012), despite the fact that attention was not linearly associated with eCrCl. Figure 3 illustrates the mean cognitive scores for categories of disease severity. While a downward trend with increasing severity is observed across all cognitive domains, statistical analysis confined to only the 15 non-dialysis patients yielded similar but less robust correlations among all areas of cognition, with IQ being the strongest (r = 0.46, P = 0.08).
Fig. 1Relationship between IQ and estimated renal functionFig. 2Relationship between memory and estimated renal functionFig. 3Mean cognitive scores by level of renal disease
Age at disease onset and CKD duration
Increased CKD duration in years was associated with lower memory scores (r = −0.40, P = 0.03). Age at disease onset did not correlate significantly with IQ, memory, or attention scores in our original analysis. However, it was noted that many participants in our study sample had presented with already severe disease, making the date of disease diagnosis less reflective of the actual age at which reduced renal function began. In a secondary exploratory analysis, we repeated our analysis using only those subjects (n = 10) for whom we had a clearly documented date on which the eCrCl dropped below 90 ml/min per 1.73 m2. Among these patients were six with obstructive uropathy or structural congenital renal anomalies, three with glomerulonephritis, and one with cystinosis. In this secondary analysis we observed that the direction of prior relationships was preserved, with a stronger relationship between IQ and both age at disease onset (r = 0.69, P = 0.03) and percent of life with CKD (r = −0.66, P = 0.04). This may indicate that younger age at onset of CKD and longer percent of life with CKD correlate with lower IQ scores.
Hypertension and anemia
Table 2 summarizes the results of our analysis of hypertension and anemia. The dichotomous separation of these two variables did not produce significant group differences. These findings suggest that the presence of anemia or hypertension at the time of testing did not correlate with differences in neurocognitive test results between study participants with or without these clinical features. In a secondary analysis we also explored designation of hypertension, defined initially as either the use of antihypertensive medications or the presence of hypertension at the time of examination, on the basis of the presence of each criterion separately, and we found no differences. Additional examination of anemia revealed that only three patients had a hemoglobin level below the anemia definition of < 11 mg/dl, with values of 10.8 mg/dl, 10.7 mg/dl and 10.1 mg/dl. Consequently, we were unable to assess anemic patients across a wide range of hemoglobin (Hb) values. Within our sample of hemoglobin ranging between 10.1 mg/dl and 17.0 mg/dl, no association between our cognitive domains and hemoglobin was observed.
Table 2Relationships between hypertension, anemia and cognitive measuresNumber (n = 29)IQaGeneral memoryaAttentionaTotal cohort91 (16)88 (16)96 (23)Non-hypertensive90 (18)87 (16)89 (24)Hypertensive92 (15)89 (17)100 (21)Non-anemic91 (16)89 (16)98 (22)Anemic (<11 mg/dl)92 (17)81 (23)76 (20)aFor each represented test among the normal population, the mean is 100 with a standard deviation of 15. No significant differences on Student’s t-tests for hypertension or anemia.
The use of a contemporary blood pressure or hemoglobin value to represent the hypertension or anemia status of our participants evaluated the potential effect of these factors on their cognitive performance on the day of testing. Day-to-day changes in blood pressure could cause changes in cognitive function. Another approach is to use time-averaged hemoglobin and blood pressure values as markers of long-term strain on cognitive skills. Therefore, we also did a retrospective chart review of all blood pressure and hemoglobin values recorded in the 6 months prior to the study visit and generated a mean value for each of these two variables. On the basis of these time-averaged values, we repeated our analysis. In the blood pressure range represented, hypertension remained unrelated to any of the cognitive variables. Hemoglobin levels, however, demonstrated a subtle correlation with memory performance in the continuous analysis (r = 0.41, P = 0.03). Dichotomous analysis of anemia yielded a significant difference in cognitive scores only when defined as a time-averaged hemoglobin level less than 10.5 mg/dl (mean memory score of 67 among anemic patients versus 91 among non-anemic participants, P = 0.01). However, this must be interpreted with caution, since only three participants fulfilled this criterion for anemia.
We should also acknowledge that there is a high degree of correlation among the results of the individual cognitive domains tested. Among the children included in our study, 12 (41%) had no cognitive scores greater than one standard deviation below the normative mean of 100, eight (28%) deviated in this fashion in a single cognitive domain, three (10%) did so in two areas, and six (21%) did so in all three areas. The level of overlap is, in part, likely due to the nature of cognitive testing, whereby testing in one area is, to some degree, dependent upon function in another area. The fact that there is not complete overlap, however, indicates that cognitive testing can distinguish among these deficits with some level of specificity.
Discussion
Neurocognitive deficits among children with ESRD have been demonstrated in the literature, with some suggestion that key clinical variables can be associated with the level and, perhaps, the pattern of these deficits. The primary purpose of this study was to examine the relationship between targeted clinical variables, based on the available literature, and selected neurocognitive functions as defined by IQ, memory, and attention. Further, the current study examines these relationships across the full spectrum of CKD, including the mild to moderate stages of CKD. While it is recognized that some of the etiologies leading to CKD in our patients, namely cystinosis, calcineurin inhibitor toxicity, and ischemic injury, could potentially be independently associated with some level of cognitive dysfunction, in all three cases the children did not demonstrate evidence of other neurologic signs that would indicate central nervous system damage from their underlying disorders. Additionally, these children are representative of a typical pediatric CKD population, and any contribution from the presence of their comorbid conditions would not compromise the validity of our findings.
In the current study, several key findings were evident. First, disease severity significantly correlated with IQ and memory, while duration of disease significantly correlated with memory in the expected direction. Age at onset and percent of life with CKD did not initially correlate with any of the neurocognitive indices. When the age at onset and percent of life with the disease were examined in a secondary analysis restricted to a group of participants with more precisely defined onset of true decreased renal function, there was a clear trend that suggested that the younger the age at onset and the greater the percent of life with CKD, the lower the IQ score. The finding that younger age at renal insufficiency onset is significantly related to lower IQ complements previous observations in two prior studies of children with ESRD [3, 15]. Lawry et al. [15] found that among 24 children, including both dialysis and transplant patients, younger age at ESRD onset correlated with lower IQ scores. Brouhard et al. [3] also found that younger age at renal diagnosis was associated with lower achievement scores, although not specifically with lower IQ scores.
Also interesting to note is the wide range of IQ and memory scores among the ESRD subset of our study sample, as can be observed in Figs. 1 and 2. This might reflect the presence of other clinical variables, such as duration on dialysis, dialysis adequacy, or presence of residual renal function, which could also influence cognitive performance. A similar wide range of results among children with ESRD has been observed in other study samples, such as that of Brouhard et al. [3], in which children with renal disease had scores that included some in the average range but still had mean IQ and achievement scores significantly lower than their healthy sibling controls. These findings support the hypothesis that disease severity plays a strong role in predicting neurocognitive vulnerability, yet also suggest that there might be additional contributing variables characterizing end stage disease that warrant further investigation. In an effort to explore this issue further, the sub-analysis confined to the relationship between disease severity and cognitive outcomes in the non-dialysis participants demonstrated a more subtle downward trend of scores across all cognitive domains that did not reach statistical significance. This was likely, in part, due to the reduction in power resulting from our limiting the analysis to only 15 participants. It also might suggest that therapy with dialysis itself contributes to cognitive dysfunction.
The literature has been more ambiguous with regard to attention, and our findings did not demonstrate a significant deficit in attention. Our sample did, however, demonstrate significantly more variation in the attention measure among children with CKD than one would anticipate in the general population, as exhibited by the large standard deviation in our study sample. This suggests the possibility that there may be a subset of children with CKD who are more vulnerable to attention-related problems. More extensive exploration of the various components of attention may be required to explore this observation further.
Hypertension, as a single measure or time-averaged, was not associated with the neurocognitive outcomes evaluated. Hypertension in the general pediatric population has been correlated with decreased performance in tasks requiring memory, attention, and concentration [16]. Using school-aged children from a population-based US survey who were diagnosed with hypertension on the basis of systolic or diastolic blood pressure above the 90th percentile for age, height and gender, Lande et al. [16] showed that hypertension was significantly associated with lower neurocognitive scores representative of short-term memory, attention and concentration problems. In our study sample of children with CKD, the majority of our participants were on antihypertensive therapy, so any existing hypertension in our study sample was at least partially treated, thus significantly restricting the range of variance available for correlation analysis. Furthermore, some antihypertensive therapies, for instance clonidine, have the potential to cause sedating effects in children but can actually help concentration in other children. The effects of medications on just a few children could appear amplified in our small study sample, and, thus, a true relationship could be obscured.
The hemoglobin level at the time of testing did not predict cognitive function. Time-averaged hemoglobin concentrations less than 10.5 mg/dl were associated with lower memory performance. It has also been well established that anemia is associated with decreased cognitive function in adult patients with renal disease [17, 18]. Stivelman’s review on the topic highlights several studies investigating the use of erythropoietin in uremic adult patients. Increasing hematocrit was associated with improved neurocognitive measures [17]. For example, Marsh et al. [18] used erythropoietin in 24 adult hemodialysis patients to improve their average hematocrit from 23% to 36%, resulting in significantly improved neuropsychological test scores reflecting memory, learning and attention. In our study sample of children with CKD, only three children had a low hemoglobin level, and these were between 10.1 mg/dl and 10.8 mg/dl. The mean scores for memory and attention among those three children were 8 points and 22 points lower, respectively, than those for non-anemic children, suggesting that there could be a relationship that would require a larger sample size to identify. In the normal or near-normal range, detrimental effects of lower hemoglobin levels are likely more subtle and, thus, less likely to be captured in analysis of a small sample. Our time-averaged hemoglobin analysis supported this as well.
This is the first study to date that focuses specifically on identifying potential risk factors for neurocognitive decline in children and adolescents with CKD. Its value is further enhanced by the inclusion of children with mild to moderate CKD, thus extending findings to a wider range of pediatric CKD patients. Increased disease severity, duration of CKD, and younger age at CKD onset were identified as potential risk factors for the targeted neuropsychological functions of IQ and memory. Our results further suggest a significant linear relationship with disease severity, with IQ scores continuously declining as disease severity worsens. Not only does this finding argue against a threshold effect, it implicates disease severity as an important risk factor for neuropsychological dysfunction. These findings also suggest the possible utility of these variables in a cumulative risk model to predict neurocognitive dysfunction in CKD and lay the foundation for exploration of such a model. Finally, these findings emphasize the importance of conducting further research in neurocognitive development among children with CKD. This includes research both to more clearly predict which children with CKD are most vulnerable to neuropsychological dysfunction and to identify specific correlates of this dysfunction. While there have been great strides in improving quality and length of life among children with CKD, a better understanding of those processes that interfere with normal neurodevelopment is a critical element of providing optimal care to these children.

pediatrics
developmental delay
chronic renal insufficiency
cognitive deficits