Healthcare Utilization of Individuals with Opiate Use Disorders: An Analysis of Integrated Medicaid and State Mental Health/Substance Abuse Agency Data

Data from the Substance Abuse and Mental Health Services Administration’s Integrated Database (IDB) were used to examine the service use patterns of individuals with possible opiate use disorders in Washington State. Results indicate that regardless of Medicaid enrollment status, individuals who received mental health (MH) or substance abuse (SA) services only through state agencies received no inpatient substance abuse service. Furthermore, when compared with individuals who received at least one MH/SA service through Medicaid, those who received services only through the state agencies were less likely to have received any MH services and were more likely to have received residential SA services. This analysis highlights the importance of using integrated client data in providing a more comprehensive understanding of services to inform policy and raises significant questions about how regulatory requirements affecting different funding mechanisms might drive settings of care in ways not related to the care needed.
Introduction
The use of, abuse of, and dependence on opiates is a major public health concern.1,2 Although only about 0.1% of the U.S. population reported past-year heroin use in 1998,3 heroin and other opiate use accounted for about 30% of total spending for illicit drug use treatment and almost 18% of spending on drug-related crime.4 Psychological and physical health problems were also common among heroin and other opiate users in the mid- to late-1990s.5 As recently as 2003, heroin accounted for 23% of the mentions of substances used among emergency room patients and 41% of drug-related deaths recorded by medical examiners or coroners.6 The social costs of opiate abuse are not limited to illegal drugs. A recent study suggests that in 2001, the social cost of prescription opioid abuse in the United States was $8.6 billion.7
Despite the overwhelming societal costs associated with opiate use disorders, few studies have investigated the substance abuse (SA) or mental health (MH) treatment service patterns of individuals suffering from opiate abuse or dependence; rather, most studies focus almost exclusively on those in methadone maintenance treatment.8–10 These studies suggest that the co-occurrence of MH problems and other illicit drug dependence is quite high among individuals with an opiate use disorder.11–13 Yet, despite the increased incidence of MH conditions, individuals with a substance use disorder may not receive adequate levels of MH care beyond that directly related to their substance use disorder.10,11,14,15 Given these findings and the major public health concerns caused by opiate abuse and dependence, the lack of information about the broader MH/SA treatment service patterns of individuals with an opiate use disorder is a critical gap in the knowledge base informing policies affecting this population.
This study used data from the Substance Abuse and Mental Health Services Administration’s (SAMHSA) Integrated Database (IDB) on individuals in Washington State with an indication of an opiate use disorder to determine what MH/SA services they received and through which auspice (i.e., Medicaid or state agency) they received them. Findings from this study offer two contributions to the current literature. First, the IDB presents a unique opportunity to study the behavioral health care utilization of individuals with opiate use disorders because it contains service use data linked at the client level from Washington Medicaid and from the Washington State Department of Social and Health Services’ (DSHS) Mental Health Division (MHD) and Division of Alcohol and Substance Abuse (DASA). The combination of Medicaid and DSHS data represented in the IDB provides a more comprehensive picture of service use patterns than might be obtained from studies that focus on only one data source. Second, the late 1990s is often characterized as a time of a heroin epidemic in the United States.16 Therefore, examining the MH/SA treatment service use patterns of individuals with opiate use disorders during this period can provide an especially relevant baseline for today’s policy makers as they attempt to address issues surrounding the emergence of new opiates.
Data and Methods
This paper uses IDB data on Washington State from three full calendar years (1996–1998). For a more detailed description of the IDB, see Coffey et al.,17 and for a detailed description of the methods used to link IDB service records across state organizations, see Whalen et al.18 In addition to service use information, the IDB contains information on patient demographics (e.g., age, gender, race/ethnicity), Medicaid enrollment status, MH/SA diagnosis and service codes, and limited provider information.
Study population
The study population for this analysis consists of individuals who have at least one record in the IDB indicating an opiate use disorder. An opiate use disorder could be indicated by one or more of the following: a diagnosis (either primary or secondary) of an opiate use disorder, a provider type indicative of opiate treatment, a service or procedure code indicative of opiate treatment (including methadone maintenance therapy but excluding methadone used for pain management), or a report of an opioid as the drug of choice. Opiate use disorder diagnoses were defined using the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM). ICD-9-CM codes of 304.0 or 305.5, including any subclassifications, were used to identify opiate dependence and abuse, respectively. State-specific provider codes were used to identify opiate treatment providers. Both standard [e.g., Healthcare Common Procedure Coding System (HCPCS)] and local procedure codes were used to identify opiate treatment services. Finally, drug-of-choice information was available from self-reports obtained by state agencies during client intake. In some cases, the drug-of-choice information was obtained more than 1 year before or after any SA or MH service provision, but these cases represent less than 3% of the sample.
Preliminary analyses revealed that very few agency service records include diagnosis codes, but most Medicaid records do. Further investigation revealed that this is not an issue of Medicaid requiring a diagnosis for eligibility, but rather an issue of the data systems themselves. Agency services do not require a diagnosis code for reimbursement, so agency data systems do not track diagnosis. Conversely, Medicaid services often require a diagnosis for reimbursement, so Medicaid data systems track diagnosis. Because the presence or absence of a diagnosis is almost completely confounded by the use or nonuse of Medicaid services, information on service use differences associated with an opiate use disorder diagnosis is not presented.
Client classification
One of the primary objectives of this study was to examine the extent to which the MH/SA service use patterns of individuals with an opiate use disorder varied based on whether their MH/SA services were tracked by Medicaid or a state MH/SA agency. Importantly, service tracking may, or may not, be associated with full or partial financial coverage. Accordingly, for this study, individuals were classified based on the data source (Medicaid or state MH/SA agency) from which their IDB MH/SA service records were obtained. Based on this information, individuals were classified into three categories:
Any Medicaid service: individuals who have at least one Medicaid MH/SA service record, regardless of whether they have MH/SA state agency service recordsAgency services only with Medicaid enrollment: individuals who have at least one MH/SA state agency service record and were Medicaid-enrolled at some point between their first and last observed MH/SA service record but have no record of receiving an MH/SA service through MedicaidAgency services only without Medicaid enrollment: individuals who have at least one MH/SA state agency service record and were not Medicaid-enrolled at any time between their first and last observed MH/SA service record
Because the IDB integrates information from state Medicaid and state MH/SA agency data sources, overlapping records may occur if Medicaid reimburses a bill, but the state agency provides the service. To avoid overstating utilization rates, only one service date was counted for cases in which the same client, service type (MH or SA), modality/setting of service [i.e., inpatient (IP), residential/long-term care, or outpatient (OP)], and service date were reported on both the Medicaid and state agency databases. Individuals with these types of records were classified as any Medicaid service. Importantly, although individuals in the any Medicaid service group may have received any number, or even the majority, of their services through the state agency, preliminary analyses indicated that individuals who received both Medicaid and agency services were more similar to those who received only Medicaid services than they were to those who received only agency services. For this reason, individuals receiving any Medicaid service were combined into a single category.
In addition to the client categorization described above, the standard IDB client classification was also used. The IDB client classification was used to identify individuals who received services for only MH conditions (MH-only), only SA conditions (SA-only), or co-occurring conditions (both MH and SA) during the study period. The IDB classifies individuals as having co-occurring conditions if they had any of the following within the 3-year study period: (1) both a primary MH and a SA diagnosis, (2) a primary MH and a secondary SA diagnosis, or (3) a primary SA and a secondary MH diagnosis. Individuals classified as having co-occurring conditions did not necessarily have MH and SA conditions concurrently. A client with an MH record at the beginning of the study period and an SA record at the end of the study period, for example, is classified by the IDB as having co-occurring conditions. In the absence of diagnosis information, MH-only and SA-only classifications were assigned based on the type of service received during the study period (see Coffey et al.17 and Bray et al.19 for a detailed definition of the primary MH/SA diagnosis category).
The IDB client classification does not incorporate information on secondary diagnoses unless a primary MH/SA diagnosis is also present, nor does it incorporate drug-of-choice information from state agency intake records. Because both of these pieces of information were used to identify individuals with an opiate use disorder for this study, it is possible for individuals with an opiate use disorder to be classified as MH-only or having received no MH/SA service based on the IDB client classification.
Service classification
Standard IDB service type classifications were used to classify the MH/SA services received by individuals with an opiate use disorder. The IDB MH/SA service type classifies MH/SA service records as either MH or SA and within MH/SA as IP, residential, or OP. Many inpatient programs are part of psychiatric or general hospitals and generally use a medical model of substance disorders in which intensive medication and counseling are provided over a relatively short period of time.20 Residential programs typically are provided in a free-standing, designated residential treatment facility. Residential treatment is usually of longer duration than IP treatment and relies less on medical professionals. Residential treatment provides organized services by designated treatment personnel who provide a planned regimen of care in a 24-h setting and is intended to serve clients who need a safe and stable living environment to develop sufficient recovery skills.21 For a complete description of the criteria used to classify services, see Coffey et al.17 The vast majority of individuals with a possible opiate use disorder have at least 1 SA service record, but relatively few have MH service records; therefore, the IP, residential, and OP subclassifications were examined for SA service records but not for MH service records.
Service encounters
An individual’s total number of service encounter dates was defined as the count of unique dates within the MH/SA service window on which the individual had a record with at least one service of a given service category (MH, IP SA, residential SA, or OP SA). Within a single IP or residential stay, each daily service encounter date was counted separately. Using standard IDB definitions for the full SA population, this same information is presented for the broader SA population, excluding individuals with an indication of an opiate use disorder.
Methods
To characterize the level of contact individuals with an opiate use disorder have with the public treatment system, the analysis examined four key domains: (1) the proportion of clients using services, (2) the median length of the service window (i.e., the length of time between an individual’s first and last MH/SA service), (3) the number of days of Medicaid enrollment within the service window, and (4) the number of unique MH/SA encounter dates within the service window.
Regression analyses were conducted to assess whether the service use patterns of individuals with an opiate use disorder differed significantly across the client classification categories after controlling for differences in the length of the MH/SA service window, the length of Medicaid enrollment, and demographics across the client categories. First, logistic regression models of the following form were estimated:
where SERVi is a series of indicators for receipt of services of a given type. For the regression analyses, any MH services and OP and residential SA services were considered. Regression analyses for IP SA services were not conducted because those services were received solely by the any Medicaid service group. DEMOGi is a set of demographic characteristics (i.e., gender, age, and race/ethnicity); GROUPi is a vector of variables representing the data source categories of any Medicaid service (the referent), agency services only with Medicaid enrollment, and agency services only without Medicaid enrollment; WINDOWi is the MH/SA service window length in days; and ENROLLi is the months of Medicaid enrollment (including 0 months). The βs are vectors of coefficients to be estimated. Variables reflecting the primary diagnosis categories are not included because much of the information used to classify individuals as MH-only, SA-only, or co-occurring was also used to classify services as MH or SA.
Next, regressions of the following form were run on days of service, conditional on service use:
where DAYSi is a set of variables reflecting the unique days of care for each of the same types of care, and all other terms are as previously defined. Consistent with the recommendations of Manning and Mullahy,22 generalized linear model (GLM) estimation with a log link and a gamma distribution on the natural scale was used rather than ordinary least squares (OLS) on the log scale.
Results
Table 1 presents the demographic characteristics of the individuals identified as having an opiate use disorder in the IDB. For a point of comparison, Table 1 also presents the same information for the general IDB SA population, as defined in Coffey et al.,17 but excluding individuals with an opiate use disorder. Individuals with an opiate use disorder accounted for approximately 16% of the population with any SA disorder. In terms of demographics, when compared with individuals with a non-opiate SA disorder, individuals with an opiate use disorder are less likely to be male and more likely to be adults (as opposed to youth or elderly), but only minor differences in the distribution of clients across racial/ethnic categories are observed. Individuals with an opiate use disorder are less likely to be in the SA-only IDB client classification category. This is largely by construction because as discussed earlier, the current paper uses more inclusive data to identify individuals with a possible opiate use disorder than is used by the IDB client classification. Individuals with an opiate use disorder were more likely to have IP and residential SA services than the general SA population, but less likely to have any OP SA service. Individuals with an opiate use disorder were also more likely to have received any MH service compared to the general SA population. They also had longer MH/SA service windows, indicating longer periods of contact with the public MH/SA treatment system, and were more likely to be in the any Medicaid service and the agency services only with Medicaid enrollment groups.
Table 1Characteristics of individuals with a possible opiate use disorder compared with the non-opiate SA populationPopulation characteristicNon-opiate SA populationOpiate usersAll users (N)83,79315,652Percentage of total SA population (%)84.315.7Gender (%) Male63.256.8 Female36.843.2 Unknown0.00.0Age (%) Youth (0–17)19.93.1 Adult (18–64)78.896.5 Elderly (65+)1.30.4 Unknown0.00.0Race/ethnicity (%) White70.077.6 Black9.010.6 Hispanic8.54.3 Native American7.84.5 Other3.62.6 Unknown1.00.3IDB client category (%) SA-only68.859.9 Co-occurring (MH+SA)31.234.7 MH-only0.01.9 Neither MH nor SA0.03.4MH/SA service type (%) SA services (%)  Any setting94.994.6  Inpatient3.06.2  Residential31.957.7  Outpatient80.971.4  No SA services5.15.4  Any MH service31.236.5 MH/SA service window length  25th percentile (days)38.078.0  Median (days)168.0348.0  75th percentile (days)446.0770.0 MH/SA service data source (%)  Any Medicaid46.051.0  Agency services only with Medicaid enrollment17.322.7  Agency services only without Medicaid enrollment36.826.3SA Substance abuse, MH mental health
Figure 1 presents the median MH/SA service window and length of Medicaid enrollment across individuals with a possible opiate use disorder in each of the data source categories. The any Medicaid service group has the longest median MH/SA service window and the most median days of Medicaid enrollment within that window, followed by the agency services only with Medicaid enrollment group and then the agency services only without Medicaid enrollment group. Because the analysis only examines Medicaid enrollment within the MH/SA service window, the length of Medicaid enrollment is always less than the total service window length. The total Medicaid enrollment of an individual may be greater than that reported here, but by definition of the service window, no MH/SA service use occurred during days of Medicaid enrollment not captured by this measure. Importantly, the any Medicaid service group may have received substantial services from MH or SA state agencies, because individuals in this group are categorized as any Medicaid service only because they received at least one Medicaid service.
Figure 1Median MH/SA service window length and days of medicaid enrollment among individuals with a possible opiate use disorder by data source category
Figures 2 and 3 present the probability of service use and the median days of service conditional on service utilization for each of the data source categories. IP SA care was not included in Figures 2 and 3 because only individuals in the any Medicaid service group had IP SA utilization (the conditional median days of IP SA care for that group were 6). Figure 2 suggests that the two agency services only groups are more likely to receive residential SA services and are less likely to receive OP SA services or MH services. Conditional on receipt of services, Figure 3 suggests that the agency services only with Medicaid enrollment group received the most days of residential SA service, the agency services only without Medicaid enrollment group received the most days of OP SA care, and the any Medicaid services group received the most days of MH care.
Figure 2Percentage of individuals with a possible opiate use disorder using MH/SA services by service type and data source categoryFigure 3Median days of care conditional on service use among individuals with a possible opiate use disorder by service type and data source category
Table 2 presents results from the logistic regressions, including logit coefficients, their standard errors, and associated odds ratios (ORs) for the data source grouping variables. For all other covariates, only the estimated logit coefficients and their standard errors are presented. Table 2 shows that even after controlling for the longer service window and more months of Medicaid enrollment, the pattern observed in Figure 2 still holds. Compared with individuals in the any Medicaid service group, individuals in the agency services only with Medicaid enrollment and the agency services only without Medicaid enrollment groups had significantly higher odds of receiving at least residential SA service (OR = 2.941 and OR = 1.376, respectively) and lower odds of receiving any OP SA (OR = 0.311 and OR = 0.162, respectively) or any MH service (OR = 0.217 and OR = 0.110, respectively). Briefly examining the results for the control variables in the regression, females are significantly less likely to receive residential SA services. The racial/ethnic categories that are statistically significant suggest that racial/ethnic minorities are less likely than non-Hispanic whites to receive services of any type. Age categories reflecting individuals both younger and older than the referent of 36 to 40 were also, in general, less likely to receive services of any type when the associated coefficients were statistically significant. The exception is that individuals aged 21 to 35 with an opiate use disorder were more likely to receive residential SA services. Results with regard to demographic characteristics, especially race/ethnicity, should not be interpreted as evidence of disparities, however. Rather, they indicate the differential representation of demographic groups across the data and highlight the importance of controlling for those factors when assessing statistical significance. Unexpectedly, months of Medicaid enrollment are positively associated with a greater likelihood of service use only for MH services. For both types of SA care examined, longer Medicaid enrollment was negatively associated with the probability of service use, although the relationship was not significant for residential care.
Table 2Logistic regression results for the probability of service useParametersProbability of residential SA service useProbability of OP SA service useProbability of any MH service useAgency services only with Medicaid enrollment1.079***−1.167***−1.526***Standard error0.0500.0610.052Odds ratio2.9410.3110.217Agency services only without Medicaid enrollment0.319***−1.819***−2.210***Standard error0.0520.0690.072Odds ratio1.3760.1620.110Control variablesIntercept0.446***1.091−0.274***Standard error0.0590.0780.065Female−0.519***0.344−0.064Standard error0.0360.0460.042Race/ethnicity (referent is non-Hispanic White)Black−0.269***0.371−0.493***Standard error0.0570.0750.069Hispanic−0.0810.036−0.402***Standard error0.0860.0970.116Native American0.342***−0.067−0.221**Standard error0.0870.1010.101Other−0.357***0.229−0.169Standard error0.1100.1450.128Unknown−1.656***−1.122**0.863*Standard error0.5070.4410.459Age (referent is 36 to 40)0 to 17−0.384***0.765−0.058Standard error0.1030.1460.12418 to 20−0.032−0.037−0.126Standard error0.1120.1320.13421 to 250.361***−0.0980.097Standard error0.0750.0860.08526 to 300.279***−0.0600.027Standard error0.0630.0760.07231 to 350.175***0.0340.093Standard error0.0580.0720.06641 to 45−0.205***−0.047−0.116*Standard error0.0550.0690.06546 to 50−0.465***−0.010−0.268***Standard error0.0650.0820.07851 to 55−0.537***0.001−0.425***Standard error0.0990.1290.12156 to 60−1.096***0.443**−0.718***Standard error0.1590.2200.18361 to 64−0.656***−0.713**−0.729**Standard error0.2410.2970.28865 plus−1.417***−0.285−0.675**Standard error0.3010.3440.322Service window length (days)0.0000.0030.001***Standard error0.00010.00010.0001Medicaid enrollment (months)−0.005−0.017**0.053***Standard error0.0040.0070.005IP Inpatient, SA substance abuse, OP outpatient, MH mental health*p < 0.10**p < 0.05***p < 0.01
Table 3 presents the regression results for days of care, conditional on having at least 1 day of service of that type of care. Because the natural logarithm of days of care is the dependent variable, the coefficient estimates, standard errors, and associated percentage changes for the data source categories are presented. For all other variables, only the estimated coefficients and their standard errors are presented. For residential SA care, the agency services only with Medicaid enrollment group is significantly associated with more days of residential SA care (28% increase), while the agency services only without Medicaid enrollment group is significantly associated with fewer days of care (56% decrease). Both agency services only groups are significantly and positively related to OP SA days of care: an estimated 18% increase for the agency services only with Medicaid enrollment group and an estimated 60% increase for the agency services only without Medicaid enrollment group. Finally, the agency services only without Medicaid enrollment group is associated with significantly more days of MH care than the any Medicaid service group (56% increase). Unlike in Table 2, no consistent pattern emerges with regard to the demographic control variables included in the linear regression. The length of the MH/SA service window is positively and significantly associated with days of care. Months of Medicaid enrollment are negatively and significantly associated with days of residential and OP SA care, but positively and significantly associated with days of MH care.
Table 3Linear Regression Results for Unique Health Care Service Dates ParametersUnique dates of residential SA serviceUnique dates of OP SA serviceUnique dates of MH serviceAgency services only with Medicaid enrollment0.248***0.169***−0.009Standard error0.0300.0450.063Percentage change0.2820.185−0.009Agency services only without Medicaid enrollment−0.818***0.472***0.448***Standard error0.0380.0770.094Percentage change−0.5590.6040.564Control variablesIntercept3.310***2.552***2.337***Standard error0.0420.0650.067Female−0.0170.322***−0.045Standard error0.0250.0390.041Race/ethnicity (referent is non-Hispanic White)Black−0.0070.121**−0.010Standard error0.0400.0610.074Hispanic0.208***0.013−0.153Standard error0.0570.1060.133Native American0.254***−0.039−0.700***Standard error0.0520.0840.106Other−0.057−0.0160.211*Standard error0.0790.1230.128Unknown−1.268***0.000−1.340***Standard error0.4830.0000.443Age (referent is 36 to 40)0 to 170.549***0.374***0.224*Standard error0.0760.1120.12318 to 200.193***0.1350.366**Standard error0.0740.1230.14321 to 25−0.0280.188***0.062Standard error0.0450.0720.08526 to 300.0030.174***0.071Standard error0.0390.0610.07131 to 35−0.0260.0390.040Standard error0.0370.0570.06541 to 45−0.0310.137**0.115*Standard error0.0370.0580.06446 to 500.0370.1150.309***Standard error0.0460.0750.07851 to 550.0400.317***−0.080Standard error0.0730.1220.12356 to 60−0.229*0.264−0.037Standard error0.1340.2100.19661 to 64−0.618***0.283−0.093Standard error0.1900.3570.30865 plus0.701***−0.7000.116Standard error0.2711.3210.353Service window length (days)0.001***0.003***0.002***Standard error0.0000.0000.000Medicaid enrollment (months)−0.019***−0.024***0.013***Standard error0.0030.0040.003IP Inpatient, SA substance abuse, OP outpatient, MH mental health*p < 0.10**p < 0.05***p < 0.01
Implications for Behavioral Health
This analysis examined the service use patterns of individuals with an indication of an opiate use disorder using IDB data from Washington for the period 1996 through 1998. Among individuals with opiate use disorders, the receipt of at least one MH/SA service through Medicaid appears to be positively associated with IP SA service use in that only individuals who met this condition had any record of an IP SA service. The receipt of at least one MH/SA service through Medicaid was also positively associated with OP SA service and with MH service use among individuals with opiate use disorders. The use of only state MH/SA agency services, on the other hand, was positively associated with the use of residential SA services.
The findings suggest that the regulatory restrictions faced by state agencies and Medicaid may drive observed patterns of care for individuals with opiate use disorders. Specifically, the finding that agency-only MH/SA service use is associated with higher rates of residential service use and with no IP SA service use is likely tied to regulatory differences between Medicaid and the state agencies in Washington. For example, SA block grant funds, which are a key source of funding for both DASA and MHD, could not be used for IP hospital care during the period covered by this analysis. This restriction most likely induced state agencies to route patients for whom outpatient care is insufficient to residential care. Similarly, the Medicaid Institutions of Mental Disorders exclusion prohibits payment for psychiatric services received by adults in residential care facilities with more than 16 beds and so may induce providers to route more severe patients to IP care rather than to residential care. This explanation suggests that using administrative data to track service use patterns may be misleading because the collection of service data is driven by regulatory environments and billing systems that may not capture the actual intensity of care given.
The results are subject to several limitations. First, although the IDB represents one of the most comprehensive cross-system databases used to examine this critical issue to date, it does not capture all possible services that could be used by individuals with possible opiate use disorders in Washington. Other possible sources include self-pay, private insurance, and the Department of Veterans Affairs (VA) system, among others. Another important limitation common to all administrative databases is that the actual treatment need of the population studied is unknown, so definitive statements cannot be made about the appropriateness of the services received. Furthermore, because of the limited time frame of the IDB, data are unavailable for individuals who used MH/SA services either before 1996 or after 1998. As a result, it is possible that this study has not captured the full service use history of some individuals who appear in the treatment system briefly at the beginning or end of the study period. A final limitation of this study is that information on prescription drug use is not available in the agency service records contained in the IDB and is therefore not considered in this study.
Despite these limitations, the analysis of service use patterns of individuals with possible opiate use disorders during the late 1990s offers key implications for today’s policy makers as they attempt to address issues surrounding the emergence of new opiates. First and foremost, if policy makers are trying to track the service use of a small but important segment of the overall SA population, using integrated data is a necessity. When funding for treatment services is cut in an effort to contain costs, it is important to determine if those services have simply been shifted to other state programs, reflecting little net cost savings for states overall. The present study combines state MH/SA agency data with state Medicaid data, but including additional data sources (e.g., VA or criminal justice system) would provide an even more complete picture of service use patterns. Second, the utility of administrative data for analyses such as these is often limited by the influence of the regulatory environment, clinical practice patterns, and the institutional history of the data systems used. Given that state and federal policy makers increasingly rely on administrative data to assess the performance of the treatment system, the results clearly highlight the need to better track service provision. SAMHSA’s IDB, therefore, represents the vanguard of a new, expansive, cross-agency philosophy regarding administrative data sources and serves as a model for new and more comprehensive data integration efforts.

opiate use disorder
medicaid
state mh/sa agencies
mh/sa service utilization


Pancreatic intraductal papillary-mucinous neoplasms: a new and evolving entity

For a long time, intraductal tumors of the pancreas were neglected because they were misdiagnosed as mucinous cystadenocarcinoma, ordinary ductal adenocarcinoma, or chronic pancreatitis. Only in recent years have they been recognized as clinical and pathological entities. Most common are the intraductal papillary-mucinous neoplasms. Although they show an adenoma-carcinoma sequence, they have proved to have a more favorable prognosis than ductal adenocarcinoma, when resected in a preinvasive state. Recently, it has become clear that they constitute a heterogeneous group with at least four subtypes. Their stratification reveals that the various intraductal papillary-mucinous neoplasm subtypes have different biological properties with different prognostic implications.
Historical notes and a rising incidence
The pancreatic tumors that are characterized by an intraductal origin and growth pattern include intraductal papillary-mucinous neoplasms [3, 24, 41], intraductal tubular carcinomas [22, 45], intraductal tubular adenomas of the pyloric type [6], and intraductal acinar cell carcinomas [15]. Most common are the intraductal papillary-mucinous neoplasms (IPMNs). They are mucin-producing epithelial tumors that usually show a papillary architecture and are associated with dilatation of the ducts. Before 1990, these tumors were thought to be rare. They first started to be recognized approximately 20 years ago [31, 36, 39], when the many different names given to the tumor in the 1980s were replaced by the term IPMN [41]. This name was also introduced in the classification of exocrine pancreatic tumors propagated by the World Health Organization (WHO) [24] and the fascicles of the Armed Forces Institute of Pathology [44]. Since then, IPMNs have been reported with increasing frequency (Table 1) and currently account for about 7% of clinically diagnosed pancreatic neoplasms and up to 16% of surgically resected pancreatic neoplasms and for almost 50% of pancreatic cysts found incidentally [8, 17]. When only the cystic tumors of the pancreas are considered, IPMNs take first place, with a frequency of 24% [26].
Table 1Incidence data on intraductal papillary-mucinous neoplasmsAuthorPeriod 1Number of incidencePeriod 2Number of incidenceSohn et al. [43]1987–2001582001–200378Wada et al. [47]1988–2000632001–200337Our series1981–2000552001–200750
The new incidence data on IPMNs raise the question whether their increase in number is real or not. Of course, it is difficult to accept that IPMNs might have been overlooked in the past, not only clinically but also morphologically. There are good reasons, however, to believe that IPMNs did always exist and did not really increase in frequency. One reason is related to the rapid improvements in modern imaging techniques, which enable more precise recognition of cystic lesions, even if they are small and asymptomatic. Another is connected with the decreasing risk of pancreatic surgery. The most important fact, however, may be that until 1999, the distinction between IPMNs and mucinous cystic neoplasms (MCNs) was unclear, so that many IPMNs were classified as MCNs [50] or regarded as ductal adenocarcinomas or chronic pancreatitis.
Adenoma-carcinoma sequence
In IPMNs, the normal ductal epithelium is replaced by mucin-producing columnar cells showing papillary proliferations and variable degrees of cellular atypia, even within an individual neoplasm. They are graded according to the most atypical area as IPMN with low grade dysplasia (adenoma), IPMN with moderate dysplasia (borderline), and IPMN with high grade dysplasia (carcinoma in situ). An invasive component may be found in 38–50% of the cases [7, 26, 40, 43]. Progression from adenoma to carcinoma is estimated to occur at about 5 years [43]. IPMNs therefore provide a model of neoplastic progression from a benign intraductal neoplasm through increasing grades of dysplasia to invasive carcinoma.
Prognosis after resection
Between 80 and 90% of IPMNs are surgically resectable. For these IPMNs, a 5-year survival rate of 77–100% was reported, provided the tumors did not have an invasive component (Table 2). By contrast, IPMNs with an invasive component had a 3- to 5-year survival rate of only 36–46% [12, 16, 43] (Table 2). Interestingly, the survival rate did not appear to be dependent on the grade of dysplasia in the IPMN if there was no invasive component [12, 16, 43, 47]. These data imply that the overall outcome of IPMNs therefore largely depends on the presence of an invasive component. If the tumor is already invasive, criteria for a poor outcome are lymph node involvement, vascular invasion, and bilirubin elevation [13]. A comparison of the prognosis of all patients with invasive IPMNs with that of patients with ductal adenocarcinoma reveals that patients with IPMNs survive longer than those with ductal adenocarcinomas [29, 40, 43].
Table 2Five year survival rate and recurrence in 349a intraductal papillary-mucinous neoplasms NoninvasiveInvasive77–100%36–46%No recurrence93–98.7%52–70%Recurrence1.3–7%30–48%Localup to 6%8–48%Distant (metastases)1%12%Both0%10–48%a[12, 43, 47]
Several studies have reported recurrences after resection of noninvasive IPMNs, some of which revealed only moderate dysplasia [12, 43, 47, 48]. The recurrences were either local or metastatic (Table 2). To explain the recurrences, particularly the local ones, it has to be assumed that either tumor tissue was overlooked at the pancreatic resection margin, or an invasive component remained undetected in the resected specimen, or there was multifocal disease. The last possibility has to be considered if the surgical margins were negative and the recurrence occurred in the pancreatic remnant. This has been observed only in a few cases [40]. When metastatic recurrences occur, it is most likely that they resulted from inadequate sampling that failed to detect an invasive component. Regarding the impact of a positive resection margin on IPMN recurrence, it is interesting to note that it has been reported that even IPMNs with positive margins did not recur during a median follow-up period varying from 19–40 months [13, 48]. The reason for this phenomenon might be that the growth of the remaining intraductal tumor tissue is so slow that clinical symptoms only appear after a follow-up period of 2 to 3 years. However, even if intraductal recurrences may take a long time to become clinically apparent, a positive margin in any IPMN case should lead to further tissue resection.
Histological type and prognosis
In 1991, it was reported that the invasive component of IPMNs corresponded either to an ordinary ductal adenocarcinoma or, more frequently, to that of a mucinous (colloid) carcinoma [49]. This observation suggested that IPMNs form a group of heterogeneous neoplasms. A further argument for the heterogeneity of IPMNs was the detection of IPMNs in branch ducts rather than in the main duct, where most of the IPMNs are found. Finally, it was recognized that IPMNs differ in their histological and cytological features and in their mucin profile [3, 4, 18, 28, 32, 33]. Currently, four subtypes of IPMN can be distinguished: an intestinal type, a pancreatobiliary type, an oncocytic type, and a gastric type [18].
The most common type of IPMN is the intestinal type (Table 3). It usually occurs in the main duct of the pancreatic head [9] and shows a villous growth pattern similar to that of villous adenoma in the colon. It also expresses MUC2 and CDX2 but not MUC1 (Fig. 1a,b). When this IPMN type becomes invasive, the invasive component resembles mucinous (colloid) carcinoma [5, 28], a tumor of which at least 80% is composed of pools of extracellular mucin containing single cells or strands of neoplastic glandular epithelium or even a small component of signet ring cells. Patients with colloid carcinoma have a 55% 5-year survival rate after resection [5]. These tumors therefore seem to be much less aggressive than ordinary ductal adenocarcinomas.
Fig. 1Histological subtypes of intraductal papillary-mucinous neoplasms of the pancreas and their usual mucin pattern. a, b IPMN of the intestinal type positive for MUC2; c, d IPMN of the pancreatobiliary type positive for MUC1; e, f IPMN of the oncocytic type showing scattered positivity for MUC2; g, h IPMN of the gastric type, positive for MUC5Table 3Histopathological data on 105 intraductal papillary-mucinous neoplasms collected during a period of 26 yearsIPMNGastric (n = 27) (26%)Intestinal (n = 57) (54%)Pancreatobiliary (n = 7) (7%)Oncocytic (n = 14) (13%)Noninvasive (65%)n = 20 (74%)n = 35 (62%)n = 3 (43%)n = 10 (72%)Adenoma91215Borderline71821Carcinoma in situ4504Invasive (35%)n = 7 (26%)n = 22 (38%)n = 4 (57%)n = 4 (28%)
The pancreatobiliary type of IPMN is much rarer than the intestinal type IPMN (Table 3). It shows complex arborizing papillae and expresses MUC1 only (Fig. 1c,d). Its invasive component usually corresponds to a conventional ductal adenocarcinoma. The prognosis of this type of IPMN, if invasive, seems to be similar to that of ductal adenocarcinoma and therefore poorer than that of the intestinal type of IPMN [4].
The oncocytic type of IPMN (also called intraductal oncocytic papillary neoplasm [2]) shows the same complex papillae as the pancreatobiliary type, but the lining cells reveal strongly eosinophilic cytoplasm. In addition, there are often numerous goblet cells. The tumor cells express MUC1 and MUC2 inconsistently (Fig. 1e,f). With fewer than 20 cases reported in the literature to date [2, 20, 34, 35, 37, 38, 42], the clinical and pathological behavior of this type is still unclear. Most of the cases (94%) were diagnosed as carcinoma, some of them with an invasive component or even distant metastases [37]. As the follow-up in this patient group is very short, no relevant data are available yet on survival and outcome.
The gastric type of IPMN exhibits papillary projections lined by epithelial cells resembling gastric foveolar cells and shows pyloric gland-like structures at the base of the papillae. These cells express MUC5 (Fig. 1g,h), while MUC1, MUC2, or CDX2 positivity is only occasionally observed. The gastric type of IPMN corresponds to the branch duct type, which occurs in the periphery of the pancreatic parenchyma, most often in the uncinate process, where it usually presents as a multicystic lesion with cysts no larger than 3 cm [9]. The gastric type seems to be less aggressive, i.e., less invasive, than the other IPMN subtypes [10, 25, 33, 46] but may show severe cellular atypia in a few cases (up to 25%) [46] (Table 3, Fig. 2) The size of the lesion was unrelated to the grade of cellular atypia [46].
Fig. 2IPMN of the gastric type showing severe cellular atypia and MUC5 positivity
Interestingly, pancreatic intraepithelial neoplasia (PanIN)-like complexes are frequently observed next to gastric type IPMNs. This raises the question whether IPMNs of the gastric type are a focal accentuation of a diffuse disease rather than a localized lesion. They might therefore also be related to the small peripheral cystic changes described by Kimura et al. [21] in non-neoplastic pancreata or the patchy lobular fibrosis associated with PanIN-1B lesions described by Detlefsen et al. [14] (Fig. 3). If this were the case, IPMNs of the gastric type would actually be large PanIN-1 lesions. An argument for this assumption is that both IPMNs of the gastric type and PanIN-1 lesions stain for MUC5 in the absence of MUC1 and MUC2 positivity. This assumption would also explain why it is difficult to distinguish PanIN lesions from some IPMNs [27] (Fig. 4), despite a consensus definition of both lesions [19].
Fig. 3PanIN-1 lesion associated with lobular fibrosisFig. 4Small multicystic duct-associated lesion in the periphery of pancreatic tissue suggestive of an IPMN of the gastric type but difficult to distinguish from a large PanIN-1 lesion
Although the malignant potential of IPMNs of the gastric type seems to be rather low, it has to be pointed out that the fibrocystic changes that have been described in pancreata removed from patients with a strong family history of pancreatic cancer [11, 30] are similar, if not identical, to IPMNs of the gastric type and their associated PanIN lesions. This implies that IPMNs of the gastric type/PanIN-1 lesions are not innocuous lesions but have a malignant potential.
Summary and perspectives
The significance of IPMNs among the pancreatic tumors has increased greatly in recent years because of their improved recognition, both clinically and histopathologically and their much better prognosis than ordinary ductal adenocarcinomas. Moreover, they appear to fall into four subtypes that have special biological properties with prognostic implications. Of particular interest in relation to the development of ductal adenocarcinomas is the fact that the so-called gastric type IPMNs seems to occur in pancreata from patients with a strong family history of pancreatic cancer. Furthermore, it is of interest that the pancreatic IPMNs have their counterparts in IPMNs of the biliary duct system, where the same subtypes may occur [1, 23, 51, 52]. The treatment of choice is resection, but future trials may reveal that the extent of resection could depend on the IPMN subtype.

pancreas
outcome
intraductal papillary mucinous neoplasm


A 15-year-old girl with a large pericardial effusion

Pericarditis is a rare manifestation of tuberculosis and can be fatal. We describe a 15-year-old girl admitted for a large pericardial effusion. Subxiphoid pericardial biopsy was performed. Biopsy samples were positive for M. tuberculosis DNA by PCR, which confirmed the diagnosis of tuberculous pericarditis.
A 15-year-old girl was admitted with chest pain, progressive shortness of breath, fever, nonproductive cough, decreased appetite, weight loss, and fatigue. The patient was born in Angola, but had lived in the Netherlands for 14 years. Seven months before admission she had traveled to the Democratic Republic of Congo in Western Africa.
Her temperature was 39.7°C, her pulse 90 beats/min, respiratory rate 28 breaths/min, and blood pressure 96/58 mmHg. No enlarged lymph nodes were found. Soft cardiac tones and a friction rub were noticed. The liver was enlarged.
Laboratory results showed normal white blood cells and platelets with a decreased hemoglobin (4.3 mmol/l). The erythrocyte sedimentation rate was 60 mm/h.
A chest radiograph showed marked enlargement of the cardiac silhouette with no other abnormalities. Echocardiography revealed a large pericardial effusion containing exudative debris and fibrin strands (Fig. 1). Extensive laboratory studies for auto-immune diseases and infections, including HIV, did not reveal the cause.
Fig. 1Echocardiography showing a large pericardial effusion with exudative debris and fibrin strands. RV right ventricle, LV left ventricle, LA left atrium, PE pericardial effusion
Under general anesthesia the pericardial fluid was drained and a subxiphoid pericardial biopsy was performed. The PCR for M. tuberculosis DNA was positive on the pericardium, though not in the pericardial fluid. The patient was treated with four anti-tuberculous drugs (isoniazide, ethambutol, pyrazinamide, rifampicin) for 4 months and two anti-tuberculous drugs for an additional 4 months. Adjunctive treatment with predinisolone was tapered over a 12-week period. The patient completely recovered and did not develop any signs of constrictive pericarditis. She was followed up for more than 1 year and then discharged because of uneventful recovery.
Discussion
Pericarditis is a rare manifestation of tuberculosis that can be fatal and accounts for approximately 1–2% of all cases of tuberculosis [6]. Children in particular are at high risk of the development of extra-pulmonary disease [5]. Clinical manifestations of tuberculous pericarditis are nonspecific and cardiopulmonary complaints usually develop later. Accumulation of pericardial fluid may compromise venous return, leading to cardiac failure.
Echocardiography plays a major role in confirming the presence of a pericardial effusion. In addition, several echocardiographic abnormalities including pericardial thickening, exudative coating and strands crossing the pericardial space are suggestive of tuberculous pericarditis. Thickened pericardium and fibrin strands are highly specific (94% and 88% respectively), and exudative coating has a high sensitivity (100%) in tuberculous pericarditis [4].
The diagnosis is confirmed with detection of Mycobacterium tuberculosis in either pericardial fluid or pericardial tissue. Pericardial fluid aspiration, however, has low diagnostic yield, both for PCR and culture, whereas pericardial biopsy provides the best chance of definitive diagnosis [2, 6]. A positive tuberculin skin test may increase the suspicion of tuberculous pericarditis, but a negative skin test does not exclude the diagnosis. A tuberculin skin test was not performed in this case because the girl had been immunized with BCG. There was no history of any family members being diagnosed with TBC.
The spread of tuberculosis to the pericardium, resulting in an effusion, occurs most often from the mediastinal lymph glands. However, pericarditis may also represent reactivation of disease in the absence of an apparent primary focus of infection [3].
Current recommendations for treatment of tuberculous pericarditis include an initial four-drug regimen for a period of 8 weeks with a subsequent continuation phase of treatment for 4 months when the isolate is drug-susceptible [1]. Controversy exists with respect to the use of corticosteroids for tuberculous pericarditis. The American Thoracic Society’s consensus statement on tuberculosis recommends adjunctive therapy with corticosteroids (1 mg/kg of prednisolone with tapering over 11 weeks) for tuberculous pericarditis [1].

pericarditis
tuberculosis
corticosteroids
subxiphoidal biopsy


The primary headaches: genetics, epigenetics and a behavioural genetic model

The primary headaches, migraine with (MA) and without aura (MO) and cluster headache, all carry a substantial genetic liability. Familial hemiplegic migraine (FHM), an autosomal dominant mendelian disorder classified as a subtype of MA, is due to mutations in genes encoding neural channel subunits. MA/MO are considered multifactorial genetic disorders, and FHM has been proposed as a model for migraine aetiology. However, a review of the genetic studies suggests that the FHM genes are not involved in the typical migraines and that FHM should be considered as a syndromic migraine rather than a subtype of MA. Adopting the concept of syndromic migraine could be useful in understanding migraine pathogenesis. We hypothesise that epigenetic mechanisms play an important role in headache pathogenesis. A behavioural model is proposed, whereby the primary headaches are construed as behaviours, not symptoms, evolutionarily conserved for their adaptive value and engendered out of a genetic repertoire by a network of pattern generators present in the brain and signalling homeostatic imbalance. This behavioural model could be incorporated into migraine genetic research.
Introduction
The genetics of the primary headaches scored recent scientific successes due to the unravelling of the genetics of FHM. Deciphering of the patho-physiological mechanisms of these common diseases promises to bring the much needed knowledge for pharmacological treatments and therapeutic interventions. There are however also problems and controversies, some not solved by the genetic studies performed to date. The following is a brief subjective review of the available evidence, suggesting a role for epigenetic mechanisms and ending with the proposal of a behavioural model of the primary headaches possibly useful for the genetic studies.
Primary and secondary headaches: symptoms, syndromes or diseases? Idiopathic and syndromic migraines
Headaches/migraines are plagued by problems of definition: these terms describe symptoms (a feature which indicates a condition of disease, in particular one apparent to the patient, CED 2003), and at the same time, distinctive syndromes (a group of symptoms which consistently occur together) [1] or diseases (a disorder of structure or function in a human, animal, or plant, especially one that produces specific symptoms) [1] with recognisable diagnostic features, internationally defined [2]. The problems encountered with definitions become evident when dealing with primary or secondary headaches, and when considering idiopathic and syndromic migraines. Secondary headaches are those in which attacks occur due to a recognisable cause or disease, which itself represents the primary cause of the attacks. Syndromic migraines, contrasted with the idiopathic ones, are those in which attacks of migraine, clinically barely or not distinguishable from those occurring in the primary migraines, occur compounded with involvement of other systems. Syndromic migraines are often genetically determined. The concept of “syndromic,” potentially useful in the exploration of headache pathogenesis, has been applied to conditions such as deafness, visual loss and epilepsy, but has no place in the HCS classification that classifies headache attacks and not diseases, albeit distinguishing between primary and secondary headaches. These considerations may apply to the genetics of the primary headaches, since by adopting the HCS (2004), we consider symptoms, not diseases (much as if, studying the genetics of diabetes mellitus, we adopted a classification of the hyperglycemias).
Genetic epidemiology of the typical migraines
The typical primary migraines (MO and MA) all have a substantial risk of familial recurrence. When estimating the population relative risk of migraine in specified groups of relatives (i.e. the ratio between the probability that a relative versus a random member of the population is affected), first-degree relatives of migraine without aura probands have 1.9 times the risk of MO and 1.4 times the risk of MA, whereas first-degree relatives of MA probands have nearly four times the risk of MA and no increased risk of MO [3]. Since a family aggregation is implied when the risk ratio exceeds one, this confirms the familial liability for the migraines, even though familiarity is not yet heredity. A further analysis showed however that spouses of MO probands have 1.4 times the risk of MO, and spouses of MA probands have no increased risk of MA [3], thus backing a hereditary liability for MO and especially MA. Twin studies concur with this increased familial liability. Concordance rates for migraine are consistently higher among monozygotic (MZ) than dizygotic (DZ) twins. In particular, heritability estimates were around 52% in female twin pairs raised together or apart since infancy. In MZ Danish twin pairs, liability to MO resulted from additive genetic effects (61%) and from individual-specific environmental effects (39%), while in MA, correlation in liability was 0.68 in MZ and 0.22 in DZ, with heritability estimated at 0.65. Therefore, twin studies reveal that approximately one-half of the variation in migraine is attributable to additive genes, while the remainder is caused by unshared rather than shared environmental factors between twins [4, 5]. Several studies have analysed pedigrees with migraine, segregation analysis being performed to discover the genetic transmission pattern. Studies at first envisioned migraine as a simple mendelian disorder, inherited according to monogenic rules of transmission. Various modes of inheritance, autosomal dominant with female preponderance, possibly sex determined; autosomal recessive with 70% penetrance; polygenic; maternal and X-linked transmissions have been proposed, or rejected [6, 7]. Finally, based on complex segregation analysis, a multifactorial inheritance was considered the most likely pattern even in high-risk families with MA [8]. A single gene was considered unlikely, but, notably, in some families, a mendelian or mitochondrial inheritance could not be excluded [3]. Currently, migraine is widely considered a complex disease with multifactorial inheritance. This type of inheritance applies to many complex/quantitative traits, i.e. traits that vary continuously in a phenotypic range, and in which variation is quantitative, not qualitative. Examples of quantitative traits are height, body weight, etc. Such traits are influenced by multiple genes (each a quantitative trait locus QTL), each having a small quantitative effect and interacting with the environment. However, there is still no unequivocal evidence that migraine as a quantitative trait varies continuously in the general population, and moreover, genetic variation underlying a continuous character distribution can result from segregation at a single locus too. Therefore, considering migraine as a quantitative trait may still be unwarranted.
The primary headaches also display considerable comorbidity, rarely incorporated into genetic studies. MA is comorbid with hypomania, depression and anxiety, and MO with phobia, panic and major depression. Other comorbidities are stroke, dyslipoproteinemias, essential tremor, paroxysmal dyskinesia and epilepsy. Merikangas et al. in a longitudinal genetic epidemiology study found that migraine was associated with mood disorders and drew attention to the fact that age at onset of anxiety disorders preceded, while onset of affective disorders followed that of migraine, findings consistent with a syndromic relationship between migraine and anxiety/depression [9].
These findings have been replicated, maternal depression being significantly associated with development of migraine in children [10]. Asthma, rhynitis and allergic bronchitis are also important comorbidities recurring in migraine families [11–13]. These comorbid clinical features should be properly incorporated in the genetic studies of the primary headaches.
Mendelian migraines? The genetics of FHM and their putative relationship with the typical migraines MA/MO
Migraines may be multifactorial, but mendelian migraines, i.e., migraines that conform to a mendelian type of genetic transmission, do exist. FHM is classified as a subtype of migraine with aura in the HCS (2004), and it conforms to an autosomal dominant pattern of hereditary transmission. Joutel et al. mapped FHM to chromosome 19, and in 1996 the first FHM gene, CACNL1A4, later termed CACNA1A, encoding the alpha1A subunit of the P/Q neural calcium channel, was discovered, accounting for both FHM 1 and episodic ataxia type 2 (EA2) phenotypes [14, 15]. Spinocerebellar atrophy type 6 (SCA6) was added to the FHM and EA2 phenotypes in 1997 [16]. Thus, FHM 1, EA2 and SCA6 are all allelic channelopathies, with missense mutations mostly accounting for FHM, mutations disrupting the reading frame for EA2 and polyglutamine expansions in the COOH gene terminal for SCA6. The phenotypic spectrum of the CACNA1A mutations was at first believed to consist either of pure FHM or of FHM associated with cerebellar atrophy. Why some mutations originate pure FHM while others elicit progressive or intermittent cerebellar features remains unclear [17]. Ictal coma after trivial trauma and essential tremor were associated clinical features in families harbouring particular CACNA1A mutations. The phenotypic spectrum of the CACNA1A mutations has further expanded to include ataxia induced by fever or high temperature [18], childhood epilepsy [19,20] and status epilepticus [21], paroxysmal paranoid psychosis with anxiety [22], benign paroxysmal torticollis of infancy, considered a migraine equivalent [23], and even myasthenic syndrome [24], since CACNA1A is also expressed on presynaptic neuromuscular junction terminals where it modulates transmitter release [25] even in the absence of any morphological changes in the junction or muscle weakness [26].
The paroxysmal clinical features of migraine, ataxia and epilepsy, together with the consideration that CACNA1A specifies for a calcium channel and that in the tottering and leaner mouse with epilepsy and ataxia, similar mutations are found in the mouse homologue of the calcium channel alpha1A subunit gene, led to the proposal that migraine be considered a calcium channelopathy [27]. The concept of migraine as a brain channelopathy fits well with the phenomenon of spreading depression [28], implicated in migraine attack pathophysiology. It is now accepted by the scientific community as an explicative model for migraine. However, the available genetic evidence is controversial or negative (see below).
FHM was soon proved to be genetically heterogeneous, some families linking to chromosome 1 [29,30], and a second gene, ATP1A2, encoding the alpha2 subunit of the Na/K ATPase, was discovered in Italian families and accounting for a phenotype of pure FHM (FHM 2) [31]. New mutations were found in FHM 2 pedigrees [32], and soon the phenotypic spectrum of FHM 2, initially thought to be confined to pure FHM, broadened to include such features as coma, triggered by minor head trauma and angiography [33], recurrent comas [34] and epilepsy, namely benign familial infantile febrile convulsions [35]. Finally, cerebellar ataxia associated with epilepsy and mental retardation was described in an Italian FHM 2 family [36,37], findings later confirmed by Spadaro et al. and Vanmolkot et al. in other families [38, 39]. Phenotypes of alternating hemiplegia of childhood [40–42] and basilar migraine [43] described with ATP1A2 mutations further enlarged the clinical spectrum of FHM 2. Variability within the same family is notable, with FHM, cerebellar ataxia, recurrent paroxysmal dystonia and mental retardation all recurring together [42].
Lastly, mutations in the neuronal voltage-gated sodium channel SCN1A were reported by Dichgans et al. [44] to account for a phenotype of pure FHM (FHM 3), and there are still FHM families without mutations in any of the previously described genes, implying further genetic heterogeneity. Sporadic patients with HM, more common in clinical practice, also present problems, since mutations in the known FHM genes are only rarely encountered in this population [45].
An important corollary of the genetic discoveries obtained in the FHM was the proposal to consider FHM as a model for the typical migraines MO and MA [27]. This spurred the search for the involvement of FHM genes in MO/MA. Up to now the effort has been largely unrewarding. This in our opinion is also due to the misclassification of FHM as a subtype of MA [2], whereas FHM represents a syndromic migraine (see below). Some evidence in favour of linkage of typical migraines to the FHM locus on chromosome 19 was initially offered by May et al. [46], Nyholt et al. [47] and Terwindt et al. [48]. However, early negative studies [49–51] were later substantiated by systematic screening investigations of the CACNA1A in families with MO and/or MA [52–55], and to date, mutations in CACNA1A have never been demonstrated in kindreds without hemiplegic migraine, with or without aura. The same negative considerations apply to ATP1A2. Earlier evidence in favour of a role of the Chrlq3l locus or ATP1A2 gene in the typical migraines [56, 57] was superseded by negative findings and absent ATP1A2 mutations in typical migraine only pedigrees, even those displaying an apparently autosomal dominant mode of inheritance [58–61]. The FHM 3 SCN1A gene was discovered too recently for any conclusive study. Von Brevern et al. [62] however failed to find any CACNA1A, ATP1A2 or SCN1A mutations in patients with migrainous vertigo. Thus, there is no current evidence that the genes causing FHM represent major susceptibility loci for the typical migraines.
Does such negative genetic evidence imply that FHM is not a useful model for migraine etiology? Several reviews of migraine pathogenesis apply the FHM model of neural channelopathy to the typical migraines. While such models are not justified genetically, it may be contended that FHM is nonetheless helpful in elucidating the pathophysiology of the migraine attacks. This consideration however is likely to apply to several clinical conditions all characterised by headache attacks of the migraine type. Migraine-like attacks indeed are found not only in the typical migraines, but also in other conditions, diseases or syndromes, in which they occur together with symptoms and signs of multisystem nervous or extra-nervous involvement. These “syndromic migraines” thus display bona fide migraine headache attacks at some times in their clinical course, and most of them have a genetic basis (Table 1). FHM is also characterised by multisystem neurologic involvement (migraine, hemiplegia, ictal recurrent comas, cerebellar atrophy, mental retardation, epilepsy, movement disorders, myasthenic syndrome, etc.), and therefore we make a plea for FHM to be considered more appropriately as a syndromic migraine and not a subtype of MA, as with the current HCS classification (2004).
Table 1A list of proposed (and provisional) syndromic migrainesSyndromic migrainesGenes (chromosome) involvedMigrainous features (references)MELAS (mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes)MTTL1, MTTQ, MTTH, MTTK, MTTS1, MTND1, MTND5, MTND6, and MTTS2 (mtDNA)Most frequent symptom: episodic sudden headache with vomiting and convulsions [63, 64]CADASIL (cerebral arteriopathy, autosomal dominant, with subcortical infarcts and leukoencephalopathy)NOTCH 3 (19p13.2–p13.1)MA in 22% [65]; migraine in 38% [66]HERNS (retinopathy, vascular, with cerebral and renal involvement and Raynaud and migraine phenomena)TREX1 (3p21.3–p21.2)Migraine in 70% [67]CCM (familial cerebral cavernous malformations)KRYT 1 (7q11.2–q21)Convulsions and migraine attacks [68, 69]
Linkage and association studies in the typical migraines
Several studies on the genetics of the typical migraines MO and MA applied genetic association, linkage and genome wide scanning methods. Most of these studies resulted in findings that either lack verification or are controversial. For MA, a genome wide scan on 50 multigenerational families in Finland identified a susceptibility locus on chromosome 4q24 [70]. Other loci for MA have been reported on chromosome 11q24 in Canadian families with an autosomal dominant transmission pattern [71], and on chromosome 15q11–q13 to a genomic region containing genes encoding for GABA-A receptors in ten Italian families again displaying an autosomal dominant transmission pattern [72].
For MO, or for pedigrees with MO mixed with MA, susceptibility loci have been reported on chromosome 6p12.2–p21.1 in Sweden [73], chromosome 5q21 [74], chromosome 14q21.2–q22.3 in an Italian family with MO [75], chromosome Xq24–28 in two large Australian pedigrees [76] and chromosome 19p13.3/2 to the insulin receptor gene INSR [77]. While many of such findings have still to be replicated, in some cases (the INSR gene) sequence studies have given negative results [78].
Other studies have examined candidate genes, implying that a pathogenetic (and a priori) hypothesis was formulated beforehand. This may be risky, considering that the pathogenesis of the migraine headaches is still imperfectly understood. Candidate genes explored were the mitochondrial DNA (mtDNA), or genes involved in prothrombotic or cardiovascular disease, or in the metabolism of biologic amines such as dopamine or serotonin, or in a variety of other metabolic systems. Several of the studies applied to mtDNA genes have yielded negative results, even though in some families migraine was reported to segregate with the Leber mtDNA 14484 mutation [79], and mtDNA mutations and haplotypes (haplotype U) have been associated with juvenile migraine stroke [80, 81] and with cyclic vomiting, considered a migraine equivalent in the pediatric population [82–84]. Contrasting results for genes involved in prothrombotic/cardiovascular risk, and for those involved in the metabolism of the biological amines serotonin and dopamine, or in several other metabolic pathways are summarised in Tables 2, 3, 4, and 5.
Table 2Prothrombotic and cardiovascular risk genes and typical migraine geneticsProthrombotic/vascular risk genes or mutations examinedPhenotypesLDL receptor (19p13.2)Associated with MO [87]; not associated [88]Factor V R/Q 506 (Leiden mutation)Associated with MA [89]Not associated with migraine stroke [90]; not associated with MA/MO [91]; not associated with juvenile MA [92]Factor II 20210 G/ANot associated with MA/MO [91]Not associated with migraine stroke [93]Factor XIII Val 34 LeuNot associated with migraine [94]Decanucleotide insertion/deletion factor VII promoterNot associated with MA/MO [91]Alloantigenic platelet systems HPA-1 and HPA-2Not associated with MA/MO [91]Deficit of protein SAssociated with MA [89]Angiotensin converting enzyme (ACE)Allele D associated with MO and more frequent migraine attacks [95]Endothelial NO synthase inducible (NOS3; iNOS)Not associated with migraine [96, 97]Endothelin receptor A (ETA-231 A/G) polymorphismAllele G protecting from migraine [98]MTHFR (methylene-tetra-hydrofolate reductase) C677T/A1298CHomozygous mutation associated with MA [99], associated with MA [100]; risk for MA, modulated by thymidilate synthase gene [101]Table 3Serotonin metabolism genes and typical migraine geneticsSerotonin metabolism genes examined Phenotypes5-HTSERT (17q11.2–12) Allelic association with MO (increase of allele STin2.12 + decrease of allele STin2.10) and MA (same + increase of allele Stin2.9) [102]; 5HT-TLPR with MA [103]Allelic association with migraine (allele Stin2.10) [104]; borderline association with migraine [105]No association/linkage with migraine [106, 107]5-HT2A (13q14–21)Allelic (allele C) association with migraine aura [108]No association with migraine [105, 106, 109, 110]5-HT1B (6q13)No association with migraine [106, 110, 111]5-HT1D (1p36.3–34.3)No association with migraine [106, 110, 111]5-HT2B (2q36.3–q37.1)No association with migraine [106, 110, 111]5-HT2C (Xq22–25)No association with migraine [106, 110, 111]5-HT1B (6q13)No association with therapeutic response to triptans [112, 113]5-HT1F (3p12)No association with therapeutic response to triptans [112, 113]Table 4Dopamine metabolism genes and typical migraine geneticsGenes examinedPhenotypesDopamine receptor 2 (DRD2)Allelic association (allele NcoI) with MA comorbid with anxiety/depression [114]Allelic association (allele 1) with yawning/nausea during attack of MO [115]No allelic association (allele NcoI) with MA [116]No allelic association with MO/MA [107, 117, 118, 119]Dopamine receptors 1, 3, 4, 5 (DRD1, DRD3, DRD4, DRD5)No allelic association with migraine [115, 117, 120]Dopamine transporter (DAT)Association with chronic daily headache with drug abuse [86]COMT; MAO-A No association with migraine [117, 121]Dopamine-betahydroxylase (DBH)Association with migraine [107], especially males with MA [122]No association [123]Table 5Other genes implicated in typical migraine geneticsGenes examinedPhenotypesAndrogen/progesterone receptorsAndrogen receptor not associated; progesterone receptor associated with migraine [124]K channel KCNN3Allelic association (CAG repeats) with MO/MA [125]Not associated (CAG repeats) [126]Cytotoxic T lymphocyte antigen 4 (CTLA-4) Not associated with migraine [127]HLA-DRB1Allelic association with MA [128]
Finally, a few studies have focused on the genetics of the chronic headaches, a major social problem, since these chronic headaches are often associated with drug abuse and afflict a remarkable percentage of the general population. Chronic tension-type headache displays a substantial familial recurrence, with lifetime relative risk estimated at 3.87 for parents and 3.53 for children of probands; the risk is greater for females (3.35) than for males (2.59) [85]. A genetic association study of chronic headache with drug abuse versus the dopamine metabolism genes by Cevoli et al. [86] found that allele 4 of the exon III VNTR polymorphism of the dopamine receptor 4 gene DRD4 was associated with chronic daily headache, and allele 9 of the dopamine transporter gene SLC6A3 was more common in chronic daily headache associated with drug abuse than in episodic migraine.
Genetics of tension-type headache
Remarkably, apart from an epidemiological genetic study that demonstrated a familial aggregation for chronic tension-type headache [85], there are no other genetic studies of this common disorder.
Genetics of cluster headache
Cluster headache (CH) has long been considered a sporadic disease. In recent decades, however, a familial recurrence has been appreciated, and the new HCS classification (2004) now states that CH may be transmitted as an autosomal dominant disease in about 5% of cases. Several CH cases have been reported among monozygotic twins and in family pedigrees [129–137], and family studies indicate that I-degree relatives of CH probands carry a 5- to 18-fold, and II-degree relatives a 1- to 3-fold increased relative risk of the disease [138–141]. CH has been considered a probable autosomal dominant disease with a penetrance of 0.3–0.34 in males and 0.17–0.21 in females [142]. The exact transmission pattern is however still debated [143, 144], and an autosomal recessive pattern has been advocated in certain families [137]. Several candidate genes have been analysed, in particular mtDNA mutations [145–148], HLA antigens [149–151] and CACNA1A polymorphisms [152, 153], usually with negative or controversial results. Other genes, such as the NO synthases NOS1, NOS2A and NOS3 [154], the elusive amine gene cluster [155], the CLOCK gene involved in the regulation of circadian rhythms [156,157] and the hemochromatosis gene [158], have been found not associated with CH. Recently, an association between CH and a polymorphism in the hypocretin receptor 2 gene HCRTR2 was reported by Rainero et al. [159], possibly accounting for the circadian recurrence of the CH attacks. Such an association, while confirmed by Schürks et al. [160], was rejected in a European multicentric study [161]. Recently, reports of CH associated with hemiparesis during the attacks suggested a relationship with FHM and ionic channelopathies [162]. Preliminary genic expression studies instead documented the activation of proinflammatory genes during the CH attack [163].
Genetics and epigenetics
Epigenetics is the study of the changes in DNA and DNA-binding proteins that, albeit altering the structure of chromatin, do not modify the nucleotide sequence of DNA. The remarkable feature here is that some of these modifications may be associated with heritable changes in gene function.
Commonly held concepts of heredity indeed pit environmental influences (nurture) against genetic background (nature) as totally separate causative factors. Genetic advances themselves have however demonstrated that the hereditary transmission of biological changes not encoded in the DNA sequence and dictated by environmental influences is possible. This part of genetics, called epigenetics, has received little or no attention in the genetic studies of the primary headaches. It is the contention of the author however that future epigenetic studies will account for several hereditary features of the primary headaches, in particular their comorbidities.
All those (meiotic and mitotic) modifications in gene expression that are heritable but not encoded in the DNA sequence are defined as epigenetic. Molecular mechanisms implicated include (1) methylation of cytosine residues at C5 in dinucleotide CpG sites (localised especially in promoters of well over 40% of the genes and that, when methylated, cause silencing of the gene); (2) mechanisms of RNA interference, whereby microRNAs silence gene expression; (3) histone (DNA associated proteins) changes: activation or inactivation of genomic regions according to the “histone code”. All of these mechanisms result in the expression or silencing of genes, and underlie such phenomena as inactivation of the X chromosome and genomic imprinting. Several epigenetic diseases are already known that may be inherited through the somatic and the germinal line: fragile X syndrome, in which ATRX gene mutations modify the methylation pattern of ribosomial RNA and, by methylation of CGG expansions in the FMR1 gene, silence the gene; the Angelman and Prader-Willi, and Rett syndromes; also, many colonic cancers and leukemias. Important epigenetic differences that increase with age are found even between monochorial twins [164]. Notably, epigenetic modifications may increase with age and may also be prevented through interventions directed at DNA or histone methylation (with azanucleotides, antisense oligonucleotides, histone deacetylase). Even more remarkably, there is some evidence that lifestyles and even diet may play a role [165].
Epigenetic models for the primary headaches?
There is consistent evidence that behavioural differences typical of specific inbred animal strains are the consequence of environmental influences acting especially during development rather than DNA changes. Mice strains with decreased environmental exploration behaviour (B6 strain) develop enhanced exploratory behaviour if nurtured in their first 3 months of life by BALB dams, a strain displaying intense exploratory behaviour; changes in behaviour appear to be linked to the type of maternal care, particularly licking of the pup by the mother, a behaviour demonstrated to affect the status of the endocrine stress system in mice [166]. Weaver et al. [167] showed how maternal care in the rat (licking and grooming the pup) modifies the methylation pattern of the promoter of the glucocorticoid receptor gene in the hippocampus; such epigenetic changes, evident from the first week of life, persist throughout the animal’s life but are reversible upon treatment with histone deacetylase inhibitors or upon intracerebral administration of methionine (an intervention that modifies the methylation pattern) [168].
Stress plays a remarkable role in the development of the nervous system: removal of rat pups from the mother causes reduced neurogenesis in the adult hippocampus through steroid-dependent mechanisms [169], and alters serotonergic transporter densities and serotonergic 1A receptors in the rat brain [170]. Administration of steroids to the mother before delivery causes changes in behavioural patterns in juvenile rats [171], and maternal deprivation in the immediate post-natal period modifies locomotor and steroid release patterns in the adult rat [172]. Epigenetic mechanisms also seem relevant for the formation of memory traces [173] and more generally for cognitive development [174]. Epigenetic mechanisms have been hypothesised for psychiatric disorders [175, 176] and many complex and multifactorial diseases affecting the brain or the inflammatory and immune systems [177–179].
There are still no studies of epigenetic mechanisms in the primary headaches. When considering, however, the important maternal influence in migraine genetics; the consistent and inherited co-morbidities especially for psychiatric and inflammatory-immune disorders; twin studies documenting that only about half of the variability is due to “genetic” factors; it is possible to envision that epigenetic mechanisms, especially those acting during nervous system development in early infancy and childhood, play a role in the heritability and pathophysiology of the primary headaches. Preliminary studies have already analysed attachment styles in adult migraineurs [180, 181], and a prospective investigation demonstrated correlations between events suffered during pregnancy and early life, and quality of adult life 31–33 years later [182]. It is reasonable to suggest that early life factors and attachment styles between mother and child represent determinants of epigenetic changes relevant in migraine pathogenesis. Such early pre- and post-natal environmental behavioural factors could be usefully analysed to define endophenotypes of adaptive behaviour useful in the genetic studies of the primary headaches.
Final comments: a behavioural model of the primary headaches as fight-or-flight response and sickness behaviour to be incorporated into genetic research
Consideration of epigenetic mechanisms may help in analysing behaviours during the headache attacks. Any genetic studies are ultimately dependent upon the definition of the phenomenon taken into consideration, and on how it is conceptualised. Therefore, studies have to rely upon conventional diagnostic criteria, in turn based on a priori interpretations. Most genetic studies have been performed within the frame of migraine interpreted simply as a “pain” trait with multifactorial inheritance. In a “harlequin” model, several genetic factors, each one having a small specific weight, interact with environmental factors to determine the migraine attack. Such a model should however be better tailored to suit phenomena such as the migraine attack and the migraine diseases that are really behavioural “processes” with an intrinsic logic of their own [183], one that is consistent within attacks, within patients and within populations. There is a need to conceive of the primary headaches along more useful scientific lines. Consistently lacking in the genetic studies is for instance any consideration of migraine as a behavioural response to environmental and/or endogenous triggers, a view that has scientific support [184] and that we recently revised to accomodate a Darwinian perspective [185]. According to our view, migraine and other primary headaches such as CH are behaviours, not symptoms, evolutionarily conserved for their adaptive value and engendered out of a genetic repertoire by networks of pattern generators present in the brain. These neural networks serve the homeostasis of the brain, with migraine pain considered a kind of visceral pain signalling homeostatic imbalance. The behavioural repertoire enacted during the migraine attack, complete with its full panoply of pain, cognitive, autonomic, motor, etc., symptoms and signs, is comparable to that defined as sickness behaviour and already known to develop in all mammals and other animals following challenge with infective and other pathogenic agents [186]. In contrast, behaviour during the CH attacks [187] resembles the fight-or-flight response of hypothalamic animals. These behaviours during the headache attacks really represent “healing” processes, and migraine may even be evolutionarily advantageous [188]. Thus, what is relevant in this new behavioural model is not the manifestations of the attack, but the factors triggering it, that, migraine being of the brain, must relate to still unknown disturbances of brain homeostasis [185]. Accordingly, it is these triggering factors rather than the manifestations during the attacks that may represent the features most relevant for a true dissection of the genetics of the primary headaches.

genetics
epigenetics
migraine
cluster headache
tension-type headache