Prevalence of Sanfilippo Syndrome Across Countries

Sanfilippo syndrome’s prevalence — the estimate of how common a disease is in a specific population — varies between geographic areas around the world. There also is variation between the different subtypes of the disease across geographic locations.

The following gives information about various Sanfilippo prevalence rates, as well as some of the possible reasons for the differences across the globe.

Prevalence across the globe

The prevalence of Sanfilippo syndrome is estimated to be between 1 in 50,000 and 1 in 250,000 people worldwide. Numerous studies have investigated how common Sanfilippo is in different populations of the world.

Some countries where Sanfilippo syndrome is most prevalent include Oman (2.35:100,000 population), Saudi Arabia (2:100,000), and the Netherlands (1.89:100,000). Countries with the lowest prevalence are Colombia (0.17:100,000), Norway (0.27:100,000), and Taiwan (0.39:100,000). Some studies gave conflicting results, however. For example, one study estimated Great Britain to have a prevalence of 0.36:100,000 while another estimated the number as being three times higher, at 1.21:100,000 people.

Prevalence of different subtypes

There seems to be wide variability between the most common subtype of Sanfilippo syndrome within a given region as well. The two most common forms of the disease are Sanfilippo type A, which has an estimated prevalence of 1:100,000, and type B, with its estimated occurrence rate of 1:200,000. Meanwhile, type C has an estimated occurrence rate of 1:1,500,000, while type D is slightly more common at 1:1,000,000.

Sanfilippo type A is the most common type in northern and eastern European countries. In southern European countries, Type B is the most prevalent form. Among people from Turkey or Italy, meanwhile, Sanfilippo type D is more common.

Possible reasons for geographic variability

Founder effect

Geographic location can play an important role in genetic diversity due to the founder effect — a situation in which a small population of people starts a new civilization in an isolated area, such as an island, resulting in genetic similarities in the descendants. If one of the founding members of the new group had a genetic mutation, then it is possible that many future inhabitants of that civilization also may have that same or a similar mutation.

The founder effect may be involved in the Cayman Islands, where between 1/7 and 1/10 of people in the West Bay district of Grand Cayman are carriers of Sanfilippo type A — meaning they carried one copy of the mutated gene but were not affected by the disease. Genetic testing of 77 family members of a child with Sanfilippo type A revealed that all of the carriers of the disease had the same mutation, called R245H.

A study of five patients with Sanfilippo type B in Japan revealed another possible example of the founder effect. All five people had the same mutation, called R565P, and had parents who came from the Okinawa islands but were not related in an obvious manner. A previous study found three patients from two different families in the Okinawa islands who also had the R565P mutation. This further supports the idea that there may be a common distant relative who caused a founder effect.

Founder effects also might be responsible for other geographically specific mutations. These include a high frequency of 1091delC mutations in Spain, a prevalence of R245H mutations in German and Dutch populations, and documented R456H mutations in Australian populations.

Poor estimation from low study numbers

Sanfilippo overall is a rare disease and some of its subtypes are exceptionally rare, such as type C and D. Because of this, many of the studies done to estimate the prevalence of the disease only have a very small number of patients. That can lead to variability. The populations of countries also vary considerably, which can cause differences in prevalence as well.

Variability in testing

In addition, some variability between countries may occur due to differences in access to healthcare and testing, and physician knowledge of the disease. All of these factors could lead to misdiagnoses or a lack of diagnosis, which would affect the reported prevalence.

Last updated: Nov. 24, 2020

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