Fetal Valproate syndrome

Fetal Valproate Syndrome OMIM #609442
* This composite image of Fetal Valproate syndrome was created to help geneticists get a better analysis

What is Fetal Valproate Syndrome?

Fetal Valproate Syndrome is a condition that can develop when an unborn baby is exposed to valproic acid or sodium valproate in the first trimester. Sodium valproate is used as a common medication for epilepsy, migraine, and bipolar disorder. Not all babies exposed are affected by the syndrome, but exposure increases the risk.

Exposure to sodium valproate in utero increases the risk of an exposed fetus being born with congenital defects. These can include skull, facial, and skeletal abnormalities.

This syndrome is also known as:
Fetal Valproate Syndrome; FVS

What gene change causes Fetal Valproate syndrome?

The syndrome is not caused by gene changes, it is caused by exposure to valproic acid or sodium valproate in the first trimester.

Environmental causes, or exposure to external environmental factors, can sometimes contribute to the cause of a rare disease.

What are the main symptoms of Fetal Valproate syndrome?

The main symptoms of the syndrome include neural tube defects- the most common being spina bifida in which the bones of the spine do not close properly. Babies exposed to sodium valproate have a 20% higher chance of developing fetal valproate syndrome.

Other symptoms include heart defects and musculoskeletal abnormalities. Developmental delay and other behavioral disorders, such as ADD and Autism Spectrum Disorder are also linked to the syndrome.

Babies are also at risk for being born with a cleft lip and palate, a small head, underdeveloped nails, a club foot, and softening of the windpipe.

How is it diagnosed?

To find out if someone has a diagnosis of Fetal Valproate syndrome, it is important to have a consultation and evaluation with a clinical genetic specialist.  Specialists may also suggest specific genetic testing or other types of tests to help reach a diagnosis.  FDNA’s AI technology can help speed up the diagnostic process by analyzing facial features and other health information.

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