{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T16:54:30Z","timestamp":1788195270160,"version":"build-2803163510"},"reference-count":57,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[1999,3,1]],"date-time":"1999-03-01T00:00:00Z","timestamp":920246400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Child Neurol"],"published-print":{"date-parts":[[1999,3]]},"abstract":"<jats:p>A large body of evidence suggests that genetic factors influence liability to many common neurodevelopmental disorders. Examples include Tourette syndrome, attention-deficit hyperactivity disorder, autism, and dyslexia. Characterization of the genetic component of susceptibility to these conditions at a molecular level should improve classification, elucidate fundamental neurobiologic mechanisms of disease, and suggest novel approaches to treatment. Susceptibility loci for complex traits could be identified by detecting linkage to a well-mapped genetic marker or by detecting association with a putative high-risk allele at a candidate locus. This article reviews the principles underlying these complementary approaches, and notes recent progress in specific conditions. As the molecular epidemiology of susceptibility to common neurodevelopmental disorders emerges, it might be increasingly possible to identify \"high-risk\" and \"low-risk\" genotypes. Clinicians should understand the nature of this kind of information in order to appreciate its power as well as its limitations. 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