At this time, research is suggesting that some genes are risk factors for what have until now been regarded as unrelated syndromes. Most patients with psychiatric disease may have many attributable causes; in that case, common disease process-based descriptions
will need to be developed, just as in the case of SIVD. Conclusion I have used two conditions to suggest a potential new taxonomy for depression. The one striking Inhibitors,research,lifescience,medical aspect of defining it on this basis is dropping the word “comorbidity” in this context. When we classify using a non-nominalist approach, the basic terminology is altered. Common co-occurrence of disorders gives us clues that could be helpful in looking for antecedents, and at the same time tell us that perhaps our current method is blinding our vision. As we open our eyes and look at emerging data in a nonbiased light, other conditions Inhibitors,research,lifescience,medical will emerge that could be useful in conveying information and treating patients. One cautionary note is the danger of overinterpreting genetic information.
As potential genes at risk for one or more depressive disorders are identified and developed, defining the level of harm attributable to the gene is important, because any behavior associated with a genetic abnormality is in danger of being construed as disease-associated. This can overemphasize the genetic contribution of any one gene to disease etiology, Inhibitors,research,lifescience,medical and may lexicalize behavior Inhibitors,research,lifescience,medical patterns with unfortunate consequences. Patients with a genetic variation who are at minimal or no increased risk for adverse consequences should not be labeled as diseased. If the definition of disease is based solely on a genetic abnormality rather than on a clear specification of the risk, the label may harm the patient.
and structural neuroimaging studies have assumed Inhibitors,research,lifescience,medical a unique position in defining the neuroanatomy of depression. Studies of cerebral blood flow and glucose metabolism with positron emission tomography (PET) scans in primary depression and depression associated with brain lesions have consistently isothipendyl revealed that major depressive disorder is a system-level disorder.1,2 Resting state studies The majority of neuroimaging studies assessing resting state neural response have involved ventral and dorsal prefrontal cortex, anterior cingulate, basal ganglia, amygdala, and hippocampal regions in depression. The bestrcplicatcd behavioral correlate of a resting state abnormality in depression is that of an inverse relationship between prefrontal activity and depression severity.3 Changes in specific neural networks have also been associated with symptomatic dimensions of depression. Dimensions of depression can be categorized into behavioral subsystems – mood and Dasatinib chemical structure affect, circadian-somatic, cognitive, and motor – where mechanisms mediating variations within a normal behavior domain might, be more easily evaluated.