Home Random Page


CATEGORIES:

BiologyChemistryConstructionCultureEcologyEconomyElectronicsFinanceGeographyHistoryInformaticsLawMathematicsMechanicsMedicineOtherPedagogyPhilosophyPhysicsPolicyPsychologySociologySportTourism






Obsessive compulsive disorder

OCD is characterized by recurrent, intrusive thoughts (obsessions) that cause marked distress and/or by repetitive behaviors (compulsions) which are aimed at preventing or reducing anxiety. Importantly, the obsessions and compulsions are time consuming, or significantly interfere with the person s normal routine, occupational functioning, or social activities (American Psychiatric Association, 1994). The OCD category is heterogeneous in terms of symptoms, because the obsessions and compulsions can be related to many different dimensions (e.g., contamination/cleaning, hoarding/collecting, checking) as listed in the Yale-Brown Obsessive Compulsive Scale (Goodman et al., 1989). The most frequent comorbid diagnoses are other anxiety disorders (e.g., social phobia), mood disorders, tic disorders, and substance abuse (Abramowitz et al., 2009). According to an American survey, the lifetime prevalence of OCD is 1.6%, and the median age of onset is 19, with 25% of the cases starting in adolescence (Kessler et al., 2005). Twin studies indicate the importance of separating childhood-onset OCD, because the observed genetic influence on OCD symptoms is much higher in children (ranging from 45% to 65%) compared to adults (ranging from 27% to 47%) (van Grootheest et al., 2005).

Based on the efficiency of serotonin reuptake inhibitors in the pharmacotherapy of OCD, most candidate gene studies focused on the serotonin transporter linked polymorphic region (5-HTTLPR) and serotonin receptor polymorphisms (see review papers by Grados, 2010 and by Walitza et al., 2010). A meta-analysis of the serotonin transporter gene studies reported that the long 5-HTTLPR allele was associated with childhood-onset OCD (Bloch et al., 2008). In terms of dopaminergic polymorphisms, there are fewer candidate gene studies in the OCD literature, although the high comorbidity with tic disorders and the usefulness of additive antipsychotic treatment in serotonin reuptake inhibitor resistant cases point to the involvement of the dopamine system (Abramowitz et al., 2009). A meta-analysis of the COMT Val158Met polymorphism indicated an association of the Met-allele with OCD in men (OR = 1.88, 95% CI 1.45 2.44) but not in women (Pooley et al., 2007). Recent studies started to utilize dimensional symptom scales or factors in the COMT candidate gene analyses (Lochner et al., 2008; Katerberg et al., 2010), but these results have not been confirmed by independent workgroups. Of the dopamine receptor polymorphisms, only the DRD4 VNTR showed positive associations: The protective effect of the DRD4 4-repeat allele in OCD was indicated by a case-control study (Camarena et al., 2007) and by a family-based study (Walitza et al., 2008); whereas the increased frequency of the DRD4 7-repeat allele was shown in late-onset OCD group (Hemmings et al., 2004), and in a subgroup of OCD patients with comorbid tics (Cruz et al., 1997). The MAOA genetic findings are less consistent (Grados, 2010). Interestingly, both linkage studies and family-based association analyses indicated the glutamate transporter gene (SLC1A1) on chromosome 9p24 in the development of OCD (Grados, 2010), which started pharmacological trials of glutamate antagonist riluzole augmentation in treatment-resistant cases (Abramowitz et al., 2009), showing the possible usefulness of genetic study findings.



Substance abuse

Substance use disorders can be subdivided according to the abuse/dependence state and the type of substance abused. According to the DSM-IV (American Psychiatric Association, 1994), substance abuse is a maladaptive, non-medical use of psychoactive drugs that leads to functional impairments or distress, whereas substance dependence involves tolerance to the effects of the drug and the presence of withdrawal symptoms when the use of the drug is reduced or stopped. In general, drug-seeking and drug-taking behavioral patterns persist despite serious negative consequences. Repeated exposure to addictive substances, such as nicotine, cannabinoids, ethanol, psychostimulants, and opioids can initiate adaptive changes in the central nervous system, causing physical and psychological dependency. The lifetime prevalence of any substance use disorder was 14.6% in an American survey from 2005 with diagnoses starting from late-adolescents (25% of cases at age 18 and 50% of cases at age 20) (Kessler et al., 2005). Epidemiological studies indicate that genetic factors play a significant etiologic role in the development of substance use disorders, estimating a varying (30% to 60%) heritability of heroin addiction and stimulant abuse (Tsuang et al., 1998; Kendler et al., 2003). The heritability is approximately 50 to 60% in alcohol dependence (Gelernter and Kranzler, 2009) and approximately 50% in nicotine dependence (Ho and Tyndale, 2007) and cannabis use disorders (Agrawal and Lynskey, 2009). Neurobiological models emphasize the key role of the reward system in addiction, as the dopaminergic mesolimbic pathway interacts with other stimulatory and inhibitory neurotransmitter systems (Comings and Blum, 2000). Various drugs of abuse act at different points in these systems, but they all lead to an elevated level of dopamine in the nucleus accumbens (Koob and Volkow, 2010). Therefore, genes of the dopaminergic system are logical candidates for association studies of substance use disorders.

Results from the association studies of the dopamine receptor gene variants have been summarized recently and have been supplemented with detailed descriptions of the animal studies that investigated the dopamine models of drug addiction (Le Foll et al., 2009). The most conclusive findings are related to the DRD2 TaqIA polymorphism. Recent meta-analyses of nearly 40 studies confirmed the association of alcoholism with the DRD2 A1-allele, showing a modest but significant effect (OR = 1.22 by Smith et al., 2008 and OR = 1.31 by Le Foll et al., 2009). Additional studies have suggested that the DRD2 A1-alelle is associated not only with alcoholism but also with smoking and other type of substance abuse, as well as with pathological gambling. These behaviors are manifested as part of the aptly named reward deficiency syndrome (Comings and Blum, 2000). A meta-analysis of 29 smoking-related studies did not confirm the DRD2 effect (Munafo et al., 2009), whereas a few studies investigating opiate addiction reported a higher consumption of heroin in DRD2 A1-carriers among different nationalities (Le Foll et al., 2009). Studies investigating multiple SNPs of the DRD2 and surrounding genes in haplotype analyses indicated distinct haplotypes in different ethnic populations at alcohol dependence (Yang et al., 2007; Kraschewski et al., 2009), nicotine dependence (Huang et al., 2009), and heroine dependence (Xu et al., 2004). Therefore, the usefulness of haplotype detection needs to be supported by further studies.

In terms of other D2-like receptor genes, the DRD3 studies resulted in mostly negative findings at alcohol and cocaine dependence, however, two large scale studies showed association of the Ser9Gly (rs6280) SNP with nicotine dependence or heaviness of smoking (reviewed by Le Foll et al., 2009). The DRD4 VNTR findings are also less straightforward. Although the DRD4 long allele was initially associated with alcohol dependence, other studies failed to replicate this finding (Le Foll et al., 2009). According to a recent study in heavy-drinking college students, a significant association between the DRD4 VNTR and alcoholism was found; however, the association was diminished when the novelty seeking personality trait was included in the analysis (Ray et al., 2009). To date, only the intermediate phenotype approach has resulted in a consistent association. The DRD4 long allele carriers were reported to exhibit a greater urge to drink compared to subjects with short (less than 5-repeat) alleles (reviewed by McGeary, 2009). The quantitatively measured phenotypes have also been used for association studies of smoking behavior: The DRD4 7-repeat allele carriers exhibited higher rates of lifetime smoking, higher smoking cue reactivity, and poorer quit rates compared to subjects without the 7-repeat allele, although, negative results have also been reported (McGeary, 2009). The DRD4 7-repeat or long allele has been associated with a more severe smoking phenotype (heavy smoking), that may influence cessation outcome. In terms of the association between the 7-repeat allele and opiate or psychostimulant use, both positive and negative results have been reported (Le Foll et al., 2009); however, the urge phenotype and a higher quantity and frequency of drug use have been repeatedly linked to the DRD4 long allele (McGeary, 2009).

At the D1-like receptor genes, the DRD1 association results have been positive in relation to alcohol dependence, although only three studies were summarized (Le Foll et al., 2009). Interestingly, DRD1 haplotype analyses resulted in positive findings as well: the rs686A-rs4532C haplotype was associated with alcohol dependence (Batel et al., 2008), and the rs265973C-rs265975T-rs686A haplotype formed by the 3′ UTR SNPs was associated with nicotine dependence (Huang et al., 2008). Studies investigating DRD5 polymorphisms are even fewer: only one study resulted in negative findings at nicotine dependence, and one study showed modestly positive association with heroin addiction (Le Foll et al., 2009).

The other frequently studied dopaminergic gene is DAT1, especially among stimulant drug abusers. Recent reviews have not confirmed the association of the DAT1 3′ UTR VNTR with methamphetamine use disorders or with nicotine and alcohol dependence (Ho and Tyndale, 2007; Bousman et al., 2009; van der Zwaluw et al., 2009). One study showed the importance of the intron 8 VNTR in the DAT1 gene among cocaine abusers (Guindalini et al., 2006), but no replication has been published yet. Results from the Mannheim Study of Children at Risk provided evidence for the DAT1 3′ UTR VNTR: nicotine dependence and alcohol abuse was associated with the 10/10 genotype in subjects who started daily smoking and experienced the first alcohol intoxication earlier in life (Schmid et al., 2009). In addition, the intention to quit smoking was lower in adolescents with the DAT1 10/10 genotype (Laucht et al., 2008). However, these findings have not yet been confirmed. There are also interesting observations about nicotine usage among adult ADHD patients. A decreased striatal DAT availability was detected in smoking ADHD subjects, which was similar to the effect of methylphenidate medication (Krause et al., 2003) and supported the self-medication hypothesis for psychiatric patients. The NET gene polymorphisms were less frequently studied. Negative findings were reported in relation to alcohol dependence in European and Chinese populations (Samochowiec et al., 2002; Huang et al., 2008). In terms of stimulant drug use, only one study reported association of acute response to amphetamine with NET genotypes and haplotypes among healthy young adults (Dlugos et al., 2009).

In terms of dopamine synthesizing and catabolizing enzyme genes, the K4 (7-repeat) allele of the TH tetranucleotide repeat polymorphism has been repeatedly shown to be a protective factor in smoking (Ho and Tyndale, 2007). Positive association findings related to COMT are scarce (Tammimäki and Männistö, 2010), and no consistent MAOA findings have been reported in the substance abuse literature (Ho and Tyndale, 2007; Lachman, 2008; Bousman et al., 2009). A recent approach of genetic association analysis used a set of dopaminergic gene polymorphisms to create high or low activity dopaminergic genetic groups (Conner et al., 2010). In this way, the hypodopaminergic functioning was shown to be related to drug use in male adolescents among the studied children of alcoholics.

Go to:


Date: 2016-01-03; view: 210


<== previous page | next page ==>
Attention deficit hyperactivity disorder | Attentional performance
doclecture.net - lectures - 2014-2017 year. Copyright infringement or personal data (0.01 sec.)