ObjectiveTo determine the impact of cannabis use disorder (CUD) on the inpatient outcomes of attention deficit hyperactivity disorder (ADHD) in adolescentsBackgroundPrevious studies have evaluated the impact of CUD on the health-related quality of life in ADHD patients.MethodsWe used the nationwide inpatient sample (NIS) from the Healthcare Cost and Utilization Project (HCUP) from years 2010–2014. We identified ADHD and cannabis use (CU) as the primary and the other diagnosis, respectively, using validated International Classification of Diseases, 9th Revision, and Clinical Modification (ICD9–CM) codes. We used the binomial logistic regression model to generate adjusted odds ratios (aOR).ResultsWe analyzed a total of 11,232 ADHD adolescent hospital admissions from years 2010–2014; of these, 1.79% had CUD. The mean age of adolescents was 14.1 years (SD = 1.79). The prevalence of CUD was highest in ADHD adolescents of 15-18 years (73%) and common in the white race (71%). A higher proportion of ADHD with CUD was transferred to acute care hospitals and skilled/other nursing facilities . CUD increases the risk of inpatient charges > $12,247 (median) by 0.6 times  and increases the risk of inpatient stay > 5 days (median) by 0.7 times . The utilization of psychotropic medications was reduced by 0.8 times in ADHD with CUD adolescents by 0.8 times , and the implication of behavioral therapy in the management of ADHD with CUD adolescents was reduced by 0.9 times . Also, there is a 2.8 times higher risk of comorbid alcohol abuse in ADHD with CUD adolescents .ConclusionThe increased risk of substance use is a long-term implication of ADHD in adolescents. It has been determined that comorbid CUD in patients with ADHD not only increases the risk of acute inpatient care but also prolongs the inpatient stay, thus increasing the healthcare cost. Surprisingly, comorbid CUD decreases the utilization of psychotropic medications and behavioral therapy in ADHD. Another major issue is the higher risk of comorbid alcohol abuse in ADHD with CUD adolescents. Further exploration with randomized controlled studies would be required to support and highlight the growing issue of cannabis use among adolescents with ADHD. Cannabis is the most commonly used illicit drug for individuals aged 12 and over. Moreover, the prevalence of cannabis use in this age group has markedly increased from 6.2% in 2002 to 8.3% in 2015 [Attention deficit hyperactivity disorder (ADHD) is a common psychiatric disorder in childhood and adolescence that is characterized by impaired function in the areas of attention, hyperactivity, and impulsivity. ADHD and cannabis use disorders  often have clinical co-occurrence . EarlierThe estimation of the population size of the increasing prevalence of ADHD  and cannThe primary objectives of this study are to analyze and discern the variance in the demographic pattern, risk of morbidity and mortality, disposition, inpatient length of stay, inpatient total charges, and utilization of psychotropic medications in ADHD patients in contrast to ADHD patients with CUD. To effectively assess the patient care of CUD in ADHD, the results obtained from this study will allow for strategic developments and clinical care models to screen and treat CUD and improve the utilization of psychotropic medications in ADHD patients, together with the overall improvement of the patients’ quality of life by means of decreasing morbidity.Data sourceA retrospective analysis was performed using the healthcare cost and utilization project's (HCUP) nationwide inpatient sample (NIS) data from the years 2010 to 2014 . The ageVariables of interestBased on the ICD-9-CM diagnosis codes, we identified the individuals with a primary diagnosis of ADHD at the time of admission. Correspondingly, based on the ICD-9-CM diagnosis codes, the patients with a primary diagnosis of ADHD and another diagnosis as CUD patients at the time of admission had been identified as the comparison group. In HCUP databases, more than 14,000 ICD-9-CM diagnosis codes and 3,900 procedure codes had been mentioned. ADHD was identified using diagnosis code 314.00 and 314.01, and CUD was identified using diagnosis codes 304.30, 304.31, 304.32, and 305.2. The age limit was set between 12 years to 18 years to study the impact of CUD in ADHD adolescents.To measure the differences in hospitalization outcomes in ADHD patients versus ADHD with CUD patients, the outcome variables of interest included the severity of illness that measures the loss of body functions, the risk of mortality that measures the likelihood of dying, the disposition of the patient, and in-hospital mortality. In the NIS, we defined death as in-hospital mortality and, in this paper, it is reported as all-cause. We calculated the length of inpatient stay as the number of nights the patient remained in the hospital for a particular discharge. The length of inpatient stay in this analysis was all-cause. Inpatient charges during hospitalization do not include professional fees and non-covered charges. If the source provided total inpatient charges with professional fees, the professional fees were removed from the charge during HCUP processing. For the analysis, among the predictor variables, transfers out of the current hospital setting, the total number of ICD-9 CM procedures, primary ICD-9 procedures, and the duration of the hospital stays were considered important. The utilization of psychotropic medications during inpatient stay was identified using ICD-9 CM procedure codes 94.25. And, the utilization of behavioral therapy during inpatient stay was identified using ICD-9 CM procedure codes 94.33, 94.39, 94.42, and 94.44.Comorbidities are considered coexisting conditions to ADHD, which is the primary disorder under this study. AHRQ comorbidity software was utilized to generate binary variables. Using ICD-9-CM codes, this variable identified three comorbidities in the records of discharge alcohol abuse , psychosis , and depression .ApproachesA retrospective analysis was performed over the HCUP-NIS  databaseDemographicsWe analyzed 11,232 inpatient admissions for ADHD from 2010–2014 in adolescents and about 1.79% patients had comorbid CUD (N = 201). The mean age of ADHD patients at the time of hospitalization was 14.13 years  and 15.89 years  for ADHD with CUD patients. About 39.9% of ADHD patients and 85.1% of ADHD with CUD patients were in the age group of 15 to 18 years, comprising the most common age of presentation of ADHD and ADHD with CUD  in adolescents.ADHD and ADHD with CUD were found in the greater proportion of males  . Male gender is an important risk factor for CUD, as ADHD with CUD was seen in 90% males and only 10% females.ADHD was discovered in 51.6% of whites whereas ADHD with CUD was found in 71.1% of whites. This indicates that the white race is an important risk factor for both ADHD and ADHD with CUD. A greater proportion of ADHD was found in blacks (27.2%) and Hispanics (16.1%) as compared to ADHD with CUD adolescents  . On the contrary, a greater proportion of ADHD with CUD was found in Asian or Pacific Islanders (3.9%) than in ADHD without CUD adolescents (0.6%) .The demographic distribution of the sample population is mentioned in Table Inpatient outcomesA higher proportion of ADHD with CUD (97.5%) adolescents had non-elective or emergency admission compared to ADHD without CUD adolescents (86.1%) . About 6.3% ADHD patients had a major loss of body function or severe morbidity compared to 5% ADHD with CUD patients , whereas a moderate likelihood of dying was seen in a higher proportion of ADHD with CUD patients (2.5%) than in ADHD patients (0.7%) .The mean length of inpatient stay for ADHD with CUD adolescents was 4.81 days, which was lower as compared to ADHD without CUD adolescents who had a mean length of inpatient stay of 7.46 days . The median length of stay for all patients was five days. But still, ADHD with CUD adolescents had a greater risk of longer inpatient stay of more than five days than ADHD without CUD adolescents (adjusted OR (aOR) = 2.099; 95% CI = 1.387 – 3.178; p-value < 0.001).Despite a shorter duration of hospitalization, the mean inpatient total charges was higher in ADHD with CUD adolescents  compared to ADHD without CUD adolescents  . The median inpatient total charges for all patients was USD 12,247. ADHD with CUD adolescents had a greater risk of higher inpatient charges of more than USD 12,247 than ADHD patients . The association of the utilization of psychotropic medications was 0.8 times lower in ADHD with CUD adolescents compared to ADHD adolescents without CUD . Also, the association of implication behavioral therapies in the management of ADHD is 0.9 times lower in adolescents with comorbid CUD . A major proportion of ADHD with CUD patients (7.4%) was transferred to a skilled nursing facility (SNF), an intermediate nursing facility (INF), or another type of facility compared to 2.6% ADHD patients . Also, 5.4% ADHD with CUD patients were disposed to short-term or acute care hospitals compared to 1.1% ADHD patients . This indicates that greater numbers of ADHD with CUD patients needed specialized care in comparison to ADHD patients.The distribution of the sample population based on inpatient outcomes is mentioned in Table ComorbiditiesComorbid alcohol abuse is seen in 43.3% ADHD with CUD adolescents, which is 10 times higher than seen in ADHD without CUD adolescents . Thus, there is a 2.8 times higher risk of comorbid alcohol abuse in ADHD with CUD adolescents . On the contrary, comorbid depression and psychosis is seen in a lower proportion of ADHD with CUD adolescents compared to those without CUD . The risk of comorbidities in ADHD with CUD adolescents is mentioned in Table This analysis of population-based hospital data from adolescents admitted with ADHD and ADHD with CUD discloses the impact of CUD on hospitalization and related outcomes in ADHD. Our study had analyzed the NIS data with hospitalizations from 2010 to 2014, and over a five-year period, 1.79% of ADHD adolescents had comorbid CUD. As per a previous study, the risk of substance use disorder is higher for females as opposed to males with ADHD . But as A study done by Dalsgaard et al. states that ADHD patients with CUD have a higher risk of inattention and hyperactivity-impulsivity symptoms . As per To point out, the noteworthy strength of our study lies in the national representation of the dataset with the inclusion of a uniform collection of data through ICD-9-CM codes over the span of five years. To our knowledge, this is the first study to report the impact of CUD in ADHD adolescents regarding hospital outcomes, morbidity, mortality, and the utilization of psychotropic medications and behavioral therapy. With the intention of obtaining an appropriate sample size, we included 11,232 ADHD adolescents and 201 ADHD adolescents with CUD through the incorporation of the NIS dataset. The NIS dataset is subject to a minimal reporting bias. In addition, all the information from this dataset is coded independently of the practitioner, which makes it a reliable source.However, our study has several limitations. As an administrative database, the NIS dataset lacks the patient-level data needed to make accurate clinical associations. Furthermore, such retrospective studies are always subject to selection bias, which might be accentuated by the moderate sensitivity of diagnostic codes for ADHD and CUD. Given the nature of the database, we could not account for re-hospitalizations despite the fact that they add to the total inpatient burden. All things considered, these potential limitations, when compared overall, present the NIS database as an unparalleled population-based perspective on disease associations with systematic and temporal factors providing a rationale for further in-depth studies.The increased risk of substance use is a long-term implication of ADHD in adolescents. It has been determined that comorbid CUD in patients with ADHD not only increases the risk of acute inpatient care but also prolongs the inpatient stay, thus increasing the healthcare cost. Surprisingly, comorbid CUD decreases the utilization of psychotropic medications and behavioral therapy in ADHD. Another major issue is the higher risk of comorbid alcohol abuse in ADHD with CUD adolescents. Further exploration with randomized controlled studies would be required to support and highlight the growing issue of cannabis use among adolescents with ADHD.


Bartonella  that is transmitted primarily by blood-sucking arthropods such as sandflies, ticks and fleas. In Tunisia, there are no data available identifying the vectors of Bartonella spp. In our research, we used molecular methods to detect and characterize Bartonella species circulating in fleas collected from domestic animals in several of the country’s bioclimatic areas.Bartonellosis is an emerging vector-borne disease caused by different intracellular bacteria of the genus Ctenocephalides felis (83%) (Siphonaptera: Pulicidae), 266 C. canis (12%) and 109 Pulex irritans (5%) (Siphonaptera: Pulicidae). Using conventional PCR, we screened the fleas for the presence of Bartonella spp., targeting the citrate synthase gene (gltA). Bartonella DNA was detected in 14% (121/866) of the tested flea pools . The Bartonella infection rate per pool was broken down as follows: 55%  in C. canis; 23.5%  in P. irritans and 6.7%  in C. felis. Infection rates, which varied significantly by bioclimatic zone (P < 0.0001), were highest in the humid areas. By sequencing, targeting the gltA gene and the 16S–23S rRNA Intergenic Spacer Regions (ITS), we identified three Bartonella zoonotic species: B. elizabethae, B. henselae, B. clarridgeiae, as well as uncharacterized Bartonella genotypes.A total of 2178 fleas were collected from 5 cats, 27 dogs, 34 sheep, and 41 goats at 22 sites located in Tunisia’s five bioclimatic zones. The fleas were identified as: 1803 Bartonella. The dog flea, Ctenocephalides canis, should be considered the main potential vector of Bartonella. Our study not only provides new information about this vector, but also offers a public health update: medical practitioners and farmers in Tunisia should be apprised of the presence of Bartonella in fleas and implement preventive measures.To the best of our knowledge, this is the first time that fleas in Tunisia have been shown to carry zoonotic species of The online version of this article (10.1186/s13071-017-2372-5) contains supplementary material, which is available to authorized users. Bartonella  belonging to the α2-subgroup of the proteobacteria. These organisms can infect animal and human erythrocytes and endothelial cells and cause polymorphic clinical diseases [Bartonella by transfusions/organ transplants, arthropod saliva  or by flea feces in the case of Cat-Scratch-Disease (CSD) [Global changes, including climate and land use, are among the most significant influences on the distribution and density of hematophagous arthropod species, which may affect zoonotic diseases including bartonellosis, caused by bacteria of the genus diseases . A host se (CSD) , 2.Bartonella-Alpha-Proteobacteria-Growth Medium combined with PCR and sequencing (ePCR) [Bartonella species and subspecies in hosts and vectors [Bartonella henselae, which is transmitted by cat fleas, Ctenocephalides felis. Bartonella henselae, which is frequently transmitted to humans by a cutaneous trauma (scratch and/or bite) from an infected cat [B. quintana endocarditis were also reported [Several tools that are useful and more sensitive than culture and serological techniques, including conventional PCR, RFLP, MST, MLVA and also the pre-enrichment culture using g (ePCR) , have be vectors , 5. More vectors , 7. CSD cted cat , was reccted cat . Severalreported , 11.B. vinsonii, B. henselae, B. clarridgeiae and B. bovis. This correlated well with tick and/or flea infestations of the dogs that were tested [Candidatus B. merieuxii” DNA in dogs [Bartonella species circulate among patients and dogs in Tunisia [Serological studies conducted in Tunisia showed canine seropositivity for e tested . Moreove in dogs . While s Tunisia –10, 12, Bartonella species circulating in fleas collected from domestic animals and to compare its infection rates in Tunisia’s various bioclimatic areas.This research used molecular methods to detect and characterize An entomological investigation was carried out to collect fleas infesting domestic animals  in 22 sites located in Tunisia’s five bioclimatic zones . The identified fleas were removed from the 70% ethanol flasks, washed, dried, and minced with disposable scalpels, and placed in 200 μl ATL buffer. We followed the manufacturer’s instructions for the QIAamp® DNA tissue extraction kit . The final elution step was done using 90 μl of AE buffer and then stored at -20 °C for further use. To monitor for contamination during the processes, an extraction control (distilled water) for every 10 flea pools was added in each extraction experiment. The DNA concentration was determined with a NanoDrop spectrophotometer , and ranged between 50 and 400 ng/μl. For the PCR reaction, the extracted DNA was diluted to reach a suitable concentration (50 ng/μl).Bartonella spp. using the citrate synthase gene (gltA). The amplification of Bartonella DNA was carried out as described by Norman et al. [Fleas were screened for the presence of n et al.  using th2 (1.5 mM), 2.5 μl of deoxyribonucleotide triphosphate (200 μM), 0.5 μl of each primer (200 nM) and 0.75 U of Taq Platinum polymerase , followed by the addition of 3 μl of flea DNA extracts. The amplification reaction was carried out in a thermocycler (Perkin Elmer 2400). PCR cycling conditions were 10 min at 94 °C for an initial denaturation, followed by 35 cycles of 30 s at 94 °C, 45 s at 51 °C, and 30 s at 72 °C, with a final extension of 7 min at 72 °C. Positive and negative controls were included in each series of experiments. To avoid false-positive results, negative controls included sterile water and Bartonella-negative fleas DNA were added as the templates in each run. DNA extracted from B. elizabethae culture  was used as a positive control. To avoid cross-contamination, the extraction, amplification and gel electrophoresis were done in separate rooms. PCR products were visualized by ethidium bromide staining after electrophoresis in a 1.5% agarose gel  and their size was estimated by comparing them with Gene RulerTM 100-bp DNA Ladder  as a molecular marker. PCR of the 16S-23S rRNA Intergenic Spacer Regions (ITS) used the primers ITS2F (5′-GGG GCC GTA GCT CAG CTG-3′) and ITS2R (5′-TGA ATA TAT CTT CTC TTC ACA ATT TC-3′) [PCR amplifications were performed in a final volume of 25 μl containing 2.5 μl of 10× Taq buffer , 1,5 μl of MgClgltA Bartonella gene were confirmed by sequencing, targeting the two loci . Some PCR products were sequenced using the same oligonucleotides as for PCR to confirm the PCR results and to characterize the Bartonella species: PCR products were purified using the ExoSAP cleanup procedure . All nucleotide sequences were obtained using the Big Dye Terminator v.3.1 Cycle Sequencing Kit  and the 3130 automated sequencer . Sequences were determined on both forward and reverse strands to maximize data accuracy for the two used loci. The gltA and ITS sequences identified in this study were submitted to the GenBank database . Data sequences were compared and analyzed using the BLAST program (http://www.ncbi.nlm.nih.gov/BLAST).All flea pools that had tested positive for the gltA gene were used to construct a phylogenetic tree using the neighbor-joining method.The CLUSTAL W algorithm was used for sequence alignments and MEGA 6.06 software for phylogenetic analyses. Sequences of the Estimated infection rates (EIR) of all analyzed pools and of each flea species with corresponding 95% confidence intervals (CI) were calculated, based on equal pool sizes (2 fleas/tube), using the binGroup package  in the sBartonella infection rate of flea pools by species, animal host and bioclimatic area. The observed differences were considered significant when the resulting P-value was <0.05.The Chi-square test (EpiInfo 6.04) was used to compare the n = 51), 27 dogs (n = 664), 34 sheep (n = 341) and 41 goats (n = 1122) from all sites in Tunisia where the investigation was carried out. The largest number of fleas was removed from goats. Ctenocephalides felis was found on all examined animals  and was the dominant species of those collected , followed by Ctenocephalides canis  and Pulex irritans   were collected from 5 cats  and C. canis , whereas for P. irritans males outnumbered females .A predominance of females was observed in the collected C. felis, while dogs were infested with C. felis, C. canis and P. irritans  were screened for the presence of Bartonella DNA, which was detected in 14% (121/866) of the tested flea pools based on the gltA gene ; details are summarized in Table Bartonella infection rates per pool of C. canis and P. irritans were 55% (65/118) and 23.5% (8/34), respectively. For C. felis, only 6.7% (48/714) of the flea pool samples tested positive for Bartonella DNA . The largest number of infected C. felis was removed from cats  and dogs . However, 5.8% (10/170) and 1.6% (6/376), of infected C. felis were collected from sheep and goats, respectively. The differences in numbers of infected C. felis observed by animal host were statistically significant . The Bartonella infection rate per pool of all identified flea species was analyzed by the animal host: The rates in the flea pools collected from cats (33.3%) and dogs (32.7%) was higher than in those collected from sheep (5.8%) and goats (1.6%) . In this study we found that fleas  infected with Bartonella were collected from 11 of the 22 sites in the different bioclimatic areas , followed by the semi-arid , sub-humid  and arid zones . No Bartonella DNA was found in fleas collected in the Saharan areas  .Among the 2178 collected fleas, 1732 specimens pooled in 866 tubes  was detected in 50 flea pool samples. A Bartonella sp. with 100% identity with B. elizabethae detected in dog ticks in Taiwan [Bartonella sp. with a 99% identity score with B. clarridgeiae, described in Switzerland [Bartonella sp. with an identity score varying between 97 and 100% with uncultured Bartonella sp. clone B224RnF isolated from rodents [Bartonella sp. with an identity score varying between 99 and 100% with Bartonella sp. BR10 detected in dog ticks in Taiwan [Only 81 out of 121 amplicons, obtained by targeting the n Taiwan   detected by the gltA gene, with an identity score between 99 and 100% with the published sequences in GenBank . In addition, a Bartonella sp. with an identity score of 100% with Bartonella sp. Lao/Nh2 isolated from rodents (GenBank: EU714977) [Bartonella sp. B224RnF clones TUN by gltA gene. Targeting the ITS region, we were unable to amplify and sequence the pools revealed positive for Uncultured Bartonella sp. BR 10 TUN clones by the gltA gene  , was detgltA phylogenetic tree made it possible to visualize the arrangement of the Bartonella species identified in our study as compared to those identified in other studies. It showed that Tunisian sequences were clustered in 4 different groups , an ubiquist ectoparasite, was found on all investigated animal species in all regions. The same predominance has been observed in Germany, where Beck et al. [C. felis, followed by C. canis and P. irritans. A survey conducted in Iran also showed C. felis to be the most frequent species infested dogs (42%), followed by P. irritans (26.5%) and C. canis (16.5%) [C. canis collected from dogs was most prevalent in Ireland [Fleas are blood-sucking ectoparasites that are important vectors of pathogens including the bacteria of the r owners . The colk et al.  identifi (16.5%) . The sam (16.5%) , Algeriairritans .5% and C (16.5%)  and Moro (16.5%) . Such da Ireland  and New  Ireland .Ctenocephalides canis and P. irritans were found only on dogs in northern Tunisia ; 40.7% (11/27) had a mixed infestation of C. felis, C. canis and P. irritans ; 40.7% 1/27 had in Libya , Moroccoin Libya  and Iranin Libya .Bartonella DNA was detected in 14% of flea pools analyzed by the gltA gene. This rate is lower than those in studies from the UK  [Bartonella infection rates of flea pools in the different bioclimatic zones. The rates were highest in the humid area. No Bartonella infection was reported in the Saharan zone, confirming the results of a recent study undertaken in Tunisia showing that Bartonella seropositivity rates in dogs were highest in the humid zone [Our study showed that a pools)  and Frana pools) , but higa pools) , Israel a pools) , Hungarya pools)  and in ca pools)  and Algemid zone .Bartonella infection rates in countries, bioclimatic zones, and sites could be attributed to the detection methodologies used (culture or molecular approach), or to such bioclimatic parameters as temperature and humidity, the principal factors influencing flea survival, development, reproduction, and the abundance of Bartonella reservoirs. Fleas must be therefore carefully studied to better understand the relationships among climatic factors, Bartonella hosts and vectors [The variation of  vectors , 36, 37.Bartonella infection rates in the pools also vary with flea species: 55% for C. canis, 23.5% for P. irritans and 7% for C. felis. In Japan, all tested (single specimens) C. canis were infected with Bartonella compared to 33% in C. felis [Bartonella infection rates of C. felis and C. canis were 2.4% and 0.4%, respectively [The C. felis . In Germectively .Bartonella species, B. elizabethae, B. henselae and B. clarridgeiae, as well as uncharacterized Bartonella genotypes. The first three species are zoonotic and were also reported in fleas in neighboring countries, where B. clarridgeiae and B. henselae were identified in C. felis collected from cats, goats and sheep in Morocco [B. henselae, B. clarridgeiae and B. vinsoniiberkhoffii were detected in C. felis and Xenopsylla cheopis collected from cats and dogs [B. elizabethae, B.tribocorum and B. clarridgeiae were detected in fleas collected from hedgehogs, rats, and mice [gltA gene and the ITS, we detected genotypes of uncultured Bartonella sp. . Bartonella sp. BR10 TUN was detected in C. felis and C. canis collected from dogs. This Bartonella species was also detected in fleas (Pulex simulans) and in brown dog ticks  collected from dogs in Taiwan and Costa Rica , respectively [Bartonella sp. clone B224RnF TUN (gltA) and uncultured Bartonella sp. Lao/Nh2 TUN (ITS) described in P. irritans collected from dogs were found in rodents in the USA and in Southeast Asia [The positive PCR products were sequenced and analyzed in this study; thus, we were able to report for the first time in Tunisia that fleas harbor three known  Morocco . In Algeand dogs  whereas and mice . Based oectively , 40. In ast Asia , 21.gltA phylogenetic tree shows that sequences of uncultured Bartonella sp. clone B224RnF TUN group in the same cluster with B. elizabethae TUN and very closely to B. tribocorum and B. grahamii, which are commonly detected in rodents and micromammals  was most frequent followed by uncharacterized Bartonella genotypes (23.4%), B. elizabethae (9.8%) and B. clarridgeiae (4.9%)  while in C. canis we detected only B. henseale and uncharacterized Bartonella genotypes. Only uncharacterized Bartonella genotypes were detected in P. irritans (Table B. henselae in our survey is unsurprising, given that it is considered to be the most common Bartonella species in infected fleas, mainly in C. felis [B. henselae, the main agent of CSD, was also detected in C. felis collected from goats and sheep [Bartonella henselae can multiply in the digestive system of the cat flea and survive for several days in flea feces [The enselae 6.7% was mnotypes 2.4%, B. enotypes 2.4%, B. eC. felis . In Morond sheep . This spnd sheep . Bartonebethae 9.% and B. Bartonella endocarditis seems to be common. Indeed, 9.8% of infective endocarditis was caused essentially by B. quintana, while 2.5% were caused by B. henselae [B. quintana, which was isolated from other hosts, including a cynomolgus monkey in Ireland [B. quintana, which is a louse-borne pathogen, was associated with homelessness [B. quintana DNA was detected in cat fleas, which means that this flea species may be an unrecognized vector for the transmission among cats of B. quintana [In Tunisia, henselae . The lat Ireland  and dogs Ireland . Endocarlessness . Recentlquintana . It was quintana  and was quintana .Bartonella sp. was first reported in Tunisia in 49% of fat rats, Psammomys obesus, captured in the arid zone [Candidatus B. merieuxii”, B. vinsonii, B. henselae, B. clarridgeiae and B. bovis, correlating with tick and/or flea infestations of examined dogs [B. henselae, whereas cats are their natural reservoir [Bartonella vinsonii berkhoffii, B. henselae and B. rochalimae are the main species known to infect canids [Bartonella species, including B. elizabethae, have been detected in domestic dogs [B. hensale and B. elizabethae. We also reported that small ruminants were infested with C. felis that were positive for B. elizabethae, a rodent-associated zoonotic Bartonella species. It is likely that dogs, sheep and goats were infected with B. elizabethae, or that the fleas had been exposed to infected rodents. B. elizabethae DNA was previously detected in dog blood in the USA [B. elizabethae in fleas collected from sheep and goats. Infections caused by B. elizabethae in humans have been associated with endocarditis and neuroretinitis [rid zone . A molecned dogs , 13. Humeservoir . Bartonet canids . Recentltic dogs , confirm the USA . To the etinitis , 51.B. clarridgeiae DNA. This species was first isolated in the USA, where a patient displayed worrying clinical signs six months after adopted an infested kitten [C. felis could be a potential vector for B. clarridgeiae [Bartonella spp.[Our results revealed that fleas infesting domestic cats were positive for d kitten . Severalridgeiae , 16, whiella spp., 55.Ctenocephalides felis was predominant in comparison to C. canis and P. irritans fleas. To our knowledge, this study has shown for the first time in Tunisia, that fleas carry three zoonotic Bartonella species, B. elizabethae, B. henselae and B. clarridgeiae, as well as uncharacterized Bartonella genotypes. Our results indicate that the dog flea, C. canis, should be considered to be the principal potential vector of Bartonella. The highest Bartonella infection rate of flea pools was recorded in the humid area of northern Tunisia. These data may open up prospects for further studies of the effect of bioclimatic factors on the biology of fleas and their infection by Bartonella. Extensive molecular studies are needed to identify the uncharacterized Bartonella genotypes. Given the high rate of Bartonella infection in fleas in Tunisia, medical practitioners, pet owners and farmers should be informed about the vectorial role of fleas in transmitting Bartonella.Our study shows the presence of three flea species infesting domestic animals in Tunisia;


Pgrmc2 in adrenals and gonads of wild-type (WT) and Aaas knock-out (KO) mice. Female Aaas KO mice are sterile due to delayed oocyte maturation and meiotic spindle assembly. A participation in meiotic spindle assembly confirms the recently investigated involvement of ALADIN in mitosis and emphasises an interaction with PGRMC2 which is a regulator of the cell cycle. By identification of a novel interaction partner of ALADIN, we provide novel aspects for future research of the function of ALADIN during cell cycle and for new insights into the pathogenesis of triple A syndrome.It has been shown that the nucleoporin ALADIN plays a significant role in the redox homeostasis of the cell, but its function in steroidogenesis contributing to adrenal atrophy in triple A syndrome remains largely unknown. In an attempt to identify new interaction partners of ALADIN, co-immunoprecipitation followed by proteome analysis was conducted in different expression models using the human adrenocortical tumour cell line NCI-H295R. Our results suggest an interaction of ALADIN with the microsomal protein PGRMC2. PGRMC2 is shown to be activity regulator of CYP P450 enzymes and, therefore, to be a possible target for adrenal dysregulation in triple A syndrome. We show that there is a sexual dimorphism regarding the expression of  Summary: We report the interaction of the microsomal integral membrane protein progesterone receptor membrane component 2 with the nucleoporin ALADIN at the perinuclear ER and nuclear envelope. AAAS  encoding the protein ALADIN  (Triple A syndrome (MIM#231550) is an autosomal recessive disorder characterised by three distinct symptoms: ACTH-resistant adrenal insufficiency, oesophageal achalasia and absent tear production  in combination with progressive neurological impairment . The disisorder) . ALADIN isorder) .S. cerevisiae)] (ALADIN is a scaffold nucleoporin (NUP) anchored within the nuclear pore complex (NPC) by the transmembrane NUP NDC1 [nuclear division cycle 1 homologue (visiae)] . It belovisiae)] . Over thvisiae)] .Our group has reported that ALADIN is involved in the oxidative stress response of fibroblasts and adrenocortical cells, but the role of ALADIN in adrenal steroidogenesis contributing to the adrenal phenotype in triple A patients is largely unknown . RecentlBy attempting to identify new interaction partners of ALADIN, we aimed to clarify the cellular functions of ALADIN at the NPC and to explain the mechanisms which contribute to the adrenal insufficiency in triple A syndrome. Our observations give the basis for further research on the association between ALADIN and PGRMC2, and about the function of ALADIN during cell cycle and steroidogenesis.Co-IP was conducted in NCI-H295R cells either expressing endogenous ALADIN or additionally exogenous GFP-ALADIN.Tables S1 and S2.We performed mass spectrometry analyses of bound fractions of GFP(-ALADIN) and ALADIN co-IP. In the GFP-ALADIN expression model adequate peptides of ALADIN could be detected . The anaPGRMC2 was simultaneously identified by mass spectrometry analysis in co-IP of GFP-ALADIN using GFP-Trap_A agarose beads and in co-IP of ALADIN using anti-ALADIN coupled to Protein G UltraLink resin sepharose beads. Exclusive unique peptides of ALADIN and PGRMC2 detected in mass spectrometry after GFP-ALADIN are shown in We additionally confirmed the identification of PGRMC2 in GFP-ALADIN and ALADIN co-IP by western blot. Successful GFP-ALADIN pulldown in lysates of NCI-H295R cells stably expressing GFP-ALADIN (86 kDa) is presented in Successful endogenous ALADIN pulldown is shown in In order to further evaluate a possible interaction between the nucleoporin ALADIN and microsomal PGRMC2 we conducted reciprocal co-IP assays.Reciprocal pulldowns were done in NCI-H295R cells transiently expressing exogenous PGRMC2-GFP and endogenous PGRMC2.Efficient pulldown of (PGRMC2-)GFP in lysates of NCI-H295R cells transiently expressing PGRMC2-GFP (51 kDa) is presented in PGRMC2 pulldown is shown in Further evidence of possible co-localisation of ALADIN and PGRMC2 is given after immunofluorescent staining. Cells expressing GFP-ALADIN and PGRMC2-GFP were used to verify the specificity of anti-ALADIN and anti-PGRMC2 staining in NCI-H295R cells. Staining was done using anti-ALADIN, anti-PGRMC2 and anti-NPC proteins (mAb414).Immunostaining with mAb414 in all adrenal cell expression models gave a thin circle around the nucleus indicating punctate localisations of NPCs .Fig. 3.Immunofluorescent staining of the nucleoporin ALADIN appeared at the nuclear envelope at the proximity of NPCs in all adrenal cell expression models. In the exogenous GFP-ALADIN cell model, the fusion protein was correctly targeted to the nuclear envelope and did not accumulate to a greater extent in the cytoplasm. We showed that ALADIN almost completely co-localises with anti-NPC proteins (mAb414) immunostaining at the nuclear envelope, substantially verifying the localisation of ALADIN at the nuclear pore .Fig. S1A,B, respectively). In the exogenous adrenal cell model the PGRMC2-GFP fusion protein was still correctly targeted to the central ER and perinuclear space. In the staining with the anti-PGRMC2 in NCI-H295R cells we could also observe nuclear staining in some adrenal cells , and in the specific control cell lines (NCI-H295R1-TR/Scrambled shRNA and NCI-H295R1-TR), recently described by our group .We could not find an alteration on PGRMC2 mRNA level after induction of ALADIN depletion by doxycycline in NCI-H295R1-TR cells in at least ten triplicate experiments ] to the nuclear envelope and the perinuclear ER.Microsomal CYP P450 systems are haemoproteins and are localised to the membrane of the ER . PGRMC2 in vitro model for triple A syndrome   using X-tremeGENE HP DNA transfection reagent  following the manufacturer's protocols. Cells were harvested or fixed after 48 h.In all exogenous expression models clones were selected by moderate expression of the desired fusion protein and true cellular localisation in order to exclude the possibility of false positive protein interactions.NCI-H295R cells were cultured in DMEM/F12 medium  supplemented with 1 mM L-glutamine , 5% Nu-serum , 1% insulin-transferrin-selenium  and 1% antibiotic-antimycotic solution .AAAS knock-down or scrambled shRNA were generated, selected and cultured as described previously  in accordance with the institutional guidelines for the care and use of laboratory animals. C57BL/6J mice were obtained from Janvier Labs . eviously .n=10) and from frozen murine organs  was isolated using the NucleoSpin RNA  according to the protocol from the manufacturer. Purity of the RNA was assessed using Nanodrop Spectrophotometer (ND-1000) . 500 ng of total RNA was reverse transcribed using the GoScript Reverse Transcription System  following the protocols from the manufacturer. Primers for the amplification of the target sequence were designed using Primer Express 3.0  and compared to the human or murine genome database for unique binding using BLAST search (https://blast.ncbi.nlm.nih.gov/Blast.cgi). The primer sequences are listed in Table S3.Total RNA from cultured cells  according to the manufacturer's reaction parameter on an ABI 7300 Fast Real-Time PCR System (Applied Biosystems). In all results repeatability was assessed by standard deviation of triplicate CAfter SDS-PAGE separation onto 4-12% PAGE (150 V for 1.5 h) and electroblotting (30 V for 1.5 h)  onto Amersham hybond-ECL nitrocellulose membrane (0.45 µm)  non-specific binding of proteins to the membrane was blocked by incubation in PBS containing 3% BSA  at room-temperature.The membrane was then probed with primary antibodies either anti-ALADIN  , anti-PGRMC2   or anti-PGRMC2   overnight at 4°C. Secondary antibodies goat anti-mouse IgG conjugated to horseradish peroxidase (1:2000 in 3% PBS/BSA)  or goat anti-rabbit IgG conjugated to horseradish peroxidase (1:3000 in 5% PBS/milk powder)  were incubated for 1 h at room-temperature.For GFP co-IP lysates from NCI-H295R expressing GFP-ALADIN or PGRMC2-GFP were used. Lysates from cells expressing GFP were used as negative control. Cell lysates (500 µg protein) were added to the pre-equilibrated GFP-Trap_A agarose beads , gently re-suspended by flipping the tube and bound overnight at constant mixing at 4°C. After washing steps, the beads were gently re-suspended in 60 µl NUPAGE 2X LDS sample buffer and in order to dissociate the captured immunocomplexes from the beads, boiled at 95°C for 10 min and western blot analysis was conducted with 20 µl of the eluate. The leftover 40 µl of the eluate using the lysates of NCI-H295R expressing GFP-ALADIN or GFP was further processed for proteomic profiling using mass spectrometry. These experiments following mass spectrometry analysis were repeated three times.For co-IP of ALADIN or PGRMC2 lysates from NCI-H295R cells and Protein G UltraLink resin sepharose beads  were used. Beads were gently re-suspended in anti-ALADIN (2 µg/ml) or anti-PGRMC2 (HPA041172) (2 µg/ml) and as negative controls normal mouse or rabbit IgG (2 µg/ml) . All antibodies were bound to the beads over-night at 4°C in a rotation chamber. After washing cell lysates (500 µg protein) were added to the beads, gently re-suspended by flipping the tube and bound overnight as described before. After washing the beads were gently re-suspended in 60 µl sample buffer containing dilution buffer, NUPAGE 1X LDS Sample Buffer and 1× reducing agent. The captured immunocomplexes were dissociated and the eluates were collected and processed by western blot as described previously. These experiments were repeated three times. The left 40 µl of the eluate after ALADIN co-IP and negative control was further processed for proteomic profiling using mass spectrometry. Mass spectrometry analysis was conducted once.Entire gel lanes were cut into 40 slabs, each of which was in-gel digested with trypsin . Gel anahttps://www.ncbi.nlm.nih.gov/protein, updated in June 2014) using MASCOT software v.2.2. Scaffold software v.4.3.2 was used to validate MS/MS-based protein identifications. Protein probabilities were assigned by the Protein Prophet algorithm  in PBS, permeabilised for 5 min with 0.5% Triton-X-100 in PBS and fixed again for 5 min. Blocking was performed for 30 min with 2% BSA/0.1% Triton-X-100 in PBS at room temperature.All antibodies used for immunofluorescence were diluted in blocking solution. Primary antibodies anti-ALADIN (1:25), or anti-PGRMC2  or anti-PGRMC2  and anti-NPC proteins  were incubated at 4°C overnight in a humidified chamber. Secondary antibodies goat anti-mouse IgG Cy3 , Alexa Fluor 488 and 555 goat anti-rabbit IgG  were incubated one hour at room temperature in the dark.Fluorescence was visualised using the confocal laser microscope TCS SP2 . The experiments were repeated at least three times.U-test was performed. During evaluation of the results a confidence interval alpha of 95% and P-values lower than 0.05 were considered as statistically significant. Results are shown as box plots which give a fast and efficient overview of median, first and third quartile , interquartile range (IQR), minimal and maximal values and outliers.Statistical analyses were made using the open-source software R version 3.3.0 and R Studio version 0.99.902 . Unpaire


CTNNAP1, for the CTNNA1 gene, was dysregulated in colorectal cancer and the degree of dysregulation was remarkably associated with tumor node metastasis (TNM) stage (P<0.05). The mechanistic experiments revealed that pseudogene CTNNAP1 played a pivotal role in the regulation of its cognate gene CTNNA1 by competition for microRNA-141. Moreover, gain-of-function approaches showed that overexpression of CTNNAP1 or CTNNA1 significantly inhibited cell proliferation and tumor growth in vitro and in vivo by inducing G0/G1 cell cycle arrest. Our findings add a new regulatory circuit via competing endogenous RNA (ceRNA) cross-talk between pseudogene CTNNAP1 and its cognate gene CTNNA1, and provide new insights into potential diagnostic biomarker for monitoring human colorectal cancer.Accumulating evidence indicates that deregulation of cancer-associated pseudogene is involved in the pathogenesis of cancer. In the study, we demonstrated that pseudogene  Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and the leading cause of cancer-related deaths in the world . In factPTENP1 sequesters microRNAs  away from its mRNA target PTEN, thereby influencing parent gene expression [Foxo3 pseudogene (Foxo3P) could suppress tumor growth and angiogenesis by functioning as a sponge for microRNAs, and upregulate expression of the forkhead family of transcription factors, Foxo3.Lately, advances in the analysis of whole-genome sequencing data have showed that most genomic sequences is transcribed as non-coding RNA species, including long non-coding RNA (lncRNAs), pseudogenes and microRNAs etc. Numerous studies demonstrate that these non-coding transcripts are implicated in regulation of various cellular processes –7. In repression . In the pression , Foxo3 pCTNNAP1 was aberrantly expressed in CRC and was positively associated with CTNNA1 expression. Furthermore, gain-of-function assays were further explored that pseudogene CTNNAP1 could act as a ceRNA to increase CTNNA1 gene expression through competition for microRNA-141, subsequently inhibiting cell proliferation and tumor growth. This study showed the first evidence for the cross-talk between CTNNAP1 and CTNNA1 via competing for microRNA-141, shedding a better understanding of molecular etiology of CRC.In the present study, we investigated that pseudogene CTNNAP1, we performed qRT-PCR assay in a cohort of 56 pairs of CRC tissues and paired nontumor tissues. The result showed that the expression of CTNNAP1 was downregulated in 70% tumor samples (39/56) compared to adjacent normal samples  than in the nucleus of fractionated SW480 and SW620 cells.As an intriguing class of lncRNAs, recent evidence increasingly discovered that pseudogenes have crucial roles in normal physiology as well as quite recently in the context of cancer. To evaluate the expression of pseudogene CTNNAP1 expression with clinicopathological features of CRC patients to assess its clinical significance. According to the median value (0.68) of relative CTNNAP1 expression in CRC tissues, 56 CRC patients were classified into high group  and low group . We found that CTNNAP1 expression levels in CRC tissues were remarkably associated with tumor node metastasis (TNM) staging    Figure . Taken tCTNNAP1 and its cognate gene CTNNA1, we further determined whether CTNNAP1 can regulate the expression of CTNNA1 through operating as a ceRNA. Based on the bioinformatics tools and the reference [CTNNAP1 transcript as well as the sequence of CTNNA1 3′-UTR . Among these microRNAs, microRNA-141 was found to be up-regulated in the same CRC tissues in comparison with matched normal tissues   Figure .CTNNAP1 and CTNNA1 genes   or microRNA-141 inhibitors along with microRNAs mimics. Expression of CTNNAP1 and knockdown of microRNA-141 partially abrogated the inhibitory effect of microRNA-141  Figure , which cs Figure . Further1 Figure . As we es Figure , suggest1 Figure . TogetheCTNNAP1 and CTNNA1 half-life after inhibiting transcription by incubating cells with actinomycin D using qRT-PCR. As showed in Figure CTNNAP1 and CTNNA1 was declined in CRC cells after RNA synthesis was blocked with Actinomycin D in the presence of microRNA-141. Furthermore, the half-life of CTNNAP1 and CTNNA1 regulated by microRNA-141 was shorter in CRC cells  after actinomycin D treatment than in control cells . These results indicate that microRNA-141 could suppress CTNNAP1 and its cognate gene CTNNA1.We measured the CTNNAP1, for the human alpha E-catenin CTNNA1 gene, was originally characterized by fluorescence in situ hybridization [CTNNA1 in various tumors [CTNNA1 gene on the progression of CRC. To elucidate the functions of CTNNAP1 and CTNNA1 in CRC, a series of functional assays were performed to investigate the roles of CTNNAP1 and CTNNA1 in cell proliferation and tumor growth in SW480 and SW620 cells. pcDNA3.1-CTNNAP1 or pcDNA3.1-CTNNA1 were transfected into SW480 and SW620 cells, respectively, and the transfection efficiency of CTNNAP1 and CTNNA1 overexpression were subsequently confirmed by qRT-PCR analysis. After 48h post-transfection, the RNA levels of CTNNAP1 and CTNNA1 revealed that CTNNAP1 expression was increased by 11-fold and 13-fold in SW480 and SW620 cells than the empty vector pcDNA3.1, respectively    Figure . In addi) Figure . These roncogenes or tumor-suppressor genes by acting as modulators of microRNAs [CTNNAP1 resulted in CTNNA1 mRNA level suppression by microRNA-141, and conferred a malignant phenotype to colorectal cancer cells lines  were enrolled, and written informed was obtained from each subject. The patient who received chemotherapy or radiotherapy prior to surgery were excluded. Clinical characteristics including age, sex, lymph node metastasis, tumor differentiation and TNM stage are shown in Table 2.Human CRC cell lines (SW480 and SW620) were purchased from the American Type Culture Collection (USA). These cell lines were cultured routinely in RPMI Medium 1640 (Invitrogen) supplemented with 10% fetal bovine serum  and were grown in incubator at 37°C with 5% COFor subcellular fractionation experiments, cytosolic and nuclear extracts from CRC cells (SW480 and SW620) were collected using a Nuclear/Cytosol Fractionation kit (Biovision) as previously described .CTNNAP1 and CTNNA1 were synthesized and then subcloned into pcDNA3.1 . The microRNA mimics, and microRNA inhibitors were from GenePharma . The stable CRC cells with ectopic expression of CTNNAP1 or CTNNA1 were achieved based on previously described method [The cDNAs sequence of d method . The empTo measure half-life of CTNNAP1 and its cognate gene CTNNA1 regulated by microRNA-141. SW480 and SW620 cells were plated in 24-well culture plates. Twenty-four hours after cells were transfected with 40 pmol microRNA-141 mimics , cells were incubated with Actinomycin D (Sigma) for 2, 4 or 6h. Actinomycin D was used at a final concentration of 2.5 mg/ml.GAPDH) or U6 using the 2−ΔΔCt. Each sample was analyzed in triplicate.Total RNAs of tissues or cultured cells were extracted with TRIzol reagent  according to the manufacturer's protocol. The expression of mRNA was evaluated using SYBR Green Assays and microRNA expression was detected using Taqman microRNA Assays (Applied Biosystems) on ABI 7500 system . The relative expression was normalized to the expression of glyc-eraldehyde-3-phosphate dehydrogenase (CTNNAP1 and CTNNA1 3′-UTR. The sequence of CTNNA1 3′-UTR containing microRNAs putative target sites or CTNNA1 3′-UTR with point mutations in the microRNA response elements were amplified and then were cloned into psiCHECK-2 vector (promega). The vectors were cotransfected with microRNAs mimics or inhibitors into CRC cells using Lipofectamine 2000 (Invitrogen) for the reporter assay, according to the manufacturer's instructions.We used online software program TargetScan, starbase v2.0 and miRanda databases to predict potential microRNAs that have complementary base pairing with CTNNAP1, pcDNA3.1-CTNNA1 or pcDNA3.1 empty vectors were collected and were plated in each well of a 96-well plate. Cell viability was measured every 24h by the Cell Counting Kit-8 (CCK-8) kit. For the colony formation assay, approximately 300 CRC cells transfected with pcDNA3.1-CTNNAP1, pcDNA3.1-CTNNA1 or pcDNA3.1 empty vectors were plated into per well for six-well plates for 2 weeks incubation. The colonies were counted after fixing with methanol and staining with crystal violet  according to the manufacturer's instructions.CRC cells transfected with pcDNA3.1-CTNNAP1, pcDNA3.1-CTNNA1 or pcDNA3.1 empty vectors with overexpressed CTNNAP1 or CTNNA1 as described above were plated in six-well plates. After cultivation for 48h, the cells were harvested and subjected to analyze for cell cycle by a flow cytometer  according to the manufacturer's instructions. Each experiments was repeated three times independently.These CRC cells transfected with pcDNA3.1-6 CRC cell lines with overexpressed CTNNAP1 or CTNNA1 were injected subcutaneously in the posterior flank of BALB/c nude mice (6 mice per group). Tumor volumes were calculated every 3 days by measuring the length and width with calipers (Tumor volumes=0.5×length×width2).All female athymic BALB/c mice (5-week-old) were purchased from the Shanghai Experimental Animal Center of the Chinese Academy of Sciences and randomly were divided into control or experimental group. The animal study protocol was approved by the Animal Experimentation Ethics Committee of the Third Affiliated Hospital of Harbin Medical University. For a CRC mouse model system, 5×10CTNNAP1, CTNNA1 and microRNAs in tissues was determined via linear regression model. Statistical analysis was performed using SPSS software . P values <0.05 was defined as statistically significant.An unpaired two-tailed student's t-test and one-way analysis of variance (ANOVA) test were used to evaluate the significance of the differences. The expression relationship between


We hypothesize that it is plausible that biologically distinct developmental ASD–ADHD subtypes are present, each characterized by a distinct time of onset of symptoms, progression and combination of symptoms. The aim of the present narrative review was to explore if structural brain imaging studies may shed light on key brain areas that are linked to both ASD and ADHD symptoms and undergo significant changes during development. These findings may possibly pinpoint to brain mechanisms underlying differential developmental ASD–ADHD subtypes. To this end we brought together the literature on ASD and ADHD structural brain imaging symptoms and particularly highlight the adolescent years and beyond. Findings indicate that the vast majority of existing MRI studies has been cross-sectional and conducted in children, and sometimes did include adolescents as well, but without explicitly documenting on this age group. MRI studies documenting on age effects in adults with ASD and/or ADHD are rare, and if age is taken into account, only linear effects are examined. Data from various studies suggest that a crucial distinctive feature underlying different developmental ASD–ADHD subtypes may be the differential developmental thinning patterns of the anterior cingulate cortex and related connections towards other prefrontal regions. These regions are crucial for the development of cognitive/effortful control and socio-emotional functioning, with impairments in these features as key to both ASD and ADHD. N = 17,000 children (9–12 years) concluded that ‘individuals with all three  ASD domains in the sample never showed hyperactivity alone but often exhibited co-occurring impulsivity, or co-occurring impulsivity and inattention’  and attention deficit hyperactivity disorder (ADHD) frequently co-occur. Exact comorbidity rates are not well known due to the DSM-IV restriction of diagnosing ASD and ADHD in the same individual. Hence, available diagnostic comorbidity estimates are based on only a few papers and are likely biased ;It may be expected that in adolescence and young adulthood, when ADHD symptom improvement is most pronounced in a proportion of individuals, ASD symptoms will likely improve as well. That is, this ‘transitory’ subtype suggests that the severe form of the overarching disorder is not likely to remain in the absence of the milder ADHD symptoms ;For some children, once development has derailed and the most severe form of the disorder (ASD) has become manifest, an unrepairable damage has taken place and full recovery does not take place. These individuals that have developed ASD will always remain symptomatic to some extent, with co-occurring ADHD symptoms present. This ‘scarring’ subtype finds its parallel in, for example, permanent hearing loss after recurrent ear infections, leading to permanent bone malformations in the inner ear despite the absence of recurrent ear infections .Thus, the above outlined results indicate changes occur in (the overlap of) ADHD and ASD symptom domains across the lifespan, which may be linked to age-related changes in involved etiological mechanisms. We hypothesize that it is plausible that biologically distinct developmental ASD–ADHD subtypes are present, each characterized by a distinct time of onset of symptoms, progression and combination of symptoms. We previously hypothesized that ASD and ADHD may be seen as different manifestations of one overarching disorder  determined, in accordance with DSM-5 criteria. Electronic literature searches via PubMed and Psychinfo were conducted for articles that were published before October 2016 (unlimited by date of publication) in the English language (unlimited by date of publication). We used broad search terms to not miss out on relevant work, subsequently scrutinizing abstracts, and if needed the full text, to determine if the study reported on findings relevant in relation to developmental aspects of core symptoms and brain characteristics. We were particularly keen on finding studies with multiple measures over time to capture possible longitudinal change. We confined ourselves to studies bases on humans and filtered out those that were not described in English. Given that the information we were after is oftentimes “hidden” in papers , our research strategy was to employ a very lenient threshold at the level of inclusion based on the title, after which we made a more stringent selection of those paper that provided relevant developmental information. The following combinations of keywords were used to identify the relevant articles: ‘autism/ASD’, ‘ADHD’, ‘social’, ‘attention’, ‘activity’, ‘impulsivity’ ‘adolescence/adolescents’, ‘adult’, ‘longitudinal’, ‘prospective’, ‘development’, ‘brain’, ‘structural MRI’, ‘neuro’, and ‘structural imaging’. Both original research articles and meta-analyses, and systematic and narrative reviews were included, and references in these papers were checked for additional relevant literature. Despite these attempts, we do not claim to be exhaustive and cover all papers that may have met the search criteria. Rather we want to highlight the need for a lifespan-approach in studying ASD–ADHD co-occurrence in relation to structural brain imaging and discuss findings in the context of an overarching disorder hypothesis.We will start with an overview on the normal developmental pattern of structural brain correlates and associated etiological factors, followed by the findings for ADHD, then ASD and—although scarcely available—by findings directly related to both. Findings will be summarized and in the discussion we elaborate on new insights in the light of the overarching disorder hypothesis.Recent years have seen much progress in our knowledge on life course, and in particular adolescent brain development. These normative changes may follow different patterns, and in transaction with the environment, have unique consequences for ASD and ADHD similar for males and females, since most MRI studies do not provide sufficient data to investigate differential effects between males and females across development  show greater heritability in adolescence relative to childhood  variation; what matters is the relative contribution. It has been reported that brain areas that develop phylogenetically and ontologically early, such as the primary sensory cortex, show greater heritability Zooming in on sex differences regarding genetic effects on brain development is particularly relevant given that the prevalence of ASD and ADHD are known to differ between the sexes. Brain specific sex-biased gene expression may to some extent underpin this prevalence difference. A meta-analysis specifically examining the role of sex-chromosomes on brain development, concluded that although the X and Y chromosomes have opposing effects on overall brain size, they exert highly convergent influences on local brain anatomy across phylogenetically and ontologically differentially developing brain areas, particularly centers for social perception, communication, and decision-making  parenting  in frontal networks, smaller prefrontal volumes, decreased orbitofrontal volumes and abnormalities in insula, occipital, and somatosensory areas have been documented. in early adulthood  in adolescents . Effortful control—the ability to voluntarily manage attention and inhibit or activate behavior as needed to adapt, especially in the context of low motivation—is associated with both ASD and ADHD. A study in healthy control participants reported that a greater age-related thinning of the left anterior cingulate cortex was associated with less reduction in effortful control and in turn with improvements in socio-emotional functioning and reductions of psychopathological symptoms   childhood on. This likely changes the brain further on in development, compounding effects due to altered daily life experiences and compensatory brain changes. That the typically developing human brain is not fully mature until well into adulthood—and also remains to a certain degree receptive and flexible during the entire life—suggests that in ASD and ADHD cortical maturation is likely protracted until further across the lifespan, in combination with permanent alterations. The vast majority of existing MRI studies, however, has been cross-sectional, based on small samples and conducted in children, and sometimes did include adolescents as well, but without explicitly documenting on this age group. MRI studies documenting on age effects in adults with ASD and/or ADHD are rare, and if age is taken into account, only linear effects are examined. The few studies directly comparing brain characteristics associated with ASD and ADHD provide a heterogeneous mix of findings that is difficult to interpret due to the lack of longitudinal brain measures, the various methods used, and the sometimes arbitrary distinction between both clinical groups.ADHD and ASD symptoms are developmentally complex phenotypes characterized by both continuity and change across the life span. We plotted six hypothetical developmental ASD–ADHD subtypes based on the overarching disorder hypothesis see Fig. . We hypoOur review indicates that findings on neural mechanisms underlying ASD and ADHD in childhood years cannot be automatically extrapolated to adolescence and adulthood. Findings from genetic factors underlying brain structure show greater heritability in childhood for earlier maturing areas and greater heritability in adulthood for later maturing areas. Understanding the mechanisms underlying these normative brain changes—particularly during windows of increased plasticity—may contribute to distinguishing progressive brain changes in ADHD and ASD from healthy developmental processes. It is likely that adolescence and young adulthood are crucial phases wherein new genetic effects may become relevant in determining further development of cortical thickness, general cognitive ability and potentially neurodevelopmental disorders (Greven et al. The clear age effects on—and large within group heterogeneity of—brain anatomy in relation to ASD and ADHD symptoms, do call into question the attempts to design uniform brain-based diagnostic classification algorithms that largely ignore these age effects and within group heterogeneity (see for extensive reviews Arbabshirani et al.


Most research on motivational processes in attention deficit hyperactivity disorder (ADHD) has been undertaken in Western Europe and North America. The extent to which these findings apply to other cultural groups is unclear. The current study evaluated the behavioral sensitivity of Japanese children with and without ADHD to changing reward availability. Forty-one school-aged children, 19 diagnosed with DSM-IV ADHD, completed a signal-detection task in which correct discriminations between two stimuli were associated with different reinforcement frequencies. The response alternative associated with the higher rate of reinforcement switched twice during the task without warning.Both groups of children developed an initial bias toward the more frequently reinforced response alternative. When the reward contingencies switched the response allocation (bias) of the control group children followed suit. The response bias scores of the children with ADHD did not, suggesting impaired tracking of reward availability over time.Japanese children with ADHD adjust their behavioral responses to changing reinforcer availability less than their typically developing peers. This is not explained by poor attention to task or a lack of sensitivity to reward. The current results are consistent with altered sensitivity to changing reward contingencies identified in non-Japanese samples of children with ADHD. Irrespective of their country of origin, children with ADHD will likely benefit from behavioral expectations and reinforcement contingencies being made explicit together with high rates of reinforcement for appropriate behaviors. Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by elevated levels of inattention, hyperactivity and/or impulsivity that impair daily functioning. Upwards of 5% of elementary school-age children are diagnosed with ADHD , 50–65% The disorder is known to be highly heritable . Aase eThe results of these studies suggest the association between ADHD and altered reward processing is not a Western cultural phenomenon. However, further research is needed to confirm the presence of altered motivational processing in children with ADHD across cultures, preferably using the same paradigms so that findings can be directly compared. This becomes increasingly important as Western-styled behavior management programs are progressively adopted in non-Western countries .In the current study we evaluate the sensitivity of Japanese children with and without ADHD to unequal frequency of reward and to changing reinforcement availability, using the signal detection task described by Alsop et al. . ParticiBased on the findings of Alsop et al. , and theThe overall sensitivity of the two groups of Japanese children to the asymmetric reward distribution is more difficult to predict. Praise is used sparingly in Japan –34 and hData from 41 children, 19 meeting DSM-IV diagnostic criteria for ADHD  and 22 typically developing children (50.0% boys) living in Okinawa, Japan, are included in the study. Within the ADHD group, 10 children were diagnosed with inattentive type, one with hyperactive/impulsive type and eight with combined type ADHD. Four children were prescribed stimulant medication, which was discontinued for at least 24 h prior to study participation. Table Inclusion criteria for the study were estimated IQ scores above 70, participation in regular education classesChildren were required to display six or more symptoms of inattention and/or hyperactivity/impulsivity in at least one setting, evidence of symptoms in a second setting, and functional impairment. Symptoms were not summed across informants. Assessments were carried out by a team including a US-licensed, Japanese-speaking clinical psychologist (EF), and clinicians with advanced counseling or other relevant degrees, all fluent in Japanese and experienced in working with children with ADHD. Control group children were recruited through invitation letters sent home to parents through public schools. These children completed an abbreviated IQ assessment (WISC-III Vocabulary/Block Design). Their parents and teachers completed the behavior rating scales, which were used to rule out the presence of ADHD or other significant behavioral or emotional disorders. Those demonstrating fewer than four symptoms of inattention or hyperactivity/impulsivity were included. Parent and teacher reports were reviewed for other inclusion criteria.sometimes earn rewards. A multi-element reinforcement system was used to maximize reward effectiveness: the message “Well done!” and an animated cartoon appearing on screen, verbal praise from the examiner, and colored tokens placed in a clear plastic container next to the child. Following incorrect and non-rewarded correct responses, the screen was blank and the experimenter remained silent. All children received a prize at the end of the session irrespective of their performance on the task.The experimental task and procedure used is described in detail in Alsop et al.  and illuSuccessive blocks of eight trials contained an equal number of each array type, randomized within blocks. The computer determined quasi-randomly which correct responses were reinforced. At the start of the session, correct identifications of one stimulus (“more blue”) were rewarded four times more often than correct identifications of the other stimulus (“more red”). After the child had received 20 rewards with this distribution, the computer reversed the contingencies and correct identifications of “more red” stimuli were reinforced four times as often. After another 20 rewards, the original reward distribution was reinstated, with the game ending after the children received a further 20 rewards. Each successive block of ten reinforcements contained eight reinforcements for correct identification of one array type and two for correct identification of the other, randomized within each block.d) i.e., accuracy, and response bias (logb) i.e., the systematic preference for the more frequently reinforced alternative [Three measures of performance were calculated for each child: median response time, discriminability between stimuli , reinforcements 21–30 and 31–40 (reward distribution 1:4), and reinforcements 41–50 and 51–60 (reward distribution 4:1).Discriminability between the stimuli was calculated by the equation:Mean scores for response bias, discriminability and median response time for the six blocks  were analyzed with SPSS GLM. Mixed ANOVA was conducted to examine the main effects of Block  and Group , and the interaction effects. The bias scores were expected to change with the two shifts in the contingency schedule, therefore polynomial contrasts examined quadratic and linear trends in the bias scores over the six blocks, separately for the ADHD and control groups. Post-hoc pairwise comparisons were performed when significant univariate effects were observed. There were differences in the mean age and IQ, and gender, between the ADHD and control groups. Although the difference in IQ scores did not reach statistical significance, given the small sample size, IQ was entered as a covariate along with age and gender, when the two groups were compared on the performance measures.F = 2.64, p < .05) for bias, controlling for age, IQ and gender . The bias scores of the two groups were significantly different from one another during blocks two and six . Two polynomial contrasts were performed to assess quadratic and linear trends in the bias scores over the six blocks, separately for the control and ADHD groups. For the control group, there were significant quadratic  = 9.50, p < .01) and linear  = 12.02, p < .01) effects. Pairwise comparisons indicated a significant difference in the bias scores for the second and forth blocks . Mean bias scores decreased across both blocks of the reversal phase, increasing during the first block of the reinstatement phase. For the ADHD group, only the linear trend was significant  = 31.68, p < .001). For this group the bias score for the first block was significantly larger than the bias scores for the two reinstatement blocks (p < .05).Mixed ANOVA indicated a significant univariate Block × Group interaction effect  = 10.81, p < .01) after controlling for age, IQ and gender .Mixed ANOVA indicated a significant main effect of Group  = 3.50, p < .10), after controlling for age, IQ and gender .Mixed ANOVA indicated a trend toward a main effect of Group  for the more frequently reinforced alternative, demonstrating their behavioral sensitivity to the asymmetric reward distribution.As the task progressed the response allocation of the typically developing children reflected the availability of reward, i.e., as the reward contingencies changed the children’s response bias scores changed with them. The overall response pattern that emerged was very similar to that reported by Alsop et al.  for theiThe response bias pattern of the Japanese children with ADHD suggests their ability to track changing reward availability is impaired. After developing a significant response bias toward the more frequently reinforced alternative during the first half of the initial phase, the children’s bias score dropped to near zero. This was followed by a slight increase in bias during the first half of the reversal phase, then a slow decrease across the remainder of the task. These data suggest a loss of behavioral control by the asymmetric reward distribution. Although the exact response pattern differed, Alsop et al.  also repPoorer behavioral tracking of the reinforcement contingencies by the ADHD group does not reflect a lack of sensitivity to reinforcement. As noted, both groups of children developed a clear bias toward the more frequently reinforced response alternative early in the task. Nor does it reflect difficulty completing the signal detection task. Although discriminability scores were significantly lower for the children with ADHD, possibly reflecting less attention to the stimuli, their mean accuracy exceeded 70% across all phases of the task. The children with ADHD initially responded more quickly on the task than controls, the latter’s response times decreasing to a similar level with time on task. While the response speed of the ADHD group may have impacted their discriminability, it does not show a consistent relationship with bias scores, arguing against impulsive responding leading to poorer tracking of reward availability.While the mechanisms underlying the poor alignment between reward availability and response allocation in children with ADHD remains to be determined, the current study provides further evidence that children with ADHD have difficulty adapting their behavior to situational demands when levels of reinforcement are relatively low and contingency changes are not signaled. We previously suggested such a disparity might arise as children with ADHD have difficulty adjusting their internal representations of reinforcement contingencies under low rates of partial reinforcement , 48. AddThe overall similarity of the results to those reported by Alsop et al. , lends wGroups in the current study were not well matched for age, IQ or gender, in part reflecting the challenges of data collection. As potential confounds, all three variables were included as covariates in the analyses, resulting in more conservative probability estimates, but no change in the findings. Importantly, within the control group there were no significant gender differences for age, IQ, response bias or discriminability.The signal detection task used in the current study has good ecological validity. Just as in children’s every day experiences, not all instances of correct behavior  were rewarded and changes in reward availability were unsignaled . These cThe present findings suggest similarities between Japanese and Western children with ADHD that go beyond symptom presentation. The results are consistent with reduced sensitivity to unsignaled contingency changes identified in non-Japanese samples of children with ADHD. Parents and teachers of Japanese children with ADHD should be advised of the importance of reducing ambiguity regarding behavioral expectations, irrespective of normative practices. Although Japanese culture has many daily rituals marking the transition from one setting to another , children with ADHD would benefit from explicit information regarding behavioral expectations in different settings and when these change. Furthermore, it should not be assumed that children with ADHD will carry this information forward to new environments, or that a failure to adapt behavior to situational demands is evidence of misbehavior. For children with ADHD, frequent, immediate and consistent reward for appropriate behavior is recommended across cultures.The current results provide additional evidence that children with ADHD do not track reward contingencies as consistently as typically developing children, when rates of reinforcement are low and the contingencies change without warning. The similarity of the findings, across studies and cultures, using the same paradigm and diagnostic procedures, offers further evidence for altered reward sensitivity playing a role in the pathophysiology of ADHD. Altered motivational processes may be a common, defining characteristic of the disorder expressed similarly across cultures. These findings also suggest recommendations to alert children with ADHD to situational expectations, and the consequences of their actions, are relevant across cultures. Further experimental research in non-Western countries, across the range of neurodevelopmental and psychiatric disorders, is important to confirm the cross-cultural continuity of core deficits and underlying neurobiology. Such efforts will help refine behavioral and pharmacological treatments and ensure their appropriateness for different cultural groups.


Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that affects individuals across the lifespan. ADHD medication use among pregnant women is increasing  women during 2003–2015. These data represent a convenience sample of persons with private employer-sponsored insurance and their dependents in the United States. Demographic data are available for all persons enrolled at any point during the year, regardless of whether a claim is filed, and are linkable to submitted outpatient pharmacy claims. This analysis was restricted to women aged 15–44 years with ≥11 months of enrollment in a private health insurance plan that included prescription drug coverage during the year of interest. Outpatient pharmacy claims for ADHD medications were identified using national drug codes, irrespective of the indication for use. Data were analyzed to assess the annual percentage of reproductive-aged women who filled any ADHD medication prescription during 2003–2015, as well as by age group, U.S. geographic region, and medication class. To examine time trends, the percentage change in the percentage of reproductive-aged women dispensed ADHD medications from 2003 to 2015 was estimated. Among women who filled at least one ADHD medication prescription in the given year, CDC examined the distribution of specific medications and average number of prescriptions filled per year.Approximately 2.3–6.8 million privately insured reproductive-aged women constituted the analytic sample each year during 2003–2015 (median = 4.6 million). The percentage of reproductive-aged women with private employer-sponsored insurance who filled a prescription for any ADHD medication increased 344% from 2003 (0.9%) to 2015 (4.0%). The increase in the percentage of women prescribed ADHD medications was confined to a rise in the prescribing of stimulant medicationsThe percentage of reproductive-aged women who filled a prescription for any ADHD medication increased over time for all age groups and geographic regions . In 2015In 2015, among reproductive-aged women who filled any ADHD prescription, 60.8% filled a prescription for mixed amphetamine salts, 26.7% filled a prescription for lisdexamfetamine, and 18.1% filled a prescription for methylphenidate . Among rThe percentage of reproductive-aged women with private employer-sponsored insurance that included drug coverage who filled an ADHD medication prescription increased 344% from 2003 to 2015. In 2015, 4.0% of reproductive-aged women in this large convenience sample filled an ADHD medication prescription. A rise in stimulant ADHD medication prescriptions accounted for this increase; prescriptions for the nonstimulant atomoxetine have remained stable since 2003. The substantial increase in the percentage of reproductive-aged women filling ADHD medication prescriptions from 2003 to 2015, across age groups and U.S. geographic regions, is of public health concern given the high percentage of unintended pregnancies  helps address this need by conducting research on medication safety before and during pregnancy to help women and their health care providers make evidence-based decisions regarding the risks and benefits of pharmacologic and behavioral treatment options for common conditions, including ADHD.This analysis used a large database to estimate the percentage of privately insured reproductive-aged women who filled an ADHD medication prescription during 2003–2015. The increasing trend toward prescribing ADHD medications to reproductive-aged women highlights the importance of research examining ADHD medication safety in this population, including safety before and during pregnancy. CDC’s Treating for Two: Safer Medication Use in Pregnancy initiative (Attention-deficit/hyperactivity disorder (ADHD) medication use has increased among U.S. pregnant women, and consensus about its safety during pregnancy is lacking. Given that half of U.S. pregnancies are unintended, ADHD medication use among reproductive-aged women might result in early pregnancy exposure, a critical period for fetal development.The percentage of privately insured reproductive-aged women who filled a prescription for an ADHD medication increased 344% from 2003 (0.9%) to 2015 (4.0%). ADHD medication prescriptions increased across all age groups and U.S. geographic regions, and the increase was confined to stimulant medications.ADHD medication prescriptions are increasingly common among privately insured, reproductive-aged women. Additional research on ADHD medication safety among this population, including safety before and during pregnancy, could help women and their health care providers make evidence-based decisions concerning the risks and benefits of pharmacologic and behavioral treatment options for common conditions, including ADHD.


The aim of this study was to explore the comorbidity of Attention-Deficit Hyperactivity Disorder (ADHD) for the Korean national health insurance data (NHID) by using association rule mining (ARM).th revision (ICD-10) diagnosis system from NHID from 2011 to 2013 in youths aged 18 yr or younger. Overall, 211420 subjects, comorbid cases with ADHD were present in 105784. ARM was applied to the Apriori algorithm to examine the strengths of associations among those diagnosed, and logistic regression was used to evaluate the relations among rules.We used data categorized mental disorder according to the international classification of disease, 10The most prevalent comorbid psychiatric disorder of ADHD youths was mood/affective disorders. From results of ARM, nine association rules  were produced. The highest association was found between specific developmental disorders of scholastic skills and ADHD. Among association of three comorbid diseases, tic disorder was an important role in the association between ADHD and other comorbid diseases through results of ARM and logistic regression.The practical application of ARM for discovering the comorbidity of ADHD in large amount real-data such as the Korean NHID was mostly confirmed by past studies. The results of this study will be helpful to researchers evaluating the stability of their diagnosis in ADHD. Attention-Deficit Hyperactivity Disorder (ADHD) is the most common mental disorders that develop in children. The presence of ADHD in children has been known to give negative effects for many aspects of life, such as self-esteem, academic performance, social functions, and parent-child relationships .Many studies have suggested estimating the prevalence of ADHD. In the United States, the prevalence of ADHD is generally estimated 3%–10% .According to American Psychiatric Association, the prevalence of ADHD in school-aged children ranges 3%–7%. Furthermore, residual or full symptoms of ADHD is continued to adulthood in 30%–60% . In IndiA substantial proportion of patients with ADHD also have been reported comorbidity with psychiatry disorders other than ADHD, such as anxiety disorder, mild mental retardation, depression neurosis, major depressive disorder, autism and bipolar disorder –11.Inspecting the associations of comorbidities based on diagnostic data will be useful in predicting their risk and thus more effectively treating patients with ADHD. Many comorbidity studies of ADHD related to association of dual-diagnosis or estimation of the prevalence of co-occurring of two diagnoses and three or more comorbidities have been applied some data mining techniques .We consider the relationship among comorbidities of ADHD based on association rule mining (ARM) among these data mining techniques.ARM, also known as market basket analysis, is the discovery of association relationships or correlations among a set of attributes (items) in a database . It applThe Korean National Health Insurance (KNHI) established in 2000, is a single-payer program and currently has served mandatory social insurance system for all residents in Korea. The National Health Insurance Data (NHID) is provided by KNHI represents the entire Korean population and can be used as a population-based database. The Korean NHID consists of four databases of the insured that contain data on health checkups, health insurance claims and long-term care insurance (LTCI) .Researchers can be analyzed the Korean NHID for policy and academic research purposes after the Institutional Review Board approval. Identifying the incidence or prevalence of specific disease by using Korean NHID have been studied and published in some previous study ,20, but This study utilized the Korean NHID from 2011 to 2013. This dataset shows information including socioeconomic characteristics, health examinations, medical care institution data, and details of medical treatment and disease classification codes based on the International Classification of Diseases, 10th revision (ICD-10) . We examThe present study was approved by the Institutional Review Board of the Chonbuk National University (IRB No: 2016-01-007) in Jeonbuk, South Korea.The proposed framework is to focus on the investigating the associations of the comorbid diseases with ADHD. We considered ARM, also known as market basket analysis that is a popular data mining method.A transaction (T) is denoted a collection of ADHD /non-ADHD comorbid records in database of Korean NHID. In this transaction, D1 and D2 denote diseases that enrollees have. Formally, an association rule generated from denoted ‘D1 → D2’, it means the appearance of D1 implies the appearance of D2 in the same transaction. A rule does not have to imply cause and effect necessarily. The measures for ARM are the values of support, confidence, and lift of the rule. The support for the rule (D1 → D2) is defined as the probability that contains both D1 and D2.The confidence for D1 → D2 is the conditional probability of D2 given that a person has diagnosis D1.The lift of the rule D1 → D2 is the ratio of the confidence of the rule to the expected confidence, assuming the diagnoses are independent. The lift is interpreted as a measure of importance of a rule. The lift value greater than 1 indicates a positive effect; smaller than 1 indicates a negative effect, near 1 indicates no effect.Apriori algorithm, the most commonly used ARM rule, computes the frequent item sets in the database through several iterations. It was introduced by Agrawal and Srikant , and claThe ARM is fundamentally based on two-step principles –23. In t1, as in line 1. From this point, the algorithm applies k number of iterations  algorithm. The idea of the apriori-gen algorithm is to generate all the supersets of the large k-items sets from all the (k-1)-item sets (line 3 in k-1)-item sets to generate a candidate c. The two frequent Lk-1 item sets have exactly same items except the last one. After the join step, the candidate item sets Ck are generated. The pseudo SQL code for this step is given below -subest of c is not in Lk-1. This step can be seen below:forall itemsets c ∈ Ckdoforall (k-1)-subsets s of cdoif (s ∉ Lk-1) thendeletec from CkThe second step is the prune steps, which remove all item, sets k is calculated  and corresponding 95% confidence intervals (CI) were indicated.P-values under 0.05.Data management and analysis were used SAS v9.3 and R-package 3.4.0. Statistical significance was considered for The most prevalent comorbid psychiatric disorder  of ADHD The results of ARM between ADHD and specific psychiatric disorders listed in The highest association was the rule ‘specific developmental disorders of scholastic skills → ADHD’ with confidence 72.41% which means ratio of the co-occurrence rate of specific developmental disorders of scholastic skills and ADHD over the prevalence of specific developmental disorders of scholastic skills. The support value of 1.53% indicates that prevalence rate of both specific developmental disorders of scholastic skills and ADHD within a certain period. The lift value of 1.45 means specific developmental disorders of scholastic skills were positively associated with ADHD. The second was ruled ‘conduct disorders → ADHD’ with confidence 66.55% and support 5.19%. The other rules were ‘tic disorders → ADHD’ , ‘emotional disorders with onset specific to childhood → ADHD’ , ‘mixed disorders of conduct and emotions → ADHD’ .All lifts of rules were interpreted positively associated with ADHD.Among association of three comorbid diseases, tic disorder was an important role in association between ADHD and other comorbid diseases, such as mood/affective disorders and anxiety disorders.In Considering the left side of the association rules as explanatory variable, and the right side of the rules as response variables, we present adjusted odds ratio for sex and age with their 95% confidence intervals from the logistic regression to evaluate the ARM results . All of Tic disorder with anxiety disorder was observed higher odds ratio (OR=1.54) than with mood/affective disorder (OR=1.51). In addition, OR for tic disorder with controlling adjusted comorbid disease (anxiety disorder or mood/affective disorders) appeared similar to unadjusted comorbid disease.ADHD have known as high risk of comorbidity with other illness, especially the psychiatric diseases . This stFrom the ARM results, mood/affective disorders show to be associated with ADHD and other prevalent comorbid diseases, such as tic disorder and conduct disorders. In addition, associated comorbid diseases, including tic disorder and anxiety disorders can be contributors to ADHD. These results reveal to be compatible with the previous studies for comorbidities of ADHD . In the In this study, the logistic regression analysis was presented that the risk pattern distribution of the ADHD group and non-ADHD group were given by OR. The three most frequently OR for comorbid disease among ADHD were specific developmental disorders of scholastic skills, conduct disorder, and tic disorder. These results seem to be relatively lower than other researches because the study population is limited to more than two comorbid psychiatric diseases.There are several limitations on this investigation. First, the comorbidity rate of each psychiatric disorder in this study is lower than in previous studies. It seems to be limitations of our data source as clinical referral patterns. Therefore, our future research will be investigating more large data, such as long-term (more 3 yr) Korean NHID or Health Insurance Review and Assessment (HIRA) database. Second, this study is not able to consider causal relationship because of cross-sectional data.The highest association between ADHD and comorbid diseases was tic disorders, which is compatible with previous neurologic and epidemic studies. Our study also demonstrated the usefulness of ARM in ADHD comorbidity study in a large-scale, nationally representative dataset, namely the Korean NHID. The result of this study will be helpful to researchers evaluating the stability of their diagnosis with ADHD, and still, need some further evidence for establishing causal relationships.Future research focuses on experiment with summarization of ARM results into a predictive model such as Bayesian network or decision tree model.Ethical issues  have been completely observed by the authors.