Two functional variants of IRF5 influence the development of macular edema in patients with non-anterior uveitis.

OBJECTIVE Interferon (IFN) signaling plays a crucial role in autoimmunity. Genetic variation in interferon regulatory factor 5 (IRF5), a major regulator of the type I interferon induction, has been associated with risk of developing several autoimmune diseases. In the current study we aimed to evaluate whether three sets of correlated IRF5 genetic variants, independently associated with SLE and with different functional roles, are involved in uveitis susceptibility and its clinical subphenotypes. METHODS Three IRF5 polymorphisms, rs2004640, rs2070197 and rs10954213, representative of each group, were genotyped using TaqMan® allelic discrimination assays in a total of 263 non-anterior uveitis patients and 724 healthy controls of Spanish origin. RESULTS A clear association between two of the three analyzed genetic variants, rs2004640 and rs10954213, and the absence of macular edema was observed in the case/control analysis (P FDR =5.07E-03, OR=1.48, CI 95%=1.14-1.92 and P FDR =3.37E-03, OR=1.54, CI 95%=1.19-2.01, respectively). Consistently, the subphenotype analysis accordingly with the presence/absence of this clinical condition also reached statistical significance (rs2004640: P=0.037, OR=0.69, CI 95%=0.48-0.98; rs10954213: P=0.030, OR=0.67, CI 95%=0.47-0.96), thus suggesting that both IRF5 genetic variants are specifically associated with the lack of macular edema in uveitis patients. CONCLUSION Our results clearly showed for the first time that two functional genetic variants of IRF5 may play a role in the development of macular edema in non-anterior uveitis patients. Identifying genetic markers for macular edema could lead to the possibility of developing novel treatments or preventive therapies.

Is missing maxillary lateral incisor in complete cleft lip and palate a product of genetics or local environment?

Objective: To test the null hypothesis: Subjects with isolated complete unilateral cleft lip and palate (UCLP) show no differences in overall frequency of tooth agenesis (hypodontia), comparing a subsample with cleft-side maxillary lateral incisor (MxI2) agenesis to a subsample without cleftside MxI2 agenesis. Findings could clarify the origins of cleft-side MxI2 agenesis. Materials and Methods: Tooth agenesis was identified from dental radiographs of 141 subjects with UCLP. The UCLP cohort was segregated into four categories according to the status and location of MxI2 in the region of the unilateral cleft: group M: subjects with one tooth, located on the mesial side of the alveolar cleft; group D: subjects with one tooth, located on the distal side of the alveolar cleft; group MD: subjects with two teeth present, one mesial and one distal to the cleft; and group ABS: subjects with lateral incisor absent (agenesis) in the cleft area. Results: The null hypothesis was rejected. Among UCLP subjects, there was a twofold increase (P < .0008) in overall frequency of tooth agenesis outside the cleft region in a subsample with cleftside MxI2 agenesis (ABS), compared to a subsample presenting with no agenesis of the cleft-side MxI2 (M+D+MD). Conclusions: Cleft-side MxI2 agenesis in CLP subjects appears to be largely a genetically controlled anomaly associated with cleft development, rather than a collateral environmental consequence of the adjacent cleft defect, since increased hypodontia involving multiple missing teeth observed remote from a cleft clearly has a significant genetic basis. (Angle Orthod. 2012;82:959-963.)

Validation of Electronic Health Record Phenotyping of Bipolar Disorder Cases and Controls

Objective: The study was designed to validate use of elec-tronic health records (EHRs) for diagnosing bipolar disorder and classifying control subjects. Method: EHR data were obtained from a health care system of more than 4.6 million patients spanning more than 20 years. Experienced clinicians reviewed charts to identify text features and coded data consistent or inconsistent with a diagnosis of bipolar disorder. Natural language processing was used to train a diagnostic algorithm with 95% specificity for classifying bipolar disorder. Filtered coded data were used to derive three additional classification rules for case subjects and one for control subjects. The positive predictive value (PPV) of EHR-based bipolar disorder and subphenotype di- agnoses was calculated against diagnoses from direct semi- structured interviews of 190 patients by trained clinicians blind to EHR diagnosis. Results: The PPV of bipolar disorder defined by natural language processing was 0.85. Coded classification based on strict filtering achieved a value of 0.79, but classifications based on less stringent criteria performed less well. No EHR- classified control subject received a diagnosis of bipolar dis- order on the basis of direct interview (PPV=1.0). For most subphenotypes, values exceeded 0.80. The EHR-based clas- sifications were used to accrue 4,500 bipolar disorder cases and 5,000 controls for genetic analyses. Conclusions: Semiautomated mining of EHRs can be used to ascertain bipolar disorder patients and control subjects with high specificity and predictive value compared with diagnostic interviews. EHRs provide a powerful resource for high-throughput phenotyping for genetic and clinical research.